Nanoplatform-Based Molecular Imaging

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Printer Name: Yet to Come

NANOPLATFORM-BASED MOLECULAR IMAGING


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NANOPLATFORM-BASED MOLECULAR IMAGING

Edited by

Xiaoyuan Chen Laboratory of Molecular Imaging and Nanomedicine National Institute of Biomedical Imaging and Bioengineering National Institutes of Health Bethesda, Maryland

A JOHN WILEY & SONS, INC., PUBLICATION


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C 2011 by John Wiley & Sons, Inc. All rights reserved. Copyright

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com Library of Congress Cataloging-in-Publication Data: Nanoplatform-based molecular imaging / edited by Xiaoyuan Chen. p. ; cm. Includes bibliographical references and index. ISBN 978-0-470-52115-1 1. Molecular probes. 2. Diagnostic imaging. I. Chen, Xiaoyuan. [DNLM: 1. Molecular Imaging–methods. 2. Molecular Imaging–trends. 3. Molecular Probes–diagnostic use. 4. Nanoparticles–diagnostic use. 5. Nanotechnology–trends. WN 180 N1865 2010] QP519.9.M64N36 2010 616.07 54–dc22 2010007984 Printed in the United States of America eBook ISBN: 978-0-470-76703-0 oBook ISBN: 978-0-470-76704-7 10 9 8 7 6 5 4 3 2 1


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CONTENTS

Preface

ix

Acknowledgments

xi

Contributors

PART I

xiii

BASICS OF MOLECULAR IMAGING AND NANOBIOTECHNOLOGY

1. Basic Principles of Molecular Imaging

3

Sven H. Hausner

2. Synthesis of Nanomaterials as a Platform for Molecular Imaging

25

Jinhao Gao, Jin Xie, Bing Xu, and Xiaoyuan Chen

3. Nanoparticle Surface Modification and Bioconjugation

47

Jin Xie, Jinhao Gao, Mark Michalski, and Xiaoyuan Chen

4. Biodistribution and Pharmacokinetics of Nanoprobes

75

Nagesh Kolishetti, Frank Alexis, Eric M. Pridgen, and Omid C. Farokhzad

PART II

NANOPARTICLES FOR SINGLE MODALITY MOLECULAR IMAGING

5. Computed Tomography as a Tool for Anatomical and Molecular Imaging

107

Pingyu Liu, Hu Zhou, and Lei Xing

6. Carbon Nanotube X-Ray for Dynamic Micro-CT Imaging of Small Animal Models

139

Otto Zhou, Guohua Cao, Yueh Z. Lee, and Jianping Lu

7. Quantum Dots for In Vivo Molecular Imaging

159

Yun Xing

8. Biopolymer, Dendrimer, and Liposome Nanoplatforms for Optical Molecular Imaging

183

David Pham, Ling Zhang, Bo Chen, and Ella Fung Jones v


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CONTENTS

9. Nanoplatforms for Raman Molecular Imaging in Biological Systems

197

Zhuang Liu

10. Single-Walled Carbon Nanotube Near-Infrared Fluorescent Sensors for Biological Systems

217

Jingqing Zhang and Michael S. Strano

11. Microparticle- and Nanoparticle-Based Contrast-Enhanced Ultrasound Imaging

233

Nirupama Deshpande and Jürgen K. Willmann

12. Ultrasound-Based Molecular Imaging Using Nanoagents

263

Srivalleesha Mallidi, Mohammad Mehrmohammadi, Kimberly Homan, Bo Wang, Min Qu, Timothy Larson, Konstantin Sokolov, and Stanislav Emelianov

13. MRI Contrast Agents Based on Inorganic Nanoparticles

279

Hyon Bin Na and Taeghwan Hyeon

14. Cellular Magnetic Labeling with Iron Oxide Nanoparticles

309

Sébastien Boutry, Sophie Laurent, Luce Vander Elst, and Robert N. Muller

15. Nanoparticles Containing Rare Earth Ions: A Tunable Tool for MRI

333

C. Rivière, S. Roux, R. Bazzi, J.-L. Bridot, C. Billotey, P. Perriat, and O. Tillement

16. Microfabricated Multispectral MRI Contrast Agents

375

Gary Zabow and Alan Koretsky

17. Radiolabeled Nanoplatforms: Imaging Hot Bullets Hitting Their Target

399

Raffaella Rossin

PART III NANOPARTICLE PLATFORMS AS MULTIMODALITY IMAGING AND THERAPY AGENTS 18. Lipoprotein-Based Nanoplatforms for Cancer Molecular Imaging

433

Ian R. Corbin, Kenneth Ng, and Gang Zheng

19. Protein Cages as Multimode Imaging Agents

463

Masaki Uchida, Lars Liepold, Mark Young, and Trevor Douglas

20. Biomedical Applications of Single-Walled Carbon Nanotubes

481

Weibo Cai, Ting Gao, and Hao Hong

21. Multifunctional Nanoparticles for Multimodal Molecular Imaging

529

Yanglong Hou and Rui Hao

22. Multifunctional Nanoparticles for Cancer Theragnosis Seulki Lee, Ick Chan Kwon, and Kwangmeyung Kim

541


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CONTENTS

23. Nanoparticles for Combined Cancer Imaging and Therapy

vii

565

Vaishali Bagalkot, Mi Kyung Yu, and Sangyong Jon

24. Multimodal Imaging and Therapy with Magnetofluorescent Nanoparticles

593

Jason R. McCarthy and Ralph Weissleder

25. Gold Nanocages: A Multifunctional Platform for Molecular Optical Imaging and Photothermal Treatment

615

Leslie Au, Claire M. Cobley, Jingyi Chen, and Younan Xia

26. Theranostic Applications of Gold Nanoparticles in Cancer

639

Parmeswaran Diagaradjane, Pranshu Mohindra, and Sunil Krishnan

27. Gold Nanorods as Theranostic Agents

659

Alexander Wei, Qingshan Wei, and Alexei P. Leonov

28. Theranostic Applications of Gold Core–Shell Structured Nanoparticles

683

Wei Lu, Marites P. Melancon, and Chun Li

29. Magnetic Nanoparticle Carrier for Targeted Drug Delivery: Perspective, Outlook, and Design

709

R. D. K. Misra

30. Perfluorocarbon Nanoparticles: A Multidimensional Platform for Targeted Image-Guided Drug Delivery

725

Gregory M. Lanza, Shelton D. Caruthers, Anne H. Schmieder, Patrick M. Winter, Tillmann Cyrus, and Samuel A. Wickline

31. Radioimmunonanoparticles for Cancer Imaging and Therapy

755

Arutselvan Natarajan

PART IV TRANSLATIONAL NANOMEDICINE 32. Current Status and Future Prospects for Nanoparticle-Based Technology in Human Medicine

783

Nuria Sanvicens, Fátima Fernández, J.-Pablo Salvador, and M.-Pilar Marco

Index

815


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PREFACE

This book focuses on the rational design of water-soluble, biocompatible nanoparticles for the visualization of the cellular function and follow-up of the molecular processes in living organisms without perturbing them. Molecular imaging probes based on nanotechnology hold great potential in diagnosis, imaging guided intervention, and treatment response monitoring of diseases. This book is logically organized by including the basics of molecular imaging, general strategies of particle synthesis and surface chemistry, applications in computed tomography (CT), optical imaging, magnetic resonance imaging (MRI), ultrasound, multimodality imaging, and theranostics, and finally clinical perspectives of nanoimaging. This comprehensive title provides expert opinions on the latest developments in molecular imaging using nanoparticles. This book consists of 32 chapters and was contributed by nearly 100 authors worldwide, who are among the world’s prominent scientists in material science and/or molecular imaging. Part I consists of Chapters 1–4 Chapter 1 describes the basic principles of molecular imaging, how nanoparticles can be applied to different molecular imaging modalities, and challenges in developing nanoparticle-based molecular imaging probes; Chapter 2 highlights the general strategies to produce narrowly dispersed nanomaterials for molecular imaging; Chapter 3 emphasizes the importance of surface modification to render nanoparticles biocompatible and suitable for molecular imaging applications; and Chapter 4 talks about the toxicity and factors such as size, shape, coating, and surface charge that affect the biodistribution and pharmacokinetics of nanoprobes. Part II consists of Chapters 5–17 Chapter 5 illustrates the basic principles of CT, the evolution of CT imaging technology, and the rationale for nanoparticle-based CT contrast agents; Chapter 6 describes the advantages of fascinating carbon nanotube field emission X-ray technology over conventional thermionic X-ray tubes that are used in current X-ray imaging systems; Chapter 7 describes the use of unique optical properties of semiconductor quantum dots (QDs) for near-infrared fluorescence imaging in living animals; Chapter 8 introduces macromolecular nanoconstructs such as biopolymers, dendrimers, and liposomes as carriers for fluorophore conjugation and optical imaging; Chapter 9 summarizes recent progress in developing nanoplatforms for Raman imaging of biological systems; Chapter 10 summarizes the work in using single-walled carbon nanotubes (SWNTs) as near-infrared fluorescent sensors for biomolecule detection; Chapter 11 describes the use of micro- and nanoparticles as ultrasound contrast agents; Chapter 12 proposes the use of metal nanoparticles in ultrasound-based photoacoustic and magnetoacoustic imaging modalities; Chapter 13 reports the progress on magnetic resonance imaging (MRI) contrast agents based on inorganic nanoparticles; Chapter 14 emphasizes the use of iron oxide nanoparticles for cellular labeling followed by T2 - and T∗2 -weighted MRI; Chapter 15 covers the use of rare earth based nanoparticles for MR imaging as positive contrast agents; Chapter 16 reviews the top–down microfabrication technology to synthesize multispectral MRI contrast agents; ix


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PREFACE

and Chapter 17 gives an overview of the strategies to label nanoparticles with radionuclides to study in vivo distribution. Part III consists of Chapters 18–31 Chapter 18 introduces techniques to incorporate imaging agents into lipoproteins and to reroute lipoproteins to cancer specific epitopes; Chapter 19 exemplifies the use of protein cages such as virus capsids and ferritins as platforms for MRI contrast agents and fluorescent imaging agents; Chapter 20 provides a comprehensive summary of the state-of-the-art of SWNTs for multimodality biomedical imaging applications; Chapter 21 reviews the progress in the controlled synthesis, surface modification, and multimodality imaging applications of multifunctional nanoparticles in recent years; Chapter 22 argues the use of cancer theranostics as a promising new strategy in cancer management, permitting simultaneous cancer diagnosis, drug delivery, and real-time monitoring of therapeutic efficacy; Chapter 23 provides more examples of multifunctional nanoparticles for combined cancer imaging and therapy (theranostics); Chapter 24 describes the recent progress in modifying magnetic nanoparticles for multimodality imaging as well as targeted treatment of a number of diseases; Chapter 25 introduces gold nanocages as contrast agents for optical bioimaging (such as optical and spectroscopic coherence tomography amd photoacoustic tomography) and photothermal treatment; Chapter 26 describes the biological inertness, ease of manufacture and bioconjugation, and presumed lack of toxicity of gold nanoparticles for simultaneous sensing, imaging, and treatment of tumors; Chapter 27 presents the recent developments in the chemistry and photophysics of gold nanorods and their applications toward biological imaging and photothertmally activated therapies; Chapter 28 describes a number of gold core–shell nanostructures for cancer molecular optical imaging, controlled drug delivery, and photothermal ablation therapy; Chapter 29 describes a novel temperature and pH-responsive magnetic nanocarrier that combines tumor targeting and controlled drug release capabilities; Chapter 30 deals with perfluorocarbon nanoparticles as a multidimensional platform for targeted image-guided drug delivery; and Chapter 31 describes the use of radiolabeled nanoparticles and radiolabeled immunonanoparticles for imaging and therapy. Part IV is the concluding Chapter 32 that highlights some of the nanoparticle-based novel technologies for molecular imaging, diagnosis, and drug delivery formulations. The limitations and future challenges of nanoparticle-based systems are also discussed. Bethesda, Maryland

Xiaoyuan Chen


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ACKNOWLEDGMENTS

The editor thanks the nearly 100 authors throughout the world for their contributions and collaboration on this book project. The editing work of this book was accomplished using a significant amount of the editor’s spare time including family time. Therefore the editor also thanks his wife, Michelle Ji, and his daughter, Grace Chen, for their wonderful support and understanding.

xi


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CONTRIBUTORS

Frank Alexis, Department of Bioengineering, Clemson University, Clemson, South Carolina, USA Leslie Au, Department of Biomedical Engineering, Washington University, St. Louis, Missouri, USA Vaishali Bagalkot, School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, South Korea R. Bazzi, Laboratoire Physico-Chimie des Electrolytes, Colloides et Sciences Analytiques, Université Pierre et Marie Curie, Paris, France C. Billotey, Laboratoire CREATIS–Animage, Université Claude Bernard, Lyon, France Sébastien Boutry, Department of General, Organic and Biomedical Chemistry, NMR and Molecular Imaging Laboratory, University of Mons, Mons, Belgium J.-L. Bridot, Service de Chimie Générale, Organique et Biomédicale, Laboratoire de RMN et d’Imagerie Moléculaire, Université de Mons-Hainaut, Mons, Belgium Weibo Cai, Departments of Radiology and Medical Physics, School of Medicine and Public Health, University of Wisconsin–Madison, and University of Wisconsin Carbone Cancer Center, Madison, Wisconsin, USA Guohua Cao, Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Shelton D. Caruthers, Department of Medicine, Washington University Medical School, St. Louis, Missouri, and Philips Healthcare, Andover, Massachusetts, USA Bo Chen, Center for Molecular and Functional Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA Jingyi Chen, Department of Biomedical Engineering, Washington University, St. Louis, Missouri, USA Xiaoyuan Chen, Molecular Imaging Program at Stanford and Bio-X Program, Department of Radiology, Stanford University School of Medicine, Stanford, California, and Laboratory for Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA Claire M. Cobley, Department of Biomedical Engineering, Washington University, St. Louis, Missouri, USA

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CONTRIBUTORS

Ian R. Corbin, Department of Medical Biophysics, University of Toronto, Toronto, Ontario, and Division of Biophysics and Bioimaging, Ontario Cancer Institute, Toronto, Ontario, Canada Tillmann Cyrus, Department of Medicine, Washington University Medical School, St. Louis, Missouri, USA Nirupama Deshpande, Department of Radiology and Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford, California, USA Parmeswaran Diagaradjane, Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA Trevor Douglas, Department of Chemistry and Biochemistry and Department of Plant Science, Center for Bio-inspired Nanomaterials, Montana State University, Bozeman, Montana, USA Luce Vander Elst, Department of General, Organic and Biomedical Chemistry, NMR and Molecular Imaging Laboratory, University of Mons, Mons, Belgium Stanislav Emelianov, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA Omid C. Farokhzad, Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA Fátima Fernández, Applied Molecular Receptors Group, CIBER de Bioingenier´ıa, Biomateriales y Nanotecnolog´ıa, IQAC-CSIC, Barcelona, Spain Jinhao Gao, Molecular Imaging Program at Stanford and Bio-X Program, Department of Radiology, Stanford University School of Medicine, Stanford, California, USA Ting Gao, Tyco Electronics Corporation, Menlo Park, California, USA Rui Hao, Department of Advanced Materials and Nanotechnology, College of Engineering, Peking University, Beijing, China Sven H. Hausner, Department of Biomedical Engineering, University of California– Davis, Davis, California, USA Kimberly Homan, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA Hao Hong, Departments of Radiology and Medical Physics, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin, USA Yanglong Hou, Department of Advanced Materials and Nanotechnology, College of Engineering, Peking University, Beijing, China Taeghwan Hyeon, National Creative Research Initiative Center for Oxide Nanocrystalline Materials, and School of Chemical and Biological Engineering, Seoul National University, Seoul, South Korea Sangyong Jon, School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, South Korea


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CONTRIBUTORS

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Ella Fung Jones, Center for Molecular and Functional Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA Kwangmeyung Kim, Biomedical Research Center, Korea Institute of Science and Technology, Seoul, South Korea Nagesh Kolishetti, Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA Alan Koretsky, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA Sunil Krishnan, Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA Ick Chan Kwon, Biomedical Research Center, Korea Institute of Science and Technology, Seoul, South Korea Gregory M. Lanza, Department of Medicine, Washington University Medical School, St. Louis, Missouri, USA Timothy Larson, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA Sophie Laurent, Department of General, Organic and Biomedical Chemistry, NMR and Molecular Imaging Laboratory, University of Mons, Mons, Belgium Seulki Lee, Biomedical Research Center, Korea Institute of Science and Technology, Seoul, South Korea Yueh Z. Lee, Department of Physics and Astronomy and Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Alexei P. Leonov, Department of Chemistry, Purdue University, West Lafayette, Indiana, USA Chun Li, Department of Experimental Diagnostic Imaging, University of Texas M.D. Anderson Cancer, Houston, Texas, USA Lars Liepold, Department of Chemistry and Biochemistry and Department of Plant Sciences, Center for Bio-Inspired Nanomaterials, Montana State University, Bozeman, Montana, USA Pingyu Liu, Palo Alto Unified School District, Palo Alto, California, USA Zhuang Liu, Institute of Functional Nano & Soft Materials, Soochow University, Suzhou, Jiangsu, China Jianping Lu, Department of Physics and Astronomy, Curriculum in Applied Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Wei Lu, Department of Experimental Diagnostic Imaging, University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA


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CONTRIBUTORS

Srivalleesha Mallidi, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA M.-Pilar Marco, Applied Molecular Receptors Group, CIBER de Bioingenier´ıa, Biomateriales y Nanotecnolog´ıa, IQAC-CSIC, Barcelona, Spain Jason R. McCarthy, Center for Molecular Imaging Research, Harvard Medical School and Massachusetts General Hospital, Charlestown, Massachusetts, USA Mohammad Mehrmohammadi, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA Marites P. Melancon, Department of Experimental Diagnostic Imaging, University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA Mark Michalski, Molecular Imaging Program at Stanford and Bio-X Program, Department of Radiology, Stanford University School of Medicine, Stanford, California, USA R. D. K. Misra, Center for Structural and Functional Materials, University of Louisiana at Lafayette, Lafayette, Louisiana, USA Pranshu Mohindra, Department of Radiation Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA Robert N. Muller, Department of General, Organic and Biomedical Chemistry, NMR and Molecular Imaging Laboratory, University of Mons, Mons, Belgium Hyon Bin Na, National Creative Research Initiative Center for Oxide Nanocrystalline Materials, and School of Chemical and Biological Engineering, Seoul National University, Seoul, South Korea Arutselvan Natarajan, Department of Radiology and Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford, California, USA Kenneth Ng, Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada P. Perriat, Groupe d’Etudes de Métallurgie Physique et de Physique des Matériaox, Université Claude Bernard, Lyon, France David Pham, Center for Molecular and Functional Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA Eric M. Pridgen, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA Min Qu, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA C. Rivière, Laboratoire de Physique de la Matière Condensée et Nanostructures, Université de Lyon, Lyon, France Raffaella Rossin, Department of Biomolecular Engineering, Philips Research Europe, Eindhoven, The Netherlands S. Roux, Laboratoire de Physico-Chimie des Matériaux Luminescents, Université de Lyon, Lyon, France


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CONTRIBUTORS

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J.-Pablo Salvador, Applied Molecular Receptors Group, CIBER de Bioingenier´ıa, Biomateriales y Nanotecnolog´ıa, IQAC-CSIC, Barcelona, Spain Nuria Sanvicens, Applied Molecular Receptors Group, CIBER de Bioingenier´ıa, Biomateriales y Nanotecnolog´ıa, IQAC-CSIC, Barcelona, Spain Anne H. Schmieder, Department of Medicine, Washington University Medical School, St. Louis, Missouri, USA Konstantin Sokolov, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, and Department of Medical Physics, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA Michael Strano, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA O. Tillement, Laboratoire de Physico-Chimie des Matériaux Luminescents, Université de Lyon, Lyon, France Masaki Uchida, Department of Chemistry and Biochemistry and Department of Plant Science, Center for Bio-Inspired Nanomaterials, Montana State University, Bozeman, Montana, USA Bo Wang, Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA Alexander Wei, Department of Chemistry, Purdue University, West Lafayette, Indiana, USA Qingshan Wei, Department of Chemistry, Purdue University, West Lafayette, Indiana, USA Ralph Weissleder, Center for Molecular Imaging Research, Harvard Medical School and Massachusetts General Hospital, Charlestown, Massachusetts, USA Samuel A. Wickline, Department of Medicine, Washington University Medical School, St. Louis, Missouri, USA Jurgen K. Willmann, Department of Radiology and Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford, California, USA Patrick M. Winter, Department of Medicine, Washington University Medical School, St. Louis, Missouri, USA Younan Xia, Department of Biomedical Engineering, Washington University, St. Louis, Missouri, USA Jin Xie, Molecular Imaging Program at Stanford and Bio-X Program, Department of Radiology, Stanford University School of Medicine, Stanford, California, and Laboratory for Molecular Imaging and Nanomedicine, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA Lei Xing, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, USA


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CONTRIBUTORS

Yun Xing, Department of Material Science and Engineering, University of Dayton, Dayton, Ohio, USA Bing Xu, Department of Chemistry, Brandeis University, Waltham, Massachusetts, USA Mark Young, Department of Chemistry and Biochemistry and Department of Plant Science, Center for Bio-Inspired Nanomaterials, Montana State University, Bozeman, Montana, USA Mi Kyung Yu, School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, South Korea Gary Zabow, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA Jingqing Zhang, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA Ling Zhang, Center for Molecular and Functional Imaging, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA Gang Zheng, Department of Medical Biophysics and Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, and Division of Biophysics and Bioimaging, Ontario Cancer Institute, Toronto, Ontario, Canada Hu Zhou, Community Cancer Center of Roseburg, Roseburg, Oregon, USA Otto Zhou, Department of Physics and Astronomy, Curriculum in Applied Sciences and Engineering, and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

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PART I

BASICS OF MOLECULAR IMAGING AND NANOBIOTECHNOLOGY


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CHAPTER 1

Basic Principles of Molecular Imaging SVEN H. HAUSNER Department of Biomedical Engineering, University of California–Davis, Davis, California, USA

1.1 INTRODUCTION The ability to identify diseased tissue for detection and treatment remains a central goal for medical research. Several noninvasive or minimally invasive diagnostic modalities have been developed which allow one to obtain anatomical, physiological, and molecular information. “Molecular imaging” can be defined as in situ visualization, characterization, and measurement of biological processes in the living organism at the molecular or cellular level. Diagnosis and visualization at the molecular level, that is, detection of a disease in its infancy, may significantly improve treatment and patient care. By combining two or more imaging modalities, each with its different strengths, high-quality complementary (e.g., molecular and anatomical) information can be obtained and analyzed in the context of each other. This has led to the rise of dual- and multimodality imaging approaches. Depending on the modality, imaging probes or contrast agents are required or highly desirable; they can range in size from single atoms to cell-sized constructs. Nanoparticles, that is, entities with dimensions in the range of several tens of nanometers, can display desirable pharmacokinetic properties and permit the combination of different clinically relevant moieties (e.g., targeting groups, molecular beacons, and contrast agents for different modalities, surface coatings, enclosed payload) in a single unit. The inclusion of a therapeutic component yields “theranostics.” Taken together, nanotechnology-based molecular probes offer the promise for tailor-made clinical tools required for “personalized medicine.” This chapter provides an introductory overview of molecular imaging, major imaging modalities, and imaging probes, with particular focus on the promises and challenges of nanoparticle-based compounds.

1.2 IMAGING IN MEDICINE Most areas of clinical practice require identification and localization of diseased tissue for detection and treatment. Ideally, reliable, specific, and noninvasive high-contrast Nanoplatform-Based Molecular Imaging Edited by Xiaoyuan Chen C 2011 John Wiley & Sons, Inc. Copyright

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BASIC PRINCIPLES OF MOLECULAR IMAGING

whole-body evaluations would allow physicians to detect serious abnormalities before patients present with symptoms, thus permitting early intervention, thereby increasing the chance for cure or, at a minimum, allow for better patient management and improved quality of life. Given these incentives, it is clear that practical (i.e., minimally inconvenient for the patient) and affordable (i.e., overall cost-saving to the health care system and society) diagnostic approaches are highly desirable. Ever since Wilhelm Röntgen’s first use in 1895 of the then newly discovered X-rays to noninvasively image the interior of the body, the keen interest in medical imaging has been met by increasingly sophisticated technologies (Fig. 1.1). While Röntgen’s X-ray image was a grainy two-dimensional anatomical projection, physicians nowadays have access to tomographic (three-dimensional) imaging modalities with, depending on the technique, submillimeter resolution, which allows visualization of anatomical, physiological, and, increasingly, molecular (cellular) biological information. Since diseases often arise from changes on the molecular and cellular levels, long before manifesting themselves in detectable large-scale physiological or anatomical changes, molecular imaging is gaining increasing attention. If a disease can be diagnosed and visualized at the molecular level, that is, detected in its infancy, it can be treated at a much earlier stage, the treatment’s efficacy can be determined much sooner and, if necessary, the treatment plan can be adjusted accordingly. This benefits the individual patient and society as a

FIGURE 1.1 (Left) Wilhelm Röntgen’s (1845–1923) first X-ray image, depicting the hand of his wife, Anna, taken on 22 December 1895. (Right) A slice of a modern whole-body multimodality positron emission tomography/computed tomography (PET/CT) scan showing glucose metabolism within the body, including a large, metabolically active tumor (arrow). (PET/CT image courtesy of Dr. Cameron Foster and Dr. Ramsey Badawi, UC Davis Medical Center, Davis, California.)


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IMAGING IN MEDICINE

5

whole. Molecular biology is discovering a growing number of disease-specific cellular targets and is determining their distribution in patient populations [1]. For certain diseases this has already had significant effects on determining beforehand which patients will benefit from a certain treatment (“patient stratification”). A prime example is testing for the expression of HER2/neu in breast cancer for prognosis, as well as for selection and monitoring of treatment: expression has been linked to aggressiveness of the disease, but it also provides a target for highly effective treatment with antibodies (Trastuzumab, Herceptin® ) [2, 3]. Similarly, monitoring glucose metabolism with the imaging agent 18 F-fluorodeoxyglucose (18 F-FDG) has proved itself to be the preferred approach for staging, restaging, and evaluation of response to treatment for several cancers [4]. Concurrently with the advances in molecular biology, engineers and physicists are developing increasingly sophisticated imaging instrumentation capable of localizing imaging agents in the body at high sensitivity and high resolution in short acquisition time [5]. By bridging the clinical and engineering worlds, research in imaging agents plays a central role. To that end, the development of target-specific (and disease-specific) nanoparticle-based molecular probes draws on research in several fields including biology, molecular biology, medicine, chemistry, and biomedical engineering. 1.2.1 Molecular Imaging Rather than relying only on intrinsic large-scale differences of tissue characteristics (e.g., density) or passive accumulation of administered probes to reveal disease in vivo, molecular imaging strives to make use of disease-specific (“targeted”) interactions of imaging probes with the target tissue on a molecular and a cellular level. The goal is the real-time in situ visualization of biological processes in the living organism. This focus is also reflected in the Society of Nuclear Medicine’s definition of molecular imaging as “an array of non-invasive, diagnostic imaging technologies that can create images of both physical and functional aspects of the living body. It can provide information that would otherwise require surgery or other invasive procedures to obtain. Molecular imaging differs from microscopy, which can also produce images at the molecular level, in that microscopy is used on samples of tissue that have been removed from the body, not on tissues still within a living organism. It differs from X-rays and other radiological techniques in that molecular imaging primarily provides information about biological processes (function) while [computed tomography] CT, X-rays, [magnetic resonance imaging] MRI and ultrasound, image physical structure (anatomy)” [6]. As stated above, the information obtained is linked to which imaging modality is chosen. Individual imaging modalities can be grouped by the energy spectrum and energy type evaluated (X-ray, photons, sound; positrons), the resolution that can be achieved, and the type of information obtained (anatomical, physiological, cellular/molecular) (Table 1.1). Widely used clinical imaging modalities include magnetic resonance imaging, ultrasound (US), computed tomography, as well as positron emission tomography (PET) and single photon emission computed tomography (SPECT). All of these modalities allow for the noninvasive imaging of living subjects. Although the first three imaging modalities are primarily anatomical and not molecular, the two types of modalities can be combined for dual- or multimodality imaging. In addition, MRI, US, and CT can be used with molecular imaging probes, especially as part of nanoplatforms. In addition, a number of more specialized optical modalities are being used or are under investigation, including endoscopic methods [12].

6 M, P

M, P

M, P

Positron emission tomography (PET)

Single photon emission computed tomography (SPECT)

Typeb

Optical imaging (fluorescence and bioluminescence)

Imaging Modalitya −15

Sensitivity (Concentration of Imaging Probe/Contrast Agent)

Photon emitted by radioactive isotope of imaging probe.

∼10−11 mole/L [7]

∼10−11 –10−12 mole/L

Depth

0.5–2 mm (preclinical) 10–15 mm (clinical)

1–2 mm (preclinical) 4–8 mm (clinical)

No limit

No limit

Yes

Yes

∼1 to ∼10 mm Centimeters (Yes, limited quantification possible)

Resolution

Quantitative Modality

Minutes to tens of minutes

Minutes to tens of minutes

Seconds to minutes

Typical Scan Acquisition Time

Clinical and preclinical. High cost. Versatile imaging probe chemistry. Possibility to distinguish different radioisotopes based on photon energy.

Clinical and preclinical. High cost. Versatile imaging probe chemistry.

Preclinical; limited clinical translation (close to skin or requiring endoscopic approaches) Low cost. Depth limitation based on wavelength-dependent absorption by tissue. Resolution is depth dependent. Two-dimensional (surface) image.

Other

21:44

511-keV Photons generated during annihilation of positron emitted by radioactive isotope of imaging probe.

Fluorescence: External As low as ∼10 mole/L excitation light absorbed by fluorochrome of imaging probe and reemitted at longer wavelength. Bioluminescence: Chemiluminescence of enzymatic reaction.

Basis for Detection

TABLE 1.1 Widely Used Imaging Modalities

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b

Less than ∼50 ␮m (preclinical) 5 × 109 QDs/cell or >2.3 ␮M) of these QDs were shown to cause toxic or inflammatory responses in Xenopus embryos for reasons that are not fully understood [89, 90]. Another report showed that colloidal instability causing precipitation of nanoparticles on cells led to the detachment of cells from cell culture substrates [83]. Other studies suggest that the toxicity is controlled by the size of the QDs. For example, cystamine-coated QDs (2 nm) were shown to accumulate in the nucleus. Small QDs (below 3 nm) were found to adsorb nonspecifically to intracellular proteins and impair cellular functions by invading the nucleus and binding to histones or nucleosomes, causing DNA damage [43, 91–93]. Biotinylated CdSe/ZnS QDs incubation with supercoiled DNA for 60 min showed 56% and 29% of DNA damage in the presence of UV exposure and dark, respectively [91, 93]. DNA damage was due to the free radicals generated by light and oxidation. In addition, Geys et al. [94] reported higher toxicity of negatively charged nanoparticles change to period and end sentence. They observed that negatively-charged nanoparticles caused pulmonary vascular thrombosis and suggested that the negative charge contributed to the activation of the coagulation through aggregation with plasma proteins. A current problem for in vivo applications is that a major fraction of the QDs remain at the site of injection for a very long time [95] and the long-term fate of these QDs in the body is yet to be clearly understood. Recently, Yang et al. [77] reported a long-term study (over 7 weeks) in mice showing that signal was found in the intestinal tract, suggesting fecal as the primary excretion pathway. Tissue histology and neurological evaluations did not show apparent changes 100 days post-injection. The long-term toxicity of QDs coated with crosslinked polymers does not show harmful effects at dosages of ∼10 mg/kg, but

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distress was reported at 42 mg/kg. This dose-dependent toxicity was previously reported for QDs containing mercury, which is known to have major safety concerns. These results suggest that the potential release of cytotoxic elements from QDs and their distribution in specific organs, tissues, cell types, and subcellular locations must be well understood before they can be used in humans. Due to their enhanced optical properties, QDs might be injected at doses below their cytotoxicty threshold, although the minimum dose for precise diagnosis remains to be determined. QDs with reduced or no heavy metal toxicity and colloidal stability may find an important role as clinical contrast agents in future optical imaging techniques. 4.3.2 Gold Nanoparticles Gold is known to be an inert material and it is reported that gold nanoparticles (GNPs) (size range 10–250 nm) can be taken up by various human cells without any cytotoxic effects at up to 4000 particles per cell [96, 97]. Murphy and co-workers did not observe any in vitro cytotoxic effect using gold nanoparticles of various sizes (4, 12, and 18 nm) and surface coatings (anionic, neutral, and cationic) on leukemia cells [98, 99]. The purification process for gold nanoparticles was a key step because residual chemical impurities such as surfactants were shown to be toxic to the cells at the nanomolar level. Ofek et al. [100] showed that zebrafish embryos treated with gold nanoparticles at sizes ranging from 3 to 100 nm did not show significant increase in mortality with increasing concentrations up to 250 ␮mol of gold in contrast to silver nanoparticles. The difference in toxicity between silver and gold nanoparticles was thought to be due to the chemical composition and residual impurities of silver nitrates [100]. Leonov et al. [101] showed that polystyrenesulfonate sodium salt (PSS, 70 kDa) could efficiently remove residual surfactant from gold nanorods. However, cytotoxicity profiles using three different cell lines (porcine kidney, human liver carcinomas, and human nasopharyngeal carcinomas) [101] showed unexpected results indicating that purified gold nanorods had higher toxicity than the surfactant-coated nanorods. These results indicated that PSS adsorption on the gold nanorods is not stable enough, leading to complexes with residual surfactants [101]. Several other studies have examined the effect of gold nanoparticle size on in vitro and in vivo toxicity [67, 102]. Hainfeld et al. [51] observed no in vivo toxicity after 30 days for 1.9-nm sized gold nanoparticles using mice as an animal model (dose = 2.7 g/kg) and the LD50 was found to be 3.2 g/kg. The nanoparticles were quickly cleared through kidneys without significant accumulation in the liver and spleen. Others have shown that gold nanoparticles with hydrodynamic diameter smaller than 2 nm are more toxic than larger particles. Maria et al. [103] showed that small gold nanoclusters (Au55 ) with a size of 1.4 nm are toxic to various human cancer and healthy cell lines in contrast to larger gold nanoparticles. Toxicity studies with 18-nm and 1.4-nm GNPs showed that larger NPs were less toxic [104], with the results attributed to the intercalation of GNPs in the DNA major groove. The smaller GNPs were also found to easily translocate in significant amounts through the blood barrier of the respiratory tract. Positively-charged, small nanoparticles were shown to increase cytotoxicity due to electrostatic interactions with cell membranes and/or DNA. No significant cytotoxicity differences have been reported due to shape when comparing spherical and nanorod gold nanoparticles. However, most of the surfactants used for stabilizing gold nanoparticles have been found to be cytotoxic. Therefore significant efforts are being devoted to using biocompatible materials. These results were consistent with data showing that gold nanorods


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coated with polyethylene glycol were less toxic than surfactant-coated nanorods based on cellular micromotility assays. No general conclusion can be drawn at present, although most of the research has clearly shown the effect of the size on the increased cytotoxicity profile of GNPs. Thus, these results suggest that more in vivo studies need to be carried out to understand the size, charge, and shape-dependent toxicity of GNPs. 4.3.3 Carbon Nanotubes Carbon nanotubes are known to cause significant cytotoxic responses such as induction of oxidative stress, inhibition of cell proliferation, and apoptosis in different cell lines [105]. Carbon nanotubes have also demonstrated major cytotoxicity in the lungs upon inhalation [106–109]. Lam et al. [106] showed pulmonary toxicity of SWNTs in mice after intratracheal instillation. All the mice showed epithelioid granulomas and interstitial inflammation after 7 and 90 days. Similar pulmonary toxicities were observed in rats by another group [110]. The gene expression of macrophages that had taken up SWNTs showed activation of oxidative stress and an inflammatory response [111]. For example, interleukin-6 (IL-6) was overexpressed (25-fold increase) upon incubation of macrophage with SWNTs [109]. The potential hazard of SWNTs strongly depends on the metal content and the size of the agglomerates [112]. CNT products contain impurities such as amorphous carbon and metals such as, Co, Fe, Ni, and Mo. The amount and type of impurities depends on the manufacturer and synthetic methods [112, 113]. Elemental analysis of raw SWNTs (uncoated) using ICP-MS showed substantial content of iron (10%), sodium (0.03%), and nickel (0.02%). A large number of studies over the past several years reported varied toxicity levels suggesting a dependence on the type of nanotube materials used and functionalization strategies. In vitro and in vivo toxicological studies have suggested reduced toxicity due to surface functionalization of carbon nanotubes [108, 114–116]. For example, glycodendrimercoated SWNTs were found to be nontoxic to HEK292 cells at a concentration of 100 ␮g/mL, while the non-functionalized SWNTs greatly inhibited cell growth [116]. In another report, biotinylated SWNTs were found to be nontoxic up to concentrations of 0.05 mg/mL in HL60 cells [114]. In mice, 151 and 47 mg of PEG-functionalized SWNTs was found to be nontoxic even after a 4-month period [108]. SWNTs suspended in Tween-80 exhibited toxicities due to accumulation in the liver and lungs after 3 months at higher dose (40 mg/kg), while no detectable toxicity was observed at 2 mg/kg [117]. However, SWNTs functionalized with phenyl-carboxylic groups were shown to be less cytotoxic than surfactant-coated (Pluronic F108) SWNTs. Functionalized CNTs with biocompatible surface coatings have been shown to be nontoxic with greater renal clearance and insignificant reticuloendothelial system (RES) uptake and are promising candidates for future studies [46, 50, 108, 117–119]. For example, PEGylated SWNTs administered through IV injection in mice at a concentration of 3 mg/kg showed normal blood chemistry and histological observations after 4 months [108]. This study did not show significant systemic toxicity of SWNTs after a single dose injection but white blood cell concentrations decreased by 50%. In another example, 20 ␮g of linear and branched PEG functionalized SWNTs showed no toxic side effects, low RES uptake, and near complete clearance two months after IV injection [119]. Although no acute toxicity is reported using histological assessment of tissues, multiple reports suggested increased levels of oxidative stress. Overall, SWNT have been shown to be more toxic than MWNTs, possibly due to their geometry [67]. Poland et al. [120] showed that non-functionalized long MWNTs pose a carcinogenic risk in mice.


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The report systematically studied various commercially available MWNTs with different lengths. Upon administration at a concentration of 100 mg/mL via peritoneal injection in mice, MWNTs demonstrated asbestos-like, length-dependent, pathogenic behavior. The longer length of MWNTs is believed to be the reason for the inflammatory response and granuloma formation within a week post-injection due to less aggregation and increased macrophage uptake. 4.3.4 Magnetic Nanoparticles The chemical toxicity of iron and its derivatives is well studied [121, 122]. Iron oxides have been shown to degrade in vivo according to natural iron pathways. Normal human tissues contain iron or iron oxides in the form of hemosiderin, ferritin, and transferrin [123]. Therefore, numerous iron oxide-based magnetic nanoparticles (MNPs) have been reported and studied for MRI applications over the last two decades [60–62]. SPIOs must be functionalized during the synthesis process for biocompatibility before medical use [59]. A variety of methods have been developed to encapsulate SPIO particles within a sheath of benign polymers such as dextran [124], polysaccharides [125], PEG, and polyethylene oxide [126]. Weissleder and co-workers reported the proof of concept profiling 50 different iron oxide based nanoprobes. The in vitro assays addressed the effect of the core composition, coating, and surface functionalization on the interactions of nanoparticles with the biological environment [70]. All the nanoparticle formulations were organized into clusters based on their biological activity and compared to Feridex as an FDA approved control [70]. The data from the four cell toxicity assays, five different cell types, and four different doses and incubation times showed that the core composition had a strong contribution to the biological effects. For example, nanoparticle formulations with carboxylic or ethylenediamine surface coatings had similar biological acitivty. The analysis of the data showed that crosslinked iron oxide (CLIO)-amine was in the same cluster as dextran-coated Feridex even though their surface coatings were significantly different. More importantly, results showed that these two formulations did not affect monocytes in the blood and spleen in contrast to the control sample that was clustered in a different group based on in vitro assays. In addition, Jain et al. [127] did not observe significant differences in the liver enzyme activity in vivo compared to the group of mice injected with saline. Overall, the histology and enzymatic activity data suggested that the oxidative stress was minor and did not affect cellular and tissue integrity. Iron oxide concentration in liver did not exceed 300 ␮g/g of tissue during the experimental period of 3 weeks, which included the redistribution of iron through protein binding. Iron oxide concentrations were 10 times lower than the toxic concentration reported to develop cirrhosis and hepatocellular carcinoma and 4 times lower than the dose used for Feridex in humans (2.6 vs. 10 mg/kg, respectively). Many iron oxide-based MNPs are thought to have suitable toxicity profiles and are now being evaluated in clinical trials. The promising results of the Phase I clinical trial using ultrasmall superparamagnetic iron oxide colloids (USPIOs) BMS180549 showed mild to moderate side effects for 45% of the volunteers [128, 129] and the most common adverse event was urticaria. This is possibly due to the dosage of iron oxide NPs used for diagnostic imaging (1–2 mg Fe/kg bodyweight), which was less than the normal iron store and dose required to develop chronic iron toxicity. The reported iron concentration for cirrhosis and hepatocellular carcinoma is over 4 mg of Fe per gram of wet liver [63]. These SPIO formulations passed the standard toxicological and pharmacological requirements, most


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likely due to the low doses used in humans and their use as a single-dose contrast agent. However, patients injected with SPIO generated anti-dextran antibodies and developed allergic reactions. 4.4 NANOPROBE CLINICAL TRANSLATION Two SPIOs and one USPIO are currently approved by the FDA for clinical use. In 1996, Feridex I.V. became the first FDA approved nanoprobe for imaging liver lesions based on the differential amount of Kupffer cells in metastatic tumors in the liver, allowing detection of small metastases using magnetic resonance imaging (MRI). Feridex is a SPIO nanoparticle (120–180 nm) coated with dextran (MW = 10 kDa) given at a dose of 0.56 mg Fe/kg and has a circulation half-life of ∼1 hour in humans. In addition, Resovist, which is an SPIO formulation coated with carboxydextran (Molecular weight = 20 kDa) dosed at ∼2.6 mg/kg, was approved in 2001 for the European market. The advantage of Resovist is safety because it allows rapid injection without cardiovascular side effects and lumbar pain. This is due to its smaller size (∼60 nm) and increased cell internalization. In June 2009, the FDA approved the first USPIO nanoprobe, Ferumoxytol, which is used for the treatment of iron-deficiency anemia in adult patients with chronic kidney disease. Clinical data showed that patients treated with Ferumoxytol demonstrated greater hemoglobin enhancement compared to iron given orally. In addition, many USPIO magnetic nanoparticles (Table 4.1) are currently in different clinical trials as contrast agents for several different applications. In TABLE 4.1 Various Nanoprobes Under Clinical or Preclinical Investigations Trade Name

Composition

Status

Indication/Application

Size (nm)

Circulation Time (h)

Feridex I.V. (Ferumoxides AMI-25) Combidex (Ferumoxtran10, AMI-227, BMS-180549) Gastromark (Ferumoxsil AMI-121) Resovist (Ferucarbotran SHU-555A) Supravist (Ferucarbotran SHU-555C) Ferumoxytol code 7228

Dextran-coated SPIO

Approved

Liver imaging, cellular labeling

120–180

2

Dextran-coated USPIO

Phase IV

15–30

24–36

Siloxane-coated SPIO

Approved

Lymph nodes, RES directed liver diseases, macrophage imaging, cellular labeling Bowel marking, oral GI imaging

300

Oral

Carboxydextrancoated SPIO

Approved

Liver imaging, cellular labeling

60

2.4–3.6

Carboxydextrancoated SPIO

Phase III

Blood pool agent, cellular labeling

21

6

Cyclomethyl dextran-coated USPIO Citrate-coated VSSPIO Pegylated colloidal gold nanoparticles

Phase II

Macrophage imaging, blood pool agent

30

10–14

Phase II

Blood pool agent, cellular labeling Tumor therapy and tumor vasculature imaging

7

0.5–1.5

30

2–6

VSOP-C184 Aurimune (CYT-6091)

Phase I


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general, USPIOs have longer circulation times and are mostly used for cancer metastases diagnosis. For example, Ferumoxtran-10 was shown to be a very sensitive and specific agent in human cancer trials allowing accurate diagnosis of metastatic lymph nodes with a reported circulation half-life of ∼24 h [130]. Ferumoxtran-10 is currently being tested in 8 clinical trials for tissue neoplasm (brain and bladder), aortic aneurysm, and prostate metastases diagnosis (www.clinicaltrials.gov) in Europe. Aurimune (CYT-6091) is the only system based on materials other than iron oxide that has reached clinical trials. Aurimune delivers TNF-␣ bound to PEG-coated gold nanoparticles (∼27 nm) for solid tumor therapy [131] and possible imaging abilities. TNF-␣ is a potent cytokine with antitumor cytotoxicity which requires incorporation into a nanocarrier formulation to reduce systemic toxicity. The toxicity data from the Phase I trial showed that gold nanoparticles could deliver 3 times more TNF-alpha systemically than a free dose of TNF-alpha. The TNF-alpha dose was reported to be 1.2 mg and considered to be in the therapeutic range used previously in isolated limb perfusion (ILB).

4.5 FACTORS AFFECTING THE BIODISTRIBUTION AND PHARMACOKINETICS Nanoparticle-based technology is being increasingly employed in drug delivery and imaging applications. For most applications, intravenous administration of nanoprobes is required. Compared to in vitro studies, different challenges arise in vivo due to the increased complexity of the organism. The unique physiochemical properties of nanoprobes include size, shape, chemical composition, surface chemistry, porosity, and agglomeration state. These properties control their interactions with the biological environment. In addition to toxicity, understanding the fate of nanoprobes in a complex biological environment is very important for potential clinical translation. Biodistribution and pharmacokinetic studies give a detailed knowledge about the fate of nanoprobes in the body, including circulation time, excretion pathway, degradation time, and plasma protein binding. We discuss the main factors affecting nanoprobe biodistribution and pharmacokinetics such as size, shape, surface functionality/coating, and charge. 4.5.1 Effect of Size In general, nanoparticles enter the body through the vein, skin, lungs, or gastrointestinal adsorption. Circulating nanoparticles in the body will differentially distribute/accumulate in major organs according to cell interaction properties and pathological defects [132].For example, filtration in the spleen and liver is dependent on the opsonization effect and related to the size of the nanoparticles. The endothelial barrier controls and prevents the diffusion of circulating nanoparticles out of the bloodstream. Blood vessel defects can form under pathological conditions, leading to enhanced permeability and differential accumulation of nanoparticles at specfic site in the body. This phenomenon can be taken advantage of to facilitate nanoparticle (10-500 nm) accumulation in cancer tissue due to the relatively leaky tumor vasculature and absence of a lymphatic network, resulting in the enhanced permeability and retention effect (EPR). Hence the effect of particle size on interactions with plasma components, blood cells, endothelium, and distribution in various tissues are of great interest.


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There are only a few reports of QD biodistribution and pharmacokinetics parameters. However but it is well established that QDs accumulate significantly in the reticuloendothelial system (RES), including the liver, spleen, and the lymphatic system [135–137]. Kim et al. [39] reported a critical size of ∼15–19 nm for the retention of QDs in the sentinel lymph node during imaging of the lymphatic system. The injection of QDs of different colors at different intradermal locations allowed imaging of their drain to common nodes [138, 139]. Similarly, it was reported that QDs smaller than 9 nm could migrate into the lymphatic system with up to 5 nodes showing fluorescence [140]. QDs with size ∼9 nm could be entirely eliminated from the kidneys and directly extravasate out of blood vessels into interstitial fluid [140]. Another study found that the renal clearance of QDs was closely related to hydrodynamic diameter and the renal size threshold was defined as ∼5–6 nm [141]. The blood half-life of QDs varied from 48 min to 20 h for sizes ranging from 4.4 to 8.7 nm, respectively, demonstrating rapid urinary excretion [141]. Smaller QDs (∼5 nm) were found in detectable amounts only in the liver (4.5%) and kidneys (2.6%). Larger QDs (∼8 nm) showed higher uptake in the liver (26.5%), lungs (9.1%), and spleen (6.3%) 4 h post-intravenous injection. This was possibly due to longer circulation times allowing higher accumulation in tissues [141]. However, more studies need to be carried in vivo to determine the effects of QD size. Many reports on the biodistribution of MNPs examined the effect of particle size [142–144]. In vivo biodistribution data for five neutral particles with different sizes ranging from 30 to 90 nm was reported. [142] and the results showed that smaller nanoparticles (10 min for 50% clearance) and less uptake by the liver (∼20% for small particles and >50% for larger particles). After 20 min, it was found that the liver uptake increased as the size of the NPs increased. Pharmacokinetic profiles were studied with nanoparticles of three different sizes ranging from 46 to 75 nm to determine the clearance time. It was found that increasing the particle size decreased the plasma half-life, with 46-nm particles showing 50% clearance from the bloodstream in the first 10 min in contrast to only 5 min for 90-nm particles [142]. Neuberger et al. [143] reported that 200-nm MNPs were cleared faster than MNPs of sizes 30–100 nm. It was also demonstrated that for iron oxide particles smaller than 40 nm in diameter, both biodistribution and blood half-life were mostly controlled by the coating material rather than the mean particle size [11, 145]. For example, circulation half-life of two magnetic nanoparticles with the same polymeric surface coating, Ferumoxtran-10, had a longer circulation time compared to Feridex due to its smaller size (∼15–30 nm vs. ∼120 nm, respectively). The slower clearance of Ferumoxtran-10 was believed to be due to larger particle size and/or surface charge affecting degradation and biodistribution. Blood half-lives of magnetic nanoparticles in human are reported to be up to 2 days and USPIOs were found to have the longest circulation time partially due to their smaller size and lower accumulation in the liver. Functionalizing the surface of MNPs with targeting ligands can significantly affect the circulation half-life and biodistribution. Reddy et al. [146] found that MNPs of 40 nm showed increased tumor contrast half-life in mice from 39 min to 123 min by attaching a targeting F3 ligand. Montet et al. [147] showed that the MNP–RGD conjugates with sizes 28 and 36 nm were found to have blood half-lives of 180 and 207 min in rats. Biodistribution studies 24 h after IV administration showed accumulations in the liver, spleen, skin, kidneys heart, and tumor [147]. According to the reported data, the overall size of MNPs should be smaller than 200 nm to evade rapid splenic filtration [148], but larger than ∼5 nm to avoid renal clearance [141].


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Carbon nanotubes have been shown to penetrate into the lungs and cross the blood–brain barrier, leading to neurotoxicity. The first study of CNTs in animals to compare tissue distribution characteristics after subcutaneous, oral, and intravenous administration was performed using iodine-labeled hydroxyl-functionalized carbon nanotubes (125 I-CNT) with a length of 300 nm. It was found that CNT accumulated in the stomach, kidneys, and bone similar to small molecules. The results showed no tissue damage and excretion through urine [149]. Later, this same group reported that the functionalized CNTs showed persistent liver accumulation after IV injection [150]. Additional biodistribution data using indiumlabeled carbon nanotubes (111 I-CNT) also showed accumulation in kidneys, bone, muscle, and skin. The circulation half-life was found to be ∼3 h with rapid clearance through urine. In a recent report, yttrium-labeled carbon nanotubes (86 Y-CNT) with 42 ± 17 nm length were shown to be cleared from the bloodstream within 3 h when injected intravenously in mice [151]. The PET images indicated that the major sites of accumulation of 86 Y-CNT were the liver (18%), spleen (14%), kidneys (8%), and to a less extent bone (2%). The uptake of CNTs in the kidneys, liver, and spleen was slightly lower when the CNTs were administered via intraperitoneal (IP) injection, suggesting a relatively slow egress from the intraperitoneal compartment into the vascular compartment. It was observed that the clearance of CNTs from the kidneys was much faster than from the spleen and liver. Elgrabli et al. [152] used commercial uncoated MWNTs with a diameter of 20–50 nm and length of 500–2000 nm to study the biodistribution in rats. The results showed CNT bio-persistence and clearance 6 months after respiratory administration. The MWNTs were intratracheally instillated and 53% of the initial dose accumulated in the lungs after 24 h and 16% of MWCNTs were still found in the lungs after 6 months. However, most of the biodistribution studies were carried out using a radiolabel tracking method. Therefore, the dissociation of the label could affect the measurements. There are few reports describing the size-dependent cellular uptake and biodistribution of gold NPs over the last decade. Chithrani et al. [96] reported in vitro cellular uptake of GNPs with different sizes in HeLa cells. It was found from the uptake kinetic studies that the uptake half-lives of 14-, 50-, and 74-nm colloidal gold nanoparticles were 2.1, 1.9, and 2.24 h, respectively. De Jong and co-workers studied size-dependent (10-, 50-, 100-, and 250-nm) biodistribution of spherical gold nanoparticles after intravenous administration in rats [97]. A clear difference was observed between the biodistribution of the 10-nm particles and the larger NPs. Small gold nanoparticles (10 nm) were found in various organs including the blood, kidneys, testes, thymus, heart, lungs, and brain, whereas larger particles (>10 nm) were only detected in the blood, liver, and spleen after 24 h [97]. However, Wolfgang and co-workers studied the biodistribution of gold NPs with 1.4- and 18-nm sizes in rats after intravenous injection and found no clear differences between the nanoparticle sizes tested [104]. Similar accumulation and biodistribution of the NPs was observed in the liver, blood, carcass, spleen, skin, kidneys, urine, and feces 24 h post-injection. Intratracheal administration of the same nanoparticles using rats as an animal model showed 99.8% and 91.5% accumulation in the lungs after 24 h for 18-nm and 1.4-nm GNPs, respectively. Small amounts of the instilled 1.4-nm NPs (0.6–3.3% I.D.) were detected in the blood, urine, skin, and carcass, whereas no detectable amounts of larger nanoparticles (18 nm) were found [104]. Hillyer and Albrecht [153] showed in mice that metallic colloidal gold nanoparticles of different sizes (4, 10, 28, and 58 nm) distributed to other organs after oral administration in mice. The 4-nm GNPs showed differential accumulation in the kidneys, liver, spleen, lungs, and even in the brain in contrast to the 58-nm particles detected solely inside the gastrointestinal tract. Hainfeld et al. [51] subcutaneously injected 1.9-nm GNPs


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into mice and examined their long-term distribution (11 and 30 days) in various organs. The biodistribution of the gold nanoparticles in an EMT-6 syngeneic mammary carcinoma xenograft mouse model showed very low retention of GNPs in the liver and spleen due to elimination by the kidneys after 24 h. Pharmacokinetic studies revealed a biphasic clearance, with a drop of 50% between 2 min and 10 min post-injection followed by a slower decrease of another 50% between 15 min and 1.4 h. Accumulation of the NPs in the kidneys (10.6% I.D.), tumor (4.2% I.D.), liver (3.6% I.D.), and muscle (1.2% I.D.) was evaluated 15 min post-injection. In another report, Vijaya Kattumuri et al. [154] used 15–20-nm size gum arabic stabilized GNPs to study biodistribution in larger animals such as pigs. Following intravenous administration of the GNPs (0.8 mg/kg), identical amounts (∼50 ppm) of Au were observed in the lungs and liver after 24 h, while 40 ppm of gold was measured in the spleen. After 72 h, 43–69% of the administered dose was retained in the liver while only 1–2% was observed in the kidneys, indicating slow clearance of GNPs. 4.5.2 Effect of Shape Most NPs exhibit a spherical shape as a result of surface energy minimization during their synthesis. The advent of mimicking nature with nanoparticles of different shapes such as a virus or bacterium is now possible due to the development of new fabrication processes. The ability to make particles with shapes other than spheres is opening a path to new design solutions for systemically administered particulates. Decuzzi et al. [155] reported that the intravascular journey of the particle can be broken down into three events: (1) margination dynamics, (2) firm adhesion, and (3) control of internalization. This report compared the predictions of mathematical models and showed that the particle geometry plays an important role in all three events [155]. In addition, recent studies performed using polystyrene nanoparticles of different shapes showed that the phagocytosis pathway by macrophages exhibits a strong dependence on shape [156, 157]. A recent report used a physiologically based pharmacokinetic (PBPK) model along with experimental data of biodistribution of QDs with various shapes, sizes, and exposure routes, to predict the biodistribution of other QDs [158]. The model estimated partition coefficients for various tissue concentrations of QDs in the blood, kidneys, liver, muscle, and skin using the experimental data from commercial QD705. The ellipsoid particles showed increases in the steady-state concentration of QDs in the liver and kidneys, similar to experimental observations. This model considered that the QDs initially distributed to the kidneys, then redistributed to other compartments with higher partition coefficients but much slower flow rates per mass of tissue as these compartments approach steady-state concentrations. Gold nanoparticles can also be made in different shapes such as rods and pyramids with an aspect ratio of 1:1 to 1:5 [96]. The cellular uptake in HeLa cells was studied with various shapes and found that spherical particles have a higher probability of uptake than rod-shaped nanoparticles with aspect ratios 3 and 5. Niidome et al. [159] studied the biodistribution of PEG(5000)-functionalized gold nanorods (65-nm length and 11-nm width) and surfactant-stabilized gold nanorods in mice. The results showed that the pegylated gold nanorods had a blood circulation time of 30 min (∼50% I.D.), while the residual CTABfunctionalized nanorods in blood were significantly lower (∼5%) [159]. No detectable amounts of gold were present in the blood, while 35% was accumulated in the liver and very small amounts were in the lungs, spleen, and kidneys, showing the clearance of gold nanorods after 72 h. In contrast, CNTs, which are known to have high aspect ratios, were shown to have a rapid blood clearance (circulation half-life = 1 h) in rabbits due to their


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rapid renal excretion and accumulation in the liver [49]. Another study showed a blood circulation half-life of 3 h for the water-soluble DTPA-functionalized SWNTs in mice after IV administration [160]. 4.5.3 Effect of Surface Coating and Charge Other than size and shape, the nanoparticle surface coating and charge can modulate the in vivo fate of nanoprobes. NP coatings affect surface properties such as surface charge (zeta potential), surface functionalities, and degree of hydrophilicity. Surface modification of QDs is necessary due to their low solubility in polar solvents. There are many reports addressing the surface modification of QDs with a variety of coatings such as small molecules or encapsulation in amphiphilic polymers to increase surface hydrophilicity, reduce nonspecific binding, and prolong blood circulation [38, 89, 161, 88, 162]. QD structure and surface properties have been found to strongly impact plasma halflife. The half-life of anionic, carboxylated QDs in the bloodstream of mice was significantly increased from 4.6 min to 71 min by coating QDs with PEG polymer chains of MW 5000 [135]. Schipper et al. [163] evaluated the biodistribution of commercially available PEGcoated CdSe QD525 and QD800 in mice. Both types of QDs rapidly accumulated in the liver within 6 min postinjection. In mice, PEG-coated CdSe/ZnS QDs were rapidly removed from the bloodstream into organs of the RES with detection possible for up to 4 months post-injection using fluorescence imaging [135]. TEM studies on the tissues revealed that these QDs retained their morphology, suggesting QDs are stable in vivo given the proper coating. The blood circulation half-life of these QDs was significantly increased by coating QDs with poly(acrylic) or a short PEG(750), while the half-life increased to 72 min with an increase in the length of PEG(5000) as determined from venipuncture studies [135]. Multiple approaches have been used to attach ligands to the surface. For example, heterofunctional ligands have been attached to the surface of QDs with the hydrophilic group exposed [164, 165]. In addition, biological molecules such as monoclonal antibodies (J591) or EGF receptor (erbB1) have been attached to the surface, serving the dual purpose of increasing surface hydrophilicity and acting as a targeting ligand [161, 166, 167]. Fc fragments of antibodies conjugated to QDs were reported to have longer circulation times due to the reduction of nonspecific interactions [168]. Another report demonstrated slower removal of albumin-coated QDs from the bloodstream before accumulation in the liver compared to QDs without albumin [137]. Surface charge will lead to different mechanisms of interaction with macrophages and may affect the intracellular fate of internalized NPs. Even though cationic NPs show increased cell internalization, supramagnetic particles with negative surface charge were found to exhibit a high but nonspecific affinity for the plasma membrane, favoring adsorption and endocytosis in endosomal compartments of HeLa cells [169]. In another report, rpositively-charged MNPs were prepared by the coating of monocrystalline iron oxide nanoparticles(MIONs) with cationic poly-l-lysine. The blood half-life was found to be only 1–2 min in comparison to 2–3 h for the uncharged variant [170]. Small neutral MION particles distributed to lymph nodes, whereas the positively-charged particles of similar size were found to be rapidly taken up by the liver [63]. Jallet and co-workers carried out a systematic study to analyze the effect of charge on MNPs as contrast agents for MRI [142]. When the surface charge of these nanoparticles was varied from neutral to negative, there was a slight decrease in the particle size while the change to a positive charge led to an increase in the size of the MNPs. The biodistribution results showed that charged


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particles had greater accumulation in the liver relative to neutral particles. Twenty minutes after injection of neutral MNPs into the bloodstream via intravenous injection, 40% of the NPs remained in the bloodstream. In contrast, only 10% of the negatively charged particles remained in the blood. Uptake of positively charged particles (∼60%) was higher than neutral particles (40%), but lower than the negatively charged MNPs (∼75%) in the liver. The uptake of MNPs in the liver was almost 3 times higher (∼75%) for negatively charged MNPs compared to neutral MNPs [142]. MNPs of 100 nm showed 20% more uptake when the surface charge was positive compared to neutral [142]. Citrate-coated iron oxide NPs (8.7 nm) had a blood half-life of 1 h in humans due to their highly anionic surface charge, while a commercially available Ferumoxtran-10 had a blood half-life of 24–36 h in humans and 2–3 h in rats [11]. Similarly detectable amounts of charged particles were observed in the carcass (bones, skin, muscles, and the whole head). Overall, this study concluded that the negative charge on the particle surface resulted in enhanced liver uptake [142], while the MNPs with neutral surfaces were taken up the least by the liver. More importantly, coated magnetic nanoparticles remained in the liver for a few months with sustained contrast properties and were shown to be mainly eliminated through feces in human studies. CNTs were functionalized with various groups on the surface to improve water solubility. Yuliang and co-workers used hydroxyl-functionalized, iodine-labeled carbon nanotubes (125 I-CNT), which showed blood clearance and accumulation in the stomach, kidneys, and bones [149]. Amine-functionalized CNTs with indium labeling cleared the blood compartment [160] and all tissues within 3 h except for the kidneys, liver, and spleen. Rapid clearance of indium-labeled CNTs and significant accumulation in the kidneys, liver, spleen, and, to a small extent, bone was reported within 1 h after administration. Wenxin and co-workers reported water-soluble MWNTs by surface functionalization with glucosamine (MWNT-G) [171]. MWNT-G as injected into mice by intraperitoneal injection quickly spread to measurable levels in the blood, heart, lungs, liver, spleen, kidneys, stomach, intestines, coat, muscle, enterogastric area, and feces, behaving like a small molecule. A significant amount of total activity was retained throughout the 24-h study, particularly in the stomach. Samples collected from urine and feces showed >70% activity after 24 h, indicating MWNT-G was excreted predominantly via urine and feces. The pharmacokinetic profiles indicated a blood circulation half-life of about 5.5 h. Another study by Liu et al. [172] showed PEG-wrapped SWNTs can escape the RES for a blood circulation half-life up to 2 h. A more recent study revealed the increase in blood circulation time from 2 to 15 h when branched (MW = 7 kDa) PEG is used instead of linear (MW ranging from 2 Da to 12 kDa, methoxy end group) [119]. When the branched PEG is covalently bound to SWNTs, the blood circulation time is prolonged to 15.3 h and a low hepatic uptake was observed in the biodistribution study [118]. Most of the SWNTs were shown to accumulate in the spleen and liver in contrast to other studies using a radiolabeled tracking method. PEG-SWNTs were found to be distributed throughout most of the organs within 1 h and there were still considerable amounts of PEG-SWNTs present in the liver and spleen after 50 days. However, this study confirmed earlier reports of feces as the major excretion path. McDevitt et al. [173] showed significant difference in biodistribution and pharmacokinetics for targeted and nontargeted CNTs. The targeted CNTs showed more accumulation in the spleen and liver while the nontargeted CNTs showed more accumulation in the kidneys. Gold nanoparticles tend to agglomerate in a few hours without proper stabilizers or coatings. Typical stabilizers are surfactants, organic carboxylates, long-chain amines or thiols, sugars, carbohydrates, and proteins [154]. Coating gold nanoparticles with gum


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arabic, a hydroxyproline-rich arabinogalactan, has been found to have enhanced kinetic inertness and high in vivo stability. These nanoparticles were found in the lungs, liver, and spleen within 30 min [154] and significant amounts of NPs were present in the liver 72 h after intravenous administration. Another report showed negatively charged GNPs obtained by coating with water-soluble sulfonated phosphane accumulated in the lungs (>90%) 24 h after intratracheal instillation, while 47% were found in the liver when administered via intravenous injection [104]. However, more systematic studies of biodistribution of gold nanoparticles with variations in surface charge are needed before they are tested in the clinic.

4.6 THERAGNOSTIC NANOPROBES Nanoparticle delivery systems are becoming increasingly recognized as a potential therapeutic vehicle with multiple examples approved by the FDA for therapy. The similarities to nanoprobes have led to the design of multifunctional nanoparticle systems able to perform imaging and therapy simultaneously. In general, the therapeutic agent adsorbed on the surface of the nanoprobe is directly exposed to the biological environment and delivered at a dose controlled by the surface loading, which is reported to be in the range of 10–100 molecules in most cases. There are two promising therapeutic approaches (Fig. 4.2) that have been combined with imaging. The first approach is based on the combination of imaging and hyperthermia. The second approach is based on the combination of imaging and delivery of cytotoxic drugs. We discuss both strategies for the combination of therapy and imaging. Currently, Aurimune (CYT-6091) is the only multifunctional nanoparticle with imaging and delivery properties that has reached the clinic. CytImmune Sciences Inc. developed a nanoparticle system with the ability to bind TNF-␣ on the surface of gold nanoparticles through electrostatic interactions. Preliminary SEM micrographs of nanoparticles accumulated in breast tumor tissue sections in contrast to healthy tissues showed targeting of the nanoparticles by the EPR effect. Other formulations are still in the discovery stage using combinations of drugs such as TNF-␣ with paclitaxel, doxorubicin, or interleukin–12. Although the load of therapeutic agent is reported to be several hundreds of molecules,

FIGURE 4.2 Various promising nanoprobes used for theragnostics (see Refs. 175–183).


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recent data from a Phase I clinical trial reported that gold nanoparticles could deliver a therapeutic dose (www.cytimmune.com). Most other theragnostic nanoprobes are in early discovery/development stages, but the early clinical results are clearly demonstrating the potential opportunities for the development of theragnostic agents. Gold nanoprobes have been used mostly as a hyperthermia therapeutic agent by heating the tumor through the application of a magnetic field. The local increase in temperature kills the surrounding cells. In vivo results [174] of nanoshell-mediated NIR (near-infrared) thermal therapy showed that the nanoparticles induced irreversible cancer tissue damage at a temperature ∼40 ◦ C in a human breast cancer xenograft. However, the distribution of nanoparticle in the tumor might significantly affect the control of the local temperature. Similarly, Schwartz et al. [175] reported efficient therapy in large animals for brain cancer. The results showed that the temperature reached ∼70 ◦ C in tumor tissues and ∼50 ◦ C in normal white and grey matter, which is expected to significantly damage nondiseased areas of the brain. In addition, Ross and co-workers reported targeted iron oxide based nanoparticles as a delivery system (∼40 nm) of photofrin, which can be activated. . . with wavelength light (∼630 nm) to treat brain cancer [146]. Light irradiation activates the photosensitizer to produce a single oxygen leading to apoptotic and necrotic cytotoxicity. Photofrin loading on the nanoparticles was ∼4% w/w and was administered intravenously at a dose of 7 mg/kg using a rat 9L tumor xenograft model implanted into the animal brain. Tumor size was significantly reduced and the 50% survival time was extended to at least double that observed in the nontargeted nanoparticle control group [146]. MRI was used to monitor changes in the tumor and the nanoparticles showed magnetic resonance contrast of the targeted tumor and therapeutic efficacy of photofrin [146]. Similarly, Weissleder and coworkers have reported a macrophage-targeted theragnostic system based on photodynamic therapy for cardiovascular diseases [176, 177]. A potent sensitizer, 5-(4-carboxyphenyl)10,15,20-tryphenyl-2,3-dihydroxychlorin (TPC), was covalently attached to the surface of the iron oxide nanoparticle. The load was estimated to be three photosensitizer molecules per nanoparticle and the results showed efficient killing of macrophages [177]. Others have combined imaging and therapeutic functions using drug–material interactions as a loading strategy. For example, Farokhzad and co-workers reported the loading of doxorubicin, a potent chemotherapeutic agent, through intercalation between base pairs of aptamers conjugated to the surface of quantum dots [178]. In this case, aptamers were used as a specific targeting ligand to cancer cells and molecular carrier of the chemotherapeutic drug [178]. This system was precisely designed to have doxorubicin loaded on the surface quenching the quantum dot fluorescence. Therefore, the quantum dot lit up only when doxorubicin was released, allowing simultaneous delivery of the chemotherapeutic drug into specific cells and monitoring of the delivery using fluorescent imaging [178]. Adair’s group [179, 180] reported intracellular imaging and delivery using biocompatible calcium phosphate nanoparticles (∼27 nm). This system provided controlled drug delivery through pH dissolution of calcium phosphate in the acidic tumor environment. In vitro studies showed high uptake of the nanoparticles in bovine aortic endothelial cells and efficient inhibition of human vascular smooth cells using hexanoyl-ceramide (Cer-6) as a model drug. This technology is now being developed by Keystone Nano for imaging and delivery of therapeutic agents. Recently, Perez and co-workers used poly(acrylic acid) (PAA)-coated iron oxide nanoparticles loaded with paclitaxel, a potent chemotherapeutic agent, and an NIR fluorescent dye to combine optical imaging, magnetic resonance imaging, and drug delivery [181]. The nanoparticle was functionalized with a targeting


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ligand to specifically bind cancer cells. Nanoparticle size was characterized to be ∼90 nm and taxol loading was 11 molecules per nanoparticle. Taxol release kinetics were accelerated under esterase and acidic pH -mediated degradation. In addition, the results showed multimodal imaging capabilities using NIR and MRI in vitro. Other groups have reported quantum dots delivering nucleic base therapeutics, although endosomal escape and unpacking still remain a challenge. Recently, Gao and co-workers reported the surface modification of quantum dots with tertiary amine groups for the intracellular delivery of siRNA [182]. The results showed uptake and distribution of quantum dots in the cell cytoplasm. Gene silencing efficiency using formulations suspended with and without serum was better than lipofectamine and no significant toxicity of the vehicle was reported. The quantum dot gene silencing efficiency is reported to be dependent on the ratio of carboxylic group/tertiary amine groups, which control endosomal escape. Quantum dots have also been developed to monitor RNAi delivery and improve gene silencing using cationic liposome [183].

4.7 CONCLUSION Early detection is a critical component of improving patient survival in many diseases. The development of new imaging systems and imaging agents has significantly improved the ability to detect disease earlier in its progression. Nanoprobes are an emerging technology that has the potential to increase the sensitivity and specificity of imaging systems. Early designs of nanoprobes have shown great promise, but there are significant concerns over the toxicity of these probes since they are nanomaterials composed of metallic or inorganic components. Despite toxicity concerns, nanoprobes have already reached the clinic for the diagnosis of liver lesions and cancer metastases in lymph nodes. As synthesis and modification techniques improve and a greater understanding of interactions between these nanomaterials and tissues in the body is reached, the capability to design safer nanoprobes should be possible. The ability to target nanoprobes should allow their clinical applications to expand from liver lesions to other metastatic sites, such as the brain and bones. Another promising application of nanoprobes is as theragnostic agents, combining imaging and therapeutic modalities. These systems have the potential to simultaneously image and treat disease, as well as exploit synergistic cytotoxicity by combining approaches such as hyperthermia therapy with chemotherapeutic agents. Advanced designs of nanoprobes and theragnostic agents are anticipated to significantly improve patient care and compliance. The multidisciplinary approach of combining chemistry and bioengineering with toxicology and clinical research has the potential to lead to novel agents with advanced, multifunctional properties.

ACKNOWLEDGEMENT The authors acknowledge funding from National Institutes of Health Grants CA119349 and EB003647, and the David-Koch-Prostate Cancer Foundation Award in Nanotherapeutics. EMP is supported by a National Defense Science and Engineering Graduate Fellowship (NDSEG). OCF has a financial interest in BIND Biosciences and Selecta Biosciences.


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173. McDevitt, M. R.; Chattopadhyay, D.; Kappel, B. J.; Jaggi, J. S.; Schiffman, S. R.; Antczak, C.; Njardarson, J. T.; Brentjens, R.; Scheinberg, D. A. Tumor targeting with antibodyfunctionalized, radiolabeled carbon nanotubes. J. Nucl. Med. 2007, 48, 1180–1189. 174. Hirsch, L. R.; Stafford, R. J.; Bankson, J. A.; Sershen, S. R.; Rivera, B.; Price, R. E.; Hazle, J. D.; Halas, N. J.; West, J. L. Nanoshell-mediated near-infrared thermal therapy of tumors under magnetic resonance guidance. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 13549–13554. 175. Schwartz, J. A.; Shetty, A. M.; Price, R. E.; Stafford, R. J.; Wang, J. C.; Uthamanthil, R. K.; Pham, K.; McNichols, R. J.; Coleman, C. L.; Payne, J. D. Feasibility study of particle-assisted laser ablation of brain tumors in orthotopic canine model. Cancer Res. 2009, 69, 1659–1667. 176. McCarthy, J. R.; Jaffer, F. A.; Weissleder, R. A macrophage-targeted theranostic nanoparticle for biomedical applications. Small (Germany) 2006, 2, 983–987. 177. Jaffer, F. A.; Libby, P.; Weissleder, R. Optical and multimodality molecular imaging: insights into atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 2009, 29, 1017–1024. 178. Bagalkot, V.; Zhang, L.; Levy-Nissenbaum, E.; Jon, S.; Kantoff, P. W.; Langer, R.; Farokhzad, O. C. Quantum dot-aptamer conjugates for synchronous cancer imaging, therapy, and sensing of drug delivery based on bi-fluorescence resonance energy transfer. Nano Lett. 2007, 7, 3065–3070. 179. Kester, M.; Heakal, Y.; Fox, T.; Sharma, A.; Robertson, G. P.; Morgan, T. T.; Altinoglu, E. I.; Tabakovic, A.; Parette, M. R.; Rouse, S.; Ruiz-Velasco, V.; Adair, J. H. Calcium phosphate nanocomposite particles for in vitro imaging and encapsulated chemotherapeutic drug delivery to cancer cells. Nano Lett. 2008, 8, 4116–4121. 180. Morgan, T. T.; Muddana, H. S.; Altinoglu, E. I.; Rouse, S. M.; Tabakovic, A.; Tabouillot, T.; Russin, T. J.; Shanmugavelandy, S. S.; Butler, P. J.; Eklund, P. C.; Yun, J. K.; Kester, M.; Adair, J. H. Encapsulation of organic molecules in calcium phosphate nanocomposite particles for intracellular imaging and drug delivery. Nano Lett. 2008, 8, 4108–4115. 181. Santimukul, S.; Charalambos, K.; Jan, G.; Perez, J. M. Drug/dye-loaded, multifunctional iron oxide nanoparticles for combined targeted cancer therapy and dual optical/magnetic resonance imaging. Small 2009, 5, 1862–1868. 182. Yezhelyev, M. V.; Qi, L.; O’Regan, R. M.; Nie, S.; Gao, X. Proton-sponge coated quantum dots for siRNA delivery and intracellular imaging. J. Am. Chem. Soc. 2008, 130, 9006–9012. 183. Chen, A. A.; Derfus, A. M.; Khetani, S. R.; Bhatia, S. N. Quantum dots to monitor RNAi delivery and improve gene silencing. Nucleic Acids Res. 2005, 33, e190.


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PART II

NANOPARTICLES FOR SINGLE MODALITY MOLECULAR IMAGING


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CHAPTER 5

Computed Tomography as a Tool for Anatomical and Molecular Imaging PINGYU LIU Palo Alto Unified School District, Palo Alto, California, USA

HU ZHOU Community Cancer Center of Roseburg, Roseburg, Oregon, USA

LEI XING Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, USA

5.1 INTRODUCTION X-ray and computed tomography (CT) imaging play a pivotal role in the diagnosis, staging, treatment planning, and image-guided intervention of various diseases. They are at the foundation of contemporary medical imaging and small animal imaging for biomedical research. It is estimated that 70–80% of all imaging procedures in medical applications entail the use of X-ray or CT imaging. The simplest implementation of X-ray imaging is the “plain film imaging,” and the next most common X-ray imaging approach is CT, which allows cross-sectional imaging of the body with exquisite depiction of anatomic detail. There are about 35,000 X-ray CT instruments installed worldwide for clinical applications. One of the primary advantages of X-ray imaging is the inherently simple basis of image contrast, which is the absorption of X-rays. For this reason, it has become the modality of choice in most radiology clinics. X-ray imaging can be used to image virtually every part of the body and is used for diagnosing orthopedic cases, cancer, heart disease, circulatory disease, and respiratory disease. In addition, it is also used as an aid for therapeutic interventions and as a means to follow the effects of treatment. During the last few years, innovations in X-ray detector technology have provided the capability to perform subsecond imaging of millimeter thin slices, which has opened up a host of new applications, such as blood vessel imaging, cardiac imaging, imaging of calcifications, large field imaging, and the ability to separately image the different vascular phases of medical diagnostic products. Finally, CT also plays an important role in molecular imaging of human diseases and animal model studies by providing unique and accurate spatial anatomy information. Nanoplatform-Based Molecular Imaging Edited by Xiaoyuan Chen C 2011 John Wiley & Sons, Inc. Copyright

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COMPUTED TOMOGRAPHY AS A TOOL FOR ANATOMICAL AND MOLECULAR IMAGING

In this chapter, the physical and mathematical foundations of CT imaging are first reviewed. Recent advancements in CT technologies, such as multislice CT, cone-beam CT, respiration-gated CT, and four-dimensional (4D) CT, are highlighted. Novel strategies of scatter removal, noise suppression, and dose reduction are also discussed. In the second next of the chapter, we summarize the characteristics and performance of various contrast agents for enhanced CT imaging. The success of CT imaging techniques in molecular imaging is intimately dependent on the use of X-ray contrast agents to better differentiate soft tissues and to reveal the diseased regions. In reality, while contrast media find important applications in both micro-CT small animal imaging research and clinical settings, most commercially available CT agents possess blood clearance properties that are not suitable to the time scale of small animal CT protocols. The sensitivity of the agents is also problematic. Development of novel CT contrast agents represents a forefront of micro-CT and molecular imaging research. After a brief review of conventional iodine-based contrast media, we discuss some emerging agents for disease-specific applications. Clinically, the development of disease-specific contrast agents will allow us to realize the enormous promise of molecular biology research in routine practice.

5.2 PRINCIPLE OF COMPUTED TOMOGRAPHY Although the words of “computed tomography” (CT) could have much wider meaning, the terminology is accepted to specially refer to X-ray transmission computed tomography. In this technology the projections from the X-ray transmitted through the object under investigation are mathematically processed to construct a two-dimensional image. The word tomography originates from the Greek word tomos, which means “a section” or “a cutting.” Tomographic techniques are not restricted to transmitted X-rays. In positron emission tomography (PET) the information projections are from the emitted photons instead of the transmitted ones. In optical projection tomography (OPT) the source is visible light instead of X-rays. In traditional imaging technologies such as camera or X-ray radiography the recording media are used to store the image projected onto them. In tomography the image does not exist but is mathematically constructed from indirect information by computation based on the Radon transform theory. 5.2.1 Physics of X-rays X-rays are a form of electromagnetic radiation emitted when electrically charged particles release their potential or kinetic energies in the form of photons of energy from kilo electron volts (keV) to mega electron volts (MeV), or wavelength from picometers (10−9 meters) to nanometers (10−6 meters). In CT systems the X-ray is generated in an X-ray tube. The tube contains a thermal filament and a rotational anode target in a vacuum chamber. The target is set to a positive voltage relative to the filament, usually from 30 to 150 kV. The electrons emitted from the filament are accelerated by the electric field toward the target. When these electrons strike the target, they experience electrostatic forces from the electrons and nuclei in the target and are decelerated in a short distance. According to electrodynamics, a charged particle will emit electromagnetic radiation when it is accelerated or decelerated. The kinetic energies suddenly lost from the incident electrons are released in the form of electromagnetic


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109

waves called bremsstrahlung radiation. The electrons which lose most of their kinetic energies in the first collision emit high-energy photons, and those electrons which lose their energies gradually emit low-energy photons. Thus bremsstrahlung radiations form a continuous energy spectrum, whose maximum energy equals the acceleration potential times the electron charge. As in most of the X-ray tubes used for diagnostics, the acceleration potential is high enough so that electrons in the inner orbits of the target atoms may be kicked out by the incident electrons, or by the photons generated by the incident electrons, and the vacancies are filled up by higher orbit electrons. In this process a photon will be emitted whose energy equals the energy difference between the two orbits. Since this process has a resonance property, the photons emitted form the characteristic energy spikes on top of the bremsstrahlung spectrum. The energies of these spikes are specified by the target material, independent of the acceleration potential. The X-ray photons then pass through a window that separates the vacuum in the tube from the ambience, and form the X-ray beam. The window usually consists of a layer of millimeter-thick low-Z metal, which also plays a role in filtration, absorbing most of the low-energy photons. The spectrum from a kilovolt X-ray tube is specified by its acceleration potential, the target material, and the filtration. Figure 5.1 shows the output spectra from a tungsten target with acceleration potentials of 80 kV, 100 kV, and 120 kV with a 2.5-mm Al filter. The surface normal of the tungsten target is 10◦ with respect to the incident electron beam. The data of a spectrum specified in this way can be generated by Monte Carlo simulations or by empirical formulas [1]. When an X-ray beam passes through a material, the photons in the beam are either scattered or absorbed. Therefore the intensity of the outgoing beam is attenuated in comparison with the incident beam. If the incident photons are not monochromic, usually the lower-energy photons are attenuated more than the high-energy photons, so the transmitted 10

Photon Number (arbitrary)

9 8 7 6 5 4 3 2 1 0

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Photon Energy (MeV) FIGURE 5.1 Energy spectrums from an X-ray tube with 80 kV (dotted), 100 kV (dashed), and 120 kV (solid) acceleration potentials, with 2.5 mm Al filtration. The spectrums are generated with program Spektr [2]. The continuous component is from bremsstrahlung radiation and the spikes are the tungsten characteristic peaks. Note that the maximum photon energy equals the acceleration voltage.


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beam will contain a higher fraction of high-energy photons than low-energy photons than the incident beam. This effect is called “beam hardening.” Since the X-ray emitted from the target contains a large portion of low-energy photons, and these photons do not make significant contributions to the image contrast, as we will discuss shortly, a filter of a few millimeters of aluminum is usually placed in front of the X-ray tube window to reduce the low-energy component. Also, beryllium filtration is used for low-energy and copper in high-energy systems. The filtration thus changes the shape of the output spectrum. A photon in the energy range between 1 and 200 kV may experience one of three types of interactions when it passes through a material: Rayleigh scattering, photoelectric absorption, and Compton scattering. In Rayleigh scattering, or coherent scattering, the photon is bounced by an electron or an atom without loss of its energy. It is this process that causes the sky to be blue. Rayleigh scattering mainly happens with low-energy photons. In X-ray radiography and CT it can cause image blurring. Photoelectric absorption happens when an electron is knocked out from an inner orbit of an atom. The energy of the photon is completely absorbed and causes ionization. In Compton scattering the photon energy is partially transferred to an electron. The outgoing photon changes its direction and has lower energy compared with the incident photon. The probabilities of all three interactions increase with electron density and are energy dependent. As the energy increases, the probabilities of Rayleigh scattering and the photoelectric absorption reduce. The probability of Compton scattering increases at low energy, then stays nearly constant over the energy range for X-ray imaging. When a monochromic X-ray beam passes through a material, the attenuation can be described by the Beer–Lambert law: I = I0 exp(−␮x)

(5.1)

where I and I 0 are the transmitted intensity and incident intensity, respectively, ␮ is the linear attenuation coefficient (in cm−1 ), which is energy dependent, and x is the thickness (in cm) of the body through which the beam penetrated. The Beer–Lambert law can easily be understood by looking at Figure 5.2. In this figure the X-ray beam of intensity I 0 is incident on a uniform material from the left side and transmits to the right side. The beam passes through the first block with some attenuation, and we denote the beam intensity outgoing from the block as I , and that from the second block as I , and so on. Because every block generates the same attenuation, I /I0 = I /I = · · · we have I/I 0 = (I /I 0 )n = exp[−n ln(I 0 /I )]. That is, the attenuation is an exponential function of the material thickness. The logarithm of the attenuation by a unit thickness of the material is the linear attenuation coefficient ␮.

I0

I'

I"

...

I

FIGURE 5.2 Attenuation of X-ray through material. The material is made by n identical blocks.


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111

The linear attenuation coefficient ␮ is often expressed as the product of mass attenuation coefficient (␮/␳ ) and density ␳ : ␮ = (␮/␳ )␳

(5.2)

The significance of this expression comes from the fact that for all condensed matter the mass attenuation coefficient (␮/␳ ) is an intrinsic property of the material, depending only on its elemental compositions. Therefore water and ice have the same ␮/␳ , and so do diamond and graphite. Since the mass attenuation coefficient of all the elements have been tabulated over a wide range of photon energies (NIST), once the elemental compositions of a material are known, its (␮/␳ )mat can be calculated from the mass attenuation coefficients of the component elements (␮/␳ )elem and their mass weights welem (␮/␳ )mat =

welem (␮/␳ )elem

(5.3)

elem

Mass Attenuation Coefficients (cm²/g)

The mass attenuation coefficients of water, soft tissue, aluminum, copper, lead, and tungsten are shown in Figure 5.3. The mass attenuation coefficients of all the materials are strongly energy dependent in the energy range up to 100 kV. From Figure 5.3 it can be seen that the low-energy component of X-rays, especially at photon energies below 10 kV, all the materials have very large attenuation coefficients. Therefore the component of an X-ray beam in this energy range is not useful for imaging of a body because it will be entirely absorbed after a layer of a few millimeters. In other words, nearly all the materials are opaque. On the high-energy end of the spectrum, a photon of energy higher than 250–300 kV would have long penetration depth comparable with typical body size, making all the tissues nearly equally transparent so the X-ray would not create significant contrast. These phenomena dictate that the spectrum ranges of X-ray imaging systems

10

10

10

10

10

10

4

water soft tissue Al Cu Pb W

3

2

1

0

-1

10

0

10

1

10

2

10

3

Photon Energy (keV) FIGURE 5.3 Mass attenuation coefficients ␮/␳ of water, soft tissue, aluminum (Al), copper (Cu), lead (Pb), and tungsten (W). Note that mass attenuation coefficients of water and soft tissue are almost overlapped in this figure.


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must lie between 10 and 250 kV. The upper limit of the spectrum is set by the acceleration potential of the X-ray tube and the lower limit is set by filtration. If the photon energies in the incident X-ray beam expand to a spectrum S0 (E), after passing through an object of thickness x, the transmitted beam intensity I(x) is expressed by extending Eq. (5.1) as I (x) =

d E S(E, x) =

d E S0 (E) exp(−␮(E)x)

(5.4)

where S(E, x) is the transmitted beam spectrum at thickness x. If the material in the object is inhomogeneous, the mass attenuation coefficient and the density vary with the location, and Eq. (5.4) is further extended as I (x) =

d E S(E, x) =

S0 (E) exp −

x 0

␮ (E, ␰)␳ (␰)d␰ d E ␳

(5.5)

If a wide X-ray beam passes through an object, different parts of the beam pass through different parts of the body and will experience different attenuations. The spatial intensity variations then form an image projected to the record medium. This is how an X-ray radiographic image is formed. In cases where the spectrum is concentrated within a relatively narrow range of energy, the beam can be approximated to be monochromatic, and Eq. (5.5) is reduced to I (x) ≈ I0 exp −

x 0

␮ (␰)␳ (␰)d␰ ␳

= I0 exp −

x

␮(␰)d␰

(5.6)

0

or − ln

I ≈ I0

x

␮(␰)d␰

(5.6a)

0

From Eq. (5.5) and (5.6a) it is seen that each pixel in a projection is an overlap of the linear attenuation coefficients of many layers of the object. If the object is divided into many small voxels, the logarithm of the projection pixel value would be proportional to the sum of the attenuations of the voxels along the path of the ray that projects to the pixel. If the X-ray is incident on the object from a different direction, in the new projection the logarithm of the pixel values would be proportional to the sum of another group of the voxel attenuations. Therefore if the X-ray beam can be arranged to pass through the object from many different directions, the three-dimensional distribution of the attenuations of the voxels could be resolved from the projections. In 1917 an Austrian mathematician, Johann Radon, proved that it is in principle possible to reconstruct a cross-sectional image of an unknown object using an infinite number of projections through the object [3], which set the theoretical foundation of computed tomography. Recently, Liu et al. [4] proposed a higher level image reconstruction theory, the P-transform, which unified X-ray and photoacoustic CT reconstruction theories into one theory. The Radon transform becomes a special case of the P-transform. Further description of the P-transform is beyond the scope of this chapter. Readers who are interested in the P-transform theory may refer to the original P-transfer theory [5].


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5.2.2 Mathematics of Computed Tomography

Radon Transformation

The Radon transform of a function f (x, y) can be expressed as

R(r, ␣) = R[ f (x, y)] =

f (x, y)␦(r − x cos ␣ − y sin ␣)d x d y

(5.7)

where r and ␣ are the polar coordinates of the projection, as shown in Figure 5.4a. The integration runs over the whole x-y plane. For a given value of ␣, a series of line integrals are computed along the lines r = x cos ␣ + y sin ␣, perpendicular to the vector r = (r, ␣), where each r corresponds to a line integral. Figure 5.4b demonstrates the result of the line integrals of the object in Figure 5.4a at angle ␣. Solving the function f (x, y) in Eq. (5.7) from known projections R(r, ␣) is called image reconstruction. There are many algorithms performing the function of image reconstruction.

Principle of Image Reconstruction mation takes the form

When applied to X-ray CT, the Radon transfor

− ln[I (r, ␣)/I0 ] = R(r, ␣) = R[␮(x, y)] =

␮(x, y)␦(r − x cos ␣ − y sin ␣)d x d y

(5.7a) where ␮(x, y) is the linear attenuation coefficient at point (x, y), as in Eqs. (5.6) and (5.6a). Rotating the coordinate system (x, y) for an angle ␣ about its origin, so that x = x cos ␣ + y sin ␣ and y = y cos ␣ − x sin ␣ become the new coordinate system, Eq. (5.6) is then rewritten as (5.8) − ln[I (x , ␣)/I0 ] = R(x , ␣) = ␮(x, y) dy

FIGURE 5.4 The Radon transformation of a cross section of an object. In this illustration f (x, y) is uniformly distributed inside the square in (a) so that in (b) the values of the Radon transformation are proportional to the lengths of the line segments across the object.


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Taking the Fourier transformation of Eq. (5.8) with respect to x , we have FR (k, ␣) =

∞

−∞

R(x , ␣)e−i2␲kx d x =

∞

−∞

␮(x, y)e−i2␲kx d x dy

(5.9)

The linear attenuation coefficient ␮(x, y) can be solved by inverse Fourier transformation as

␲

␮(x,y) =

∞

d␣ 0

−∞

FR (k, ␣)e

i2␲kx

|k|dk =

␲

∞

d␣ 0

−∞

FR (k, ␣)ei2␲k(x cos ␣+y sin ␣) |k|dk (5.10)

Equation (5.10) is the back projection formula. With this equation the linear attenuation coefficient can be calculated from the projection data to form a cross-sectional image. A series of such cross-sectional images along a longitudinal axis are then stacked together to form a three-dimensional (3D) image. Therefore the essential step is the two-dimensional (2D) reconstruction of the cross-sectional image from the projected images. Although in principle Eq. (5.10) can be used to solve the problem of reconstruction, Eq. (5.7a) that relates ␮(x, y) to the projected image I(r, ␣) is much simplified. This equation assumes the X-ray is monochromic or can be approximated to be monochromic, and the projection is free of noise. In modern CT systems more sophisticated mathematics are used in the reconstruction, which will be discussed in more detail as a specific topic.

5.3 EVOLUTION OF CT IMAGING TECHNOLOGY The basic components of a CT system includes an X-ray source, a detector or an array of detectors, a collimator that shapes the X-ray beam, a gantry carrying the source and detectors, a patient couch, and one or more computers that control the system, acquire the data, and reconstruct the image. In medical CT systems the computers are also responsible for administration, data archiving, data transferring, and image display.

5.3.1 The First to Fourth Generations of CT Scanners The first CT scanner was designed by Godfrey Hounsfield in the early 1970s by exactly realizing the Radon transformation shown in Figure 5.4 and Eq. (5.7). In the system an X-ray source and a single detector were set at the opposite sides of the object. The X-ray was confined to a narrow beam (pencil beam) aiming at the detector. The source–detector pair was moved together so that the object was scanned by parallel beams. The pair was then rotated a small angle and the procedure was repeated to scan the object at a different angle. This arrangement is shown in Figure 5.5a. The data acquisition ran through the angles over 360◦ . Hounsfield and A. M. Cormack shared the 1979 Nobel Prize in Medicine and Physiology for this invention. In a first generation CT scanner, the X-ray is confined to a narrow pencil beam, and the single detector senses only the primary photons. Because the scattered photons are going in different directions, they are ignored. The scattering reduces the intensity of the signal reaching the detector but this amount can be compensated by calibration.


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EVOLUTION OF CT IMAGING TECHNOLOGY

(a)

(c)

115

(b)

(d)

FIGURE 5.5 Diagrams of four generations of CT: (a) first, (b) second, (c) third, and (d) fourth generations. Grey spheres represent X-ray sources.

The second generation of CT is shown in Figure 5.5b, in which the single detector is replaced by a linear array of detector elements. The X-ray was now confined in a fan beam so that all the detector elements can acquire data simultaneously. The source and the detector array translate to cover the subject being imaged, then rotate to the next angle. The data acquisition speed is multiplied because several detector elements work simultaneously, and the X-ray source is used more efficiently. But there is a price for these advantages: the noise due to scattering caused by using a wider X-ray beam. It is possible to add a grid in front of the detector array to reduce the scattering noise [6]. However, this solution has limitations because the grid not only adds extra weight to the detector but also takes away the detector area, thus reducing the efficiency. Because the wall between adjacent grid openings must be thick enough to create sufficient attenuation to the oblique photons, these walls will occupy detector area. In high spatial resolution detectors, the area taken by the grid wall becomes significant so that the benefit of noise reduction brought from the grid could be outweighed by the reduction of the element areas. In the third generation of CT, a longer array of detector elements is used and the X-ray from the single source is confined to a wider fan beam so that the whole width of the object can be covered. Therefore the translation is no longer necessary, and only the gantry that holds the source and detector array needs to rotate. The detectors are arranged on an arc, as shown in Figure 5.5c. Most modern clinical CT systems use this arrangement. The noise level of the third-generation CT scanner is higher than the second-generation scanner if all the components are the same, because of the wider X-ray beam angles. But


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the data acquisition speed is much faster, which brings tremendous benefit in medical applications, especially since it makes use of higher spatial resolution with smaller detector element area. Since the first CT scanner appeared in the 1970s, major efforts in CT engineering have been focused on increasing the data acquisition speeds and the spatial resolutions. This is discussed in the next sections. The fourth-generation CT has a set of detectors that are arranged in a ring over 360◦ around the object, and the source is mounted on a rotational gantry, as shown in Figure 5.5d. The detectors are on a fixed ring. Therefore the wiring can be greatly simplified compared to third-generation CT. The fixed relative positions of source and detectors in the third generation are no longer here. It is possible in principle to read out all the detector elements even if most of them are not irradiated, but such a procedure would slow down the acquisition speed and add work load to the reconstruction software. Therefore extra electronics and mechanical components are needed to synchronize the data acquisition—a complication that restricts the application of this generation. 5.3.2 The Fifth Generation of CT Scanner In CT history the fifth generation of CT is usually referred to as the electron beam CT, or the EBCT. The EBCT was the result of applying CT in a cardiology study, which requires a CT with higher temporal resolution. Research showed that in order to get a clear tomogram of the fastest moving part of a living heart, a complete data acquisition time should be no greater than 19.1 ms [7]. It’s obvious that there is no CT with mechanically rotating gantry that can reach this speed. An EBCT scanner can reach the goal by replacing the heavy X-ray tube with an electronically steered X-ray source. In an EBCT scanner, the X-ray source consists of a semicircular tungsten anode ring housed in a huge vacuum chamber with an electron gun, as shown in Figure 5.6. An electronically steered high-intensity electron beam generates a fast moving X-ray source along the tungsten target. Among various EBCT designs, GE’s eSpeed scanner is the fastest CT scanner in the world. Compared to other CT systems, EBCT technology has its own shortcomings, such as higher capital investment and lower signal-to-noise ratio (SNR). Currently, about 130 EBCT systems are in service worldwide. 5.3.3 CT Scanner with Nanotube X-ray Sources With the emergence of an X-ray source based on the field emission effect from the tip of a carbon nanotube [8], a new type of CT system was proposed by Alexei Ramotar in 2006 [9]. In this design the fixed detectors are arranged in a ring over 360◦ around the object as in the fourth generation, but the rotational single source is replaced by a fixed ring of many sources as shown in Figure 5.7. The sequence that turns the sources on and off is controlled by electronics. If the X-ray beam intensity of the nanotube source is sufficient, a scanner designed from this concept will completely omit the mechanical complication of the rotational gantry, and the data acquisition can be of very high speed and in more flexible patterns than just a rotational sequence. An example of possible applications of the technique is breast CT for mammograms. Compared with the current widely used breast-compression mammogram technique, breast CT offers patients more comfort and is highly sensitive in detecting early stage tumors [10]. There are restrictions to the application of traditional CT to mammograms, one of which is the consideration of radiation dose to the lungs and the heart, because of the geometry of


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Focus, bend & steering coils

Electron gun

X-rays Shielding

Detector rings

Patient Electron beams Vacuum chamber

Tungsten anode rings

Fan x-rays

FIGURE 5.6 Side view (top) and cross view (bottom) of diagram of an EBCT scanner. (From Pingyu Liu’s 1997 proposal with author’s permission.)

the breast and the limited space between two breasts. Using the new technique the detector elements could be arranged on a spherical surface around the breast in layers parallel with breast base, for left and right breasts, respectively. The sources could be arranged on the same spherical surface with the beams collimated in the corresponding layers, with limited dose to the chest wall underneath.

FIGURE 5.7 Diagram of CT scanner with nanotube X-ray sources. The little dits represent the detectors and the black lines represent the X-ray sources. In this arrangement both the sources and detectors are fixed so that the rotation gantry can be completely omitted. The emissions from the sources are controlled by electronics so the data acquisition speed can be very high and the emission can be in flexible patterns other than a rotational sequence. In the figure one of the sources is collimated so that the X-rays are confined to certain detectors.


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5.3.4 Power and Data Transmission in a CT System Power and data transmission between the stationary components and the rotational gantry of a CT system can be realized in two possible ways. Conventionally, transmission is through cables wrapped on a rack. When the gantry rotates in one direction, the cables wind up on the rack. When the gantry rotates in another direction the cables unwind. Because the cable cannot be very long, the gantry needs to rotate alternately back and forth. This technique is used in early CT systems and most modern cone-beam CT systems, where a slow gantry speed can be tolerated. In most modern CT scanners a slip ring technique is used to transmit the power and data through contact brushes and slip rings. In some systems the data are transmitted through RF couplings, or fiberoptic rotary joints. In other CT systems a more flexible optical data coupling method is utilized. An important specification of a CT system is its gantry rotation time, which determines system’s temporal resolution. In a modern CT system, gantry rotation speed can reach 0.35 second per cycle. On the rim of a gantry 2 meters in diameter, the centrifugal acceleration can reach 24g. Therefore on the gantry the components must be carefully arranged to balance the momentum. 5.3.5 Helical CT If the patient couch moves simultaneously when the gantry is rotating, the patient will see the source moving along a helical path. This arrangement is called the helical or spiral CT. With slip rings the gantry can rotate continuously so the helix can extend over the length of the whole body. In third-generation CT with an array of detectors, the distance the couch moves during one gantry rotation period defines one slice thickness, which is the spatial resolution of the image along the axial direction. This technique is used in most modern medical CT systems, because it allows fast and high-resolution imaging. Fullbody CT imaging using such a system with 0.625-mm slice thickness can be completed in 1.5 minutes, and the image reconstruction can be completed on the fly. Fast imaging speed is important for medical applications. A shorter-time scan reduces the artifacts caused by patient motion. Many CT contrast agents stay in the body only a short period of time (a few minutes) and then are washed out by the urinary system. An imaging system must complete the data acquisition within that period. Most importantly, although all the CT systems are able to provide stationary anatomical information, a fast-imaging system can also provide dynamical and functional information. In cases where motion is periodic, as the respiration or heartbeat, the acquisition and reconstruction of time-resolved or 4D CT images can be accomplished with gating technology. During gated acquisition, the CT runs in scene mode, in which the couch moves step by step instead of continuously. In each step the gantry rotates several revolutions; each corresponds to a phase. In this mode the patient sees the source moving along circles. As the couch steps through the body of the patient, these circles stack to form a scan. The projections are then sorted according to the phases of the motion, and those belonging to a phase are picked up for reconstruction. When displayed, the reconstructed images are shown phase by phase as a 3D movie. Most helical CT systems can be operated in scene mode. 5.3.6 Multidetector CT The acquisition speed and spatial resolution of helical CT can be further improved by adding one or more rows of detectors to the array, so that during one gantry revolution more than


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one slice of data can be collected at the same time. Multiple-slice CT, also referred to as multidetector CT (MDCT), makes a narrower slice thickness, more slices, and larger volume coverage simultaneously. MDCT scanners with 320 slices are now available in the market. There are many technical concerns in the design of MDCT systems. Because of the scattering effect, the MDCT data contains higher noise compared with single-slice CT. The increase in the number of slices is accomplished by reducing the row width of the detectors, and the reduction of the row width is limited by the detector sensitivity, which is proportional to the detector element area. Most manufacturers restrict the total detector width to 20 or 24 mm when the number of slices is 2, 4, 16, 20, and 24, and to 40 mm when the number of slices is 40 and 64. MDCT delivers the same X-ray dose to the object as single-slice CT for the same spatial resolution, but to get the same signal-to-noise ratio MDCT needs a higher dose because of the higher noise level. Especially, to take advantage of the high spatial resolution of MDCT, a significantly higher dose would be necessary to create a sufficient signal level from the smaller area of the detector elements. Many manufacturers have developed dose control mechanisms to automatically optimize the dose for each slice of a scan. The image reconstruction time of MDCT is expected to take longer than that of singleslice CT due to the larger amount of data. However, because of improved computer technology the reconstruction time does not significantly delay the total scan. The algorithm reconstructing on-the-fly can complete a slice reconstruction within half a second after acquisition. The fast speed and high spatial resolution brought by MDCT makes dynamic imaging of moving organs possible. An example is functional vascular imaging. In CT coronary angiography, cardiac data can be acquired continuously during 5 or 6 heartbeats. The dynamic images of the moving heart can be reconstructed corresponding to electrocardiographic gating signals. In polytrauma applications, the whole-body scan over 2 meters along the patient body can observe an upper extremity angiogram followed by pelvic and lower extremity angiography with one bolus of contrast. 5.3.7 Cone-Beam CT (CBCT) Replacement of a pencil beam and a single detector by a fan beam and a 1D detector array evolves CT from the first generation to the second generation, and extending the array size further evolves CT to the third generation [11, 12]. The array can also be extended in another direction to form a two-dimensional detector array. To irradiate the two-dimensional array the beam needs also to form a cone shape. In many cone-beam CT systems the detector areas are large enough that the beam can cover the whole region of interest in the body, so that during the acquisition of data the object does not have to move. These systems usually connect the stationary components and the gantry through cables, and rotate only one revolution for a scan. Typical scan time over 360◦ is about 1 minute, comparable to the acquisition time with helical CT. Compared to helical CT, cone-beam CT has a much simpler structure. The cable connection does not require high precision machining as the slip ring does; therefore the cost is significantly reduced. Also, cone-beam CT can be integrated into special systems such as a radiation treatment machine without interfering with the primary function of the system. The noise level of cone-beam CT is higher from 2D scattering. To obtain the same signal-to-noise level, cone-beam CT needs to deliver a several times higher dose to the object than helical CT. Also, a large-area 2D detector introduces another challenge—the


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data transmission time. A detector with 4000 × 3000 pixel size needs about 1 second to read out; therefore the frame rate cannot be faster unless the image pixels are combined in 2 × 2 binning or 4 × 4 binning. 5.3.8 Scattering Removal and Noise Reduction in CBCT In single-slice CT the X-ray beam and the detector span a narrow plane. Most of the scattered photons fall outside the plane. Only a small portion of the photons scattered in the plane are recorded. In cone-beam or multidetector CT the X-ray is collimated to a wide beam. The possibility of a scattered photon mixing with the primary photons is therefore much higher. The projection images from cone-beam or multidetector CT are therefore much noisier than those from single-slice CT, and the uncertainty in the reconstruction is correspondingly higher, which brings higher noise to the reconstructed image. Research in scattering removal techniques has shown that correction of the scattering could be carried out in several ways. If the CT systems allows object–detector distance variation, setting the distance larger helps to reduce the scattering effect, because the primary beam goes along the path defined by the desired geometry and the scattered photons move in large angles. The scattering effect can be measured by setting a small opaque shield between the source and the object, to block the primary beam from reaching the detector, so that the signal in the shielded area is all from the scattering from the object. A deconvolution algorithm in image processing based on a scattering model can be used to separate the primary beam and the scattered components in projections or sinographs. Monte Carlo simulations can fit the images as the summation of the primary beam and the scattered component. The detailed descriptions of these techniques can be found in the work by Zhu et al. [13] and the references quoted. A typical method to reduce the noise is to average a pixel in an image with its neighbors. This method also reduces the spatial resolution because it smoothes out the edges. In the work reported by Wang et al. [14], an algorithm was proposed that uses an anisotropic filter to reduce the noise. In this algorithm a pixel in a sinograph is replaced by the weighted average of the neighboring pixels. The weight is proportional to the exponential of difference between the pixel under consideration and its neighbor, so that the larger the difference the less the weight, to conserve the edges. After several iterations of such averaging the random noise can be significantly suppressed while the features remain. Numerical experiments using phantom images showed that faint features and a small spot originally flooded in noise in the original images can clearly be seen in the processed images. Advances in scattering removal and noise suppression techniques make it possible to use a lower dose to obtain sufficient image qualities in cone-beam CT and multidetector CT. The cost of using the techniques is a longer after-processing time.

5.4 SPECIAL CT SYSTEMS FOR DIFFERENT CLINICAL AND RESEARCH APPLICATIONS 5.4.1 Cardiac CT Since the advent of the first CT system for head imaging, scientists and engineers have been working on a more challenging task, cardiac CT. The challenge here is tremendous, and it stems from the restless, fast, and complex three-dimensional motion of the heart. To


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FIGURE 5.8 Dynamic Spatial Reconstructor at the Mayo Clinic in Rochester, Minnesota (http://dpi.radiology.uiowa.edu/gallery/dsr.html).

get a clear CT image of a living heart requires significant advancement in both hardware and software of routine CT scanners. The most significant example of endeavor in hardware improvement for cardiac CT should perhaps be the Dynamic Spatial Reconstructor (DSR), which was installed at the Mayo Clinic in 1983. In CT history the DSR is known for its speed, weight, size, and complexity. The DSR was designed mainly for cardiac imaging. It has the ability to obtain up to 240 contiguous 0.9-mm thick sections in a time period as short as 1/60 second and to repeat this acquisition rate 60 times per second. The DSR consists of a gantry weighing approximately 17 tons with a length of 20.5 feet and a diameter of 15 feet. Fourteen X-ray guns reside in a hemicylindrical configuration. Figure 5.8 shows an artistic view of the DSR. Following the DSR, the next milestone in cardiac CT development was electron beam CT. All currently running EBCT systems are mainly for cardiac imaging. All main CT system manufacturers pushed out their fastest CT systems for cardiac applications, including a 64-slice detector with 0.33 second of rotation time. These newer CT scanners generate cardiac images with higher temporal and spatial resolution. Smarter data acquisition, preprocessing, and image reconstruction techniques have become increasingly available for cardiac CT images. A recent development of these techniques is the Matched Cardiac X-ray CT (MCCT). Figure 5.9 shows a diagram of the MCCT. Clinical studies have showed that reasonably good cardiac CT images can be obtained with the MCCT for most medical conditions with three heartbeat in routine CT scanners with a gantry rotation time of 1 second. 5.4.2 Micro-CT for Animal Imaging Experimental animals, especially small animals such as mice and rats, are increasingly being used to model human diseases [16] in the study of specific pathways for disease, potential therapies, and safety of new pharmaceuticals. In traditional techniques,


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FIGURE 5.9 Diagram of the MCCT (U.S. Patent 6233478, Apparatus and Method for Constructing Computed Tomography Image Slices of an Object Undergoing Cyclic Motion, May 15, 2001. Pingyu Liu) [15].

observation of disease development is based on the sacrifice and dissection of the studied animals. Such approaches are labor intensive and don’t permit longitudinal studies. The development of in vivo imaging technology in small animals revolutionarily altered the situation. The special challenge in animal imaging comes from the small size of the animals. The typical size of a mouse is a few centimeters, which is about 5% of human size (Fig. 5.10). The respiration period of a mouse is about 10% of that of human beings. A CT system designed for small animals, the micro-CT system, therefore requires both spatial and temporal resolutions an order of magnitude finer compared with a human system. A micro-CT scanner is not a simple scaling of a human CT scanner. Special considerations have to be taken into account from high resolution requirements and the associated radiation dose increase to the imaged animals. A micro-CT scanner can rotate either the object or the gantry. In rotate-object animal micro-CT systems, to avoid organ movement during rotation, the animal is set in the vertical position. This position is unnatural for animals and it induces biological effects. Most animal micro-CT systems rotate gantries, in which the animal is set in the more natural horizontal position. Cone-shaped X-ray beam, two-dimensional detector, and one-revolution gantry are most commonly used in animal CT systems [17], although slip-ring CT systems are also available in the market [18, 19]. The detector sensitivity is proportional to pixel size. The high spatial resolution of a micro-CT system requires much smaller pixel size than the detector on a human system. A typical pixel size of micro-CT detector is 50 ␮m. The small area of the detector pixel requires higher flux density of the X-ray beam to obtain significant signal-to-noise ratio, which could result in a dose delivered to the experimental animal that is significant enough to alter its biology. In some systems if the accumulated imaging time is several hours the total dose delivered to the animal could reach the lethal level.


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FIGURE 5.10 A micro-CT image of a mouse head, acquired using a GE micro-CT with 2 × 2 binning. The X-ray tube acceleration voltage is 70 kV and the tube current is 25 mA.

A special technical barrier of a two-dimensional X-ray detector is its read-out time, as described for cone-beam CT. The development of high-speed electronics is therefore urgently required. One of the factors influencing spatial resolution is the X-ray source focal spot size. The spot size of animal micro CT varies from 25 to 900 ␮m. If the projection of the focal spot to the detector plane has a size comparable to or larger than the detector pixel size, a penumbral blurring of the image will occur. On the detector the penumbra width of a sharp-edged object is Penumbra width =

ODD × spot size SOD

where ODD is the object–detector distance and SOD is the source–object distance. On the other hand, for the object we can estimate its image size on the detector surface: SDD ODD × object size Image size = × object size = 1 + SOD SOD Where SDD = SOD + ODD is the distance from the X-ray source to the detector. Choosing smaller ODD and longer SOD is helpful in obtaining a sharper image through reduction of the penumbral blurring, if the image resolution is sufficient. Smaller source spot size can produce images with higher spatial resolution. However, it restricts the electron beam current because of the limit of the heat dissipation rate on the


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anode. A lower electron beam will generate lower X-ray fluence; therefore a longer imaging time would be required in order to create enough signal above the noise floor. As in the human system, short imaging time might be crucial in special cases as in respiration-gated imaging and when some contrast agents are applied whose wash-out time is within one or a few minutes. In practice, the selection of the spot size must be a compromise between the requirements of the X-ray fluence and the spatial resolution. 5.4.3 Dual-Modality Systems A CT system can provide detailed anatomic information for a body. Functional imaging systems such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) are capable of providing dynamic metabolic information for the body, but not detailed information about the body’s anatomy. To associate the spatial distribution of the metabolic activities with the anatomic structure the subject can be scanned using CT and PET or SPECT separately, and then the two images can be combined through image registration. The subject must not move in -between the two scans. With a dual-modality system combining CT and PET or SPECT, such registration becomes simple. Also, dualmodality systems used together with molecular-specific agents play important roles in molecular imaging studies and applications, as discussed in more details in Section 5.5. In a PET–CT dual-modality system the two units are placed next to one another [20]. Figure 5.11 shows a Siemens Inveon microPET/CT imaging system with a bore size of 10 cm in diameter. Its main study objects are small animals. Note that in the picture a dedicated PET imaging system is in front of a CT imaging system. The animal couch moves through one modality to another. The system is capable of imaging a variety of radionuclides such as 18 F, 15 O, 13 N, and 11 C. The spatial resolution for PET imaging is 1.4 mm, and the X-ray CT system is on the order of 50 ␮m and can achieve a resolution of 15 ␮m depending on the size of the specimen . A PET scan is about 7–14 min, and a CT scan is 10–12 min. The two images are reconstructed separately. The user can fuse them or display them individually.

FIGURE 5.11 Siemens Inveon microPET/CT. Its bore size is 10 cm in diameter and can accommodate animals up to the size of a small rabbit.


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SPECT uses radiation isotopes having half-life times of several hours to a few days and emitting ␥ -rays of about 100 keV, most commonly 99m Tc, 111 I, and 123 I. Glucose or drugs coded with these isotopes are injected into the patient and follow the blood flow to the target organ. The ␥ -rays are detected by a gamma camera, which consists of a lead or tungsten collimator and an array of photon multiplier tubes. Since a gamma camera can cover only a small solid angle, usually two to four such cameras are used in SPECT. During the CT scan, the SPECT system is turned off and shields are moved to the front of the highly sensitive gamma cameras, to avoid bombarding the photon multiplier tube with the high-intensity X-ray beam. When the SPECT system is on, the X-ray tube of the CT system is off to avoid possibly scattering photons into the gamma camera. 5.4.4 Dual Energy CT As shown in Eq. (5.5), the X-ray attenuation by a material depends on the density ␳ and the mass attenuation coefficient ␮/␳ of the material. In some applications only the geometry information is required, as in bone fracture diagnostics, in which attention is paid to increasing the contrast between different structures. In other applications, as in radiation treatment planning, both the densities and elemental components of tissues are important because the dose absorption is defined by the two. In regular conditions the density and elemental compositions are related and an empirical tissue model can be applied to find them from the CT numbers. A CT system with two energy spectra, on the other hand, can provide more direct information about the material properties [21]. In dual energy CT the same object is imaged twice with different X-ray tube acceleration potential settings, say, 80 and 140 kVp, respectively. The tube current of lower energy is usually adjusted higher than that of the higher energy so that the contrasts of the two images can be comparable. An algorithm proposed by Torikoshi et al. [22] modeled the linear attenuation coefficient ␮ of a CT voxel as ␮ = ␳ e [Z 4 F(E, Z ) + G(E, Z )]

(5.11)

where ␳ e Z 4 F(E, Z) and ␳ e G(E, Z) denote a photoelectric term and a scattering term, respectively, which can be derived from quantum mechanics; ␳ e is the electron density; Z is the atomic number; and E is the photon energy. Measuring the linear attenuation coefficients with two different energy X-rays, we obtain simultaneous equations with respect to the unknown variables of ␳ e and Z as follows: ␮(E 1 ) = ␳ e [Z 4 F(E 1 , Z ) + G(E 1 , Z )] ␮(E 2 ) = ␳ e [Z 4 F(E 2 , Z ) + G(E 2 , Z )]

(5.12)

Therefore if the X-ray beam is monoenergetic, Z4 =

␮(E 2 )G(E 1 , Z ) − ␮(E 1 )G(E 2 , Z ) ␮(E 1 )F(E 2 , Z ) − ␮(E 2 )F(E 1 , Z )

(5.13)

and the effective value of Z can be solved numerically. If the X-ray beam energy expands to a spectrum, the equation becomes [23] [S1 (E)Z 4 F(E, Z ) + G(E, Z )]d E ␮1 =0 (5.14) − ␮2 [S2 (E)Z 4 F(E, Z ) + G(E, Z )]d E


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where S1 (E) and S2 (E) are the spectra of the two energy settings, respectively. Since all the functions in Eq. (5.14) are known, the ratio ␮1 /␮2 can be tabulated as the function of effective Z. Thus the Z image can be obtained from the CT images of two energy settings. Then by either form of Eq. (5.12) the electron density ␳ e can be mapped out. The capability of differentiating the effective Z of different tissues in a dual-energy CT image makes it possible to display clear soft tissue contrast. The challenges come from the facts that the effective Z solved from the Eq. (5.14) is highly sensitive to the uncertainty of ␮1 /␮2 , and the spectra of the two energy beams need to be known in high accuracies [40]. Dual-energy CT has been available in market, as introduced by Reference [41] for example. With these systems it is possible to “remove” out some structures, such as bone, from the reconstructed images and display the blood vessel only, which brings significant advantages in the clinical diagnostics.

5.5 CT CONTRAST MEDIA AND MOLECULAR CT The intrinsic contrasts of different types of tissues are often not sufficient for radiologists to make definitive diagnoses or to accurately determine the extent of diseased tissue or certain normal structures (e.g., blood vessels or prostate gland) in X-ray and CT imaging. Various contrast media have been developed over the years and used along with the X-ray or CT imaging. There are two types of X-ray contrast agents currently approved for human use: barium sulfate suspensions, which are used for GI tract imaging, and water-soluble aromatic iodinated contrast agents, which are used primarily for imaging of the blood vessels and/or urinary system. It is estimated that the annual uses of barium suspensions and iodinated media in the United States are 5 and 20 million, respectively. Despite the tremendous success of these iodinated contrast media, the search for better contrast agents has never ceased. The major problems with existing contrast media are that they have very low retention rate and are not tissue specific. In some rare cases, the iodinated media can be severely toxic, as manifested with cardiovascular, anaphylactic, and pain reactions. A novel contrast agent that circumvents these problems is thus highly desirable. In recent years, due to the advancement of nanotechnology, some new contrast agents have emerged and showed their promising future. The field of nanotechnology has experienced significant advance in synthesis, characterization, and novel applications for various nanoscale devices. One of the important areas of nanotechnology is the synthesis and characterization of polymer, metallic, or magnetic particles, which exhibit a variety of novel properties and functions with the possibility of molecular sensing and imaging. Interfacing nanotechnology, biotechnology, and medicine has opened new vistas for biomedical research and provided an unprecedented opportunity to achieve a fundamental understanding of biological processes and contribute to disease prevention, detection, and therapy. In the last decade, the magnetic nanoparticles for MRI T2 enhancement have been extensively studied and the results showed significant promise for clinical applications. In parallel, the potential of using metallic nanoparticles has been employed to augment the intrinsic contrasts of X-ray and CT imaging. While it is a known fact that heavy elements are efficient absorbers of X-rays, the use of metallic nanoparticles as contrast media has yet to be achieved. X-ray CT is among the most convenient and widely used imaging tools in hospitals today. However, in contrast to magnetic resonance imaging (MRI) and various nuclide imaging modalities, CT is generally not considered as a molecular imaging modality since targeted and molecularly specific contrast agents have not been fully developed. But this situation is changing. Popovtzer’s group synthesized gold nanorods (AuNRs) and conjugated them


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CT attenuation (HU)

HU (Hounsfield units)

240 200 160 120 80 40

La

ra l

O

ry

nx

ca

nc

er

+A La uN ca ry R nc nx +A er ca +A 9 nc u N O er R ra (w +A lc ith 9 an La ou c ry er tA nx (w uN ca ith R nc ou ) O er tA ra + uN lc Au an R N ) R ce +K r+ H Au R Fi N I-3 R br +K ob H la R st M I-3 G +A el ol u a d N n na om R +A no a+ 9 ro Au ds N in R +A wa 9 te rs ol ut io n W at er

0

FIGURE 5.12 CT attenuation (HU) of SCC head and neck cancer cells and positive and negative control samples. Bar graph with standard deviation of three samples: larynx and oral cancer cells that were targeted with A9 antibody-coated gold nanorods (AuNRs), larynx and oral cancer cells without gold nanorods, and larynx and oral cancer cells targeted with nanorods that are coated with nonmatching antibodies (KHRI-3); normal fibroblast and melanoma cells targeted with A9 antibodies, bare gold nanorods in water solution (2.5 mg/ mL), and water [21].

with UM-A9 antibodies, which home specifically to squamous cell carcinoma (SCC) head and neck cancer [24]. Two SCC human head and neck cancer cell lines (106 cells/mL) were used: oral cancer UM-SCC-1 and larynx cancer UM-SCC-5. Both cancerous cell lines were shown before to have a significant overexpression of the A9 antigen. CT imaging was performed on the SCC cells, which were targeted with the UM-A9 antibody-coated gold nanorods. When compared with the CT number of control samples, they found that the attenuation coefficient for the molecularly targeted cells is over 5 times higher than for identical but untargeted cancer cells or for normal cells, as shown in Figure 5.12. Kim et al. [25] also utilized gold nanoparticles (GNPs) as a contrast agent for X-ray CT imaging. They prepared uniform GNPs (similar to 30 nm in diameter) by general reduction of HAuCl4 by boiling with sodium citrate. The resulting GNPs were coated with polyethylene glycol (PEG) to impart antibiofouling properties, which extends their lifetime in the bloodstream. Measurement of the X-ray absorption coefficient in vitro revealed that the attenuation of PEG-coated GNPs is 5.7 times higher than that of the current iodinebased CT contrast agent, Ultravist. Furthermore, when injected intravenously into rats, the PEG-coated GNPs had a much longer blood circulation time (>4 h) than Ultravist (1000 for 5 pmol of conjugates subcutaneously injected. One critical issue in making these self-emitting QDs is the size of the nanoparticle, since like FRET, BRET is also a distance-sensitive process. Increase in the QD conjugate size results in greater distance between the protein and the fluorescent semiconductor core, and thereby decreases the energy transfer efficiency significantly. For instance, the authors have observed that increasing the protein–nanoparticle distance by only 2–3 nm causes the BRET ratio to drop from 1.29 to 0.37 [72]. By attaching targeting moieties such as tumor homing antibodies or peptides to the BRET assembly, it is possible to use BRET for targeted tumor imaging in living animals. More recently, QD-BRET was successfully applied to proteolytic activity detection in buffer with a slightly different coupling scheme [74]. In this approach, the luciferase–protease substrate recombinant protein was genetically modified with an additional intein segment. Carboxylated QDs were functionalized first with adipic dihydrazide because hydrazides are excellent nucleophiles to attack the thioester intermediate of inteins. The reaction proceeds rapidly upon mixing the two together and results in the cleavage of the intein and ligation of the C terminus of the recombinant protein to the QDs. Using this approach, the authors have successfully applied this method to synthesize a series of nanosensors for sensitive detection of MMP-2, MMP-7, and urokinase-type plasminogen activator (uPA). These prepared nanosensors can not only detect these proteases in complex biological media such as mouse serum and tumor lysates with a sensitivity of as low as 1 ng/mL, but they can also detect multiple proteases present in one sample. Considering that irregulation of proteolytic activity is an important hallmark of various diseases such as cancer progression and the development of athersclerotic plaques [75, 76], these types of QD-BRET probes have broad potential applications as in vivo molecular imaging agents.


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QUANTUM DOTS FOR IN VIVO MOLECULAR IMAGING

7.9 RECENT DEVELOPMENTS 7.9.1 Reducing the Size One important issue with targeted in vivo imaging with nanoparticles is the opsonization and strong uptake by the RES system, which entraps the majority of the particles shortly after they enter the circulation system, thus preventing them from reaching the targted sites efficiently. RES uptake is influenced by many factors including particle size, shape, and surface chemistry. According to a study by the Frangioni laboratory [77], the hydrodynamic size (HD) of a nanoparticle has to be equal to or less than 5.5 nm in order to completely evade the RES organs (no accumulation in the liver, spleen, or lung) and be cleared by the renal system. However, the QDs are at least over 10 nm in HD. One approach to downsize QDs is through engineering the coating. Recently, Smith and Nie reported a new class of multifunctional multidentate polymer ligands, which not only minimized the HD of QDs but also preserved the colloidal stability and photobleaching/signal brightness [78]. A major finding is that a mixed composition of thiol (–SH) and amine (–NH2 ) groups grafted to a linear polymer chain can lead to a highly compact QD with long-term colloidal stability, strong resistance to photobleaching, and high fluorescence quantum yield. In contrast to the standing brush-like conformations of PEGylated dihydrolipoic acid ligands and monovalent thiols, these multidentate polymer ligands can wrap around the QD in a closed “loops-and-trains” conformation. Using this method, a new generation of bright and stable CdTe QDs with small hydrodynamic diameters between 5.6 and 9.7 nm, with fluorescence emission tunable from the visible (515 nm) to the near-infrared (720 nm), were prepared. In addition to CdTe nanocrystals, the same coating method is applicable to a broad range of core nanocrystals as well as core/shell nanostructures including CdS, ZnSe, CdSe/ZnS, and CdTe/CdS. The in vivo behavior and utility for imaging these nanoparticles remain to be evaluated.

7.9.2 Reducing/Eliminating Toxicity Cell culture studies [79] indicate that CdSe QDs are highly toxic to cultured cells under UV illumination for extended periods of time. This is not surprising because the energy of UV irradiation is close to that of a covalent chemical bond and dissolves the semiconductor particles in a process known as photolysis, releasing toxic cadmium ions into the culture medium. In the absence of UV irradiation, QDs with a stable polymer coating are likely to be much less toxic to cells and animals and this has been confirmed by a number of in vivo animal studies [17, 56]. Still, the perceived toxicity of cadmium has cast a doubtful future for cadmium-based QDs and intrigued the development of noncadmium QD alternatives. Among these alternatives are InAs QDs (will be discussed in Section 7.9.3), doped QDs, and carbon QDs. Doped QDs (d-dots) that do not contain toxic heavy metal ions have been actively studied by the Peng laboratory [80–82]. A d-dot often consists of a semiconductor nanocrystal core, such as ZnSe, doped with a transition metal ion such as Cu or Mn. In 2005, Peng and co-workers reported a method that yields doped ZnSe with high purity and tunable emission. The key feature of the related synthetic chemistry is decoupling the doping from nucleation and/or growth through nucleation-doping and growth-doping strategies [80]. Further optimization of the doping chemistry improved the PL quantum yield of the Mn-doped ZnSe d-dots (Mn:ZnSe d-dots) to the level of typical CdSe q-dots, as high as 60–70% PL QY measured against organic dyes [81]. Mn:ZnSe d-dots with a tunable


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photoluminescence peak position were made water soluble by coating with a monolayer of mercaptopropionic acid. The overall size of such d-dots/ligand complexes is only about 7–8 nm, implying an excellent permeability in biological issues. Carbon quantum dots are produced via laser ablation of a carbon target in the presence of water vapor with argon as carrier gas. The as-produced samples were dominated by nanoscale carbon particles in aggregates of various sizes and showed no detectable photoluminescence. Further acidic treatment and subsequent surface passivation resulted in bright luminescence emissions [83]. These dots are about 5 nm in diameter under TEM observation and have a continuous absorption spectra and can emit light from 450 to 700 nm depending on the excitation light. A follow-up study discovered the two-photon emissions and showed that they’re bright enough for cellular imaging [84]. Both the d-dots and carbon dots are promising nontoxic alternatives to the Cd-based QDs; however, more work is needed to make them comparable (optical properties, stability, and surface functionlization) to the CdSe QDs as in vivo molecular imaging probes. 7.9.3 Shifting to the Red: NIR QDs As mentioned earlier, the ideal QD emission for in vivo molecular imaging applications should be in the near-infrared (700–900 nm) [53]. This issue was noticed when QDs were first applied for in vivo molecular imaging and high-quality NIR QDs have been under active development since then. By far, there are two major caetgories of NIR QDs tested for in vivo imaging purposes: Cd-based (e.g., type II QDs have CdTe core [23, 55]) and non-Cd-based (InAs, InP, etc.) [85, 86]. The Bawendi laboratory at MIT and the Frangioni group at Harvard are the pioneers in developing NIR QDs and applying them for in vivo imaging [55, 85, 86]. Different formulations have been developed and tested in vivo. Type II QDs consisting of CdTe had been applied for sentinel lymph node mapping in 2004 [56]. Most recently, they reported the synthesis of a size series of (InAs)ZnSe (core)shell QDs that emit in the near-infrared and exhibit hydrodynamic size 10 ␮m in diameter. A semipermeable, hydrophobic membrane separates the interior and exterior compartments of a liposome. Echogenic liposomes contain air pockets within the lipid bilayer to generate acoustic reflectivity. The mechanism of echo contrast appears to be the backscatter from entrapped pockets of air within the liposomes that form during rehydration of freeze-dried liposomes. The size, charge, and surface properties of liposomes can easily be changed by adding ingredients to the lipid mixture before liposome preparation and/or by varying the preparation methods. The ability of liposomes to easily entrap different substances into both the aqueous phase and the liposome membrane compartments makes them suitable for manipulations to generate targeted contrast agents. Echogenic liposomes can be prepared by incorporating gases such as air, argon, or nitrogen into the liposome or by inducing the formation of gas bubbles directly inside the liposome as a result of a chemical reaction [51]. Liposomes composed of phospholipids are not echogenic, but when made with phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and cholesterol [52] they are highly acoustically reflective. These liposomes improved intravascular contrast by approximately 300% relative to blood and 150% relative to agitated saline when injected in swine [53]. Antibodies can be conjugated on these lipid shells without hindering the echogenecity. biodistribution of liposomes Phospholipid liposomes introduced into the circulation system are very rapidly sequestered by the cells of the reticuloendothelial system (RES) [54]. The clearance half-time of the liposome is usually within 30 min. A large number of liposomes need to accumulate at the target tissue to render it acoustically reflective. This can be achieved through multiple passes of the blood containing the liposomes over the target tissue. A prolonged blood circulation of the liposomes was achieved with the addition of a polyethylene glycol (PEG) coating, which efficiently minimizes their removal by macrophages of the reticuloendothelial system [55]. Marik et al. [56] conducted PET imaging and biodistribution studies of liposomes. To track liposomes, radioactive [18 F]fluorodipalmitin ([18 F]FDP) was incorporated into the lipid molecule of the phospholipid bilayer of the liposome. As a control, free [18 F]FDP was also injected in rats. Maximum intensity projection images obtained from 90-min continuous bed motion scans were used to illustrate the full body distribution of free and liposome-encapsulated [18 F]FDP. Freely injected [18 F]FDP showed an initial concentration of 3% ID/cc and was cleared from the blood within a few minutes. The greatest concentration of free [18 F]FDP was observed in the liver, 5.5% ID/cc and in the spleen at a concentration of 4.2% ID/cc. Liposomal [18 F]FDP remained in the blood circulation at near constant levels for at least 90 min, with a peak concentration near 2.5% ID/cc. In addition, liposomal [18 F]FDP quickly reached a


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steady state in the liver, spleen, kidney, and lungs, which was maintained throughout the scan, reflecting the activity within the vasculature of these organs.

11.3.3 Applications of Molecular Ultrasound Imaging Molecular ultrasound imaging with the advent of targeted contrast agents has opened a variety of diagnostic and therapeutic potentials. Using targeted agents, the clinical and experimental roles of ultrasound are further explored, into applications including noninvasive detection of pathology using disease-associated molecular signatures, detection of gene expression, investigation of drug localization, and delineation of molecular mechanisms of disease. Furthermore, the ability to differentiate between different disease-indicative molecular signatures could allow early assessment of pathology and expedite the design of customized treatments. There are many potential targets available for study by targeted contrast imaging. These molecular signatures can be used to localize ultrasound contrast agents through the use of complementary receptor ligands attached to the contrast agent shell such that the ligand–receptor interaction tethers the agent to the cell of interest. Studies published on targeted ultrasound contrast agents are briefly summarized below and in Tables 11.1 and 11.2.

Molecular Ultrasound Imaging of Tumor Angiogenesis Angiogenesis, the process of new blood vessel formation, plays an important role in tumor growth and metastasis and diverse disease processes such as atherosclerotic plaque growth and adaptation to chronic ischemic disease. Novel molecular imaging strategies that allow direct visualization and quantification of expression levels of key molecular markers of these diseases would be ideal tools for detection as well as monitoring therapeutic treatment in patients. To illustrate this concept, many molecular markers such as integrins or vascular endothelial growth factor receptor type 2 (VEGFR2) have been shown to be upregulated on angiogenic and metastatic endothelial cells in an actively growing tumor vasculature specifically (Fig. 11.5). The introduction of microbubbles targeted to key molecular markers of tumor angiogenesis is now being explored as a novel molecular imaging strategy with ultrasound [72, 73]. A number of studies have addressed assessment of tumor angiogenesis with molecular ultrasound in preclinical studies. Integrins, which are extracellular matrix molecules, have been extensively evaluated for targeting of imaging agents, drugs, and particles to the tumor endothelium. Integrin ␣v ␤3 , in particular, has received a lot of attention as it is highly expressed on activated endothelium and almost absent on normal vessels, making it very useful for detection of tumor formation. Various strategies were used to generate integrin ␣v ␤3 targeted microbubbles, namely, the use of streptavidin–biotin coupling chemistry along with monoclonal antibodies for integrin ␣v ␤3 , and the use of a cyclic RRL (arginine–arginine–leucine) peptide and echistatin as ligands on the microbubble shell that bind integrin ␣v ␤3 . Echistatin is a viper venom disintegrin containing an RGD (arginine–glycine–aspartic acid) peptide that binds integrin receptors. Ellegala et al. [57] imaged malignant gliomas in athymic rats by intracerebral implantation of U87MG human glioma cells. An increase in the acoustic reflectivity of malignant gliomas was demonstrated with the use of echistatin incorporated microbubbles targeted to ␣v ␤3 . Weller et al. [58] used the RRL peptide incorporated microbubbles to show a significant accumulation of targeted microbubbles within subcutaneously implanted, human prostate carcinoma xenografts in mice. Although the RRL peptide is known to bind

Human KDR/ VEGFR2 Endoglin

Angiogenesis

Inflammation Inflammation Inflammation Inflammation Inflammation Inflammation Arteriosclerosis Transplant rejection Transplant rejection Thrombus Thrombus Lymph node

Angiogenesis

Angiogenesis VEGFR2, Integrin alphavbeta3, Endoglin Leukocytes P-selectin P-selectin P-selectin P-selectin MadCAM-1 VCAM-1 Leukocyte ICAM-1 GP IIb/IIIa GP IIb/IIIa L-selectin

Integrin ␣v ␤3 VEGFR2 VEGFR2 VEGFR2 Human KDR/ VEGFR2 VEGFR2

Angiogenesis Angiogenesis Angiogenesis Angiogenesis Angiogenesis

mAb RGD peptide RGD peptide MECA-79 ligand

Microbubble Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles Microbubbles

Microbubbles

mAb

mAb Sulfo-Le-AAA peptide mAb mAb mAb mAb

Microbubble

Microbubbles

Microbubble

Microbubble Microbubble Microbubble Microbubble Microbubbles

Microbubble Microbubble

Contrast Agent

Heterodimeric KDR-targeted peptide mAb

Echistatin peptide Tumor endothelial cell (target was not identified) Knottin peptides mAb mAb mAb Heterodimeric KDR-targeted peptide mAb

Ligand

Animal Model

Tissue necrosis factor-treated cremaster muscle of mice Mouse model for postischemic injury in kidney Rat model for postischemic injury in the myocardium Mouse model for postischemic injury Mouse model for postischemic injury Mouse model for inflammatory bowel disease Mouse model for arteriosclerotic plaque in ApoE deficient mouse Rat cardiac transplantation model Rat cardiac transplantation model Mouse cremaster muscle model for arteriolar and venular clots Thrombi formation in dogs Lymph nodes of mice and dogs

Subcutaneous tumor model in mouse for human pancreatic cancer and orthotopic pancreatic cancer model in mice Subcutaneous tumor model in mouse for human breast, ovarian and pancreatic cancer

Subcutaneous tumor model in mouse for human pancreatic cancer and orthotopic pancreatic cancer model in mice Subcutaneous human colon cancer xenografts in mice

Subcutaneous tumor model in mouse for human ovarian cancer Subcutaneous tumor model in mouse for angiosarcoma and glioma Subcutaneous tumor model in mouse for human melanoma Subcutaneous tumor model in mouse for murine breast cancer Orthotopic rat breast cancer model in rats

Subcutaneous tumor model in rat for human glioma Subcutaneous tumor model in mouse for human prostrate carcinoma

66 67 68 33 76 69 70

20 63 64 65

62

34

15

34, 35

14 59 60 61 16

57 58

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Angiogenesis

Integrin ␣v ␤3 Integrin ␣v ␤3

Molecular Target

Angiogenesis Angiogenesis

Disease

TABLE 11.1 Summary of Published Studies on the Use of Targeted Microbubbles for Ultrasound Imaging of Angiogenesis, Inflammation, Thrombus Formation, and Lymph Nodes

P1: OTA/XYZ P2: ABC c11 JWBS037-Chen February 2, 2011 Printer Name: Yet to Come

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TABLE 11.2 Summary of Published Studies on the Use of Targeted Nanoparticles for Ultrasound Imaging of Inflammation and Thrombus Formation Molecular Target

Disease

Ligand

Contrast Agent

Atherosclerosis ICAM-1, Fibrinogen

mAb

Liposome

Thrombus

ICAM-1

mAb

Liposome

Thrombus

VCAM-1

mAb

Liposome

Thrombus

Fibrin

mAb

PFC nanoparticles

Thrombus

Stretch induced

Tissue factor mAb

PFC nanoparticles

Animal Model

References

Yucatan miniswine model for atherosclerosis Yucatan miniswine for different stages of atheroma Yucatan miniswine for different stages of atheroma Thrombi formation in the carotid artery of pigs Pig model for balloon stretch induced injury to carotid artery

53

71

71

38

72

tumor endothelium, the molecular target is still not identified. Recent studies conducted by Willmann et al. [14] showed the use of a novel peptide—knottin—that binds to integrin ␣v ␤3 with high affinity. Knottins are small, compact peptides (20–60 amino acids) that consist of a core of at least three disulfide bonds that are interwoven into a “knotted” conformation. The in vivo molecular ultrasound imaging signal seen with knottin peptide when conjugated to the shell of contrast microbubbles was similar or higher when compared with microbubbles

(a)

(b)

FIGURE 11.5 (a) Transverse B-mode ultrasound image of a subcutaneous human colon adenocarcinoma xenograft tumor (arrows) in a nude mouse. (b) Targeted contrast-enhanced ultrasound image of tumor angiogenesis in same xenograft tumor (arrows) 4 min after intravenous injection of microbubbles targeted to VEGFR2; imaging signal from contrast microbubbles bound to VEGFR2 is shown as green overlay on B-mode image. Note: Molecular ultrasound imaging signal was measured using the destruction replenishment approach described in Figure 11.3.


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conjugated to a monoclonal antibody for integrin ␣v ␤3 . Knottins have great potential for in vivo applications due to their resistance to proteolysis and their high thermal stability and are thought to be nonimmunogenic. Finally, knottins may be a promising platform for designing novel contrast agents for molecular ultrasound imaging [14]. Another angiogenic marker, VEGFR2, has also been studied as a target for molecular ultrasound imaging using high-frequency ultrasound. Overexpression of VEGFR2 has been associated with tumor progression and poor prognosis in several tumors including colorectal, gastric, and pancreatic carcinomas; angiosarcoma; breast, prostate, and lung cancers; malignant gliomas; and melanomas. Several studies reported enhanced contrast images of tumor with the use of VEGFR2 targeted microbubbles [29, 32, 34, 35, 59–62]. Willmann et al. [29] used targeted microbubbles by coupling monoclonal antibodies as the binding ligand against VEGFR2 via streptavidin–biotin coupling chemistry; as a control, microbubbles were also conjugated to isotype matched antibody along with unlabeled microbubbles. The ability of these microbubbles to adhere to the target was first confirmed in cell culture experiments. In vivo ultrasound images were then acquired with a 40-MHz linear transducer in a mouse subcutaneous tumor model for angiosarcoma and malignant glioma. Accumulation of VEGFR2 targeted microbubbles was reported within subcutaneously implanted tumors compared to unspecific control microbubbles, which was further confirmed by immunofluorescence analysis of VEGFR2 expression in both tumor types [29]. Rychak et al. [60] reported similar results on subdermal tumors derived from human melanoma cells in mice. Studies performed by Lyshchik et al. [61] compared expression of VEGFR2 by targeted microbubbles on highly invasive metastatic and nonmetastatic murine models of breast cancer cells demonstrating that targeted ultrasound can be used to characterize angiogenic activity corresponding to the degree of malignancy. They observed a higher accumulation of VEGFR2 targeted microbubbles within the more aggressive tumors. Korpanty and colleagues [34] investigated the use of targeted microbubbles to follow vascular response of therapy in addition to detection of tumor angiogenesis by molecular ultrasound. VEGFR2 targeted microbubble accumulation was assessed to quantify vascular effects of two different antitumor therapies—namely, with antivascular endothelial growth factor (VEGF) monoclonal antibodies and/or gemcitabine. The model systems used were subcutaneous as well as orthotopic pancreatic cancer tumors in mice. They detected decreasing marker densities after tumor- suppressive therapy, which correlated with the observed effects of treatment. In addition, they performed a multimarker imaging, assessing VEGFR2 followed by Endoglin targeted microbubbles in the same tumor after a long interval between scans to ensure passive clearance of previously injected microbubbles. Endoglin is a cell membrane glycoprotein that is involved in vascular development and remodeling and is overexpressed on tumor-associated vascular endothelium. Targeted microbubbles showed significant enhancement of tumor vasculature when compared with untargeted or control IgG targeted microbubbles that correlated with ex vivo expression analysis. In the same light Palmowski and colleagues [35] demonstrated an upregulation of VEGFR2 and of integrin ␣v ␤3 during the growth of untreated tumors, and a downregulation of both markers after antiangiogenic therapy using microbubbles conjugated to VEGFR2 antibodies and cyclic RGD peptides. Recently, Pysz et al. [15] evaluated a novel, clinically-translatable microbubble targeted to human kinase insert domain receptor (KDR; the human protein analogous VEGFR-2) for monitoring antiangiogenic therapy in subcutaneous human colon cancer xenografts in mice. In mice receiving antiangiogenic therapy in vivo molecular ultrasound imaging using novel KDR-targeted microbubbles significantly


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decreased as early as 24 hours after initiation of antiangiogenic therapy. In contrast, no difference in molecular ultrasound KDR-targeted imaging signal was observed in nontreated mice. Furthermore, KDR-associated molecular ultrasound signal was observed prior to any changes in tumor size; thus, demonstrating the advantage of early assessment of antiangiogenic therapy using molecular ultrasound imaging prior to overt morphological-anatomical changes become visible in tumors. Another aspect observed by Willmann et al. [59] was that multiple markers conjugated on microbubbles could significantly enhance the imaging signals, which could be a useful tool for detection of tumors early enough for effective therapy. Toward this goal, it was demonstrated that dual-targeted microbubbles carrying antibodies for VEGFR2 and integrin ␣V accumulate to higher intensities compared to single targeted microbubbles in tumor angiogenesis of human ovarian cancer in mice xenografts. These results may be of great significance for early detection of cancer when tumors are too small to cause detectable morphologic changes but large enough to induce tumor angiogenesis (Fig. 11.6). Molecular ultrasound imaging also allows noninvasive mapping of expression levels of angiogenic markers in tumor angiogenesis. In three different tumor types (breast, ovarian, and pancreatic cancer) and using noninvasive molecular ultrasound imaging, Deshpande et al. [62] showed varying expression levels of the three angiogenic markers integrin ␣v ␤3 , endoglin, and VEGFR2 during tumor growth. In this study, Using ex vivo western blotting as reference standard, the study confirmed that molecular ultrasound imaging allows longitudinal noninvasive assessment of the temporal tumor angiogenic molecular marker expression levels in vivo [62]. The results of this study provided further insights into the biology of tumor angiogenesis and may help in defining promising imaging targets for

Endothelial cell

Endothelial cell

Endothelial cell

Endothelial cell

FIGURE 11.6 Single and dual targeted microbubbles and interaction with tumor vessel endothelial cells. Gas-filled microbubbles (MBs) conjugated to ligands bind molecular markers of angiogenesis (e.g., VEGFR2) expressed on tumor vessel endothelial cells. Dual targeted MBs, which carry two types of ligands on their shells, can bind to more molecular markers compared to single targeted microbubbles. This increases the signal intensity from derived bound microbubbles, which, for example, may increase the detection of small tumors.


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both early cancer detection and treatment monitoring of cancer using molecular ultrasound imaging [62].

Molecular Ultrasound Imaging of Inflammation Inflammation is a common physiological process occurring in a vast number of diseases such as ischemia (inadequate blood supply to tissue), arthrosclerosis, or inflammatory bowel disease to mention only a few. One crucial component of inflammation is the activation of leukocytes in the blood pool and their transmigration to the extravascular compartment. The recruitment and transmigration of leukocytes are mediated by the interaction between adhesion molecules on the leukocytes and on the endothelial cell surface [20]. Several molecules including E- and P-selectin mediate the initial capture and consecutive rolling of leukocytes on the inner vessel wall. A firm arrest of the rolling leukocytes, the necessary precondition for transmigration, is promoted by a second group of adhesion molecules, namely, the intercellular adhesion molecule-1 (ICAM- 1) and the vascular cell adhesion molecule-1 (VCAM-1). All inflammatory markers are expressed rapidly during the inflammatory process and have been reported to correlate to a certain degree to the stage of inflammation. Both passive and active targeting has been explored for imaging inflammation using molecular ultrasound. Passive targeting does not provide molecular-level information, but rather enables qualitative detection of inflammation as microbubbles attach to (and eventually phagocytosed by) activated leukocytes. This leads to damping, but the microbubbles remain acoustically responsive and still produce an acoustic signal [74]. One strategy for passive targeting is to incorporate negatively charged phosphatidylserine into the shell, which promotes microbubble attachment to activated leukocytes. This technique was used to image tissue necrosis factor-␣-treated inflamed cremaster muscle in mice and to assess the severity and extent of postischemic myocardial inflammation in dogs [74]. For active targeting, monoclonal antibodies that bind inflammatory markers like E- and P-selectin, ICAM-1, and VCAM-1 have been outfitted onto microbubbles for molecular ultrasound imaging of inflammation [8]. P-selectin, which is expressed immediately after an ischemic stimulus, was used to assess postischemic injury in the mouse kidney [63]. P-selectin targeted microbubbles were also used to identify recently ischemic myocardium in a myocardial ischemia reperfusion model in mice [64]. A similar study used sialyl Lewis (a P-selectin ligand) conjugated microbubbles in a rat model for myocardial ischemia reperfusion to visualize “the ischemic memory” noninvasively using molecular ultrasound imaging [65], highlightening the potential of molecular ultrasound imaging as a rapid and straight forward bedside test for screening patients with atypical chest pain for a recent ischemic event. The gut-specific marker “mucosal addressin cellular adhesion molecule-1” (MAdCAM1) was used as a target to image a mouse model for inflammatory bowel disease [66]. Bachmann et al. [66], using transabdominal ultrasound, demonstrated a significant accumulation of MAdCAM-1 targeted microbubbles as compared to nonspecific ones in focal areas of ileal inflammation, thus producing stronger acoustic signals. VCAM-1 antibodyconjugated microbubbles were utilized by Kaufmann et al. [67] to demonstrate a correlation between different stages of arteriosclerosis and the retention of microbubbles. The inflammation disease model system used was ApoE deficient mice, which form inflammatory plaques in the aorta when fed a high-cholesterol diet. Two studies have been reported to investigate transplant rejection in vivo in animal models. The first study employed passively leukocyte-targeted microbubbles with phosphatidylserine to assess acute allograft rejection


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in a rat cardiac transplantation model [68]. The degree of rejection in transplanted hearts could be directly revealed by the magnitude of intramyocardial infiltration of macrophages and T lymphocytes due to accumulation of targeted microbubbles at the site of inflammation. The second study used microbubbles conjugated to ICAM-1 antibody for selective imaging of cardiac transplant rejection in rats; approximately a tenfold increase in contrast intensity was observed in rejecting myocardium [33].

Molecular Ultrasound Imaging of Thrombus Formation A thrombus or blood clot is achieved via the aggregation of platelets that form a platelet plug, and the activation of the humoral coagulation system. A thrombus is normal in cases of injury, but pathologic in instances of thrombosis. Research in detection of thrombus formation by ultrasound imaging has been ongoing to develop contrast agents that could detect diseases such as stroke, myocardial infarct, and deep vein thrombosis. Various molecular markers conjugated to microbubbles, PFC nanoparticles, and liposomes were developed for animal studies: for platelet targeting, antibodies against GPIIb/IIIa receptors expressed on activated platelets or RGD peptides recognized by the active binding site of GPIIb/IIIa were developed, and various monoclonal antibodies were generated against markers associated with atheroma development such as fibrin, ICAM-1, VCAM-1, and tissue factor. Microbubble binding studies on arteriolar and venular clots in a mouse cremaster muscle model were conducted by Schumann et al. [76]. They confirmed binding of targeted microbubbles in both venules and arterioles. Hamilton et al. [71] used these targeted liposomes for intravascular ultrasound imaging of injured vessels of miniswine as a model system used to create various stages of atheroma. Different types of targeted liposome were generated with conjugation of anti-ICAM-1, anti-VCAM-1, anti-fibrin, and anti-tissue factor antibodies. These targeted liposomes demonstrated targeted enhancement in the vessel walls 5 min after intravenous administration. Similarly, Demos et al. [53] injected echogenic liposome targeted to atherosclerotic plaque created in the Yucatan miniswine animal model. The liposomes were conjugated with anti-fibrinogen or anti-ICAM-1 antibody. The liposomes attached to thrombi and to atherosclerotic arterial wall. Mean acoustic intensities of blood alone and blood with nontargeted and targeted agents showed that targeted liposomes dramatically increased the echogenicity of blood. Lanza et al. [38] employed targeted PFC nanoparticles for intravascular ultrasound and MRI contrast imaging. The PFC nanoparticles were outfitted with biotin–avidin coupling system along with anti-fibrin monoclonal antibodies. Frequency of thrombus detection increased from 2% to 83% after single administration and increased to 96% after second administration of targeted PFC nanoparticles with increased acoustic reflectivity of carotid thrombi of dogs. In a related study, a stretch induced tissue factor was imaged in balloon stretched pig carotid arteries by administering a tissue factor targeted antibody on biotinylated PFC nanoparticles. After administration of the targeted nanoparticles, the arteries were imaged with a 20-MHz intravascular ultrasound system, and the targeted contrast more than doubled the gray scale intensity of the injured areas [72]. Unger et al. [69] have developed microbubbles labeled with RGD analog that enhanced the echogenicity of induced thrombi in dogs. Molecular Ultrasound Imaging of Lymph Nodes The feasibility of using targeted microbubbles to image peripheral lymph nodes under normal conditions in animal models of mice and dogs was tested by Hauff et al. [70] by the use of stimulated acoustic emission (SAE). SAE involves color or power Doppler imaging with the transmission power set high enough to ensure microbubble disruption on the first pulse. This causes a transient high-


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257

amplitude response. Since an ultrasound Doppler system correlates the signal backscattered from a target within a number of successive pulses, the loss of signal correlation caused by the transient bubble collapse is interpreted by the machine as a random Doppler shift, resulting in a mosaic of colors at the location of microbubbles even without flow. SAE works particularly well with the air-filled microbubbles, as used by Hauff and colleagues. It has proved a powerful method of studying passively targeted agents [77] but has not previously been used to image active targeting. Microbubbles were conjugated to L-selectin specific ligand MECA-79. L-selectin is expressed on circulating lymphocytes and is involved in homing of the lymphocytes to lymph nodes. In these experiments, mice were sacrificed after intravenous administration of L-selectin targeted microbubbles. The lymph nodes were removed and examined by using harmonic color Doppler ultrasound in a tank containing degassed water. The lymph nodes of all the mice showed enhanced acoustic signal due to accumulation of L-selectin targeted microbubbles. In another experiment, anesthetized dogs were scanned with ultrasound in vivo after administration of L-selectin targeted microbubbles intravenously. The targeted microbubbles accumulated significantly in healthy lymph nodes. Thus L-selectin ligand-specific US contrast agent could be a candidate for an indirect method of lymphography for the safe and less invasive US identification of lymph nodes—for example, when performing ultrasound-guided biopsy [70].

11.4 CHALLENGES AND FUTURE DIRECTIONS OF MOLECULAR ULTRASOUND IMAGING Ultrasound imaging lacked effective contrast agent to render it a molecular ultrasound imaging tool until recently. With the introduction of microbubble contrast agents, great progress has been made in the field of contrast enhanced molecular ultrasound imaging. Furthermore, the development of targeted contrast agents has made it possible to image the pathophysiology of many diseases at the molecular and cellular levels using molecular ultrasound imaging and has opened up new avenues for using molecular imaging for therapy. A lot of investigative research has been done to detect intravascular events that play a role in cardiovascular and cerebrovascular diseases, including inflammatory responses, angiogenesis, and thrombus formation by targeted contrast-enhanced ultrasound in the last few years. Yet the field currently is restricted to animal models of human disease. Humanizing antibodies used for target detection using targeted microbubbles can be very expensive. Furthermore, the current biotin–streptavidin system used for preclinical trials to attach ligands onto the shell of ultrasound contrast agents is not suitable for clinical use, due to the immunogenic and allergic risk that streptavidin presents to humans, especially in the case of repeated use. Investigation of synthetic novel peptides that recognize a variety of molecular markers are under way and may provide a cost-effective alternative, circumventing the problem of allergic reactions in humans [14, 15]. Recently, it has been shown that a novel, clinically translatable contrast microbubble targeted to human KDR (which corresponds to VEGFR2 in mice) were designed using a small peptide directly integrated into the shell of contrast microbubbles (thereby avoiding binding chemistry that would preclude a clinical translation into patients) [15]. Molecular ultrasound imaging signal using this human KDR-targeted contrast agent showed significantly higher imaging signal in human colon cancer xenografts in mice than control microbubbles and allowed monitoring of antiangiogenic therapy in vivo [15]. This novel contrast agent was the first that was designed specifically for a clinical translation into patients; first in


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human clinical trials are expected for the near future assessing the potential of molecular ultrasound imaging in a clinical environment [15]. Several new microbubble constructs such as the described human KDR-targeted microbubbles, comprehensive scanner systems, and imaging protocols are currently under development to expand this technology to the clinical arena. Targeted contrast-enhanced ultrasound imaging could potentially be used in a wide range of applications, including diagnostics, image-guided biopsies, and treatment follow-up. Lastly, microbubbles today are still restricted to intravascular space; research into nanoparticles would likely help to overcome this aspect. Finally, extensive research is being directed toward development of the next generation of microbubbles, which are capable of encapsulating therapeutic agents and releasing them when exposed to high MI ultrasound waves. Microbubbles in combination with a therapeutic agent provide the vehicle for targeting molecular events and thus combining imaging with pathophysiology and ultimately therapy. Therapeutic agents could include genes, thrombolytics, and oncological drugs, and this technique has the clinical potential to increase therapeutic efficacy while decreasing systemic side effects. Clinical use of microbubbles has faced problems with regard to safety issues. In 2007 the United States Food and Drug Administration (FDA) ordered black box warnings for two contrast agents—Definity, formerly sold by Bristol-Myers Squibb, and Optison, sold by GE Healthcare—following reports of 11 deaths allegedly associated with the two agents. Optison consists of perflutren protein-type A microspheres, whereas Definity (available as Luminity in Europe and Australia) is a preparation of liposome-encapsulated microspheres containing perflutren. Both contrast agents were initially approved for clinical use in patients for echocardiography to enhance suboptimal echocardiograms to opacify the left ventricular chamber and to improve the delineation of the left ventricular endocardial border. The related ban nearly entirely halted the use of Definity in the United States. In 2008 the FDA eased off the stringent black box warnings that greatly restricted use of Definity and Optison. The FDA announcement followed publication of a retrospective study in the Journal of the American College of Cardiology (2007; 1704–1706). The review, involving 18,671 consecutive patients at St. Luke’s Mid-America Health Institute in Kansas City, Missouri, found no increased mortality risk for patients who received Definity-enhanced echocardiography compared with patients who were imaged without the agent. Some FDA-mandated labeling restrictions remain: Definity is now contraindicated for patients with known or suspected right-to-left, bidirectional, or transient right-to-left cardiac shunts and hypersensitivity to perflutren, an ingredient of the microspherical agents. Intra-arterial injection is still banned. So far, microbubble ultrasound contrast media are not approved for noncardiac applications in the United States [78]. However, there is an ongoing Phase III clinical trial in thr USA testing the diagnostic accuracy of nontargeted contrast-enhanced ultrasound imaging (using the microbubble SonoVue) for liver lesion characterization compared to CT, MRI or histology as the golden standard. Following successful completion of this clinical trial, US FDA approval of nontargeted contrast-enhanced ultrasound imaging for radiological indications is expected. Contrast-enhanced ultrasound imaging with nontargeted microbubbles is already widely used in Canada, Europe, and Asia. and microbubbles have been shown to be nontoxic with an extremely low adverse event rate as low as 0.13% (29 per 23,988 examinations) [79]. In conclusion, molecular ultrasound is an emerging molecular imaging approach finding its niche among other molecular imaging modalities. High spatial and temporal resolution, real-time imaging, noninvasiveness, relatively low costs, lack of ionizing irradiation and wide availability among the imaging community throughout the world are important advantages that will further define the role of this novel imaging technique both in preclinical


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research and clinical applications. In addition, ongoing improvements in ultrasound technology and sophisticated contrast agent design with novel high-affinity targeting ligands using clinically translatable binding chemistry, and further improvements in biodistribution of ultrasound contrast agents beyond the vasculature will further expand the clinical role of molecular ultrasound for imaging diseases at the molecular level in medicine [80, 81, 82].

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CHAPTER 12

Ultrasound-Based Molecular Imaging Using Nanoagents SRIVALLEESHA MALLIDI, MOHAMMAD MEHRMOHAMMADI, KIMBERLY HOMAN, BO WANG, MIN QU, and TIMOTHY LARSON Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA

KONSTANTIN SOKOLOV Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, and Department of Medical Physics, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA

STANISLAV EMELIANOV Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA

12.1 INTRODUCTION The need to understand the anatomical and functional aspects of the human body has led to the development of various noninvasive imaging modalities such as X-ray computed tomography (CT), ultrasonography (US), and magnetic resonance imaging (MRI). These imaging modalities are used extensively to diagnose pathologies such as cancer. In particular, ultrasonography, or ultrasound imaging, has gained popularity due to its excellent temporal resolution, reasonable penetration depth, portability, and low cost. Furthermore, ultrasound imaging is a nonionizing technique with no known adverse bioeffects. Currently, ultrasound imaging is being used in various medical fields ranging from obstetric medicine to cardiovascular applications. Obtaining an ultrasound image can be explained as a three-step process. First, the ultrasonic transducer generates pulses of ultrasound waves that are sent through a patient’s body. These waves then interact with organ boundaries and complex tissues, producing echoes due to reflection or scattering. Finally, the backscattered echoes are detected by the same transducer used for transmission of ultrasound waves. Digital postprocessing of these ultrasound signals results in formation of a gray scale image of the body or tissue cross section. Thus contrast in ultrasound images is due to the difference in the acoustic impedance of the tissues being imaged.

Nanoplatform-Based Molecular Imaging Edited by Xiaoyuan Chen C 2011 John Wiley & Sons, Inc. Copyright

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Advancements in the field of molecular biology (i.e., discovery of various diseasespecific biomarkers) coupled with development of ultrasound biomicroscopy [1] (imaging performed at the acoustic frequency range of 40–100 MHz) has prompted development of site-specific ultrasound contrast agents that can provide molecular information in the context of a high-resolution anatomical map of the body. Indeed, microbubbles. For example, microbubbles have enhanced ultrasound contrast due to their acoustic impedance difference with tissue. When targeted to various biomarkers in the vascular lumen, these microbubbles can provide some molecular specific ultrasound imaging contrast. However, the gas-filled microbubbles have short lifespans (on the order of minutes) in the body, and due to their large size (∼0.5–500 ␮m diameter) are mostly used as intravascular tracers [2–7]. Other types of ultrasound contrast agents such as liposomes have been developed for molecular imaging [4, 8]. Liposomes have longer circulation time compared to microbubbles and they can also readily be conjugated to various biomarkers. However, passage of liposomes (∼800 nm in diameter) through endothelial gap junctions in the leaky vascular of pathologies such as cancer is size prohibitive. The vasculature of most cancers have endothelial gap junctions from 300 to 800 nm in size, and therefore liposomes would likely not reach the tumor interstitial space [9]. Recently developed ultrasound nanoparticle contrast agents such as perfluorocarbon nanoparticles [4] and silica nanoparticles [10] could extravasate through the leaky vasculature of a tumor into the interstitial space but are less echogenic compared to microbubbles. Metal based nanoparticles (∼5–100 nm in diameter) are being used extensively as molecular specific contrast agents for various imaging modalities such as optical imaging and MRI. Many researchers have demonstrated that metal nanoparticles extravasate and accumulate in tumors due to the enhanced permeability and retention (EPR) effect [11, 12]. This effect is caused by the leaky nature of tumor vessels. Thus by an injection of correctly sized metal nanoparticles, passive accumulation in tumors can be achieved. Furthermore, the metal nanoparticles can be made pathology-specific by bioconjugating them with monoclonal antibodies or antibody fragments. These bioconjugates can be attached either directly to the metal or covalently bound via linker segments. Metal nanoparticles (NPs) such as gold NPs have well-known bioconjugation protocols. Metal NPs are at the same size scale as large protein complexes and so can be targeted to subcellular structures. However, these metal nanoparticles cannot be used as ultrasound contrast agents because their size is much below the resolution of clinically available ultrasound imaging systems. On the other hand, molecular imaging with the metal NPs is possible using ultrasound based imaging modalities, namely, photoacoustic imaging [13, 14] and magneto-motive ultrasound imaging (MMUS) [15, 16]; that is, molecular and functional information could be obtained in the context of the anatomical map of the tissue. For example, gold nanoparticles exhibiting surface plasmon resonance properties and superparamagnetic iron oxide (SPIO) nanoparticles are used as photoacoustic and magnetoacoustic contrast agents, respectively. The synergy among the ultrasound, photoacoustic, and MMUS imaging modalities is schematically represented in Figure 12.1. The ultrasound transducer and the receiver electronics of an ultrasound imaging system are common for both photoacoustic and magnetoacoustic imaging. In photoacoustic imaging, the tissue is illuminated by nanosecond pulsed laser light and the subsequently emitted photoacoustic waves are detected by the ultrasound transducer (Fig. 12.1). The use of photoabsorbers such as gold nanoparticles enhances the contrast in photoacoustic imaging. In MMUS imaging, ultrasound images of the tissue labeled with magnetic nanoparticles are acquired under magnetic field excitation.


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Image display

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Contrast mechanism RF pulse transmit

Amplitude of received RF echoes

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Amplitude of tissue displacement

Magneto-motive ultrasound imaging Amplitude of photoacoustic transients

Tissue Acoustic Impedance Receive echo

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Motion induced in tissue labeled with magnetic NPs

Harmonic or Pulsed magnetic field

Tissue Optical Absorption

Pulsed Laser

Photoacoustic imaging

FIGURE 12.1 Schematic representation of contrast mechanism and image display in ultrasound, magneto-motive ultrasound, and photoacoustic imaging modalities.

The ultrasound images are then digitally postprocessed to observe the magnetically induced tissue motion (Fig. 12.1). In this chapter, we briefly review the fundamentals of photoacoustic and magnetoacoustic imaging modalities and also demonstrate their molecular imaging capabilities using metal nanoparticles. Furthermore, the feasibility of combining the photoacoustic and magnetoacoustic imaging techniques will be discussed. Finally, the advantages, limitations, and future prospects of ultrasound based photoacoustic and magnetoacoustic imaging modalities are illustrated.

12.2 PHOTOACOUSTIC IMAGING Photoacoustic imaging, also known as optoacoustic and thermoacoustic imaging, involves three steps [17–19]: (1) short laser pulses irradiate the tissue, (2) the tissue absorbs the laser energy; undergoes thermoelastic expansion, and subsequently generates a photoacoustic pressure wave; and (3) the generated pressure wave is detected by an ultrasound transducer. Note that the thermoelastic expansion occurs because the laser pulse duration is shorter than the thermal relaxation time of the tissue (thermal confinement condition). The acoustic pressure P(z) generated at a certain depth z using laser illumination of wavelength ␭ can be expressed as [17, 18] P(z) =

␤cs2 CP

␮a (␭)F(z, ␭)

(12.1)

where ␤ is the thermal expansion coefficient, cs is the speed of sound, CP is the heat capacity at constant pressure, ␮a is the optical absorption coefficient, and F(z) is the laser fluence


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at depth z. The photoacoustic pressure wave is a broadband radiofrequency (RF) signal and can be detected using an ultrasound transducer that determines the resolution of the photoacoustic imaging. A resolution on the order of tens of micrometers can be achieved using a high-frequency ultrasound transducer. The detected photoacoustic RF signals or transients are then processed and displayed as a photoacoustic image. The expression (␤cs2 /CP ) in Eq. (12.1) is called the Gruneisen coefficient, a temperaturedependent parameter. For a constant temperature and laser fluence irradiating the tissue, the photoacoustic signal strength is proportional to the optical absorption coefficient of the tissue. Indeed, the distribution of optical absorption properties of the tissues can be obtained by analyzing photoacoustic images captured at multiple wavelengths. For example, functional information such as the oxygenation of blood or the presence of atherosclerotic plaques may be extracted from multiwavelength photoacoustic images [20, 21]. Photoacoustic imaging exploits both the high contrast associated with optical imaging techniques (due to optical absorption properties) and the spatial resolution of ultrasound imaging (due to detection by the ultrasonic transducer). Unlike optical imaging modalities, where the penetration depth is limited by optical backscattering from the tissue, photoacoustic imaging can image deeper since it detects sound versus light. Moreover, greater penetration depth in tissue can be achieved using near-infrared (NIR) wavelengths because endogenous chromophores such as melanin and blood absorb less light in the NIR range. Similar to optical imaging techniques, the use of exogenous contrast agents or photoabsorbers with higher optical absorption in the optical NIR window could facilitate the detection of pathologies in photoacoustic imaging. Metal nanoparticles, which have greater absorbance compared to conventional dyes such as indocyanine green, qualify as contrast agents in photoacoustic imaging. A variety of shapes and sizes of metal nanoparticles including gold or silver nanospheres, rods, and shells can be used as photoabsorbers [14, 22–25]. It’s apparent that by varying the shape and aspect ratio of nanostructures, particles can be manufactured to absorb light at a desired wavelength across a wide spectrum including the near-infrared spectrum, where the absorption of light by tissue is minimal. Moreover, the change in the optical absorption properties due to the plasmon coupling effect of closely spaced nanoparticle assemblies can also be detected using photoacoustic imaging [14]. 12.2.1 Description of Ultrasound Based Photoacoustic Imaging System A block diagram of the combined ultrasound and photoacoustic imaging system is presented in Figure 12.2. The imaging system primarily involves an integrated probe consisting of a ultrasonic and laser light delivery [13]. The light is delivered to the tissue through a fiberoptic bundle as shown in photographs of an integrated probe with a single element high-frequency transducer or an array transducer, respectively. The laser light delivery could also be done through a combination of various optical elements such as an axicon and prisms [18, 26, 27]. The integrated probe could be handheld or controlled using a positioning stage for mechanical scanning. For special applications such as intravascular photoacoustic imaging, an intravascular ultrasound transducer can be integrated with side fire fiber as shown in Figure 12.2c. The combined imaging system can work either in the ultrasound or photoacoustic imaging mode. In the ultrasound mode, the transducer transmits the rf pulse and receives the backscattered echo from the tissue. In photoacoustic mode, the short laser pulse excites the tissue and the generated acoustic transients are received by the ultrasonic transducer. The


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Trigger Ultrasound Pulser Ultrasound imaging Mode selection

Positioning stage or handheld

Integrated probe Receive Electronics

Transducer

Digital processing of RF data

Image Display

Fiber bundle Photoacoustic imaging (a)

Trigger

Laser

Transducer

(b)

(c)

Optical Fiber

(d)

FIGURE 12.2 (a) Block diagram of combined ultrasound and photoacoustic imaging system. (b–d) Photographs of an integrated probe consisting of a high-frequency single element transducer (b), an intravascular ultrasound transducer (c), and a linear array transducer (d) with optical delivery system.

ultrasound and photoacoustic rf data can be acquired sequentially from the same imaging plane using a single element transducer or an array transducer. In either case, spatially coregistered ultrasound and photoacoustic images can be obtained [13, 28].

12.2.2 Enhancement of Photoacoustic Contrast Using Silver Nanocages In most works to date, gold nanoparticles have been used, almost exclusively, to enhance photoacoustic contrast. Here we present an alternative: silver nanoagents. Being in the noble metal category, both silver and gold exhibit plasmonic resonance in the visible to NIR spectrum of light. Silver, however, has slightly better light absorption and therefore in theory should be a stronger photoacoustic contrast agent [29, 30]. In our attempts to explore this theory, silver nanocages built around a silica core were developed with core sizes ranging from 180 to 520 nm (Fig. 12.3a). These nanocages absorb light broadly across NIR wavelengths. To test their contrast properties in tissue, these nanocages were injected into an ex vivo porcine pancreas and imaged photoacoustically. The result of the photoacoustic and ultrasound imaging performed is shown in Figure 12.3b. Specifically, the combined ultrasound and photoacoustic system with a 7.5-MHz linear array ultrasound transducer and 800-nm laser illumination was employed to image silver nanocages injected into an ex vivo porcine pancreas. The 183-nm silica core, silver outer cage particles (100 ␮L


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(a) Ultrasound

Photoacoustic

Combined

Image

Image

Image

(b)

(c)

(d)

FIGURE 12.3 (a) SEM image of silver nanocages. (b) Ultrasound, (c) photoacoustic, and (d) combined images of ex vivo pancreas tissue injected with silver nanocages. Adapted with permission from Ref. 55.

of 1010 particles/mL) were injected via syringe, approximately 8–10 mm below the pancreas surface. Spatially coregistered ultrasound and photoacoustic rf data was captured using a Cortex ultrasound imaging system (Winprobe Corporation, North Palm Beach, FL, USA). The ultrasound image (Fig. 12.3b) defines the pancreas area, the photoacoustic image (Fig. 12.3c) shows the signal received from the nanocages (white inset), and the combined image (Fig. 12.3d) clearly depicts the location of the nanocages against the background ultrasonic image of the organ. Thus if these nanocages were injected systematically and accumulated in a cancerous area, then combined ultrasound and photoacoustic images could be used to locate them inside the tissue, helping clinicians to better define diseased areas. In this example silver nanoparticles were used instead of the well-characterized gold nanoparticles. Silver nanoparticles have both advantages and disadvantages. One known advantage is silver’s ability to absorb and scatter light better than gold [29]. One disadvantage is silver’s reactivity. Gold is relatively inert, owing to its biocompatibility. Under certain conditions, silver is more reactive and has been shown to be cytotoxic in some in vitro studies [31]. However, silver is well known for its antimicrobial properties and has been used for decades in the treatment of burns [32]. In recent years, silver is being used to line catheters to decrease infection levels [33, 34]. Thus, there is a resurgence in the use of silver in biomedical applications and future studies will be needed to determine its true efficacy and biocompatibility.

12.2.3 Monitoring Accumulation of Gold Nanoparticles in Tumor Using Photoacoustic Microscopy Photoacoustic imaging can also be used to monitor accumulation of nanoparticles in the tumor site over time. A tumor xenograft with A431 cells (human epithelial cancer cell line) was performed in nude mice. After the tumor reached approximately 10 mm in diameter, gold nanoparticles (40 nm in diameter) specifically targeted to the epidermal growth factor receptor [35] (EGFR) are imaged using single element transducer (25 MHz central frequency) and 532-nm wavelength illumination. The combined ultrasound and photoacoustic images of the tumor before and after the injection of gold nanoparticles are shown in Figure 12.4. Clearly, the accumulation of gold NPs over time is evident (Fig. 12.4f–h).


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After injection of Au NPs 0 hrs

2 hrs

4 hrs

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

Ultrasound images

Photoacoustic images

FIGURE 12.4 (a) Monitoring the accumulation of 40-nm gold nanoparticles in tumor using combined ultrasound (a–d) and photoacoustic (e–h) imaging at 532-nm wavelength illumination. The images represent a 13-mm × 11.25-mm field of view.

12.3 MAGNETO-MOTIVE ULTRASOUND IMAGING Magnetoacoustic imaging is a technique that employs high-frequency ultrasound to visualize structural and physiological properties of magnetically labeled tissues. The magneto-acoustic imaging technique capitalizes on significant contrast between magnetic susceptibility of normal tissue constituents and magnetic nanoparticles as well as on deep penetration of magnetic fields into human tissue. Specifically, the magnetoacoustic imaging procedure involves two steps: (1) magnetic nanoparticles such as superparamagnetic iron oxide (SPIO) nanoparticles are used to specifically label pathological tissues, and (2) a pulsed or time-varying magnetic field excites the magnetic nanoparticles to induce motion in the magnetically labeled tissues, along with simultaneous detection of the motion using noninvasive, deep penetrating ultrasound imaging techniques [16, 24, 36–38]. In the last few decades, much research has been devoted to the synthesis of magnetic nanoparticles. Several types of commercial or custom designed nanoparticles such as the superparamagnetic iron oxide (SPIO) nanoparticles were approved by the FDA and has been widely used in clinical applications as MRI contrast agent [36, 39]. Magnetic nanoparticles have been synthesized with a number of different compositions and phases, including iron oxides (Fe3 O4 and ␥ -Fe2 O3 ), pure metals (Fe,Co), spinel-type ferromagnets (MgFe2 O4 , MnFe2 O4 , and CoFe2 O4 ), and alloys (CoPt3 and FePt). A review of the synthesis and functionalization of magnetic nanoparticles has been provided elsewhere [40, 41]. The displacement occurring in the magnetically labeled tissue is dependent on several parameters such as the applied magnetic field and the susceptibility of the magnetic NPs. To understand and estimate the induced motion in the magnetically labeled tissue, the characteristics of the nanoparticles and the magneto-motive force acting on the magnetic nanoparticles need to be analyzed. The magneto-motive force acting on a particle can be expressed as Fm = (m • ∇)B,

(12.2)


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where m is the magnetic moment. Considering a z-directional magnetic flux B = (0,0,Bz ) and the magnetic moment m of paramagnetic particles as (0,0,mz ), the magneto-motive force F m can then be expressed as Fm = (m z • ∇)Bz ,

(12.3)

The magnetic moment mz experienced by a magnetic nanoparticle located in a weakly diamagnetic medium like tissue can be written m z = Vm Mz

(12.4)

where V m is the volume of the magnetic portion of the nanoparticle and can be described as Vm = Vnp × f m , where V np is the total size of the nanoparticle and f m is dimensionless factor called the fraction of magnetite and represents the volumetric ratio of magnetic material in a nanoparticle. The volumetric magnetization M can be written as Mz = (␹ np − ␹ medium )Hz . The magnetic susceptibility of the medium, that is, human tissue, is on order of 10−6 (−11 × 10−6 ≤ ␹ Tissue ≥ −7 × 10−6 ) while the susceptibility of magnetite nanoparticles (Fe3 O4 ) is 70 and it is 250 and 600 for other nickel and cobalt magnetic agents [42, 43]. Hence ␹ medium is assumed to be negligible. Another assumption is that the magnetic flux density (B) doesn’t change significantly over the nanoparticle due to its small size; the volumetric magnetization M can be expressed as Mz = ␹ np

Bz ␮0

(12.5)

Therefore from Eqs. (12.3) and (12.4), Fm =

Vnp f m ␹ np (Bz • ∇)Bz . ␮0

(12.6)

Since (Bz • ∇)Bz = 12 ∇(Bz • Bz ) = Bz

∂ Bz , ∂z

the magneto-motive force acting on a nanoparticles F m can be expressed as Fm =

Vnp f m ␹ np ∂ Bz Bz ␮0 ∂z

(12.7)

Clearly, from Eq. (12.7) it can be seen that there is a significant contrast in the force experienced by the normal and iron-laden tissue. The magneto-motive force is proportional to size (V np f m ) and the susceptibility (␹ np ) of nanoparticles. Increasing the size of the nanoparticles has some limitations for specific labeling or cellular uptake as larger nanoparticles are harder to diffuse out of the leaky vessels. Therefore the magnetic susceptibility (␹ np ) of nanoparticles plays an important role in determining the sensitivity of the magnetoacoustic imaging technique. Iron oxide nanoparticles have high magnetization up to 70 emu/gram; Fe, but other magnetic materials like nickel and cobalt or some alloys can have higher magnetization [44–46]. However, safety and toxicity issues of these materials are still subject to more investigation. Encapsulation of the toxic magnetic alloy core into


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a carbon or polymer shell could be one of the solutions to reduce the cytotoxicity of the metal nanoparticles [47, 48]. The excitation magnetic field can be either continuous-time (harmonic) or pulsed mode. Pulsed excitation has several advantages over harmonic excitation such as shorter operation time and increased magnetic flux density, thus allowing the imaging of deeper tissue structures [15]. Pulsed excitation also has less severe thermal management constraints. On the other hand, a harmonic system creates motion at a predetermined frequency and possibly can be used to identify and filter out the sources of tissue motion due to cardiac and respiratory systems. 12.3.1 Description of Magneto-motive Ultrasound Imaging System The block diagram of the magnetoacoustic imaging system is shown in Figure 12.5. The system consists of two major parts: (1) the magnetic field generation and (2) the ultrasound imaging and data acquisition. According to Ampere’s law, the magnetic field of a solenoid coil, B, has the same time characteristics as the supplied current. Hence a controllable current amplifier or a flash circuit could be used to generate a harmonic or pulsed magnetic field. A conical iron core can also be incorporated into the solenoid to maximize and localize the magnetic field strength applied to tissue specimens [16, 36]. The displacement or the induced motion in the tissue can be monitored using an ultrasound imaging system equipped with an ultrasonic array transducer or with a single element high-frequency transducer. In magnetoacoustic imaging, it is important to capture ultrasound RF data before, during and after the application before, during and after the application of the magnetic excitation to extract the relative motion with respect to the stationary reference. The induced motion can

Trigger generator

Ultrasound Transducer

Controllable delay Positioning Control

Control Unit

Ultrasound Pulser/Receiver

Sample

Stepper Motor Magnetic coil Iron Core

Current Amplifier

Waveform Generator

Signal Acquisition A/D converter Speckle tracking module US/pMMUS image formation

Processing Unit

Cooling casing

FIGURE 12.5 Block diagram of the combined ultrasound and magneto-motive ultrasound imaging system.


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be detected using various quantitative and qualitative techniques including phase-shift or block-matching speckle tracking, Doppler ultrasound, and color/power Doppler. 12.3.2 Demonstration of Magneto-motive Ultrasound Imaging Using Magnetic Iron Oxide Nanoparticles (MIONs) The ability of magnetoacoustic imaging was demonstrated using tissue phantoms fabricated with the J774A.1 cell line (mouse monocytes–macrophages). Like most cells of macrophage phenotype, the J774A.1 cells rapidly uptake dextran-coated nanoparticles [49–51]. Two tissue phantoms were prepared for the study: (1) a control phantom with macrophage cells only and (2) a labeled phantom prepared with MION loaded macrophage cells. Briefly, the cells were cultured in Dulbecco’s Modified Eagle Media (DMEM), supplemented with 5% fetal bovine serum (FBS) at 37 ◦ C in 5% CO2 . To label cells with MIONs, they were incubated with a suspension of nanoparticles in culturing media. After 24 h of incubation with the nanoparticles, the cells were harvested and suspended in a warm (35 ◦ C) gelatin solution (8% w/v) containing 0.5% silica particles (30 ␮m in diameter). The concentration of the control (unloaded) cells in gelatin was approximately equal to those in the loaded cells. The gelatin suspension with cells (control or labeled) was then pipetted into rubber spacers placed in a petri dish. The gelatin solution was allowed to harden at room temperature for approximately 10 min. In addition, a 1–2-mm thick pure gelatin layer was placed on top of the gelatin layer with cells. Finally, to facilitate imaging, the petri dish was filled with 1× PBS solution (phosphate buffered saline) to maintain the appropriate pH in the medium surrounding the tissue phantoms. The cells from each tissue phantom were imaged optically using a Leica DM 6000 upright microscope in epi-illuminated darkfield mode (Fig. 12.6a,b). Images were collected through a 20×, 0.5 NA darkfield objective and detected using an ultrasensitive 12-bit CCD camera. The unlabeled macrophage cells appear bluish white due to their intrinsic light scattering properties (Fig. 12.6a). The macrophage cells labeled with iron nanoparticles appear as orange regions due to light scattering of iron oxide nanoparticles (Fig. 12.6b). The B-scan and the color Doppler images of the tissue phantoms were obtained using a commercially available ultrasound imaging system (Sonic RP by Ultrasonix, Inc.) equipped with a linear array transducer (38-mm aperture, 5-MHz central frequency). The B-scan images

(a)

(c)

(e)

(d)

(f)

20 m

(b)

FIGURE 12.6 Optical dark-field images of (a) nonlabeled and (b) magnetically labeled macrophages. B-scan ultrasound images (c,d) and color Doppler images (e,f) of nonlabeled and labeled macrophages embedded in 8% gelatin background.


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cannot directly differentiate between the samples as the difference in image contrast is only derived from nonspecific variations in the phantom materials. The color Doppler image of the phantom with labeled cells clearly indicates the presence of tissue motion and is different compared to that of the control phantom (no motion). The results confirm that magnetoacoustic imaging can readily detect the presence of MIONs in the cells and tissue [16].

12.4 COMBINED PHOTOACOUSTIC AND MAGNETO-MOTIVE ULTRASOUND IMAGING Currently, in the field of molecular imaging, emphasis is being laid on multimodality nano contrast agents that can provide complementary functional information regarding pathologies such as cancer. For example, core–satellite structured dual functional nanoparticles comprised of a dye-doped silica “core” and multiple “satellites” of magnetic nanoparticles were utilized for optical and MR imaging of neuroblastoma cells [52]. Hybrid gold coated iron oxide nanoparticles were also used for combined optical and MR imaging of cancer cells [53]. A combination of MR and optical imaging techniques provides both anatomical and functional information on pathology. However, obtaining the images using the two techniques at the same spatial cross section could be challenging as the imaging equipments required vary significantly. On the other hand, photoacoustic and magnetomotive ultrasound imaging modalities can utilize these hybrid nanostructures possessing both optical absorption properties and magnetic properties as contrast agents. Moreover, photoacoustic and magneto-motive ultrasound imaging techniques utilize the same receiver electronics as ultrasound imaging (Fig. 12.1), and hence can be transparently integrated to provide complementary functional and morphological information at the same imaging cross section. Tissue mimicking samples made with polyvinyl alcohol (PVA) were used to demonstrate the feasibility of combined ultrasound, photoacoustic, and magneto-motive ultrasound imaging. The procedure to make PVA inclusions has been described elsewhere [28]. Briefly, the first inclusion (Fig. 12.7a) was made with 8% PVA and contained 15 micro-meter silica powder (0.5% w/v) for ultrasound contrast, 40-nm diameter spherical gold nanoparticles for optical contrast, and 20-nm (8-nm magnetic core) diameter iron oxide nanoparticles

FIGURE 12.7 Schematic representation (left) of phantom used for combined ultrasound, photoacoustic, and magneto-motive imaging. The phantom consisted of PVA inclusions with (a) mixture of Au and Fe3 O4 iron nanoparticles and (b) no nanoparticles. (c) Ultrasound, (d) photoacoustic, and (e) magneto-motive images of the PVA inclusions. The images represent a 2.5 mm × 3.5 mm field of view. Adapted with permission from Ref. 56.


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for magnetic contrast. The second inclusion (Fig. 12.7b) was also fabricated using 8% PVA, but it contained only silica powder and no nanoparticles—that is, the inclusion had only ultrasound scatters. The inclusions were placed in a water tank attached to a threedimensional (3D) positioning stage to facilitate mechanical scanning. A schematic representation of the experimental setup used for combined ultrasound photoacoustic and MMUS imaging is shown in Figure 12.7 (left panel). The integrated probe (ultrasound transducer and optical fiber delivery system) and the magnetic solenoid are placed on opposite sides of the sample. A single element focused transducer operating at 48-MHz central frequency was used to detect ultrasound and photoacoustic signals. A Q-switched Nd:YAG laser operating at 532-nm wavelength was used to generate photoacoustic transients. A magnetic pulse excitation of approximately 0.5 tesla was delivered to the sample via the conical iron core incorporated in a solenoid. At a particular spatial location, ultrasonic A-lines (with and without magnetic excitation) followed by photoacoustic A-lines were acquired. The sample was mechanically moved to the next spatial location using the 3D positioning stage to acquire the next set of ultrasonic and photoacoustic A-lines. The step size of the mechanical scan was determined by the lateral resolution of the ultrasound transducer. During offline processing of the acquired RF data, a digital bandpass filter was applied to increase the signal-to-noise ratio. The ultrasound and photoacoustic signals were extracted from the A-line records. The analytic signals were obtained by applying a Hilbert transform on the filtered ultrasound and photoacoustic signals and the images were displayed after spatial interpolation. To obtain a MMUS image, the displacement of the inclusions due to pulsed magnetic excitation was determined by correlating ultrasonic A-line records acquired with and without magnetic excitation. The procedure was repeated for each A-line record acquired at different spatial locations and the displacements obtained were plotted as an image after spatial interpolation. The ultrasound, photoacoustic, and MMUS images of the inclusions are shown in Figure 12.7c–e, respectively. The spatial location and the anatomical shape of the two inclusions are clearly indicated in the ultrasound image. Note how, in the photoacoustic image, only one of the inclusions produced photoacoustic signals. This observation was expected since the first inclusion contained gold nanoparticles while no photoacoustic absorbers were present in the second inclusion. The displacement of the inclusions in the MMUS image is displayed on a color map, where white indicates maximum displacement of 100 ␮m and black indicates zero displacement. Clearly, the inclusion with iron nanoparticles displaced more under magnetic excitation than the second inclusion with no iron nanoparticles. The results in Figure 12.7 clearly indicate the feasibility of combining ultrasonic, photoacoustic, and MMUS imaging. In the current experimental setup, the magnetic coil and the integrated probe are placed on opposite sides of the sample. This configuration might not be feasible for in vivo applications. A transducer with an optical fiber in the center for laser light delivery [54] and magnetic coil surrounding it (Fig. 12.5) could make an effective probe for the combined ultrasound, photoacoustic, and MMUS imaging.

12.5 CONCLUSIONS The photoacoustic and magnetoacoustic imaging modalities can be integrated with the widely available ultrasound imaging system with minimum effort. The excellent features of the combined ultrasound, photoacoustic, and magnetoacoustic imaging


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system—noninvasive, nonionizing, descent spatial resolution, and extended penetration depth—can all be obtained at low cost. Moreover, these complementary imaging modalities can simultaneously provide anatomical, optical, and biomechanical properties of the tissue. Given the availability of complex nanostructures with high magnetic susceptibility and optical absorption properties, we anticipate the combination of ultrasound guided photoacoustic and magnetoacoustic imaging techniques could be a valuable tool for early detection of pathologies such as cancer. Further studies are required to evaluate this molecular imaging technique in vivo.

ACKNOWLEDGMENTS Partial support from the National Institutes of Health under grants EB008101 and EB008821 is gratefully acknowledged. The authors would like to thank Dr. Salavat Aglyamov and Dr. Andrei Karpiouk of the University of Texas at Austin for their valuable inputs regarding the development of combined imaging system.

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CHAPTER 13

MRI Contrast Agents Based on Inorganic Nanoparticles HYON BIN NA and TAEGHWAN HYEON National Creative Research Initiative Center for Oxide Nanocrystalline Materials, and School of Chemical and Biological Engineering, Seoul National University, Seoul, South Korea

13.1 INTRODUCTION Magnetic resonance imaging (MRI) is currently one of the most powerful diagnosis tools in medical science [1]. MRI produces images through monitoring the relaxation processes of water protons under a magnetic field. With this technique, it is possible to obtain realtime images of the internal anatomy and physiology of living organisms in a noninvasive manner. Since it can give anatomic images of soft tissue with high resolution, it has been the preferred tool for imaging the brain and the central nervous system, for assessing cardiac function, and for detecting tumors. Although MRI itself gives detailed images, making a diagnosis based purely on the resulting images may not be accurate since normal tissues and lesions often show small differences in relaxation time. There are several strategies to obtain high-resolution MR images such as the use of high magnetic field and the design of coil systems. In economical and practical terms, it is more feasible to develop supplements that can maximize the ability of imaging tools. One of the most effective supplements is a chemical compound known as a contrast agent that is introduced to a living body for the improvement of visibility in the image. In particular, biological and functional information can be obtained in image form as a result of the interrelation of the contrast agent and the biological system. Therefore a MRI contrast agent is an essential research field in biological and medical sciences to supply a vision for the analysis of biological information and the diagnosis of diseases. Most of the presently available MRI contrast agents are paramagnetic complexes, usually gadolinium (Gd3+ ) chelates [2]. Among them, Gd-DTPA has been the most widely used. Its main clinical applications are focused on detecting the breakage of the blood–brain barrier (BBB) and on changes in vascularity, flow dynamics, and perfusion. Twenty years ago, a different class of contrast agent, superparamagnetic iron oxide (SPIO), was developed, and it has received great attention as a liver contrasting agent [3]. It was the first nanoparticulate MRI contrast agent and is still used clinically. Gd-based contrast agents Nanoplatform-Based Molecular Imaging Edited by Xiaoyuan Chen C 2011 John Wiley & Sons, Inc. Copyright

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MRI CONTRAST AGENTS BASED ON INORGANIC NANOPARTICLES

enhance the signal in T1-weighted images [2]. On the other hand, SPIO provides a very strong contrast effect in T2-weighted images due to its different contrasting mechanism [3]. Furthermore, its nanoparticulate properties represented by the nanosized dimension and shape allow different biodistribution and opportunity beyond the conventional imaging of chemical agents. The recent development of molecular and cellular imaging, which enables visualization of the disease-specific biomarkers at the molecular and cellular levels, has led to increased recognition of nanoparticles as MRI contrast agents, where nanoparticulate iron oxide has been the prevailing and the only clinically used nanoparticulate agent. As a result of the tremendous progress in nanotechnology, many researchers have developed new nanoparticulate MRI contrast agents that have further improved contrasting abilities and have extra functions. In the following sections, we review the progress in inorganic nanoparticles as MRI contrast agents [4]. In particular, this chapter is focused on the core nanoparticles related to their contrast mechanisms. First, we discuss the T2 contrast agent based on the superparamagnetic property which is the main part in nanoparticular MRI contrast agents. Newly developed nanoparticulate T1 contrast agents are introduced in the latter part of the chapter. 13.2 BASIC PRINCIPLES AND CLASSES OF MRI CONTRAST AGENTS “Contrast” refers to the signal differences between adjacent regions in images, and when the target of the image is the living body they could be “tissue and tissue,” “tissue and vessel,” and “tissue and bone.” Contrast agents make an enhancement of contrast around those interests. Contrast agents for X-ray and CT show contrasting effects according to the electron density difference, and they make direct contrast effects on their locations. However, the contrast mechanism is more complicated for MRI where the contrast enhancement occurs as a result of the interaction between the contrast agents and neighboring water protons, which can be affected by many intrinsic and extrinsic factors such as proton density and MRI pulse sequences. The basic principle of MRI is based on nuclear magnetic resonance (NMR) together with the relaxation of proton spins in a magnetic field [1]. When the nuclei of protons are exposed to a strong magnetic field, their spins align themselves either parallel or antiparallel to the magnetic field. During their alignment, the spins precess under a specified frequency known as the Larmor frequency (␻0 ) (see Fig. 13.1a). When the “resonance” frequency in the radiofrequency (rf) range is introduced to the nuclei, the protons absorb energy and are excited to the antiparallel state. After the disappearance of the rf pulse, the excited nuclei relax to their initial, lower-energy state (Fig. 13.1b). There are two different relaxation pathways. The first, called longitudinal relaxation or T1 relaxation, involves the decreased net magnetization (Mz ) recovering to the initial state (Fig. 13.1c). The second, called transverse relaxation or T2 relaxation, involves the induced magnetization on the perpendicular plane (Mxy ) disappearing by the dephasing of the spins (Fig. 13.1d). Based on their relaxation processes, the contrast agents are classified as T1 contrast agents and T2 contrast agents. Commercially available T1 contrast agents are usually paramagnetic complexes while T2 contrast agents are based on iron oxide nanoparticles, which are the most representative nanoparticulate agents. 13.3 T2 NANOPARTICULATE MRI CONTRAST AGENTS Most of reported nanoparticualte MRI contrast agents were T2 contrast agents based on their superparamagnetic properties. Thus there has been much research on their contrast


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T2 NANOPARTICULATE MRI CONTRAST AGENTS

(a)

(b) z ω0

p rf

ul

se ω

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Mz

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281

y

=

ω0

Mz Mxy

x (c)

(d)

Mz

Mxy

M0 M0(1 – e–1)

Mxye–1

T1’ T1

t

T2’ T2

t

FIGURE 13.1 Basic principle of magnetic resonance imaging. (a) Spins align parallel or antiparallel to the magnetic field and precess under resonance frequency (Larmor frequency, ␻0 ). (b) After induction of a rf pulse, the magnetization of spins changes. Excited spins take the relaxation process of (c) T1 relaxation and (d) T2 relaxation.

effects and clinical trials, and we first introduce T2 contrast agents. The main enhancement of T2 contrast agents is the acceleration on the T2 relaxation process, spin–spin relaxation. When the rf pulse is applied to spins, transverse magnetization on the xy plane (Mxy ) perpendicular to the direction of the static magnetic field is generated (Fig. 13.1b). Net magnetization M, as a vector, has the components Mz and Mxy , which make the interrelated process of spins. The change in Mz is due to energy transfer, whereas that in Mxy is due to the process of spin dephasing, that is, the randomization of the magnetization of excited spins with the same phase coherence immediately after the application of the rf pulse. Their phase coherence in the xy plane disappears due to the difference of magnetic field experienced by the protons. The magnetic field difference is produced by the system performance in shimming and the magnetic properties of imaging objects. Although the inhomogeneity of the static magnetic field by the system imperfection can be reduced by a variety of tools including the shimming coils and shimming algorithms and the usage of the spin echo sequence to reverse this effect, it affects the decay of transverse magnetization. As other source of field inhomogeneity, the magnetic properties of imaging objects can cause phase incoherence. The spin–spin interaction between the hydrogen nuclei or electrons causes a loss of transverse coherence, which makes the true and characteristic T2 relaxation of tissues. For example, the proton interaction of macromolecules in tissue can induce a local magnetic field, as well as a change in the actual magnetic field in their vicinity. Furthermore, the local magnetic field gradient can be induced from the differences in the magnetic susceptibility between the adjacent and different tissues or by contrast agents. Therefore transverse relaxation is affected by inhomogeneous magnetic field produced from tissue-inherent factors or external sources and the total relaxation time, T2∗ , is


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described by 1 1 = + ␥ BS T2∗ T2

(13.1)

where ␥ BS represents the relaxation by the field inhomogeneities and is called susceptibility effects. The magnetization of paramagnetic materials, such as gadolinium complexes, is directly dependent on the number of ions and they have no magnetization in the absence of an external magnetic field. However, ferromagnetic iron oxide has a very large magnetic susceptibility, which can persist even upon removal of the external magnetic field. nanosized iron oxide particles are superparamagnetic, losing their magnetization in the absence of an external magnetic field. However, when an external magnetic field is applied, they exhibit a strong magnetization, which can cause microscopic field inhomogeneity and activate the dephasing of protons. Therefore iron oxide nanoparticles shorten T 2 and T2∗ relaxation times of the neighboring regions and produce a decreased signal intensity in T2- and T2*-weighted MR images. 13.3.1 Dextran-Coated Iron Oxide Nanoparticles Since their first use as MRI contrast agents 20 years ago, iron oxide nanoparticles (usually magnetite (Fe3 O4 ) or maghemite (␥ -Fe2 O3 )) have become extremely popular due to their dramatic ability to shorten T2∗ relaxation times in the liver, spleen, and bone marrow, by selective uptake and accumulation in the cells of the reticuloendothelial system (RES) [3]. With their high magnetization, their selective signal loss allowed for a new class of MRI contrast agents in the world of dominant T1 contrast agents based on ionic complexes. Since the magnetic property of the nanoparticles and their biological distribution are directly dependent on their size, they have been classified by size as follows: (1) micrometer-sized paramagnetic iron oxide (MPIO; several micrometers), (2) superparamagnetic iron oxide (SPIO; hundreds of nanometers); and ultimately, (3) ultrasmall superparamagnetic iron oxide (USPIO: less than 50 nm) [4]. Among them, two classes are widely used in MRI: SPIO and USPIO. There are several approved products in the SPIO family: Feridex® (Berlex) in the United States or Endrem® (Guerbet) in Europe, and Resovist® (Schering) in Europe and Asia. Smaller nanoparticles, USPIO, have similar composition and originate from SPIO. At the beginning they were prepared through size fraction of an SPIO mixture. Nowadays, uniform USPIOs are produced with the improvement of a synthetic technique (Combidex® (Advanced Magnetics) in the United States and Sinerem® (Guerbet) in Europe). Products with USPIO are under consideration for clinical uses by the U.S. Food and Drug Administration (FDA). The most representative and traditional method to prepare SPIOs and USPIOs is the reduction and coprecipitation reaction of a mixture of ferrous and ferric salts by addition of an alkaline solution under vigorous stirring or sonication [5]. This precipitation reaction is performed in the presence of stabilizers such as hydrophilic polymers, dextran derivatives. Figure 13.2 shows the representative synthetic scheme of SPIO and USPIO, and an electron microscopic image of ferumoxides (Feridex® or Endrem® ) and MION. Because there were insufficient controls in the synthetic process, resulting particles were formed with a broad range of sizes. Furthermore, these particles consisted of multiple iron oxide cores within a dextran stabilization shell. The size of particles is the main factor that controls their


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283

FIGURE 13.2 (a) Scheme of the preparation of SPIO and USPIO. (b,c) Transmission electron microscope (TEM) images of (b) ferumoxides [5a] and (c) MION [7] GFC*: gel filtration chromatography. (Reproduced with permission of Elsevier Inc. and the Massachusetts Medical Society.)

biological characteristics such as blood half-life and biodistribution. Because SPIO has relatively large overall size and related opsonization by phagocytic cells located in the RES, it shows fast clearance from the body and short lifetime. Small nanoparticles have a longer plasma circulation time due to their slow excretion by the liver. Therefore iron oxide nanoparticles for molecular imaging are usually in the class of USPIO (100 nm. Very recently, the Hyeon group also synthesized discrete and monodisperse core–shell mesoporous silica NPs smaller than 100 nm by using single Fe3 O4 nanoparticles as cores [29g]. The uniform 3-nm mesoporous


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(a)

(b)

FIGURE 13.7 Silica-encapsulated iron oxide nanoparticles. (a) TEM images and schematic illustration of CoFe2 O4 –silica (core–shell) functionalized with organic dyes and antibodies [28c]. (b) The synthesis of magnetite nanoparticle/mesoporous silica core–shell and their in vivo multimodal imaging (MRI and optical imaging) [29g]. (Reproduced with permission of Wiley-VCH Verlag GmbH & Co. KGaA.)

shell can contain fluorescent dye and anticancer drug and the resulting composite magnetic silica nanoparticles were applied to simultaneous in vivo magnetic resonance (MR) and fluorescence imaging, and drug delivery vehicle (Fig. 13.7b). Various natural and synthetic polymers have been used extensively in the preparation of biocompatible nanoparticles. The immobilization of polymers can reduce the safety and toxicology concerns of nanoparticles for the clinical applications. Because the silica stabilized nanoparticles often experience precipitation and gel formation, additional biocompatible polymers (e.g., PEG) have been immobilized on the surface of the silica shell to improve the colloidal stability [28, 29]. Furthermore these polymer–nanoparticle hybrids can be utilized for multifunctional biomedical applications with simultaneous drug delivery and imaging capability [29]. Polyesters, such as poly(d,l-lactide-co-glycolide) (PLGA), poly(d,l-lactide) (PLA), and poly(glycolide) (PGA), have been most popularly used for these applications [30]. Gao and co-workers employed amphiphilic block copolymers of methoxy- and maleimideterminated poly(ethylene glycol)-block-poly(d,l-lactide) (PEG-PLA) to fabricate polymer


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295

micelles [30b]. Hydrophobic iron oxide nanoparticles and hydrophobic drug (doxorubicin, DOX) were spontaneously incorporated into the hydrophobic PLA core part and hydrophilic PEG was exposed to the aqueous environment. The resulting particles were relatively large (>50 nm) because several iron oxide nanoparticles were clustered in the hydrophobic core part. They were functionalized with RGD peptide, and they targeted cancer cells in in vitro T2 MRI and showed therapeutic effects via the release of loaded doxorubicin. Kim et al. [30c] fabricated multifunctional PLGA nanoparticles with particle size of 100–200 nm by simultaneously immobilizing magnetite nanoparticles, quantum dots, and anticancer drug (doxorubicin) in PLGA matrix via a conventional oil-in-water emulsion–evaporation process [30c]. Using the multifunctional polymer nanoparticles, they demonstrated simultaneous cancer-targeted MR imaging and optical imaging, as well as drug delivery. In addition, the loaded magnetite nanoparticles facilitated the magnetic guiding of the polymer particles, thereby increasing the synergetic targeting efficiency. Jiang and co-workers fabricated hollow Fe3 O4 –polymer hybrid nanospheres by the addition of Fe3 O4 nanoparticles to an aqueous solution of polymer–monomer pairs composed of the cationic chitosan polymer and the anionic acrylic acid monomer, followed by polymerization of acrylic acid and selective crosslinking of chitosan at the end of polymerization [30d,e]. The phantom test of magnetic resonance imaging showed that the synthesized hybrid hollow nanospheres had a significant magnetic resonance signal enhancement in T2-weighted image [30e]. PEG, a representative biocompatible polymer, has received great attention due to its nonfouling property, which supports a resistance to protein adsorption and an ability to bypass the RES and natural barriers such as the nasal mucosa [31]. PEGs have been used extensively as stabilizing materials for many nanoparticles in biomedical applications, in particular, in long circulating in vivo imaging systems. Because PEG itself is very inert, surface-anchorable materials such as copolymers, phospholipids, and silica are combined with PEGs to encapsulate the nanoparticles. Dubertret et al. [32a] reported that PEGphospholipid block copolymers could form a stable micelle structure on quantum dots via the hydrophobic interaction between hydrophobic tail groups of the surfactants and phospholipid parts. The outer surface of the nanoparticles is comprised of a dense PEG layer, which is stable in biological media. This process is highly reliable and can generally be applicable to many other kinds of nanoparticles. Using a very similar strategy, various water-dispersible metal oxide nanoparticles, including iron oxide nanoparticles, were generated [32b]. Because these PEG-phospholipid block copolymers are very expensive, they cannot be applied for the large-scale preparation. Amphiphilic di- and triblock copolymers have also been used as stabilizing shell materials for water-dispersible nanoparticles. Their hydrophobic blocks can strongly interact with the hydrophobic surface of the nanoparticles, whereas the outer hydrophilic blocks can make the nanoparticles dispersible in water [33]. These block copolymers are relatively inexpensive and can be derivatized with other functional groups for additional functionalization. One disadvantage of using these block copolymers is that their large shell thickness is derived from the high molecular weight, which limits their many potential applications. Oligomeric and dendritic molecules were also used as the shell materials for water-dispersible nanoparticles because they form thinner shells while preserving their stability in aqueous media. For example, Yang and co-workers demonstrated that the cyclic oligosaccharides that have hydrophobic cavities and hydrophilic rims can transfer the nanoparticles from an organic to an aqueous phase [34]. Weller and co-workers showed that the relaxivities of magnetic nanoparticles were dependent not only on the size of the core nanoparticles but also on the types of shells [35].


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900 40 nm

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an

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r2 exchange r2* micelles r2 micelles r2* exchange r2* encapsulated r2 encapsulated r2* Resovist r2 Resovist

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FIGURE 13.8 (a) Three kinds of methods to prepare water-dispersed manganese ferrite nanoparticles. (b) The r2 relaxities of water-dispersed manganese ferrite nanoparticles with three kinds of shell systems [35]. (Reproduced with permission of the American Chemical Society.)

The MnFe2 O4 nanoparticles synthesized in high boiling ether solvent were transferred to water using three different approaches, including ligand exchange to form a watersoluble polymer shell, embedding into an amphiphilic polymer shell, and encapsulating in large micelles formed by lipids. In the first two polymer-based systems, nanoparticles are individually dispersed to form homogeneous dispersion with a hydrodynamic radius of 30–40 nm, whereas aggregated nanoparticles were randomly distributed inside the micelles with a hydrodynamic radius of 250 nm. Interestingly, the relaxivity, r2*, is much higher for the micellar system than for the polymer-stabilized particles using the same-sized nanoparticles (Fig. 13.8). Nanosized and biocompatible iron oxide nanoparticles have been applied extensively to the diagnosis of cancers. They can be accumulated spontaneously in tumor sites via the enhanced permeability and retention (EPR) effect, which is the enhanced accumulation of macromolecular species including nanoparticles in tumor tissues that have abnormal blood vessels [36]. Consequently, iron oxide nanoparticles were successfully used to image tumors without any targeting probes, which is called passive targeting [37]. For more efficient targeted imaging, the surface of the iron oxide nanoparticles needs to be conjugated with active targeting probes such as antibodies and proteins. Magnetic nanoparticles have been conjugated with various bioactive materials such as antibodies, oligonucleotides, peptides, and proteins. Cheon and co-workers prepared Herceptin-conjugated iron oxide nanoparticles, and they were delivered selectively and imaged tumor cells by interactions with the human epidermal growth factor receptor (Her2/neu), which is usually overexpressed in breast cancers [22b]. The Cheon group also demonstrated that Herceptin-conjugated manganese ferrite (MnMEIO) nanoparticles with high magnetization showed more sensitive in vivo cancer targeted imaging with large r2 relaxivity (Figure 13.9) [24]. This result demonstrated that advanced MRI contrast agents consisting of high magnetic moment nanoparticles and appropriate targeting agents could enable the ultrasensitive detection of various types of cancer in T2/T2*-weighted MRI. As another demonstration of targeted MRI, Gao and co-workers conjugated a cancer-targeting antibody, anticarcinoembryonic antigen (CEA) monoclonal antibody rch 24 onto uniform PEG-coated


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(a)

(d)

(b)

(e)

(c)

(f)

297

FIGURE 13.9 In vivo MR detection of cancer after administration of magnetic nanoparticles– Herceptin conjugates. Manganese ferrite nanoparticles (MnMEIO) (a–c) show higher signal enhancement than crosslinked iron oxide (CLIO) (d–f) [24]. (Reproduced with permission of Nature Publishing Group.)

iron oxide nanoparticles and successfully performed targeted MR imaging for human colon carcinoma tumors [38]. Zhang and co-workers demonstrated that PEG-coated iron oxide nanoparticles conjugated with targeting peptide (chlorotoxin) were preferentially accumulated within gliomas and exhibited highly contrast-enhanced MR imaging [39].

T2 Nanoparticulate Contrast Agents of Unique Structures Recently, new multifunctional nanomedical platforms have been fabricated by combining various nanostructured materials with different functions, making it possible to accomplish multimodal imaging and simultaneous diagnosis and therapy [40]. Heterodimers of magnetic nanoparticles and other nanoparticles can serve as multimodal imaging agents such as MRI contrast agents and optical probes [41]. Dumbbell-like nanoparticles composed of magnetic nanoparticles and gold nanoparticles have been used for dual MR and optical imaging. The Sun group reported the dual modal imaging properties of Fe3 O4 –Au dumbbell nanoparticles, which were prepared by the growth of Fe3 O4 on as-prepared Au nanoparticles in the presence of oleic acid and oleylamine (Fig. 13.10) [41a]. Fe3 O4 and Au components had different surface properties, and they were modified by dopamine and thiol groups, respectively. The epidermal growth factor receptor antibody (EGFRA) was conjugated on the surface of Fe3 O4 , and the resulting heterostructured nanoparticles were successfully applied to the cancer-targeted MR imaging. Furthermore, the unique surface plasmon property of the Au component enabled reflection imaging. The Cheon group demonstrated dual modal imaging using heterodimeric FePt–Au nanoparticles, which were synthesized by the catalytic growth of Au on the surface of the FePt nanoparticles [41b]. Antibody-conjugated FePt–Au nanoparticles were used as both T2 MRI contrast agent and biosensor, and neutravidin-conjugated nanoparticles acted as detecting probes on the biotin patterned


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(a)

(c)

(b)

FIGURE 13.10 (a) TEM image of Au–Fe3 O4 nanoparticles. (b) T2-weighted MR image of A431 cells labeled with Au–Fe3 O4 nanoparticles. (c) Reflection image of A431 cells labeled with Au–Fe3 O4 nanoparticles [41a]. (Reproduced with permission of Wiley-VCH Verlag GmbH & Co. KGaA.)

biochip. Ying and co-workers reported Fe3 O4 –CdSe heterodimer nanoparticles by growing CdSe on the surface of the as-synthesized Fe3 O4 nanoparticles [41c]. Although there are no MRI demonstrations in their paper, it might be a candidate as an MRI contrast agent. The Hyeon group also reported that heterostructured nanoparticles composed of various combinations of a metal (Au, Ag, Pt, or Ni) and an oxide (Fe3 O4 or MnO) were readily synthesized from thermal decomposition of mixtures of metal–oleate complexes and metal–oleylamine complexes [41d]. Nanoparticles of Au–MnO and Au–Fe3 O4 have the potential to serve in many multifunctional biomedical applications, such as multimodal imaging or detection probes. The Hyeon group fabricated biocompatible hollow iron oxide nanocapsules and demonstrated their in vitro T2 MRI and drug delivery capabilities to cancer cells. They were fabricated from akagenite (␤-FeOOH) nanorods via the wrap–bake–peel process, which involves silica coating, heat treatment, and finally the removal of the silica layer. During heat treatment at 500 ◦ C, first in air and then in 10% hydrogen atmosphere the ␥ -FeOOH nanorods were transformed into magnetite (Fe3 O4 ) capsules. Removing the silica shells resulted in the formation of water-dispersible hollow Fe3 O4 nanocapsules. Large hollow pores could be loaded with chemical drugs that were released in cancer cells, and the magnetite shells were used as the T2 MRI contrast agent (Fig. 13.11) [42].

13.3.3 T1 Nanoparticulate MRI Contrast Agents Over the last 20 years, most nanoparticulate contrast agents have been T2 contrast agents using iron oxide nanoparticles. However, these magnetic nanoparticle-based T2 contrast agents have several disadvantages that limit their extensive clinical applications. First, they are negative contrast agents, which give a signal decreasing effect. The resulting dark signal could be confused with other pathogenic conditions and makes images of lower contrast than T1 contrasted images. Moreover, the high susceptibility of the T2 contrast agents induces distortion of the magnetic field on neighboring normal tissues. This distortion of the background is called the susceptibility artifact or “blooming effect,” which generates obscure images and demolishes the background around the lesions [4]. Because of the


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299

(a) β-FeOOH

β-FeOOH/sillica

Haematite/sillica Heat treatment

Sillica coating

Haematite

Removal of sillica using NaOH

100 nm

Reduction

Removal of sillica using NaOH

Magnetite

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(c)

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FIGURE 13.11 (a) Schematic illustration of the procedure for the synthesis of uniform and waterdispersible iron oxide nanocapsules and their TEM images. (b) T2-weighted MR images of the magnetite nanocapsules. (c) In vitro cytotoxicity of free DOX and DOX loading nanocapsules against SKBR-3 cells [42]. (Reproduced with permission of the Nature Publishing Group.)

limitations of these T2 agents, most extensively and clinically used MRI contrast agents are based on gadolinium complex-based T1 agents. T1 relaxation is the process of equilibration of the net magnetization (Mz ) after the introduction of an rf pulse. This change of Mz is a consequence of energy transfer between the proton spin system and the nearby matrix of molecules. All biological systems are composed of various molecules and organisms, and they have different relaxation behaviors and different T 1 relaxation times. The presence of paramagnetic ions near the tissue enhances its relaxation and shortens the T1 relaxation time. In particular, transition and lanthanide metal ions with a large number of unpaired electrons, such as Gd3+ , Mn2+ , and Fe3+ , show very effective relaxation [2]. T1 contrast agents enhance T1 relaxation, which makes a signal enhancement on images. Compared to T2 contrast agents, the major advantage of T1 contrast agents is positive contrast imaging by signal enhancement, which can maximize the forte of MRI (i.e., anatomic imaging with high spatial resolution). Furthermore, their bright signal can be distinguished clearly from other pathogenic or biological conditions. As T1 contrasting agents are basically paramagnetic, they do not disrupt the magnetic homogeneity over the large dimension, which can disturb other anatomic backgrounds. Since Gd3+ has seven unpaired electrons with a large magnetic moment, most T1 contrast agents are Gd3+ -based agents. However, due to the toxicity of heavy metal ions, the conventional contrast agents are in the form of ionic complexes with chelating ligands,


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which are thermodynamically and kinetically stable and less toxic. There is, however, no biochemistry based on gadolinium(III) ion in natural human system. In spite of their fewer unpaired electrons and lower magnetic moments, manganese(II), iron(III), and copper(II) ions could be alternative candidates. Manganese(II) ion, in particular, plays various important roles in many biological processes such as cofactors of enzymes and a release controller of neurotransmitters. Although there are some manganese(II) complex contrast agents, Mn2+ itself, in the form of MnCl2 solution, has been most frequently used. It has shown very prominent contrasting effects that can reveal detailed physiological and biological information, and it constitutes a new imaging category known as manganese-enhanced MRI (MEMRI). In particular, MEMRI can visualize the anatomic structure of the brain and its neuronal activity [43], which cannot be obtained with any of the gadolinium(II)-based contrast agents. Unfortunately, however, MEMRI can only be applied in animal studies because Mn2+ ions cause hepatic failure and have cardiac toxicity. As shown above, the present T1 contrast agents are based on paramagnetic ions and are used in the form of ion complexes. They have short life spans in the body and work in a nonspecific manner. Most T1 contrast agents reside within the extracellular space and usually interact with the blood so that they have some limitations as molecular probes for longer time tracking. As shown in recent studies of iron oxide nanoparticles, nanoparticulate agents are very promising for molecular and cellular imaging, which aims to visualize the disease-specific biomarkers at the molecular and cellular levels, respectively. However, the negative contrasting effect and magnetic susceptibility artifacts of iron oxide nanoparticles can be significant drawbacks when using iron oxide nanoparticles. This is because the resulting dark signal can mislead the clinical diagnosis in T2-weighted MRI as the signal is often confused with the signals from bleeding, calcification, or metal deposits, and the susceptibility artifacts distort the background image [4]. Recently, intensive research has been devoted to developing new T1 contrast agents that overcome the above-mentioned drawbacks of Gd3+ ion- and Mn2+ ion-based T1 contrast agents and SPIO-based T2 contrast agents. Briefly, these new classes of contrast agents should satisfy the following characteristics: (1) positive (T1) contrast ability, (2) easy intracellular uptake and accumulation for imaging cellular distribution and functions, (3) a nanoparticulate form for easy surface modification and efficient labeling with biological and bioactive materials, and (4) favorable pharmacokinetics and dynamics for easy delivery and efficient distribution to the biomarkers with minimal side effects. The first class of particulate T1 contrast agents is based on nanostructured frames that have many anchoring sites for paramagnetic ions [44]. Those particles can carry a large number of paramagnetic payloads and produce strong T1 contrast. Various platforms, such as silicas, dendrimers, perfluorocarbons, emulsions, and nanotubes, have been used. Lanza and co-workers used perfluorocarbon nanoparticle incorporated paramagnetic Gd–DTPA complexes for the sensitive detection of fibrin and for the molecular detection of angiogenesis [44a,b]. Lin and co-workers developed silica nanoparticles [44c], metal–organic framework [44d], and mesoporous silica (Fig. 13.12) [44e] to contain a large number of Gd3+ ions and to develop multifunctional properties. Carbon nanotubes could act as the framework that holds Gd3+ ions, either on the surface [44f] or in the structural defect sites [44g]. In these materials, many metal ions are concentrated in a defined volume and their biological behavior and relaxivities are different from those of the complex agents. Basically, this type of contrast agent is an extension of the paramagnetic complex agents so that the maximum number of ions is limited by the density of anchoring groups on the surface. Furthermore, the synthetic procedures are generally very complicated and expensive. The most significant limitation is their large overall size of >100 nm, which is much larger than


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(a)

301

(b)

FIGURE 13.12 (a) Schematic illustration of Gd–hybrid mesoporous silica nanospheres. (b) Precontrast (left) and postcontrast (right) T1-weighted mouse MR images [44e]. (Reproduced with permission of the American Chemical Society.)

the inorganic nanoparticles, such as USPIO. To prevent easy excretion by the RES and to compete with the small-sized T2 contrast agents, their overall size should be

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