1
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Toomajian V, Tundo A, Ural EE, Greeson EM, Contag CH, Makela AV. Magnetic Particle Imaging Reveals that Iron-Labeled Extracellular Vesicles Accumulate in Brains of Mice with Metastases. ACS APPLIED MATERIALS & INTERFACES 2024; 16:30860-30873. [PMID: 38860682 PMCID: PMC11194773 DOI: 10.1021/acsami.4c04920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/12/2024]
Abstract
The incidence of breast cancer remains high worldwide and is associated with a significant risk of metastasis to the brain that can be fatal; this is due, in part, to the inability of therapeutics to cross the blood-brain barrier (BBB). Extracellular vesicles (EVs) have been found to cross the BBB and further have been used to deliver drugs to tumors. EVs from different cell types appear to have different patterns of accumulation and retention as well as the efficiency of bioactive cargo delivery to recipient cells in the body. Engineering EVs as delivery tools to treat brain metastases, therefore, will require an understanding of the timing of EV accumulation and their localization relative to metastatic sites. Magnetic particle imaging (MPI) is a sensitive and quantitative imaging method that directly detects superparamagnetic iron. Here, we demonstrate MPI as a novel tool to characterize EV biodistribution in metastatic disease after labeling EVs with superparamagnetic iron oxide (SPIO) nanoparticles. Iron-labeled EVs (FeEVs) were collected from iron-labeled parental primary 4T1 tumor cells and brain-seeking 4T1BR5 cells, followed by injection into the mice with orthotopic tumors or brain metastases. MPI quantification revealed that FeEVs were retained for longer in orthotopic mammary carcinomas compared to SPIOs. MPI signal due to iron could only be detected in brains of mice bearing brain metastases after injection of FeEVs, but not SPIOs, or FeEVs when mice did not have brain metastases. These findings indicate the potential use of EVs as a therapeutic delivery tool in primary and metastatic tumors.
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Affiliation(s)
- Victoria
A. Toomajian
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biomedical Engineering, Michigan State
University, East Lansing, Michigan 48824, United States
| | - Anthony Tundo
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
| | - Evran E. Ural
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biomedical Engineering, Michigan State
University, East Lansing, Michigan 48824, United States
| | - Emily M. Greeson
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Microbiology, Genetics & Immunology, Michigan State University, East
Lansing, Michigan 48824, United States
| | - Christopher H. Contag
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Biomedical Engineering, Michigan State
University, East Lansing, Michigan 48824, United States
- Department
of Microbiology, Genetics & Immunology, Michigan State University, East
Lansing, Michigan 48824, United States
| | - Ashley V. Makela
- Institute
for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48824, United States
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2
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Xie X, Zhai J, Zhou X, Guo Z, Lo PC, Zhu G, Chan KWY, Yang M. Magnetic Particle Imaging: From Tracer Design to Biomedical Applications in Vasculature Abnormality. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2306450. [PMID: 37812831 DOI: 10.1002/adma.202306450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/14/2023] [Indexed: 10/11/2023]
Abstract
Magnetic particle imaging (MPI) is an emerging non-invasive tomographic technique based on the response of magnetic nanoparticles (MNPs) to oscillating drive fields at the center of a static magnetic gradient. In contrast to magnetic resonance imaging (MRI), which is driven by uniform magnetic fields and projects the anatomic information of the subjects, MPI directly tracks and quantifies MNPs in vivo without background signals. Moreover, it does not require radioactive tracers and has no limitations on imaging depth. This article first introduces the basic principles of MPI and important features of MNPs for imaging sensitivity, spatial resolution, and targeted biodistribution. The latest research aiming to optimize the performance of MPI tracers is reviewed based on their material composition, physical properties, and surface modifications. While the unique advantages of MPI have led to a series of promising biomedical applications, recent development of MPI in investigating vascular abnormalities in cardiovascular and cerebrovascular systems, and cancer are also discussed. Finally, recent progress and challenges in the clinical translation of MPI are discussed to provide possible directions for future research and development.
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Affiliation(s)
- Xulin Xie
- Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, 518057, China
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Jiao Zhai
- Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, 518057, China
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Xiaoyu Zhou
- Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, 518057, China
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Zhengjun Guo
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
- Department of Oncology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Pui-Chi Lo
- Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, 518057, China
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Guangyu Zhu
- Department of Chemistry, City University of Hong Kong, Hong Kong SAR, 999077, China
| | - Kannie W Y Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong SAR, 999077, China
| | - Mengsu Yang
- Department of Precision Diagnostic and Therapeutic Technology, City University of Hong Kong Shenzhen Futian Research Institute, Shenzhen, 518057, China
- Department of Biomedical Sciences, and Tung Biomedical Sciences Centre, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
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3
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Nigam S, Mohapatra J, Makela AV, Hayat H, Rodriguez JM, Sun A, Kenyon E, Redman NA, Spence D, Jabin G, Gu B, Ashry M, Sempere LF, Mitra A, Li J, Chen J, Wei GW, Bolin S, Etchebarne B, Liu JP, Contag CH, Wang P. Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2305300. [PMID: 37735143 PMCID: PMC10842459 DOI: 10.1002/smll.202305300] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 08/24/2023] [Indexed: 09/23/2023]
Abstract
Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.
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Affiliation(s)
- Saumya Nigam
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Jeotikanta Mohapatra
- Department of Physics, The University of Texas at Arlington, Arlington, TX, 76019, USA
| | - Ashley V Makela
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, 48824, USA
- Department of Biomedical Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - Hanaan Hayat
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Jessi Mercedes Rodriguez
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
- Human Biology Program, College of Natural Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Aixia Sun
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Elizabeth Kenyon
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Nathan A Redman
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, 48824, USA
- Department of Biomedical Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - Dana Spence
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, 48824, USA
- Department of Biomedical Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - George Jabin
- Department of Physics, The University of Texas at Arlington, Arlington, TX, 76019, USA
| | - Bin Gu
- Department of Obstetrics, Gynecology and Reproductive Sciences, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Mohamed Ashry
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Lorenzo F Sempere
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Arijit Mitra
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan City, 701, Taiwan
| | - Jinxing Li
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, 48824, USA
- Department of Biomedical Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
| | - Jiahui Chen
- Department of Mathematics, College of Natural Science, Michigan State U, niversity, East Lansing, MI, 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, College of Natural Science, Michigan State U, niversity, East Lansing, MI, 48824, USA
- Department of Electrical and Computer Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
- Department of Biochemistry and Molecular Biology, College of Natural Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Steven Bolin
- Department of Pathobiology and Diagnostic Investigation, College of Veterinary Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - Brett Etchebarne
- Osteopathic Medical Specialties, College of Osteopathic Medicine, Michigan State University, East Lansing, MI, 48824, USA
| | - J Ping Liu
- Department of Physics, The University of Texas at Arlington, Arlington, TX, 76019, USA
| | - Christopher H Contag
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, 48824, USA
- Department of Biomedical Engineering, College of Engineering, Michigan State University, East Lansing, MI, 48824, USA
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA
| | - Ping Wang
- Precision Health Program, Michigan State University, East Lansing, MI, 48824, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, 48824, USA
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4
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Good HJ, Sehl OC, Gevaert JJ, Yu B, Berih MA, Montero SA, Rinaldi-Ramos CM, Foster PJ. Inter-user Comparison for Quantification of Superparamagnetic Iron Oxides with Magnetic Particle Imaging Across Two Institutions Highlights a Need for Standardized Approaches. Mol Imaging Biol 2023; 25:954-967. [PMID: 37386319 DOI: 10.1007/s11307-023-01829-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/17/2023] [Accepted: 05/29/2023] [Indexed: 07/01/2023]
Abstract
PURPOSE Magnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, a few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions. PROCEDURES Six users (3 from each institute) imaged a known amount of Vivotrax + (10 μg Fe), diluted in a small (10 μL) or large (500 μL) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users × triplicate samples × 2 sample volumes × 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax + quantification, and ROI selection were compared across users, within and across institutions. RESULTS MPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax + . Overall quantification yielded measurements that were within [Formula: see text] 20% from ground truth; however, SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples. CONCLUSIONS This study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental setup, image acquisition parameters, and ROI selection analysis.
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Affiliation(s)
- Hayden J Good
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville, FL, 32611, USA.
| | - Olivia C Sehl
- Department of Medical Biophysics, Imaging Research Laboratories, Western University, Robarts Research Institute, London, ON, N6A 5B7, Canada
| | - Julia J Gevaert
- Department of Medical Biophysics, Imaging Research Laboratories, Western University, Robarts Research Institute, London, ON, N6A 5B7, Canada
| | - Bo Yu
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville, FL, 32611, USA
| | - Maryam A Berih
- Department of Medical Biophysics, Imaging Research Laboratories, Western University, Robarts Research Institute, London, ON, N6A 5B7, Canada
| | - Sebastian A Montero
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville, FL, 32611, USA
| | - Carlos M Rinaldi-Ramos
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville, FL, 32611, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Dr. JG56, P.O. Box 116131, Gainesville, FL, 32611, USA
| | - Paula J Foster
- Department of Medical Biophysics, Imaging Research Laboratories, Western University, Robarts Research Institute, London, ON, N6A 5B7, Canada
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5
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Good HJ, Sehl OC, Gevaert JJ, Yu B, Berih MA, Montero SA, Rinaldi-Ramos CM, Foster PJ. Inter-user comparison for quantification of superparamagnetic iron oxides with magnetic particle imaging across two institutions highlights a need for standardized approaches. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.03.535446. [PMID: 37066180 PMCID: PMC10104026 DOI: 10.1101/2023.04.03.535446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Purpose Magnetic particle imaging (MPI) is being explored in biological contexts that require accurate and reproducible quantification of superparamagnetic iron oxide nanoparticles (SPIONs). While many groups have focused on improving imager and SPION design to improve resolution and sensitivity, few have focused on improving quantification and reproducibility of MPI. The aim of this study was to compare MPI quantification results by two different systems and the accuracy of SPION quantification performed by multiple users at two institutions. Procedures Six users (3 from each institute) imaged a known amount of Vivotrax+ (10 μg Fe), diluted in a small (10 μL) or large (500 μL) volume. These samples were imaged with or without calibration standards in the field of view, to create a total of 72 images (6 users x triplicate samples x 2 sample volumes x 2 calibration methods). These images were analyzed by the respective user with two region of interest (ROI) selection methods. Image intensities, Vivotrax+ quantification, and ROI selection was compared across users, within and across institutions. Results MPI imagers at two different institutes produce significantly different signal intensities, that differ by over 3 times for the same concentration of Vivotrax+. Overall quantification yielded measurements that were within ± 20% from ground truth, however SPION quantification values obtained at each laboratory were significantly different. Results suggest that the use of different imagers had a stronger influence on SPION quantification compared to differences arising from user error. Lastly, calibration conducted from samples in the imaging field of view gave the same quantification results as separately imaged samples. Conclusions This study highlights that there are many factors that contribute to the accuracy and reproducibility of MPI quantification, including variation between MPI imagers and users, despite pre-defined experimental set up, image acquisition parameters, and ROI selection analysis.
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Affiliation(s)
- Hayden J. Good
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville Fl, 32611, United States of America
| | - Olivia C. Sehl
- Department of Medical Biophysics, Western University; Imaging Research Laboratories, Robarts Research Institute, London, ON N6A 5B7, Canada
| | - Julia J. Gevaert
- Department of Medical Biophysics, Western University; Imaging Research Laboratories, Robarts Research Institute, London, ON N6A 5B7, Canada
| | - Bo Yu
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville Fl, 32611, United States of America
| | - Maryam A. Berih
- Department of Medical Biophysics, Western University; Imaging Research Laboratories, Robarts Research Institute, London, ON N6A 5B7, Canada
| | - Sebastian A. Montero
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville Fl, 32611, United States of America
| | - Carlos M. Rinaldi-Ramos
- Department of Chemical Engineering, University of Florida, 1006 Center Dr. P.O. Box 116005, Gainesville Fl, 32611, United States of America
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Dr. JG56, P.O. Box 116131, Gainesville FL, 32611, United States of America
| | - Paula J. Foster
- Department of Medical Biophysics, Western University; Imaging Research Laboratories, Robarts Research Institute, London, ON N6A 5B7, Canada
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6
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Magnetic Particle Imaging in Vascular Imaging, Immunotherapy, Cell Tracking, and Noninvasive Diagnosis. Mol Imaging 2023. [DOI: 10.1155/2023/4131117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023] Open
Abstract
Magnetic particle imaging (MPI) is a new tracer-based imaging modality that is useful in diagnosing various pathophysiology related to the vascular system and for sensitive tracking of cytotherapies. MPI uses nonradioactive and easily assimilated nanometer-sized iron oxide particles as tracers. MPI images the nonlinear Langevin behavior of the iron oxide particles and has allowed for the sensitive detection of iron oxide-labeled therapeutic cells in the body. This review will provide an overview of MPI technology, the tracer, and its use in vascular imaging and cytotherapies using molecular targets.
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7
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Fung KLB, Colson C, Bryan J, Saayujya C, Mokkarala-Lopez J, Hartley A, Yousuf K, Kuo R, Lu Y, Fellows BD, Chandrasekharan P, Conolly SM. First Superferromagnetic Remanence Characterization and Scan Optimization for Super-Resolution Magnetic Particle Imaging. NANO LETTERS 2023; 23:1717-1725. [PMID: 36821385 PMCID: PMC10790312 DOI: 10.1021/acs.nanolett.2c04404] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Magnetic particle imaging (MPI) is a sensitive, high-contrast tracer modality that images superparamagnetic iron oxide nanoparticles, enabling radiation-free theranostic imaging. MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10× resolution and signal improvements with dramatically sharper M-H curves. Experiments show a dependence on interparticle interactions, conforming to literature definitions of superferromagnetism. We thus call our tracers superferromagnetic iron oxide nanoparticles (SFMIOs). While SFMIOs provide excellent signal and resolution, they exhibit hysteresis with non-negligible remanence and coercivity. We provide the first quantitative measurements of SFMIO remanence decay and reformation using a novel multiecho pulse sequence. We characterize MPI scanning with remanence decay and coercivity and describe an SNR-optimized pulse sequence for SFMIOs under human electromagnetic safety limitations. The resolution from SFMIOs could enable clinical MPI with 10× reduced scanner selection fields, reducing hardware costs by up to 100×.
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Affiliation(s)
- K L Barry Fung
- UC Berkeley-UCSF Graduate Group in Bioengineering, University of California Berkeley and University of California San Francisco, https://bioegrad.berkeley.edu/
| | - Caylin Colson
- UC Berkeley-UCSF Graduate Group in Bioengineering, University of California Berkeley and University of California San Francisco, https://bioegrad.berkeley.edu/
| | - Jacob Bryan
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Chinmoy Saayujya
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California 94720, United States
| | - Javier Mokkarala-Lopez
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Allison Hartley
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Khadija Yousuf
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Renesmee Kuo
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Yao Lu
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Benjamin D Fellows
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Prashant Chandrasekharan
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
| | - Steven M Conolly
- Department of Bioengineering, University of California Berkeley, Berkeley, California 94720, United States
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California 94720, United States
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8
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Sun A, Hayat H, Sanchez SW, Moore A, Wang P. Magnetic Particle Imaging of Transplanted Human Islets Using a Machine Learning Algorithm. Methods Mol Biol 2023; 2592:185-194. [PMID: 36507994 PMCID: PMC10754649 DOI: 10.1007/978-1-0716-2807-2_13] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Human islet transplantation is a promising therapy to restore normoglycemia for type 1 diabetes (T1D). Despite recent advances, human islet transplantation remains suboptimal due to significant islet graft loss after transplantation. Various immunological and nonimmunological factors contribute to this loss therefore signifying a need for strategies and approaches for visualizing and monitoring transplanted human islet grafts. One such imaging approach is magnetic particle imaging (MPI), an emerging imaging modality that detects the magnetization of iron oxide nanoparticles. MPI is known for its specificity due to its high image contrast and sensitivity. MPI through its noninvasive nature provides the means for monitoring transplanted human islets in real time. Here we summarize an approach to track transplanted human islets using MPI. We label human islet from donors with dextran-coated ferucarbotran iron oxide nanoparticles, transplant the labeled human islet into under the left kidney capsule, and image graft cells using an MPI scanner. We engineer a K-means++, clustering-based unsupervised machine learning algorithm for standardized image segmentation and iron quantification of the MPI, which solves problems with selection bias and indiscriminate signal boundary that accompanies this newer imaging modality. In this chapter, we summarize the methods of this emerging imaging modality of MPI in conjunction with unsupervised machine learning to monitor and visualize islets after transplantation.
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Affiliation(s)
- Aixia Sun
- Precision Health Program, Michigan State University, East Lansing, MI, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Hasaan Hayat
- Precision Health Program, Michigan State University, East Lansing, MI, USA
- College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Simon W Sanchez
- Institute for Quantitative Health Science and Engineering (IQ), Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA
| | - Anna Moore
- Precision Health Program, Michigan State University, East Lansing, MI, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Ping Wang
- Precision Health Program, Michigan State University, East Lansing, MI, USA.
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
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9
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Wang W, Teng Y, Xue JJ, Cai HK, Pan YB, Ye XN, Mao XL, Li SW. Nanotechnology in Kidney and Islet Transplantation: An Ongoing, Promising Field. Front Immunol 2022; 13:846032. [PMID: 35464482 PMCID: PMC9024121 DOI: 10.3389/fimmu.2022.846032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/08/2022] [Indexed: 11/21/2022] Open
Abstract
Organ transplantation has evolved rapidly in recent years as a reliable option for patients with end-stage organ failure. However, organ shortage, surgical risks, acute and chronic rejection reactions and long-term immunosuppressive drug applications and their inevitable side effects remain extremely challenging problems. The application of nanotechnology in medicine has proven highly successful and has unique advantages for diagnosing and treating diseases compared to conventional methods. The combination of nanotechnology and transplantation brings a new direction of thinking to transplantation medicine. In this article, we provide an overview of the application and progress of nanotechnology in kidney and islet transplantation, including nanotechnology for renal pre-transplantation preservation, artificial biological islets, organ imaging and drug delivery.
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Affiliation(s)
- Wei Wang
- Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Ya Teng
- Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Ji-Ji Xue
- Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Hong-Kai Cai
- Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Yu-Biao Pan
- Taizhou Hospital of Zhejiang Province, Zhejiang University, Linhai, China
| | - Xing-Nan Ye
- Taizhou Hospital of Zhejiang Province, Shaoxing University, Linhai, China
| | - Xin-Li Mao
- Key Laboratory of Minimally Invasive Techniques and Rapid Rehabilitation of Digestive System Tumor of Zhejiang Province, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- Department of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- Institute of Digestive Disease, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- *Correspondence: Xin-Li Mao, ; Shao-Wei Li,
| | - Shao-Wei Li
- Key Laboratory of Minimally Invasive Techniques and Rapid Rehabilitation of Digestive System Tumor of Zhejiang Province, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- Department of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- Institute of Digestive Disease, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
- *Correspondence: Xin-Li Mao, ; Shao-Wei Li,
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10
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Harvell-Smith S, Tung LD, Thanh NTK. Magnetic particle imaging: tracer development and the biomedical applications of a radiation-free, sensitive, and quantitative imaging modality. NANOSCALE 2022; 14:3658-3697. [PMID: 35080544 DOI: 10.1039/d1nr05670k] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Magnetic particle imaging (MPI) is an emerging tracer-based modality that enables real-time three-dimensional imaging of the non-linear magnetisation produced by superparamagnetic iron oxide nanoparticles (SPIONs), in the presence of an external oscillating magnetic field. As a technique, it produces highly sensitive radiation-free tomographic images with absolute quantitation. Coupled with a high contrast, as well as zero signal attenuation at-depth, there are essentially no limitations to where that can be imaged within the body. These characteristics enable various biomedical applications of clinical interest. In the opening sections of this review, the principles of image generation are introduced, along with a detailed comparison of the fundamental properties of this technique with other common imaging modalities. The main feature is a presentation on the up-to-date literature for the development of SPIONs tailored for improved imaging performance, and developments in the current and promising biomedical applications of this emerging technique, with a specific focus on theranostics, cell tracking and perfusion imaging. Finally, we will discuss recent progress in the clinical translation of MPI. As signal detection in MPI is almost entirely dependent on the properties of the SPION employed, this work emphasises the importance of tailoring the synthetic process to produce SPIONs demonstrating specific properties and how this impacts imaging in particular applications and MPI's overall performance.
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Affiliation(s)
- Stanley Harvell-Smith
- Biophysics Group, Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK.
- UCL Healthcare Biomagnetic and Nanomaterials Laboratories, University College London, 21 Albemarle Street, London W1S 4BS, UK
| | - Le Duc Tung
- Biophysics Group, Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK.
- UCL Healthcare Biomagnetic and Nanomaterials Laboratories, University College London, 21 Albemarle Street, London W1S 4BS, UK
| | - Nguyen Thi Kim Thanh
- Biophysics Group, Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK.
- UCL Healthcare Biomagnetic and Nanomaterials Laboratories, University College London, 21 Albemarle Street, London W1S 4BS, UK
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11
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Coppola A, Zorzetto G, Piacentino F, Bettoni V, Pastore I, Marra P, Perani L, Esposito A, De Cobelli F, Carcano G, Fontana F, Fiorina P, Venturini M. Imaging in experimental models of diabetes. Acta Diabetol 2022; 59:147-161. [PMID: 34779949 DOI: 10.1007/s00592-021-01826-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/30/2021] [Indexed: 12/01/2022]
Abstract
Translational medicine, experimental medicine and experimental animal models, in particular mice and rats, represent a multidisciplinary field that has made it possible to achieve, in the last decades, important scientific progress. In this review, we have summarized the most frequently used imaging animal models, such as ultrasound (US), micro-CT, MRI and the optical imaging methods, and their main implications in diagnostic and therapeutic fields, with a particular focus on diabetes mellitus, a multifactorial disease extremely widespread among the general population.
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Affiliation(s)
- Andrea Coppola
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy.
| | | | - Filippo Piacentino
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
| | - Valeria Bettoni
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
| | - Ida Pastore
- Division of Endocrinology, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Paolo Marra
- Department of Diagnostic Radiology, Giovanni XXIII Hospital, Milano-Bicocca University, Bergamo, Italy
| | - Laura Perani
- Experimental Imaging Center, San Raffaele Scientific Institute, Milan, Italy
| | - Antonio Esposito
- Experimental Imaging Center, San Raffaele Scientific Institute, Milan, Italy
- Radiology Unit, San Raffaele Scientific Institute, San Raffaele Vita-Salute University, Milan, Italy
| | - Francesco De Cobelli
- Radiology Unit, San Raffaele Scientific Institute, San Raffaele Vita-Salute University, Milan, Italy
| | - Giulio Carcano
- Insubria University, Varese, Italy
- General, Emergency, and Transplant Surgery Unit, ASST Settelaghi, Varese, Italy
| | - Federico Fontana
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
| | - Paolo Fiorina
- International Center for T1D, Centro di Ricerca Pediatrica Romeo ed Enrica Invernizzi, Dipartimento di Scienze Biomediche e Cliniche "L. Sacco", Università di Milano, Milan, Italy
- Nephrology Division, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Endocrinology Division, ASST Fatebenefratelli Sacco, Milan, Italy
| | - Massimo Venturini
- Diagnostic and Interventional Radiology Unit, ASST Settelaghi, Varese, Italy
- Insubria University, Varese, Italy
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12
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Purich K, Cai H, Yang B, Xu Z, Tessier AG, Black A, Hung RW, Boivin E, Xu B, Wu P, Zhang B, Xin D, Fallone BG, Rajotte RV, Wu Y, Rayat GR. MRI monitoring of transplanted neonatal porcine islets labeled with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles in a mouse model. Xenotransplantation 2021; 29:e12720. [PMID: 34850455 DOI: 10.1111/xen.12720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/25/2021] [Accepted: 10/22/2021] [Indexed: 11/27/2022]
Abstract
Islet transplantation is a potential treatment option for certain patients with type 1 diabetes; however, it still faces barriers to widespread use, including the lack of tools to monitor islet grafts post-transplantation. This study investigates whether labeling neonatal porcine islets (NPI) with polyvinylpyrrolidone-coated superparamagnetic iron oxide nanoparticles (PVP-SPIO) affects their function, and whether this nanoparticle can be utilized to monitor NPI xenografts with magnetic resonance imaging (MRI) in a mouse model. In vitro, PVP-SPIO-labeled NPI in an agarose gel was visualized clearly by MRI. PVP-SPIO-labeled islets were then transplanted under the kidney capsules of immunodeficient nondiabetic and diabetic mice. All diabetic mice that received transplantation of PVP-SPIO-labeled islets reached normoglycemia. Grafts appeared as hypo-intense areas on MRI and were distinguishable from the surrounding tissues. Following injection of spleen cells from immunocompetent mice, normoglycemic recipient mice became diabetic and islet grafts showed an increase in volume, accompanied by a mixed signal on MRI. Overall, this study demonstrates that PVP-SPIO did not affect the function of NPI that PVP-SPIO-labeled islets were easily seen on MRI, and changes in MRI signals following rejection suggest a potential use of PVP-SPIO-labeled islets to monitor graft viability.
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Affiliation(s)
- Kieran Purich
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Haolei Cai
- Department of Surgery, 2nd Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
| | - Bin Yang
- Department of Surgery, 2nd Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
| | - Zhihao Xu
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Anthony G Tessier
- Department of Oncology, University of Alberta, Edmonton, Alberta, Canada.,Department of Medical Physics, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Adnan Black
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Ryan W Hung
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada
| | - Eric Boivin
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Baoyou Xu
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Ping Wu
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Bo Zhang
- Department of Surgery, 2nd Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
| | - Dong Xin
- Department of Surgery, 2nd Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
| | - Biagio Gino Fallone
- Department of Oncology, University of Alberta, Edmonton, Alberta, Canada.,Department of Medical Physics, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Ray V Rajotte
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Yulian Wu
- Department of Surgery, 2nd Affiliated Hospital of Medical College, Zhejiang University, Hangzhou, China
| | - Gina R Rayat
- Department of Surgery, Ray Rajotte Surgical-Medical Research Institute, Alberta Diabetes Institute, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
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13
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Knier NN, Dubois VP, Chen Y, Ronald JA, Foster PJ. A method for the efficient iron-labeling of patient-derived xenograft cells and cellular imaging validation. J Biol Methods 2021; 8:e154. [PMID: 34631910 PMCID: PMC8487865 DOI: 10.14440/jbm.2021.356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 07/07/2021] [Accepted: 07/15/2021] [Indexed: 11/23/2022] Open
Abstract
There is momentum towards implementing patient-derived xenograft models (PDX) in cancer research to reflect the histopathology, tumor behavior, and metastatic properties observed in the original tumor. To study PDX cells preclinically, we used both bioluminescence imaging (BLI) to evaluate cell viability and magnetic particle imaging (MPI), an emerging imaging technology to allow for detection and quantification of iron nanoparticles. The goal of this study was to develop the first successful iron labeling method of breast cancer cells derived from patient brain metsastases and validate this method with imaging during tumor development. The overall workflow of this labeling method is as follows: adherent and non-adherent luciferase expressing human breast cancer PDX cells (F2-7) are dissociated and concurrently labeled after incubation with micron-sized iron oxide particles (MPIO; 25 μg Fe/ml), with labeling validated by cellular imaging with MPI and BLI. In this study, NOD/SCID/ILIIrg-/- (n = 5) mice Received injections of 1 × 106 iron-labeled F2-7 cells into the fourth mammary fat pad (MFP). BLI was performed longitudinally to day 49 and MPI was performed up to day 28. In vivo BLI revealed that signal increased over time with tumor development. MPI revealed decreasing signal in the tumors over time. Here, we demonstrate the first application of MPI to monitor the growth of a PDX MFP tumor and the first successful labeling of PDX cells with iron oxide particles. Imaging of PDX cells provides a powerful system to better develop personalized therapies targeting breast cancer brain metastasis.
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Affiliation(s)
- Natasha N Knier
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Veronica P Dubois
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Yuanxin Chen
- Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - John A Ronald
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada
| | - Paula J Foster
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Imaging Laboratories, Robarts Research Institute, London, Ontario, Canada
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14
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Friedrich RP, Cicha I, Alexiou C. Iron Oxide Nanoparticles in Regenerative Medicine and Tissue Engineering. NANOMATERIALS 2021; 11:nano11092337. [PMID: 34578651 PMCID: PMC8466586 DOI: 10.3390/nano11092337] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 09/03/2021] [Accepted: 09/06/2021] [Indexed: 12/13/2022]
Abstract
In recent years, many promising nanotechnological approaches to biomedical research have been developed in order to increase implementation of regenerative medicine and tissue engineering in clinical practice. In the meantime, the use of nanomaterials for the regeneration of diseased or injured tissues is considered advantageous in most areas of medicine. In particular, for the treatment of cardiovascular, osteochondral and neurological defects, but also for the recovery of functions of other organs such as kidney, liver, pancreas, bladder, urethra and for wound healing, nanomaterials are increasingly being developed that serve as scaffolds, mimic the extracellular matrix and promote adhesion or differentiation of cells. This review focuses on the latest developments in regenerative medicine, in which iron oxide nanoparticles (IONPs) play a crucial role for tissue engineering and cell therapy. IONPs are not only enabling the use of non-invasive observation methods to monitor the therapy, but can also accelerate and enhance regeneration, either thanks to their inherent magnetic properties or by functionalization with bioactive or therapeutic compounds, such as drugs, enzymes and growth factors. In addition, the presence of magnetic fields can direct IONP-labeled cells specifically to the site of action or induce cell differentiation into a specific cell type through mechanotransduction.
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15
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Sun A, Hayat H, Liu S, Tull E, Bishop JO, Dwan BF, Gudi M, Talebloo N, Dizon JR, Li W, Gaudet J, Alessio A, Aguirre A, Wang P. 3D in vivo Magnetic Particle Imaging of Human Stem Cell-Derived Islet Organoid Transplantation Using a Machine Learning Algorithm. Front Cell Dev Biol 2021; 9:704483. [PMID: 34458264 PMCID: PMC8397508 DOI: 10.3389/fcell.2021.704483] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/15/2021] [Indexed: 12/17/2022] Open
Abstract
Stem cell-derived islet organoids constitute a promising treatment of type 1 diabetes. A major hurdle in the field is the lack of appropriate in vivo method to determine graft outcome. Here, we investigate the feasibility of in vivo tracking of transplanted stem cell-derived islet organoids using magnetic particle imaging (MPI) in a mouse model. Human induced pluripotent stem cells-L1 were differentiated to islet organoids and labeled with superparamagnetic iron oxide nanoparticles. The phantoms comprising of different numbers of labeled islet organoids were imaged using an MPI system. Labeled islet organoids were transplanted into NOD/scid mice under the left kidney capsule and were then scanned using 3D MPI at 1, 7, and 28 days post transplantation. Quantitative assessment of the islet organoids was performed using the K-means++ algorithm analysis of 3D MPI. The left kidney was collected and processed for immunofluorescence staining of C-peptide and dextran. Islet organoids expressed islet cell markers including insulin and glucagon. Image analysis of labeled islet organoids phantoms revealed a direct linear correlation between the iron content and the number of islet organoids. The K-means++ algorithm showed that during the course of the study the signal from labeled islet organoids under the left kidney capsule decreased. Immunofluorescence staining of the kidney sections showed the presence of islet organoid grafts as confirmed by double staining for dextran and C-peptide. This study demonstrates that MPI with machine learning algorithm analysis can monitor islet organoids grafts labeled with super-paramagnetic iron oxide nanoparticles and provide quantitative information of their presence in vivo.
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Affiliation(s)
- Aixia Sun
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, United States
| | - Hasaan Hayat
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Lyman Briggs College, Michigan State University, East Lansing, MI, United States
| | - Sihai Liu
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, United States.,Department of Orthopedics, Beijing Charity Hospital, Capital Medical University, Beijing, China
| | - Eliah Tull
- Medgar Evers College, City University of New York, Brooklyn, NY, United States
| | - Jack Owen Bishop
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Department of Neuroscience, College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - Bennett Francis Dwan
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - Mithil Gudi
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Lyman Briggs College, Michigan State University, East Lansing, MI, United States
| | - Nazanin Talebloo
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Department of Chemistry, College of Natural Science, Michigan State University, East Lansing, MI, United States
| | - James Raynard Dizon
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Wen Li
- Department of Electrical and Computer Engineering, College of Engineering, Michigan State University, East Lansing, MI, United States.,Institute for Quantitative Health Science and Engineering (IQ), Department of Biomedical Engineering, Michigan State University, East Lansing, MI, United States
| | - Jeffery Gaudet
- Institute for Quantitative Health Science and Engineering (IQ), Department of Biomedical Engineering, Michigan State University, East Lansing, MI, United States.,Magnetic Insight Inc., Alameda, CA, United States
| | - Adam Alessio
- Institute for Quantitative Health Science and Engineering (IQ), Department of Biomedical Engineering, Michigan State University, East Lansing, MI, United States.,Department of Computational Mathematics, Science and Engineering, College of Engineering, Michigan State University, East Lansing, MI, United States
| | - Aitor Aguirre
- Institute for Quantitative Health Science and Engineering (IQ), Department of Biomedical Engineering, Michigan State University, East Lansing, MI, United States
| | - Ping Wang
- Precision Health Program, Michigan State University, East Lansing, MI, United States.,Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, United States
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16
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Melo KP, Makela AV, Knier NN, Hamilton AM, Foster PJ. Magnetic microspheres can be used for magnetic particle imaging of cancer cells arrested in the mouse brain. Magn Reson Med 2021; 87:312-322. [PMID: 34453462 DOI: 10.1002/mrm.28987] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 08/09/2021] [Accepted: 08/09/2021] [Indexed: 02/02/2023]
Abstract
PURPOSE Magnetic particle imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIOs). MRI cell tracking with SPIOs has very high sensitivity, but low specificity and quantification is difficult. MPI could overcome these limitations. There are no reports of micron-sized iron oxide particles (MPIO) for cell tracking by MPI. Therefore, the goal was to evaluate if MPIO can be used for in vivo detection and quantification of cancer cells distributed in the mouse brain by MPI. METHODS In the first experiment mice were injected with either 2.5 × 105 or 5.0 × 105 MPIO-labeled cancer cells and MPI was performed ex vivo. In a second experiment, mice received either 2.5 × 105 or 5.0 × 104 MPIO-labeled cells and MPI was performed in vivo. In a third experiment, mice were injected with 5.0 × 104 cells, labeled with either MPIO or ferucarbotran, and MPI was performed in vivo. RESULTS MPIO-labeled cells were visible in all MPI images of the mouse brain. The MPI signal and iron content measurements were greater for brains of mice that were injected with higher numbers of MPIO-labeled cells. Ferucarbotran-labeled cells were not detected in the brain by MPI. CONCLUSION This is the first example of the use of MPIO for cell tracking with MPI. With an intracardiac cell injection, ~15% of cells will arrest in the brain vasculature. For our lowest cell injection of 5.0 × 104 cells, this was ~10 000 cells, distributed throughout the brain.
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Affiliation(s)
- Kierstin P Melo
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
| | - Ashley V Makela
- Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, Michigan, USA
| | - Natasha N Knier
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
| | - Amanda M Hamilton
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Paula J Foster
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
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17
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Hayat H, Nukala A, Nyamira A, Fan J, Wang P. A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine. Biomed Mater 2021; 16. [PMID: 34280907 DOI: 10.1088/1748-605x/ac15b2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 07/19/2021] [Indexed: 12/17/2022]
Abstract
Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem is further exacerbated when engineering and optimizing nanomaterials for biomedical purposes. To navigate this issue, artificial intelligence (AI) algorithms have been applied for data analysis and inference, allowing for a more applicable understanding of the complex interaction amongst the abundant variables in a system involving the synthesis or use of nanomedicine. Here, we report on the current relationship and implications of nanomedicine and AI. Particularly, we explore AI as a tool for enabling nanomedicine in the context of nanodrug screening and development, brain-machine interfaces and nanotoxicology. We also report on the current state and future direction of nanomedicine and AI in cancer, diabetes, and neurological disorder therapy.
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Affiliation(s)
- Hasaan Hayat
- Precision Health Program,, Michigan State University, East Lansing, MI, United States of America.,Lyman Briggs College, Michigan State University, East Lansing, MI, United States of America
| | - Arijit Nukala
- Precision Health Program,, Michigan State University, East Lansing, MI, United States of America.,Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
| | - Anthony Nyamira
- Lyman Briggs College, Michigan State University, East Lansing, MI, United States of America
| | - Jinda Fan
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI, United States of America
| | - Ping Wang
- Precision Health Program,, Michigan State University, East Lansing, MI, United States of America.,Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, United States of America
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18
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Liu H, Lu C, Han L, Zhang X, Song G. Optical – Magnetic probe for evaluating cancer therapy. Coord Chem Rev 2021. [DOI: 10.1016/j.ccr.2021.213978] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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19
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Canese R, Vurro F, Marzola P. Iron Oxide Nanoparticles as Theranostic Agents in Cancer Immunotherapy. NANOMATERIALS 2021; 11:nano11081950. [PMID: 34443781 PMCID: PMC8399455 DOI: 10.3390/nano11081950] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 07/13/2021] [Accepted: 07/22/2021] [Indexed: 11/16/2022]
Abstract
Starting from the mid-1990s, several iron oxide nanoparticles (NPs) were developed as MRI contrast agents. Since their sizes fall in the tenths of a nanometer range, after i.v. injection these NPs are preferentially captured by the reticuloendothelial system of the liver. They have therefore been proposed as liver-specific contrast agents. Even though their unfavorable cost/benefit ratio has led to their withdrawal from the market, innovative applications have recently prompted a renewal of interest in these NPs. One important and innovative application is as diagnostic agents in cancer immunotherapy, thanks to their ability to track tumor-associated macrophages (TAMs) in vivo. It is worth noting that iron oxide NPs may also have a therapeutic role, given their ability to alter macrophage polarization. This review is devoted to the most recent advances in applications of iron oxide NPs in tumor diagnosis and therapy. The intrinsic therapeutic effect of these NPs on tumor growth, their capability to alter macrophage polarization and their diagnostic potential are examined. Innovative strategies for NP-based drug delivery in tumors (e.g., magnetic resonance targeting) will also be described. Finally, the review looks at their role as tracers for innovative, and very promising, imaging techniques (magnetic particle imaging-MPI).
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Affiliation(s)
- Rossella Canese
- MRI Unit, Core Facilities, Istituto Superiore di Sanità, 00161 Rome, Italy
- Correspondence: (R.C.); (P.M.)
| | - Federica Vurro
- Department of Computer Science, University of Verona, 37134 Verona, Italy;
| | - Pasquina Marzola
- Department of Computer Science, University of Verona, 37134 Verona, Italy;
- Correspondence: (R.C.); (P.M.)
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20
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Lu C, Han L, Wang J, Wan J, Song G, Rao J. Engineering of magnetic nanoparticles as magnetic particle imaging tracers. Chem Soc Rev 2021; 50:8102-8146. [PMID: 34047311 DOI: 10.1039/d0cs00260g] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Magnetic particle imaging (MPI) has recently emerged as a promising non-invasive imaging technique because of its signal linearly propotional to the tracer mass, ability to generate positive contrast, low tissue background, unlimited tissue penetration depth, and lack of ionizing radiation. The sensitivity and resolution of MPI are highly dependent on the properties of magnetic nanoparticles (MNPs), and extensive research efforts have been focused on the design and synthesis of tracers. This review examines parameters that dictate the performance of MNPs, including size, shape, composition, surface property, crystallinity, the surrounding environment, and aggregation state to provide guidance for engineering MPI tracers with better performance. Finally, we discuss applications of MPI imaging and its challenges and perspectives in clinical translation.
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Affiliation(s)
- Chang Lu
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, P. R. China.
| | - Linbo Han
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, P. R. China
| | - Joanna Wang
- Molecular Imaging Program at Stanford, Department of Radiology, Stanford University School of Medicine, 1201 Welch Road, Stanford, California 94305-5484, USA.
| | - Jiacheng Wan
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, P. R. China.
| | - Guosheng Song
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, P. R. China.
| | - Jianghong Rao
- Molecular Imaging Program at Stanford, Department of Radiology, Stanford University School of Medicine, 1201 Welch Road, Stanford, California 94305-5484, USA.
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21
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Billings C, Langley M, Warrington G, Mashali F, Johnson JA. Magnetic Particle Imaging: Current and Future Applications, Magnetic Nanoparticle Synthesis Methods and Safety Measures. Int J Mol Sci 2021; 22:ijms22147651. [PMID: 34299271 PMCID: PMC8306580 DOI: 10.3390/ijms22147651] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 07/10/2021] [Accepted: 07/14/2021] [Indexed: 02/07/2023] Open
Abstract
Magnetic nanoparticles (MNPs) have a wide range of applications; an area of particular interest is magnetic particle imaging (MPI). MPI is an imaging modality that utilizes superparamagnetic iron oxide particles (SPIONs) as tracer particles to produce highly sensitive and specific images in a broad range of applications, including cardiovascular, neuroimaging, tumor imaging, magnetic hyperthermia and cellular tracking. While there are hurdles to overcome, including accessibility of products, and an understanding of safety and toxicity profiles, MPI has the potential to revolutionize research and clinical biomedical imaging. This review will explore a brief history of MPI, MNP synthesis methods, current and future applications, and safety concerns associated with this newly emerging imaging modality.
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Affiliation(s)
- Caroline Billings
- College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996, USA;
| | - Mitchell Langley
- Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA; (M.L.); (G.W.); (F.M.)
| | - Gavin Warrington
- Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA; (M.L.); (G.W.); (F.M.)
| | - Farzin Mashali
- Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA; (M.L.); (G.W.); (F.M.)
| | - Jacqueline Anne Johnson
- Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee Space Institute, Tullahoma, TN 37388, USA
- Correspondence:
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22
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Szunerits S, Melinte S, Barras A, Pagneux Q, Voronova A, Abderrahmani A, Boukherroub R. The impact of chemical engineering and technological advances on managing diabetes: present and future concepts. Chem Soc Rev 2021; 50:2102-2146. [PMID: 33325917 DOI: 10.1039/c9cs00886a] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Monitoring blood glucose levels for diabetic patients is critical to achieve tight glycaemic control. As none of the current antidiabetic treatments restore lost functional β-cell mass in diabetic patients, insulin injections and the use of insulin pumps are most widely used in the management of glycaemia. The use of advanced and intelligent chemical engineering, together with the incorporation of micro- and nanotechnological-based processes have lately revolutionized diabetic management. The start of this concept goes back to 1974 with the description of an electrode that repeatedly measures the level of blood glucose and triggers insulin release from an infusion pump to enter the blood stream from a small reservoir upon need. Next to the insulin pumps, other drug delivery routes, including nasal, transdermal and buccal, are currently investigated. These processes necessitate competences from chemists, engineers-alike and innovative views of pharmacologists and diabetologists. Engineered micro and nanostructures hold a unique potential when it comes to drug delivery applications required for the treatment of diabetic patients. As the technical aspects of chemistry, biology and informatics on medicine are expanding fast, time has come to step back and to evaluate the impact of technology-driven chemistry on diabetics and how the bridges from research laboratories to market products are established. In this review, the large variety of therapeutic approaches proposed in the last five years for diabetic patients are discussed in an applied context. A survey of the state of the art of closed-loop insulin delivery strategies in response to blood glucose level fluctuation is provided together with insights into the emerging key technologies for diagnosis and drug development. Chemical engineering strategies centered on preserving and regenerating functional pancreatic β-cell mass are evoked in addition as they represent a permanent solution for diabetic patients.
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Affiliation(s)
- Sabine Szunerits
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
| | - Sorin Melinte
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
| | - Alexandre Barras
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
| | - Quentin Pagneux
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
| | - Anna Voronova
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
| | - Amar Abderrahmani
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
| | - Rabah Boukherroub
- Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520-IEMN, F-59000 Lille, France.
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Rivera-Rodriguez A, Rinaldi-Ramos CM. Emerging Biomedical Applications Based on the Response of Magnetic Nanoparticles to Time-Varying Magnetic Fields. Annu Rev Chem Biomol Eng 2021; 12:163-185. [PMID: 33856937 DOI: 10.1146/annurev-chembioeng-102720-015630] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Magnetic nanoparticles are of interest for biomedical applications because of their biocompatibility, tunable surface chemistry, and actuation using applied magnetic fields. Magnetic nanoparticles respond to time-varying magnetic fields via physical particle rotation or internal dipole reorientation, which can result in signal generation or conversion of magnetic energy to heat. This dynamic magnetization response enables their use as tracers in magnetic particle imaging (MPI), an emerging biomedical imaging modality in which signal is quantitative of tracer mass and there is no tissue background signal or signal attenuation. Conversion of magnetic energy to heat motivates use in nanoscale thermal cancer therapy, magnetic actuation of drug release, and rapid rewarming of cryopreserved organs. This review introduces basic concepts of magnetic nanoparticle response to time-varying magnetic fields and presents recent advances in the field, with an emphasis on MPI and conversion of magnetic energy to heat.
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Affiliation(s)
- Angelie Rivera-Rodriguez
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida 32611, USA; ,
| | - Carlos M Rinaldi-Ramos
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida 32611, USA; , .,Department of Chemical Engineering, University of Florida, Gainesville, Florida 32611, USA
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24
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Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging. Sci Rep 2021; 11:4529. [PMID: 33633162 PMCID: PMC7907137 DOI: 10.1038/s41598-021-83821-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 02/01/2021] [Indexed: 12/03/2022] Open
Abstract
Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.
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Chandrasekharan P, Fung KB, Zhou XY, Cui W, Colson C, Mai D, Jeffris K, Huynh Q, Saayujya C, Kabuli L, Fellows B, Lu Y, Yu E, Tay ZW, Zheng B, Fong L, Conolly SM. Non-radioactive and sensitive tracking of neutrophils towards inflammation using antibody functionalized magnetic particle imaging tracers. Nanotheranostics 2021; 5:240-255. [PMID: 33614400 PMCID: PMC7893534 DOI: 10.7150/ntno.50721] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Accepted: 01/14/2021] [Indexed: 02/07/2023] Open
Abstract
White blood cells (WBCs) are a key component of the mammalian immune system and play an essential role in surveillance, defense, and adaptation against foreign pathogens. Apart from their roles in the active combat of infection and the development of adaptive immunity, immune cells are also involved in tumor development and metastasis. Antibody-based therapeutics have been developed to regulate (i.e. selectively activate or inhibit immune function) and harness immune cells to fight malignancy. Alternatively, non-invasive tracking of WBC distribution can diagnose inflammation, infection, fevers of unknown origin (FUOs), and cancer. Magnetic Particle Imaging (MPI) is a non-invasive, non-radioactive, and sensitive medical imaging technique that uses safe superparamagnetic iron oxide nanoparticles (SPIOs) as tracers. MPI has previously been shown to track therapeutic stem cells for over 87 days with a ~200 cell detection limit. In the current work, we utilized antibody-conjugated SPIOs specific to neutrophils for in situ labeling, and non-invasive and radiation-free tracking of these inflammatory cells to sites of infection and inflammation in an in vivo murine model of lipopolysaccharide-induced myositis. MPI showed sensitive detection of inflammation with a contrast-to-noise ratio of ~8-13.
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Affiliation(s)
- Prashant Chandrasekharan
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - K.L. Barry Fung
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
- UC Berkeley-UCSF Graduate Group in Bioengineering, California, United States
| | - Xinyi Y. Zhou
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
- UC Berkeley-UCSF Graduate Group in Bioengineering, California, United States
| | - Weiwen Cui
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Caylin Colson
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
- UC Berkeley-UCSF Graduate Group in Bioengineering, California, United States
| | - David Mai
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Kenneth Jeffris
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Quincy Huynh
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, United States
| | - Chinmoy Saayujya
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, United States
| | - Leyla Kabuli
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Benjamin Fellows
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Yao Lu
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Elaine Yu
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Zhi Wei Tay
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Bo Zheng
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| | - Lawrence Fong
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California 94143, United States
| | - Steven M. Conolly
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, United States
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Hayat H, Sun A, Hayat H, Liu S, Talebloo N, Pinger C, Bishop JO, Gudi M, Dwan BF, Ma X, Zhao Y, Moore A, Wang P. Artificial Intelligence Analysis of Magnetic Particle Imaging for Islet Transplantation in a Mouse Model. Mol Imaging Biol 2021; 23:18-29. [PMID: 32833112 PMCID: PMC7785569 DOI: 10.1007/s11307-020-01533-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 08/06/2020] [Accepted: 08/12/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of artificial intelligence (AI) systems for MPI analysis. PROCEDURES We utilize a canonical algorithm in the domain of unsupervised machine learning, known as K-means++, to segment the regions of interest (ROI) of images and perform iron quantification analysis using a standard curve model. We generated in vitro, in vivo, and ex vivo data using islets and mouse models and applied the AI algorithm to gain insight into segmentation and iron prediction on these MPI data. In vitro models included imaging the VivoTrax-labeled islets in varying numbers. In vivo mouse models were generated through transplantation of increasing numbers of the labeled islets under the kidney capsule of mice. Ex vivo data were obtained from the MPI images of excised kidney grafts. RESULTS The K-means++ algorithms segmented the ROI of in vitro phantoms with minimal noise. A linear correlation between the islet numbers and the increasing prediction of total iron value (TIV) in the islets was observed. Segmentation results of the ROI of the in vivo MPI scans showed that with increasing number of transplanted islets, the signal intensity increased with linear trend. Upon segmenting the ROI of ex vivo data, a linear trend was observed in which increasing intensity of the ROI yielded increasing TIV of the islets. Through statistical evaluation of the algorithm performance via intraclass correlation coefficient validation, we observed excellent performance of K-means++-based model on segmentation and quantification analysis of MPI data. CONCLUSIONS We have demonstrated the ability of the K-means++-based model to provide a standardized method of segmentation and quantification of MPI scans in an islet transplantation mouse model.
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Affiliation(s)
- Hasaan Hayat
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Lyman Briggs College, Michigan State University, East Lansing, MI, USA
| | - Aixia Sun
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Hanaan Hayat
- Lyman Briggs College, Michigan State University, East Lansing, MI, USA
- Institute for Quantitative Health Science and Engineering, Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA
| | - Sihai Liu
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
- Department of Orthopedics, Beijing Charity Hospital, Capital Medical University, Beijing, China
| | - Nazanin Talebloo
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Chemistry, College of Natural Science, Michigan State University, East Lansing, MI, USA
| | - Cody Pinger
- Institute for Quantitative Health Science and Engineering, Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA
| | - Jack Owen Bishop
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Neuroscience, College of Natural Science, Michigan State University, East Lansing, MI, USA
| | - Mithil Gudi
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Lyman Briggs College, Michigan State University, East Lansing, MI, USA
| | - Bennett Francis Dwan
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- College of Natural Science, Michigan State University, East Lansing, MI, USA
| | - Xiaohong Ma
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
- Department of Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanfeng Zhao
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
- Department of Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Anna Moore
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - Ping Wang
- Precision Health Program, Michigan State University, 766 Service Road, Rm. 2020, East Lansing, MI, 48823, USA.
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
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27
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Arifin DR, Bulte JWM. In Vivo Imaging of Pancreatic Islet Grafts in Diabetes Treatment. Front Endocrinol (Lausanne) 2021; 12:640117. [PMID: 33737913 PMCID: PMC7961081 DOI: 10.3389/fendo.2021.640117] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 01/25/2021] [Indexed: 12/22/2022] Open
Abstract
Transplantation of pancreatic islets has potential to offer life-long blood glucose management in type I diabetes and severe type II diabetes without the need of exogenous insulin administration. However, islet cell therapy suffers from autoimmune and allogeneic rejection as well as non-immune related factors. Non-invasive techniques to monitor and evaluate the fate of cell implants in vivo are essential to understand the underlying causes of graft failure, and hence to improve the precision and efficacy of islet therapy. This review describes how imaging technology has been employed to interrogate the distribution, number or volume, viability, and function of islet implants in vivo. To date, fluorescence imaging, PET, SPECT, BLI, MRI, MPI, and ultrasonography are the many imaging modalities being developed to fulfill this endeavor. We outline here the advantages, limitations, and clinical utility of each particular imaging approach.
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Affiliation(s)
- Dian R. Arifin
- Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- Institute for Cell Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Jeff W. M. Bulte
- Department of Radiology and Radiological Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- Institute for Cell Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
- *Correspondence: Jeff W. M. Bulte,
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Abstract
Many labs have been developing cellular magnetic resonance imaging (MRI), using both superparamagnetic iron oxide nanoparticles (SPIONs) and fluorine-19 (19F)-based cell labels, to track immune and stem cells used for cellular therapies. Although SPION-based MRI cell tracking has very high sensitivity for cell detection, SPIONs are indirectly detected owing to relaxation effects on protons, producing negative magnetic resonance contrast with low signal specificity. Therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles, and cell number cannot be determined. 19F-based cell tracking has high specificity for perfluorocarbon-labeled cells, and 19F signal is directly related to cell number. However, 19F MRI has low sensitivity. Magnetic particle imaging (MPI) is a new imaging modality that directly detects SPIONs. SPION-based cell tracking using MPI displays great potential for overcoming the challenges of MRI-based cell tracking, allowing for both high cellular sensitivity and specificity, and quantification of SPION-labeled cell number. Here we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods, and give our perspective on testing and applying MPI for cell tracking.
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Affiliation(s)
- Olivia C. Sehl
- Imaging Research Laboratories, Robarts Research Institute; and
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Julia J. Gevaert
- Imaging Research Laboratories, Robarts Research Institute; and
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Kierstin P. Melo
- Imaging Research Laboratories, Robarts Research Institute; and
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Natasha N. Knier
- Imaging Research Laboratories, Robarts Research Institute; and
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Paula J. Foster
- Imaging Research Laboratories, Robarts Research Institute; and
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
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29
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Demine S, Schulte ML, Territo PR, Eizirik DL. Beta Cell Imaging-From Pre-Clinical Validation to First in Man Testing. Int J Mol Sci 2020; 21:E7274. [PMID: 33019671 PMCID: PMC7582644 DOI: 10.3390/ijms21197274] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 09/21/2020] [Accepted: 09/28/2020] [Indexed: 12/14/2022] Open
Abstract
There are presently no reliable ways to quantify human pancreatic beta cell mass (BCM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. Furthermore, the lack of beta cell imaging hampers the evaluation of the impact of new drugs aiming to prevent beta cell loss or to restore BCM in diabetes. We presently discuss the potential value of BCM determination as a cornerstone for individualized therapies in diabetes, describe the presently available probes for human BCM evaluation, and discuss our approach for the discovery of novel beta cell biomarkers, based on the determination of specific splice variants present in human beta cells. This has already led to the identification of DPP6 and FXYD2ga as two promising targets for human BCM imaging, and is followed by a discussion of potential safety issues, the role for radiochemistry in the improvement of BCM imaging, and concludes with an overview of the different steps from pre-clinical validation to a first-in-man trial for novel tracers.
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Affiliation(s)
- Stephane Demine
- Indiana Biosciences Research Institute, Indianapolis, IN 46202, USA;
| | - Michael L. Schulte
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.L.S.); (P.R.T.)
| | - Paul R. Territo
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.L.S.); (P.R.T.)
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Decio L. Eizirik
- Indiana Biosciences Research Institute, Indianapolis, IN 46202, USA;
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles (ULB), 1070 Brussels, Belgium
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30
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Current Progress and Perspective: Clinical Imaging of Islet Transplantation. Life (Basel) 2020; 10:life10090213. [PMID: 32961769 PMCID: PMC7555367 DOI: 10.3390/life10090213] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/17/2020] [Accepted: 09/17/2020] [Indexed: 12/13/2022] Open
Abstract
Islet transplantation has great potential as a cure for type 1 diabetes. At present; the lack of a clinically validated non-invasive imaging method to track islet grafts limits the success of this treatment. Some major clinical imaging modalities and various molecular probes, which have been studied for non-invasive monitoring of transplanted islets, could potentially fulfill the goal of understanding pathophysiology of the functional status and viability of the islet grafts. In this current review, we summarize the recent clinical studies of a variety of imaging modalities and molecular probes for non-invasive imaging of transplanted beta cell mass. This review also includes discussions on in vivo detection of endogenous beta cell mass using clinical imaging modalities and various molecular probes, which will be useful for longitudinally detecting the status of islet transplantation in Type 1 diabetic patients. For the conclusion and perspectives, we highlight the applications of multimodality and novel imaging methods in islet transplantation.
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31
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Crist RM, Dasa SSK, Liu CH, Clogston JD, Dobrovolskaia MA, Stern ST. Challenges in the development of nanoparticle-based imaging agents: Characterization and biology. WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY 2020; 13:e1665. [PMID: 32830448 DOI: 10.1002/wnan.1665] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/13/2020] [Accepted: 07/14/2020] [Indexed: 12/15/2022]
Abstract
Despite imaging agents being some of the earliest nanomedicines in clinical use, the vast majority of current research and translational activities in the nanomedicine field involves therapeutics, while imaging agents are severely underrepresented. The reasons for this lack of representation are several fold, including difficulties in synthesis and scale-up, biocompatibility issues, lack of suitable tissue/disease selective targeting ligands and receptors, and a high bar for regulatory approval. The recent focus on immunotherapies and personalized medicine, and development of nanoparticle constructs with better tissue distribution and selectivity, provide new opportunities for nanomedicine imaging agent development. This manuscript will provide an overview of trends in imaging nanomedicine characterization and biocompatibility, and new horizons for future development. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.
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Affiliation(s)
- Rachael M Crist
- Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA
| | - Siva Sai Krishna Dasa
- Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA
| | - Christina H Liu
- Nanodelivery Systems and Devices Branch, Cancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, Maryland, USA
| | - Jeffrey D Clogston
- Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA
| | - Marina A Dobrovolskaia
- Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA
| | - Stephan T Stern
- Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA
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32
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Tay ZW, Hensley DW, Chandrasekharan P, Zheng B, Conolly SM. Optimization of Drive Parameters for Resolution, Sensitivity and Safety in Magnetic Particle Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:1724-1734. [PMID: 31796392 PMCID: PMC8034762 DOI: 10.1109/tmi.2019.2957041] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Magnetic Particle Imaging is an emerging tracer imaging modality with zero background signal and zero ionizing radiation, high contrast and high sensitivity with quantitative images. While there is recent work showing that the low amplitude or low frequency drive parameters can improve MPI's spatial resolution by mitigating relaxation losses, the concomitant decrease of the MPI's tracer sensitivity due to the lower drive slew rates was not fully addressed. There has yet to be a wide parameter space, multi-objective optimization of MPI drive parameters for high resolution, high sensitivity and safety. In a large-scale study, we experimentally test 5 different nanoparticles ranging from multi to single-core across 18.5 nm to 32.1 nm core sizes and across an expansive drive parameter range of 0.4 - 416 kHz and 0.5 - 40 mT/ μ0 to assess spatial resolution, SNR, and safety. In addition, we analyze how drive-parameter-dependent shifts in harmonic signal energy away and towards the discarded first harmonic affect effective SNR in this optimization study. The results show that when optimizing for all four factors of resolution, SNR, discarded-harmonic-energy and safety, the overall trends are no longer monotonic and clear optimal points emerge. We present drive parameters different from conventional preclinical MPI showing ~ 2-fold improvement in spatial resolution while remaining within safety limits and addressing sensitivity by minimizing the typical SNR loss involved. Finally, validation of the optimization results with 2D images of phantoms was performed.
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Chandrasekharan P, Tay ZW, Hensley D, Zhou XY, Fung BKL, Colson C, Lu Y, Fellows BD, Huynh Q, Saayujya C, Yu E, Orendorff R, Zheng B, Goodwill P, Rinaldi C, Conolly S. Using magnetic particle imaging systems to localize and guide magnetic hyperthermia treatment: tracers, hardware, and future medical applications. Am J Cancer Res 2020; 10:2965-2981. [PMID: 32194849 PMCID: PMC7053197 DOI: 10.7150/thno.40858] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 01/27/2020] [Indexed: 01/07/2023] Open
Abstract
Magnetic fluid hyperthermia (MFH) treatment makes use of a suspension of superparamagnetic iron oxide nanoparticles, administered systemically or locally, in combination with an externally applied alternating magnetic field, to ablate target tissue by generating heat through a process called induction. The heat generated above the mammalian euthermic temperature of 37°C induces apoptotic cell death and/or enhances the susceptibility of the target tissue to other therapies such as radiation and chemotherapy. While most hyperthermia techniques currently in development are targeted towards cancer treatment, hyperthermia is also used to treat restenosis, to remove plaques, to ablate nerves and to alleviate pain by increasing regional blood flow. While RF hyperthermia can be directed invasively towards the site of treatment, non-invasive localization of heat through induction is challenging. In this review, we discuss recent progress in the field of RF magnetic fluid hyperthermia and introduce a new diagnostic imaging modality called magnetic particle imaging that allows for a focused theranostic approach encompassing treatment planning, treatment monitoring and spatially localized inductive heating.
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Affiliation(s)
- Prashant Chandrasekharan
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States,✉ Corresponding author: E-mail: ; Phone: +1 (510) 642 3420
| | - Zhi Wei Tay
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Daniel Hensley
- Magnetic Insight, Inc., Alameda, CA 94501, United States
| | - Xinyi Y Zhou
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Barry KL Fung
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Caylin Colson
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Yao Lu
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Benjamin D Fellows
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | - Quincy Huynh
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, United States
| | - Chinmoy Saayujya
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, United States
| | - Elaine Yu
- Magnetic Insight, Inc., Alameda, CA 94501, United States
| | - Ryan Orendorff
- Magnetic Insight, Inc., Alameda, CA 94501, United States
| | - Bo Zheng
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States
| | | | - Carlos Rinaldi
- University of Florida, J. Crayton Pruitt Family Department of Biomedical Engineering and Department of Chemical Engineering, FL, 32611 United States
| | - Steven Conolly
- University of California Berkeley, Department of Bioengineering, Berkeley, CA 94720, United States,Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, United States
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Zhao Z, Garraud N, Arnold DP, Rinaldi C. Effects of particle diameter and magnetocrystalline anisotropy on magnetic relaxation and magnetic particle imaging performance of magnetic nanoparticles. ACTA ACUST UNITED AC 2020; 65:025014. [DOI: 10.1088/1361-6560/ab5b83] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
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35
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Zheng L, Wang Y, Yang B, Zhang B, Wu Y. Islet Transplantation Imaging in vivo. Diabetes Metab Syndr Obes 2020; 13:3301-3311. [PMID: 33061492 PMCID: PMC7520574 DOI: 10.2147/dmso.s263253] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 07/29/2020] [Indexed: 12/31/2022] Open
Abstract
Although islet transplantation plays an effective and powerful role in the treatment of diabetes, a large amount of islet grafts are lost at an early stage due to instant blood-mediated inflammatory reactions, immune rejection, and β-cell toxicity resulting from immunosuppressive agents. Timely intervention based on the viability and function of the transplanted islets at an early stage is crucial. Various islet transplantation imaging techniques are available for monitoring the conditions of post-transplanted islets. Due to the development of various imaging modalities and the continuous study of contrast agents, non-invasive islet transplantation imaging in vivo has made great progress. The tracing and functional evaluation of transplanted islets in vivo have thus become possible. However, most studies on contrast agent and imaging modalities are limited to animal experiments, and long-term toxicity and stability need further evaluation. Accordingly, the clinical application of the current achievements still requires a large amount of effort. In this review, we discuss the contrast agents for MRI, SPECT/PET, BLI/FI, US, MPI, PAI, and multimodal imaging. We further summarize the advantages and limitations of various molecular imaging methods.
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Affiliation(s)
- Lei Zheng
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
| | - Yinghao Wang
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
| | - Bin Yang
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
- Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Cancer Institute, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
| | - Bo Zhang
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
- Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Cancer Institute, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
- Correspondence: Bo Zhang; Yulian Wu Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China Tel/Fax +86 571 87783563 Email ;
| | - Yulian Wu
- Department of Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
- Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Cancer Institute, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou310000, People’s Republic of China
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36
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Nucleic acid-based theranostics in type 1 diabetes. Transl Res 2019; 214:50-61. [PMID: 31491371 DOI: 10.1016/j.trsl.2019.08.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/01/2019] [Accepted: 08/17/2019] [Indexed: 12/12/2022]
Abstract
Application of RNAi interference for type 1 diabetes (T1D) therapy bears tremendous potential. This review will discuss vehicles for oligonucleotide delivery, imaging modalities used for delivery monitoring, therapeutic targets, and different theranostic strategies that can be applied for T1D treatment.
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37
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Talebloo N, Gudi M, Robertson N, Wang P. Magnetic Particle Imaging: Current Applications in Biomedical Research. J Magn Reson Imaging 2019; 51:1659-1668. [PMID: 31332868 DOI: 10.1002/jmri.26875] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 07/03/2019] [Accepted: 07/03/2019] [Indexed: 12/12/2022] Open
Abstract
Magnetic particle imaging (MPI) is a new imaging modality with the potential for high-resolution imaging while retaining the noninvasive nature of other current modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET). It is able to track location and quantities of special superparamagnetic iron oxide nanoparticles without tracing any background signal. MPI utilizes the unique, intrinsic aspects of the nanoparticles: how they react in the presence of the magnetic field, and the subsequent turning off of the field. The current group of nanoparticles that are used in MPI are usually commercially available for MRI. Special MPI tracers are in development by many groups that utilize an iron-oxide core encompassed by various coatings. These tracers would solve the current obstacles by altering the size and material of the nanoparticles to what is required by MPI. In this review, the theory behind and the development of these tracers are discussed. In addition, applications such as cell tracking, oncology imaging, neuroimaging, and vascular imaging, among others, stemming from the implementation of MPI into the standard are discussed. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:1659-1668.
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Affiliation(s)
- Nazanin Talebloo
- Precision Health Program, Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.,Department of Chemistry, College of Natural Science, Michigan State University, East Lansing, Michigan, USA
| | - Mithil Gudi
- Precision Health Program, Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.,Lyman Briggs College, Michigan State University, East Lansing, Michigan, USA
| | - Neil Robertson
- Precision Health Program, Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA
| | - Ping Wang
- Precision Health Program, Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA
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38
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Srivastava RK, Jablonska A, Chu C, Gregg L, Bulte JWM, Koehler RC, Walczak P, Janowski M. Biodistribution of Glial Progenitors in a Three Dimensional-Printed Model of the Piglet Cerebral Ventricular System. Stem Cells Dev 2019; 28:515-527. [PMID: 30760110 DOI: 10.1089/scd.2018.0172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
White matter damage persists in hypoxic-ischemic newborns even when treated with hypothermia. We have previously shown that intraventricular delivery of human glial progenitors (GPs) at the neonatal stage is capable of replacing abnormal host glia and rescuing the lifespan of dysmyelinated mice. However, such transplantation in the human brain poses significant challenges as related to high-volume ventricles and long cell migration distances. These challenges can only be studied in large animal model systems. In this study, we developed a three dimensional (3D)-printed model of the ventricular system sized to a newborn pig to investigate the parameters that can maximize a global biodistribution of injected GPs within the ventricular system, while minimizing outflow to the subarachnoid space. Bioluminescent imaging and magnetic resonance imaging were used to image the biodistribution of luciferase-transduced GPs in simple fluid containers and a custom-designed, 3D-printed model of the piglet ventricular system. Seven independent variables were investigated. The results demonstrated that a low volume (0.1 mL) of cell suspension is essential to keep cells within the ventricular system. If higher volumes (1 mL) are needed, a very slow infusion speed (0.01 mL/min) is necessary. Real-time magnetic resonance imaging demonstrated that superparamagnetic iron oxide (SPIO) labeling significantly alters the rheological properties of the GP suspension, such that, even at high speeds and high volumes, the outflow to the subarachnoid space is reduced. Several other factors, including GP species (human vs. mouse), type of catheter tip (end hole vs. side hole), catheter length (0.3 vs. 7.62 m), and cell concentration, had less effect on the overall distribution of GPs. We conclude that the use of a 3D-printed phantom model represents a robust, reproducible, and cost-saving alternative to in vivo large animal studies for determining optimal injection parameters.
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Affiliation(s)
- Rohit K Srivastava
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Anna Jablonska
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Chengyan Chu
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Lydia Gregg
- 3 Visualization Core Laboratory, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jeff W M Bulte
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Raymond C Koehler
- 4 Department of Anesthesiology and Critical Care Medicine, Translational Tissue Engineering Center, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Piotr Walczak
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,5 Department of Neurology and Neurosurgery, University of Warmia and Mazury, Olsztyn, Poland
| | - Miroslaw Janowski
- 1 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,2 Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,6 NeuroRepair Department, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
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39
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Bulte J. Superparamagnetic iron oxides as MPI tracers: A primer and review of early applications. Adv Drug Deliv Rev 2019; 138:293-301. [PMID: 30552918 PMCID: PMC6449195 DOI: 10.1016/j.addr.2018.12.007] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2018] [Revised: 11/12/2018] [Accepted: 12/11/2018] [Indexed: 02/07/2023]
Abstract
Magnetic particle imaging (MPI) has recently emerged as a non-invasive, whole body imaging technique that detects superparamagnetic iron oxide (SPIO) nanoparticles similar as those used in magnetic resonance imaging (MRI). Based on tracer "hot spot" detection instead of providing contrast on MRI scans, MPI has already proven to be truly quantitative. Without the presence of endogenous background signal, MPI can also be used in certain tissues where the endogenous MRI signal is too low to provide contrast. After an introduction to the history and simplified principles of MPI, this review focuses on early MPI applications including MPI cell tracking, multiplexed MPI, perfusion and tumor MPI, lung MPI, functional MPI, and MPI-guided hyperthermia. While it is too early to tell if MPI will become a mainstay imaging technique with the (theoretical) sensitivity that it promises, and if it can successfully compete with SPIO-based 1H MRI and perfluorocarbon-based 19F MRI, it provides unprecedented opportunities for exploring new nanoparticle-based imaging applications.
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Affiliation(s)
- J.W.M. Bulte
- Corresponding author at: Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research; Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, 217 Traylor Bldg, 720 Rutland Ave, Baltimore, MD 21205
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40
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New Strategies and In Vivo Monitoring Methods for Stem Cell-Based Anticancer Therapies. Stem Cells Int 2018; 2018:7315218. [PMID: 30581474 PMCID: PMC6276456 DOI: 10.1155/2018/7315218] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 10/22/2018] [Indexed: 02/06/2023] Open
Abstract
Cancer is a devastating disease and the second cause of death in the developed world. Despite significant advances in recent years, such as the introduction of targeted therapies such as receptor tyrosine kinase inhibitors and immunotherapy, current approaches are insufficient to stop the advance of the disease and many cancer types remain largely intractable. In this review, we describe the latest and most revolutionary stem cell-based approaches for the treatment of cancer. We also summarize the emerging imaging modalities being applied for monitoring anticancer stem cell therapy success and discuss the implications of these novel technologies for precision medicine.
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41
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Zhou XY, Tay ZW, Chandrasekharan P, Yu EY, Hensley DW, Orendorff R, Jeffris KE, Mai D, Zheng B, Goodwill PW, Conolly SM. Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking. Curr Opin Chem Biol 2018; 45:131-138. [PMID: 29754007 PMCID: PMC6500458 DOI: 10.1016/j.cbpa.2018.04.014] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 04/16/2018] [Accepted: 04/20/2018] [Indexed: 01/04/2023]
Abstract
Magnetic particle imaging (MPI) is an emerging ionizing radiation-free biomedical tracer imaging technique that directly images the intense magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI offers ideal image contrast because MPI shows zero signal from background tissues. Moreover, there is zero attenuation of the signal with depth in tissue, allowing for imaging deep inside the body quantitatively at any location. Recent work has demonstrated the potential of MPI for robust, sensitive vascular imaging and cell tracking with high contrast and dose-limited sensitivity comparable to nuclear medicine. To foster future applications in MPI, this new biomedical imaging field is welcoming researchers with expertise in imaging physics, magnetic nanoparticle synthesis and functionalization, nanoscale physics, and small animal imaging applications.
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Affiliation(s)
- Xinyi Y Zhou
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States.
| | - Zhi Wei Tay
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States
| | - Prashant Chandrasekharan
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States
| | - Elaine Y Yu
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States
| | - Daniel W Hensley
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States
| | - Ryan Orendorff
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; UC Berkeley - UCSF Graduate Program in Bioengineering, United States
| | - Kenneth E Jeffris
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States
| | - David Mai
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States
| | - Bo Zheng
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States
| | | | - Steven M Conolly
- Department of Bioengineering, University of California Berkeley, Berkeley, CA 94720, United States; Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA 94720, United States
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42
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Chandrasekharan P, Tay ZW, Zhou XY, Yu E, Orendorff R, Hensley D, Huynh Q, Fung KLB, VanHook CC, Goodwill P, Zheng B, Conolly S. A perspective on a rapid and radiation-free tracer imaging modality, magnetic particle imaging, with promise for clinical translation. Br J Radiol 2018; 91:20180326. [PMID: 29888968 DOI: 10.1259/bjr.20180326] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Magnetic particle imaging (MPI), introduced at the beginning of the twenty-first century, is emerging as a promising diagnostic tool in addition to the current repertoire of medical imaging modalities. Using superparamagnetic iron oxide nanoparticles (SPIOs), that are available for clinical use, MPI produces high contrast and highly sensitive tomographic images with absolute quantitation, no tissue attenuation at-depth, and there are no view limitations. The MPI signal is governed by the Brownian and Néel relaxation behavior of the particles. The relaxation time constants of these particles can be utilized to map information relating to the local microenvironment, such as viscosity and temperature. Proof-of-concept pre-clinical studies have shown favourable applications of MPI for better understanding the pathophysiology associated with vascular defects, tracking cell-based therapies and nanotheranostics. Functional imaging techniques using MPI will be useful for studying the pathology related to viscosity changes such as in vascular plaques and in determining cell viability of superparamagnetic iron oxide nanoparticle labeled cells. In this review article, an overview of MPI is provided with discussions mainly focusing on MPI tracers, applications of translational capabilities ranging from diagnostics to theranostics and finally outline a promising path towards clinical translation.
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Affiliation(s)
| | - Zhi Wei Tay
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA
| | - Xinyi Yedda Zhou
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA
| | - Elaine Yu
- 2 Magnetic Insight Inc , Alameda, CA , USA
| | | | | | - Quincy Huynh
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA
| | - K L Barry Fung
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA
| | | | | | - Bo Zheng
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA
| | - Steven Conolly
- 1 Department of Bioengineering, University of California , Berkeley, CA , USA.,3 Department of Electrical Engineering and Computer Sciences, University of California , Berkeley, CA , USA
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