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Pacheco MO, Gerzenshtein IK, Stoppel WL, Rinaldi-Ramos CM. Advances in Vascular Diagnostics using Magnetic Particle Imaging (MPI) for Blood Circulation Assessment. Adv Healthc Mater 2024; 13:e2400612. [PMID: 38879782 PMCID: PMC11442126 DOI: 10.1002/adhm.202400612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 05/11/2024] [Indexed: 06/29/2024]
Abstract
Rapid and accurate assessment of conditions characterized by altered blood flow, cardiac blood pooling, or internal bleeding is crucial for diagnosing and treating various clinical conditions. While widely used imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound offer unique diagnostic advantages, they fall short for specific indications due to limited penetration depth and prolonged acquisition times. Magnetic particle imaging (MPI), an emerging tracer-based technique, holds promise for blood circulation assessments, potentially overcoming existing limitations with reduction in background signals and high temporal and spatial resolution, below the millimeter scale. Successful imaging of blood pooling and impaired flow necessitates tracers with diverse circulation half-lives optimized for MPI signal generation. Recent MPI tracers show potential in imaging cardiovascular complications, vascular perforations, ischemia, and stroke. The impressive temporal resolution and penetration depth also position MPI as an excellent modality for real-time vessel perfusion imaging via functional MPI (fMPI). This review summarizes advancements in optimized MPI tracers for imaging blood circulation and analyzes the current state of pre-clinical applications. This work discusses perspectives on standardization required to transition MPI from a research endeavor to clinical implementation and explore additional clinical indications that may benefit from the unique capabilities of MPI.
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Affiliation(s)
| | | | - Whitney L Stoppel
- Chemical Engineering, University of Florida, Gainesville FL
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville FL
| | - Carlos M Rinaldi-Ramos
- Chemical Engineering, University of Florida, Gainesville FL
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville FL
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2
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Mohn F, Scheffler K, Ackers J, Weimer A, Wegner F, Thieben F, Ahlborg M, Vogel P, Graeser M, Knopp T. Characterization of the clinically approved MRI tracer resotran for magnetic particle imaging in a comparison study. Phys Med Biol 2024; 69:135014. [PMID: 38870999 DOI: 10.1088/1361-6560/ad5828] [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: 02/09/2024] [Accepted: 06/13/2024] [Indexed: 06/15/2024]
Abstract
Objective.The availability of magnetic nanoparticles (MNPs) with medical approval for human intervention is fundamental to the clinical translation of magnetic particle imaging (MPI). In this work, we thoroughly evaluate and compare the magnetic properties of an magnetic resonance imaging (MRI) approved tracer to validate its performance for MPI in future human trials.Approach.We analyze whether the recently approved MRI tracer Resotran is suitable for MPI. In addition, we compare Resotran with the previously approved and extensively studied tracer Resovist, with Ferrotran, which is currently in a clinical phase III study, and with the tailored MPI tracer Perimag.Main results.Initial magnetic particle spectroscopy (MPS) measurements indicate that Resotran exhibits performance characteristics akin to Resovist, but below Perimag. We provide data on four different tracers using dynamic light scattering, transmission electron microscopy, vibrating sample magnetometry measurements, MPS to derive hysteresis, point spread functions, and a serial dilution, as well as system matrix based MPI measurements on a preclinical scanner (Bruker 25/20 FF), including reconstructed images.Significance.Numerous approved MNPs used as tracers in MRI lack the necessary magnetic properties essential for robust signal generation in MPI. The process of obtaining medical approval for dedicated MPI tracers optimized for signal performance is an arduous and costly endeavor, often only justifiable for companies with a well-defined clinical business case. Resotran is an approved tracer that has become available in Europe for MRI. In this work, we study the eligibility of Resotran for MPI in an effort to pave the way for human MPI trials.
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Affiliation(s)
- Fabian Mohn
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Konrad Scheffler
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Justin Ackers
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering, Lübeck, Germany
| | - Agnes Weimer
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering, Lübeck, Germany
- Institute of Physical Chemistry, University of Hamburg, Hamburg, Germany
| | - Franz Wegner
- Institute for Interventional Radiology, University of Lübeck, Lübeck, Germany
| | - Florian Thieben
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mandy Ahlborg
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering, Lübeck, Germany
| | - Patrick Vogel
- Department of Experimental Physics 5 (Biophysics), University of Würzburg, Würzburg, Germany
| | - Matthias Graeser
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering, Lübeck, Germany
- Institute of Medical Engineering, University of Lübeck, Lübeck, Germany
| | - Tobias Knopp
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-based Medical Engineering, Lübeck, Germany
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He J, Li Y, Zhang P, Hui H, Tian J. A fused LASSO operator for fast 3D magnetic particle imaging reconstruction. Phys Med Biol 2024; 69:135002. [PMID: 38815602 DOI: 10.1088/1361-6560/ad524b] [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: 01/23/2024] [Accepted: 05/30/2024] [Indexed: 06/01/2024]
Abstract
Objective.Magnetic particle imaging (MPI) is a promising imaging modality that leverages the nonlinear magnetization behavior of superparamagnetic iron oxide nanoparticles to determine their concentration distribution. Previous optimization models with multiple regularization terms have been proposed to achieve high-quality MPI reconstruction, but these models often result in increased computational burden, particularly for dense gridding 3D fields of view. In order to achieve faster reconstruction speeds without compromising reconstruction quality, we have developed a novel fused LASSO operator, total sum-difference (TSD), which effectively captures the sparse and smooth priors of MPI images.Methods.Through an analysis-synthesis equivalence strategy and a constraint smoothing strategy, the TSD regularized model was solved using the fast iterative soft-thresholding algorithm (FISTA). The resulting reconstruction method, TSD-FISTA, boasts low computational complexity and quadratic convergence rate over iterations.Results.Experimental results demonstrated that TSD-FISTA required only 10% and 37% of the time to achieve comparable or superior reconstruction quality compared to commonly used fused LASSO-based alternating direction method of multipliers and Tikhonov-based algebraic reconstruction techniques, respectively.Significance.TSD-FISTA shows promise for enabling real-time 3D MPI reconstruction at high frame rates for large fields of view.
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Affiliation(s)
- Jie He
- School of Engineering Medicine and School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, People's Republic of China
| | - Yimeng Li
- School of Engineering Medicine and School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, People's Republic of China
| | - Peng Zhang
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, People's Republic of China
| | - Hui Hui
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, People's Republic of China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
- National Key Laboratory of Kidney Diseases, Beijing 100853, People's Republic of China
| | - Jie Tian
- School of Engineering Medicine and School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, People's Republic of China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, People's Republic of China
- National Key Laboratory of Kidney Diseases, Beijing 100853, People's Republic of China
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Shan S, Zhang C, Cheng M, Qi Y, Yu D, Wildgruber M, Ma X. SPFS: SNR peak-based frequency selection method to alleviate resolution degradation in MPI real-time imaging. Phys Med Biol 2024; 69:115028. [PMID: 38593815 DOI: 10.1088/1361-6560/ad3c90] [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: 11/07/2023] [Accepted: 04/09/2024] [Indexed: 04/11/2024]
Abstract
Objective. The primary objective of this study is to address the reconstruction time challenge in magnetic particle imaging (MPI) by introducing a novel approach named SNR-peak-based frequency selection (SPFS). The focus is on improving spatial resolution without compromising reconstruction speed, thereby enhancing the clinical potential of MPI for real-time imaging.Approach. To overcome the trade-off between reconstruction time and spatial resolution in MPI, the researchers propose SPFS as an innovative frequency selection method. Unlike conventional SNR-based selection, SPFS prioritizes frequencies with signal-to-noise ratio (SNR) peaks that capture crucial system matrix information. This adaptability to varying quantities of selected frequencies enhances versatility in the reconstruction process. The study compares the spatial resolution of MPI reconstruction using both SNR-based and SPFS frequency selection methods, utilizing simulated and real device data.Main results.The research findings demonstrate that the SPFS approach substantially improves image resolution in MPI, especially when dealing with a limited number of frequency components. By focusing on SNR peaks associated with critical system matrix information, SPFS mitigates the spatial resolution degradation observed in conventional SNR-based selection methods. The study validates the effectiveness of SPFS through the assessment of MPI reconstruction spatial resolution using both simulated and real device data, highlighting its potential to address a critical limitation in the field.Significance.The introduction of SPFS represents a significant breakthrough in MPI technology. The method not only accelerates reconstruction time but also enhances spatial resolution, thus expanding the clinical potential of MPI for various applications. The improved real-time imaging capabilities of MPI, facilitated by SPFS, hold promise for advancements in drug delivery, plaque assessment, tumor treatment, cerebral perfusion evaluation, immunotherapy guidance, andin vivocell tracking.
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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
| | - Min Cheng
- Xintai hospital of traditional Chinese medicine, Tai'an, Shandong, 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
| | - Dexin Yu
- Department of Radiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People's Republic of China
| | - Moritz Wildgruber
- Department of Radiology, University Hospital, LMU Munich, Munich D-81337, Germany
| | - Xiaopeng Ma
- School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, People's Republic of China
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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: 6] [Impact Index Per Article: 6.0] [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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Nigam S, Gjelaj E, Wang R, Wei GW, Wang P. Machine Learning and Deep Learning Applications in Magnetic Particle Imaging. J Magn Reson Imaging 2024:10.1002/jmri.29294. [PMID: 38358090 PMCID: PMC11324856 DOI: 10.1002/jmri.29294] [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: 11/15/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/16/2024] Open
Abstract
In recent years, magnetic particle imaging (MPI) has emerged as a promising imaging technique depicting high sensitivity and spatial resolution. It originated in the early 2000s where it proposed a new approach to challenge the low spatial resolution achieved by using relaxometry in order to measure the magnetic fields. MPI presents 2D and 3D images with high temporal resolution, non-ionizing radiation, and optimal visual contrast due to its lack of background tissue signal. Traditionally, the images were reconstructed by the conversion of signal from the induced voltage by generating system matrix and X-space based methods. Because image reconstruction and analyses play an integral role in obtaining precise information from MPI signals, newer artificial intelligence-based methods are continuously being researched and developed upon. In this work, we summarize and review the significance and employment of machine learning and deep learning models for applications with MPI and the potential they hold for the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Saumya Nigam
- Precision Health Program, Michigan State University, East Lansing, Michigan 48824, United States
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan 48824, United States
| | - Elvira Gjelaj
- Precision Health Program, Michigan State University, East Lansing, Michigan 48824, United States
- Lyman Briggs College, Michigan State University, East Lansing, Michigan 48824, United States
| | - Rui Wang
- Department of Mathematics, College of Natural Science, Michigan State University, East Lansing, Michigan, 48824, United States
| | - Guo-Wei Wei
- Department of Mathematics, College of Natural Science, Michigan State University, East Lansing, Michigan, 48824, United States
- Department of Electrical and Computer Engineering, College of Engineering, Michigan State University, East Lansing, Michigan, 48824, United States
- Department of Biochemistry and Molecular Biology, College of Natural Science, Michigan State University, East Lansing, Michigan, 48824, United States
| | - Ping Wang
- Precision Health Program, Michigan State University, East Lansing, Michigan 48824, United States
- Department of Radiology, College of Human Medicine, Michigan State University, East Lansing, Michigan 48824, United States
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Lei S, He J, Gao P, Wang Y, Hui H, An Y, Tian J. Magnetic Particle Imaging-Guided Hyperthermia for Precise Treatment of Cancer: Review, Challenges, and Prospects. Mol Imaging Biol 2023; 25:1020-1033. [PMID: 37789103 DOI: 10.1007/s11307-023-01856-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 09/02/2023] [Accepted: 09/05/2023] [Indexed: 10/05/2023]
Abstract
Magnetic particle imaging (MPI) is a novel quantitative imaging technique using the nonlinear magnetization behavior of magnetic nanoparticles (MNPs) to determine their local concentration. Magnetic fluid hyperthermia (MFH) is a promising non-invasive therapy using the heating effects of MNPs. MPI-MFH is expected to enable real-time MPI guidance, localized MFH, and non-invasive temperature monitoring, which shows great potential for precise treatment of cancer. In this review, we introduce the fundamentals of MPI and MFH and their applications in the treatment of cancer. Also, we discuss the challenges and prospects of MPI-MFH.
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Affiliation(s)
- Siao Lei
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, People's Republic of China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
| | - Jie He
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, People's Republic of China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
| | - Pengli Gao
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, People's Republic of China
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
| | - Yueqi Wang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
| | - Hui Hui
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
| | - Yu An
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China.
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, People's Republic of China.
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
| | - Jie Tian
- School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China.
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing, 100191, People's Republic of China.
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
- Zhuhai Precision Medical Center, Zhuhai People's Hospital, Affiliated With Jinan University, Zhuhai, 519000, China.
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Mohn F, Exner M, Szwargulski P, Möddel M, Knopp T, Graeser M. Saline bolus for negative contrast perfusion imaging in magnetic particle imaging. Phys Med Biol 2023; 68:175026. [PMID: 37609892 DOI: 10.1088/1361-6560/ace309] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 06/29/2023] [Indexed: 08/24/2023]
Abstract
Objective.Magnetic particle imaging (MPI) is capable of high temporal resolution measurements of the spatial distribution of magnetic nanoparticles and therefore well suited for perfusion imaging, which is an important tool in medical diagnosis. Perfusion imaging in MPI usually requires a fresh bolus of tracer material to capture the key signal dynamics. Here, we propose a method to decouple the imaging sequence from the injection of additional tracer material, without further increasing the administered iron dose in the body with each image.Approach.A bolus of physiological saline solution without any particles (negative contrast) diminishes the steady-state concentration of a long-circulating tracer during passage. This depression in the measured concentration contributes to the required contrast dynamics. The presence of a long-circulating tracer is therefore a prerequisite to obtain the negative contrast. As a quantitative tracer based imaging method, the signal is linear in the tracer concentration for any location that contains nanoparticles and zero in the surrounding tissue which does not provide any intrinsic signal. After tracer injection, the concentration over time (positive contrast) can be utilized to calculate dynamic diagnostic parameters like perfusion parameters in vessels and organs. Every acquired perfusion image thus requires a new bolus of tracer with a sufficiently large iron dose to be visible above the background.Main results.Perfusion parameters are calculated based on the time response of the proposed negative bolus and compared to a positive bolus. Results from phantom experiments show that normalized signals from positive and negative boli are concurrent and deviations of calculated perfusion maps are low.Significance.Our method opens up the possibility to increase the total monitoring time of a future patient by utilizing a positive-negative contrast sequence, while minimizing the iron dose per acquired image.
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Affiliation(s)
- Fabian Mohn
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Miriam Exner
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
| | - Patryk Szwargulski
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
| | - Martin Möddel
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias Knopp
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Fraunhofer Research Institution for Individualized and Cell-based Medicine, IMTE, Lübeck, Germany
| | - Matthias Graeser
- Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Fraunhofer Research Institution for Individualized and Cell-based Medicine, IMTE, Lübeck, Germany
- Institute for Medical Engineering, University of Lübeck, Lübeck, Germany
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Akhtar N, Mohammed HA, Yusuf M, Al-Subaiyel A, Sulaiman GM, Khan RA. SPIONs Conjugate Supported Anticancer Drug Doxorubicin's Delivery: Current Status, Challenges, and Prospects. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:3686. [PMID: 36296877 PMCID: PMC9611558 DOI: 10.3390/nano12203686] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
Considerable efforts have been directed towards development of nano-structured carriers to overcome the limitations of anticancer drug, doxorubicin's, delivery to various cancer sites. The drug's severe toxicity to cardio and hepatic systems, low therapeutic outcomes, inappropriate dose-demands, metastatic and general resistance, together with non-selectivity of the drug have led to the development of superparamagnetic iron oxide nanoparticles (SPIONs)-based drug delivery modules. Nano-scale polymeric co-encapsulation of the drug, doxorubicin, with SPIONs, the SPIONs surface end-groups' cappings with small molecular entities, as well as structural modifications of the SPIONs' surface-located functional end-groups, to attach the doxorubicin, have been achieved through chemical bonding by conjugation and cross-linking of natural and synthetic polymers, attachments of SPIONs made directly to the non-polymeric entities, and attachments made through mediation of molecular-spacer as well as non-spacer mediated attachments of several types of chemical entities, together with the physico-chemical bondings of the moieties, e.g., peptides, proteins, antibodies, antigens, aptamers, glycoproteins, and enzymes, etc. to the SPIONs which are capable of targeting multiple kinds of cancerous sites, have provided stable and functional SPIONs-based nano-carriers suitable for the systemic, and in vitro deliveries, together with being suitable for other biomedical/biotechnical applications. Together with the SPIONs inherent properties, and ability to respond to magnetic resonance, fluorescence-directed, dual-module, and molecular-level tumor imaging; as well as multi-modular cancer cell targeting; magnetic-field-inducible drug-elution capacity, and the SPIONs' magnetometry-led feasibility to reach cancer action sites have made sensing, imaging, and drug and other payloads deliveries to cancerous sites for cancer treatment a viable option. Innovations in the preparation of SPIONs-based delivery modules, as biocompatible carriers; development of delivery route modalities; approaches to enhancing their drug delivery-cum-bioavailability have explicitly established the SPIONs' versatility for oncological theranostics and imaging. The current review outlines the development of various SPIONs-based nano-carriers for targeted doxorubicin delivery to different cancer sites through multiple methods, modalities, and materials, wherein high-potential nano-structured platforms have been conceptualized, developed, and tested for, both, in vivo and in vitro conditions. The current state of the knowledge in this arena have provided definite dose-control, site-specificity, stability, transport feasibility, and effective onsite drug de-loading, however, with certain limitations, and these shortcomings have opened the field for further advancements by identifying the bottlenecks, suggestive and plausible remediation, as well as more clear directions for future development.
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Affiliation(s)
- Naseem Akhtar
- Department of Pharmaceutics, College of Dentistry & Pharmacy, Buraydah Private Colleges, P.O. Box 31717, Buraydah 51418, Qassim, Saudi Arabia
| | - Hamdoon A. Mohammed
- Department of Medicinal Chemistry & Pharmacognosy, College of Pharmacy, Qassim University, Buraydah 51452, Qassim, Saudi Arabia
| | - Mohammed Yusuf
- Department of Clinical Pharmacy, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Mecca, Saudi Arabia
| | - Amal Al-Subaiyel
- Department of Pharmaceutics, College of Pharmacy, Qassim University, Buraydah 51452, Qassim, Saudi Arabia
| | - Ghassan M. Sulaiman
- Division of Biotechnology, Department of Applied Sciences, University of Technology, Baghdad 10066, Iraq
| | - Riaz A. Khan
- Department of Medicinal Chemistry & Pharmacognosy, College of Pharmacy, Qassim University, Buraydah 51452, Qassim, Saudi Arabia
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Pantke D, Mueller F, Reinartz S, Philipps J, Mohammadali Dadfar S, Peters M, Franke J, Schrank F, Kiessling F, Schulz V. Frequency-selective signal enhancement by a passive dual coil resonator for magnetic particle imaging. Phys Med Biol 2022; 67. [PMID: 35472698 DOI: 10.1088/1361-6560/ac6a9f] [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: 10/18/2021] [Accepted: 04/26/2022] [Indexed: 11/12/2022]
Abstract
Objective.Magnetic particle imaging (MPI) visualizes the spatial distribution of magnetic nanoparticles. MPI already provides excellent temporal and good spatial resolution, however, to achieve translation into clinics, further advances in the fields of sensitivity, image reconstruction and tracer performance are needed. In this work, we propose a novel concept to enhance the MPI signal and image resolution by a purely passive receive coil insert for a preclinical MPI system.Approach.The passive dual coil resonator (pDCR) provides frequency-selective signal enhancement. This is enabled by the adaptable resonance frequency of the pDCR network, which is galvanically isolated from the MPI system and composed of two coaxial solenoids connected via a capacitor. The pDCR aims to enhance frequency components related to high mixing orders, which are crucial to achieve high spatial resolution.Main Results.In this study, system matrix measurements and image acquisitions of a resolution phantom are carried out to evaluate the performance of the pDCR compared to the integrated receive unit of the preclinical MPI and a dedicated rat-sized receive coil. Frequency-selective signal increase and spatial resolution enhancement are demonstrated.Significance.Common dedicated receive coils come along with noise-matched receive networks, which makes them costly and difficult to reproduce. The presented pDCR is a purely passive coil insert that gets along without any additional receive electronics. Therefore, it is cost-efficient, easy-to-handle and adaptable to other MPI scanners and potentially other applications providing the basis for a new breed of passive MPI receiver systems.
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Affiliation(s)
- Dennis Pantke
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Florian Mueller
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Sebastian Reinartz
- Department of Diagnostic and Interventional Radiology, Uniklinik RWTH Aachen, Aachen, Germany
| | - Jonas Philipps
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Seyed Mohammadali Dadfar
- Institute for Experimental Molecular Imaging, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Maximilian Peters
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Jochen Franke
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.,Bruker BioSpin MRI GmbH, Preclinical Imaging Division, Ettlingen, Germany
| | - Franziska Schrank
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Volkmar Schulz
- Department of Physics of Molecular Imaging, Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.,III. Physikalisches Institut B, RWTH Aachen University, Aachen, Germany
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Xu Z, Liu Y, Ma R, Chen J, Qiu J, Du S, Li C, Wu Z, Yang X, Chen Z, Chen T. Thermosensitive Hydrogel Incorporating Prussian Blue Nanoparticles Promotes Diabetic Wound Healing via ROS Scavenging and Mitochondrial Function Restoration. ACS APPLIED MATERIALS & INTERFACES 2022; 14:14059-14071. [PMID: 35298140 DOI: 10.1021/acsami.1c24569] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Diabetic foot ulcer is a serious complication in diabetes patients, imposing a serious physical and economic burden to patients and to the healthcare system as a whole. Oxidative stress is thought to be a key driver of the pathogenesis of such ulcers. However, no antioxidant drugs have received clinical approval to date, underscoring the need for the further development of such medications. Hydrogels can be applied directly to the wound site, wherein they function to prevent infection and maintain local moisture concentrations, in addition to serving as a reservoir for the delivery of a range of therapeutic compounds with the potential to expedite wound healing in a synergistic manner. Herein, we synthesized Prussian blue nanoparticles (PBNPs) capable of efficiently scavenging reactive oxygen species (ROS) owing to their ability to mimic the activity of catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD). In the context of in vitro oxidative stress, these PBNPs were able to protect against cytotoxicity, protect mitochondria from oxidative stress-related damage, and restore nuclear factor erythroid 2-related factor 2 (NRF2)/heme oxygenase-1 (HO-1) pathway activity. To expand on these results in an in vivo context, we prepared a thermosensitive poly (d,l-lactide)-poly(ethylene glycol)-poly(d,l-lactide) (PDLLA-PEG-PDLLA) hydrogel (PLEL)-based wound dressing in which PBNPs had been homogenously incorporated, and we then used this dressing as a platform for controlled PBNP release. The resultant PBNPs@PLEL wound dressing was able to improve diabetic wound healing, decrease ROS production, promote angiogenesis, and reduce pro-inflammatory interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) levels within diabetic wounds. Overall, our results suggest that this PBNPs@PLEL platform holds great promise as a treatment for diabetic foot ulcers.
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Affiliation(s)
- Zhao Xu
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Yujing Liu
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
| | - Rui Ma
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
| | - Jing Chen
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Jinmei Qiu
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
| | - Shuang Du
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
| | - Chengcheng Li
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Zihan Wu
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Xiaofan Yang
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Zhenbing Chen
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Tongkai Chen
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
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