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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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Shan S, Zhang C, Yin L, Yang X, Yu D, Qi Y, Li M, Wildgruber M, Du Y, Tian J, Ma X. Combination of time domain-system matrix and x-space methods to reconstruct magnetic particle images with isotropic resolution. Phys Med Biol 2024; 69:035004. [PMID: 38168021 DOI: 10.1088/1361-6560/ad19f0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 01/02/2024] [Indexed: 01/05/2024]
Abstract
Objective. Imaging of superparamagnetic iron oxide nanoparticles based on their non-linear response to alternating magnetic fields shows promise for imaging cells and vasculature in healthy and diseased tissue. Such imaging can be achieved through x-space reconstruction typically along a unidirectional Cartesian trajectory, which rapidly convolutes the particle distribution with a 'anisotropic blurring' point spread function (PSF), leading to images with anisotropic resolution.Approach. Here we propose combining the time domine-system matrix and x-space reconstruction methods into a forward model, where the output of the forward model is the PSF-blurred x-space reconstructed image. We then treat the blur as an inverse problem solved by Kaczmarz iteration.Main results. After we have proposed the method optimization, the normal resolution of simulation and device images has been increased from 3.5 mm and 5.25 mm to 1.5 mm and 3.25 mm, which has reached the level in the tangential resolution. Quantitative indicators of image quality such as PSNR and SSIM have also been greatly improved.Significance. Simulation and imaging of real phantoms indicate that our approach provides better isotropic resolution and image quality than the x-space method alone or other methods for removing PSF blur. Using our proposed method to optimize the image quality of x-space reconstructed images using unidirectional Cartesian trajectories, it will promote the clinical application of MPI in the future.
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Affiliation(s)
- Shihao Shan
- School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, People's Republic of China
| | - Chenglong Zhang
- School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, People's Republic of China
| | - Lin Yin
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing 100190, People's Republic of China
| | - Xiaoli Yang
- School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, People's Republic of China
| | - Dexin Yu
- Department of Radiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People's Republic of China
| | - Yafei Qi
- Department of Radiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People's Republic of China
| | - Min Li
- Department of Nuclear Medicine, 960 Hospital of PLA, No. 25, Shifan Road, Jinan, Shandong 250031, People's Republic of China
| | - Moritz Wildgruber
- Department of Radiology, University Hospital, LMU Munich, Munich D-81337, Germany
| | - Yang Du
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing 100190, People's Republic of China
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing 100190, People's Republic of China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing 100191, People's Republic of China
| | - Xiaopeng Ma
- School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, People's Republic of China
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Friedrich RM, Sadeghi M, Faupel F. Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:nano13020347. [PMID: 36678100 PMCID: PMC9865076 DOI: 10.3390/nano13020347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 05/03/2023]
Abstract
Colored imaging of magnetic nanoparticles (MNP) is a promising noninvasive method for medical applications such as therapy and diagnosis. This study investigates the capability of the magnetoelectric sensor and projected gradient descent (PGD) algorithm for colored particle detection. In the first step, the required circumstances for image reconstruction are studied via a simulation approach for different signal-to-noise ratios (SNR). The spatial accuracy of the reconstructed image is evaluated based on the correlation coefficient (CC) factor. The inverse problem is solved using the PGD method, which is adapted according to a nonnegativity constraint in the complex domain. The MNP characterizations are assessed through a magnetic particle spectrometer (MPS) for different types. In the experimental investigation, the real and imaginary parts of the MNP's response are used to detect the spatial distribution and particle type, respectively. The experimental results indicate that the average phase difference for CT100 and ARA100 particles is 14 degrees, which is consistent with the MPS results and could satisfy the system requirements for colored imaging. The experimental evaluation showed that the magnetoelectric sensor and the proposed approach could be potential candidates for color bio-imaging applications.
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Arslan MT, Ozaslan AA, Kurt S, Muslu Y, Saritas EU. Rapid TAURUS for Relaxation-Based Color Magnetic Particle Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:3774-3786. [PMID: 35921341 DOI: 10.1109/tmi.2022.3195694] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Magnetic particle imaging (MPI) is a rapidly developing medical imaging modality that exploits the non-linear response of magnetic nanoparticles (MNPs). Color MPI widens the functionality of MPI, empowering it with the capability to distinguish different MNPs and/or MNP environments. The system function approach for color MPI relies on extensive calibrations that capture the differences in the harmonic responses of the MNPs. An alternative calibration-free x-space-based method called TAURUS estimates a map of the relaxation time constant, τ , by recovering the underlying mirror symmetry in the MPI signal. However, TAURUS requires a back and forth scanning of a given region, restricting its usage to slow trajectories with constant or piecewise constant focus fields (FFs). In this work, we propose a novel technique to increase the performance of TAURUS and enable τ map estimation for rapid and multi-dimensional trajectories. The proposed technique is based on correcting the distortions on mirror symmetry induced by time-varying FFs. We demonstrate via simulations and experiments in our in-house MPI scanner that the proposed method successfully estimates high-fidelity τ maps for rapid trajectories that provide orders of magnitude reduction in scanning time (over 300 fold for simulations and over 8 fold for experiments) while preserving the calibration-free property of TAURUS.
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Yang X, Shao G, Zhang Y, Wang W, Qi Y, Han S, Li H. Applications of Magnetic Particle Imaging in Biomedicine: Advancements and Prospects. Front Physiol 2022; 13:898426. [PMID: 35846005 PMCID: PMC9285659 DOI: 10.3389/fphys.2022.898426] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 05/16/2022] [Indexed: 01/09/2023] Open
Abstract
Magnetic particle imaging (MPI) is a novel emerging noninvasive and radiation-free imaging modality that can quantify superparamagnetic iron oxide nanoparticles tracers. The zero endogenous tissue background signal and short image scanning times ensure high spatial and temporal resolution of MPI. In the context of precision medicine, the advantages of MPI provide a new strategy for the integration of the diagnosis and treatment of diseases. In this review, after a brief explanation of the simplified theory and imaging system, we focus on recent advances in the biomedical application of MPI, including vascular structure and perfusion imaging, cancer imaging, the MPI guidance of magnetic fluid hyperthermia, the visual monitoring of cell and drug treatments, and intraoperative navigation. We finally optimize MPI in terms of the system and tracers, and present future potential biomedical applications of MPI.
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Affiliation(s)
- Xue Yang
- Beijing You’an Hospital, Capital Medical University, Beijing, China
| | | | - Yanyan Zhang
- Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Yu Qi
- Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Shuai Han
- Beijing You’an Hospital, Capital Medical University, Beijing, China
| | - Hongjun Li
- Beijing You’an Hospital, Capital Medical University, Beijing, China,*Correspondence: Hongjun Li,
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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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Utkur M, Saritas EU. Simultaneous temperature and viscosity estimation capability via magnetic nanoparticle relaxation. Med Phys 2022; 49:2590-2601. [PMID: 35103333 DOI: 10.1002/mp.15509] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 01/17/2022] [Accepted: 01/19/2022] [Indexed: 11/05/2022] Open
Abstract
PURPOSE Magnetic particle imaging (MPI) is emerging as a highly promising imaging modality. Magnetic nanoparticles (MNPs) are used as imaging tracers in MPI, and their relaxation behavior provides the foundation for its functional imaging capability. Since MNPs are also utilized in magnetic fluid hyperthermia (MFH) and MPI enables localized MFH, temperature mapping arises as an important application area of MPI. To achieve accurate temperature estimations, however, one must also take into account the confounding effects of viscosity on the MPI signal. In this work, we analyze the effects of temperature and viscosity on MNP relaxation, and determine temperature and viscosity sensitivities of relaxation time constant estimations via TAURUS (TAU estimation via Recovery of Underlying mirror Symmetry) at a wide range of operating points to empower simultaneous mapping of these two parameters. METHODS A total of 15 samples were prepared to reach 4 target viscosity levels (0.9-3.6 mPa·s) at 5 different temperatures (25-45°C). Experiments were performed on a magnetic particle spectrometer (MPS) setup at 60 different operating points at drive field amplitudes ranging between 5-25 mT and frequencies ranging between 1-7 kHz. To enable these extensive experiments, an in-house arbitrary-waveform MPS setup with temperature-controlled heating capability was developed. The operating points were divided into 4 groups with comparable signal levels to maximize signal gain during rapid signal acquisition. The relaxation time constants were estimated via TAURUS, by restoring the underlying mirror symmetry property of the positive and negative half cycles of the time-domain MNP response. The relative time constants with respect to the drive field period, τ̂, were computed to enable quantitative comparison across different operating points. At each operating point, a linear fit was performed to τ̂ as a function of each functional parameter (i.e., temperature or viscosity). The slopes of these linear fits were utilized to compute the temperature and viscosity sensitivities of TAURUS. RESULTS Except for outlier behaviors at 1 kHz, the following global trends were observed: τ̂ decreases with drive field amplitude, increases with drive field frequency, decreases with temperature, and increases with viscosity. The temperature sensitivity varies slowly across the operating points and reaches a maximum value of 1.18%/°C. In contrast, viscosity sensitivity is high at low frequencies around 1 kHz with a maximum value of 13.4%/(mPa·s), but rapidly falls down after 3 kHz. These results suggest that the simultaneous estimation of temperature and viscosity can be achieved by performing measurements at two different drive field settings that provide complementary temperature/viscosity sensitivities. Alternatively, temperature estimation alone can be achieved with a single measurement at drive field frequencies above 3 kHz, where viscosity sensitivity is minimized. CONCLUSIONS This work demonstrates highly promising temperature and viscosity sensitivities for TAURUS, highlighting its potential for simultaneous estimation of these two environmental parameters via MNP relaxation. The findings of this work reveal the potential of a hybrid MPI-MFH system for real-time monitored and localized thermal ablation treatment of cancer. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Mustafa Utkur
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey
| | - Emine Ulku Saritas
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey.,Neuroscience Program, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, 06800, Turkey
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Ludewig P, Graeser M, Forkert ND, Thieben F, Rández-Garbayo J, Rieckhoff J, Lessmann K, Förger F, Szwargulski P, Magnus T, Knopp T. Magnetic particle imaging for assessment of cerebral perfusion and ischemia. WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY 2021; 14:e1757. [PMID: 34617413 DOI: 10.1002/wnan.1757] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 08/30/2021] [Accepted: 09/03/2021] [Indexed: 02/04/2023]
Abstract
Stroke is one of the leading worldwide causes of death and sustained disability. Rapid and accurate assessment of cerebral perfusion is essential to diagnose and successfully treat stroke patients. Magnetic particle imaging (MPI) is a new technology with the potential to overcome some limitations of established imaging modalities. It is an innovative and radiation-free imaging technique with high sensitivity, specificity, and superior temporal resolution. MPI enables imaging and diagnosis of stroke and other neurological pathologies such as hemorrhage, tumors, and inflammatory processes. MPI scanners also offer the potential for targeted therapies of these diseases. Due to lower field requirements, MPI scanners can be designed as resistive magnets and employed as mobile devices for bedside imaging. With these advantages, MPI could accelerate and improve the diagnosis and treatment of neurological disorders. This review provides a basic introduction to MPI, discusses its current use for stroke imaging, and addresses future applications, including the potential for clinical implementation. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.
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Affiliation(s)
- Peter Ludewig
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Graeser
- Section for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany.,Fraunhofer Research Institute for Individualized and Cell-based Medicine, Lübeck, Germany.,Institute for Medical Engineering, University of Lübeck, Lübeck, Germany
| | - Nils D Forkert
- Department of Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Florian Thieben
- Section for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
| | - Javier Rández-Garbayo
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Johanna Rieckhoff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katrin Lessmann
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fynn Förger
- Section for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
| | - Patryk Szwargulski
- Section for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
| | - Tim Magnus
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias Knopp
- Section for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
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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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Kurt S, Muslu Y, Saritas EU. Partial FOV Center Imaging (PCI): A Robust X-Space Image Reconstruction for Magnetic Particle Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3441-3450. [PMID: 32746094 DOI: 10.1109/tmi.2020.2995410] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Magnetic Particle Imaging (MPI) is an emerging medical imaging modality that images the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles using their nonlinear response to applied magnetic fields. In standard x-space approach to MPI, the image is reconstructed by gridding the speed-compensated nanoparticle signal to the instantaneous position of the field free point (FFP). However, due to safety limits on the drive field, the field-of-view (FOV) needs to be covered by multiple relatively small partial field-of-views (pFOVs). The image of the entire FOV is then pieced together from individually processed pFOVs. These processing steps can be sensitive to non-ideal signal conditions such as harmonic interference, noise, and relaxation effects. In this work, we propose a robust x-space reconstruction technique, Partial FOV Center Imaging (PCI), with substantially simplified pFOV processing. PCI first forms a raw image of the entire FOV by mapping MPI signal directly to pFOV center locations. The corresponding MPI image is then obtained by deconvolving this raw image by a compact kernel, whose fully-known shape solely depends on the pFOV size. We analyze the performance of the proposed reconstruction via extensive simulations, as well as imaging experiments on our in-house FFP MPI scanner. The results show that PCI offers a trade-off between noise robustness and interference robustness, outperforming standard x-space reconstruction in terms of both robustness against non-ideal signal conditions and image quality.
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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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12
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Demirel OB, Kilic T, Çukur T, Saritas EU. Anatomical measurements correlate with individual magnetostimulation thresholds for kHz-range homogeneous magnetic fields. Med Phys 2020; 47:1836-1844. [PMID: 31958146 DOI: 10.1002/mp.14032] [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: 09/04/2019] [Revised: 01/06/2020] [Accepted: 01/13/2020] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Magnetostimulation, also known as peripheral nerve stimulation (PNS), is the dominant safety constraint in magnetic resonance imaging (MRI) for the gradient magnetic fields that operate around 0.1-1 kHz, and for the homogeneous drive field in magnetic particle imaging (MPI) that operates around 10-150 kHz. Previous studies did not report correlations between anatomical measures and magnetostimulation thresholds for the gradient magnetic fields in MRI. In contrast, a strong linear correlation was shown between the thresholds and the inverse of body part size in MPI. Yet, the effects of other anatomical measures on the thresholds for the drive field remain unexplored. Here, we investigate the effects of fat percentage on magnetostimulation thresholds for kHz-range homogeneous magnetic fields such as the drive field in MPI, with the ultimate goal of predicting subject-specific thresholds based on simple anatomical measures. METHODS Human subject experiments were performed on the upper arms of 10 healthy male subjects (age: 26 ± 2 yr) to determine magnetostimulation thresholds. Experiments were repeated three times for each subject, with brief resting periods between repetitions. Using a solenoidal magnetostimulation coil, a homogeneous magnetic field at 25 kHz with 100 ms pulse duration was applied at 4-s intervals, while the subject reported stimulation via a mouse click. To determine the thresholds, individual subject responses were fitted to a cumulative distribution function modeled by a sigmoid curve. Next, anatomical images of the upper arms of the subjects were acquired on a 3 T MRI scanner. A two-point Dixon method was used to obtain separate images of water and fat tissues, from which several anatomical measures were derived: the effective outer radius of the upper arm, the effective inner radius (i.e., the muscle radius), and fat percentage. Pearson's correlation coefficient was used to assess the relationship between the threshold and anatomical measures. This statistical analysis was repeated after factoring out the expected effects of body part size. An updated model for threshold prediction is provided, where in addition to scaling in proportion with the inverse of the outer radius, the threshold has an affine dependence on fat percentage. RESULTS A strong linear correlation (r = 0.783, P < 0.008) was found between magnetostimulation threshold and fat percentage, and the correlation became stronger after factoring out the effects of outer radius (r = 0.839, P < 0.003). While considering body part size alone did not explain any significant variance in measured thresholds (P > 0.398), the updated model that also incorporates fat percentage yielded substantially improved threshold predictions with R 2 = 0.654 (P < 0.001). CONCLUSIONS This work shows for the first time that fat percentage strongly correlates with magnetostimulation thresholds for kHz-range homogenous magnetic fields such as the drive field in MPI, and that the correlations get even stronger after factoring out the effects of body part size. These results have important practical implications for predicting subject-specific thresholds, which in turn can increase the performance of the drive field and improve image quality while remaining within the safety limits.
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Affiliation(s)
- Omer Burak Demirel
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey.,Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, 55455, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Toygan Kilic
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey
| | - Tolga Çukur
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey.,Neuroscience Program, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, 06800, Turkey
| | - Emine Ulku Saritas
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, 06800, Turkey.,National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, 06800, Turkey.,Neuroscience Program, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, 06800, Turkey
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Ozaslan AA, Alacaoglu A, Demirel OB, Çukur T, Saritas EU. Fully automated gridding reconstruction for non-Cartesian x-space magnetic particle imaging. Phys Med Biol 2019; 64:165018. [PMID: 31342922 DOI: 10.1088/1361-6560/ab3525] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Magnetic particle imaging (MPI) is a fast emerging biomedical imaging modality that exploits the nonlinear response of superparamagnetic iron oxide (SPIO) nanoparticles to image their spatial distribution. Previously, various scanning trajectories were analyzed for the system function reconstruction (SFR) approach, providing important insight regarding their image quality performances. While Cartesian trajectories remain the most popular choice for x-space-based reconstruction, recent work suggests that non-Cartesian trajectories such as the Lissajous trajectory may prove beneficial for improving image quality. In this work, we propose a generalized reconstruction scheme for x-space MPI that can be used in conjunction with any scanning trajectory. The proposed technique automatically tunes the reconstruction parameters from the scanning trajectory, and does not induce any additional blurring. To demonstrate the proposed technique, we utilize five different trajectories with varying density levels. Comparison to alternative reconstruction methods show significant improvement in image quality achieved by the proposed technique. Among the tested trajectories, the Lissajous and bidirectional Cartesian trajectories prove more favorable for x-space MPI, and the resolution of the images from these two trajectories can further be improved via deblurring. The proposed fully automated gridding reconstruction can be utilized with these trajectories to improve the image quality in x-space MPI.
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Affiliation(s)
- A A Ozaslan
- Department of Electrical and Electronics Engineering, Bilkent University, Ankara, Turkey. National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey
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Tay ZW, Chandrasekharan P, Zhou XY, Yu E, Zheng B, Conolly S. In vivo tracking and quantification of inhaled aerosol using magnetic particle imaging towards inhaled therapeutic monitoring. Theranostics 2018; 8:3676-3687. [PMID: 30026874 PMCID: PMC6037024 DOI: 10.7150/thno.26608] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 05/15/2018] [Indexed: 12/14/2022] Open
Abstract
Pulmonary delivery of therapeutics is attractive due to rapid absorption and non-invasiveness but it is challenging to monitor and quantify the delivered aerosol or powder. Currently, single-photon emission computed tomography (SPECT) is used but requires inhalation of radioactive labels that typically have to be synthesized and attached by hot chemistry techniques just prior to every scan. Methods: In this work, we demonstrate that superparamagnetic iron oxide nanoparticles (SPIONs) can be used to label and track aerosols in vivo with high sensitivity using an emerging medical imaging technique known as magnetic particle imaging (MPI). We perform proof-of-concept experiments with SPIONs for various lung applications such as evaluation of efficiency and uniformity of aerosol delivery, tracking of the initial aerosolized therapeutic deposition in vivo, and finally, sensitive visualization of the entire mucociliary clearance pathway from the lung up to the epiglottis and down the gastrointestinal tract to be excreted. Results: Imaging of SPIONs in the lung has previously been limited by difficulty of lung imaging with magnetic resonance imaging (MRI). In our results, MPI enabled SPION lung imaging with high sensitivity, and a key implication is the potential combination with magnetic actuation or hyperthermia for MPI-guided therapy in the lung with SPIONs. Conclusion: This work shows how magnetic particle imaging can be enabling for new imaging and therapeutic applications of SPIONs in the lung.
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Affiliation(s)
- Zhi Wei Tay
- Department of Bioengineering, University of California, Berkeley, CA 94720, United States
| | | | - Xinyi Yedda Zhou
- Department of Bioengineering, University of California, Berkeley, CA 94720, United States
| | - Elaine Yu
- Magnetic Insight, Inc., Alameda, CA 94501, United States
| | - Bo Zheng
- Department of Bioengineering, University of California, Berkeley, CA 94720, United States
| | - Steven Conolly
- Department of Bioengineering, University of California, Berkeley, CA 94720, United States
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, United States
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