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Qiu Y, Dai K, Zhong S, Chen S, Wang C, Chen H, Frydman L, Zhang Z. Spatiotemporal encoding MRI in a portable low-field system. Magn Reson Med 2024; 92:1011-1021. [PMID: 38623991 DOI: 10.1002/mrm.30104] [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: 12/05/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/17/2024]
Abstract
PURPOSE Demonstrate the potential of spatiotemporal encoding (SPEN) MRI to deliver largely undistorted 2D, 3D, and diffusion weighted images on a 110 mT portable system. METHODS SPEN's quadratic phase modulation was used to subsample the low-bandwidth dimension of echo planar acquisitions, delivering alias-free images with an enhanced immunity to image distortions in a laboratory-built, low-field, portable MRI system lacking multiple receivers. RESULTS Healthy brain images with different SPEN time-bandwidth products and subsampling factors were collected. These compared favorably to EPI acquisitions including topup corrections. Robust 3D and diffusion weighted SPEN images of diagnostic value were demonstrated, with 2.5 mm isotropic resolutions achieved in 3 min scans. This performance took advantage of the low specific absorption rate and relative long TEs associated with low-field MRI. CONCLUSION SPEN MRI provides a robust and advantageous fast acquisition approach to obtain faithful 3D images and DWI data in low-cost, portable, low-field systems without parallel acceleration.
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Affiliation(s)
- Yueqi Qiu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Ke Dai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Sijie Zhong
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Suen Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Changyue Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Hao Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Lucio Frydman
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Zhiyong Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, People's Republic of China
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Li L, He Q, Wei S, Wang H, Wang Z, Wei Z, He H, Xiang C, Yang W. Fast, high-quality, and unshielded 0.2 T low-field mobile MRI using minimal hardware resources. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01184-5. [PMID: 38967865 DOI: 10.1007/s10334-024-01184-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/25/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024]
Abstract
OBJECTIVE To propose a deep learning-based low-field mobile MRI strategy for fast, high-quality, unshielded imaging using minimal hardware resources. METHODS Firstly, we analyze the correlation of EMI signals between the sensing coil and the MRI coil to preliminarily verify the feasibility of active EMI shielding using a single sensing coil. Then, a powerful deep learning EMI elimination model is proposed, which can accurately predict the EMI components in the MRI coil signals using EMI signals from at least one sensing coil. Further, deep learning models with different task objectives (super-resolution and denoising) are strategically stacked for multi-level post-processing to enable fast and high-quality low-field MRI. Finally, extensive phantom and brain experiments were conducted on a home-built 0.2 T mobile brain scanner for the evaluation of the proposed strategy. RESULTS 20 healthy volunteers were recruited to participate in the experiment. The results show that the proposed strategy enables the 0.2 T scanner to generate images with sufficient anatomical information and diagnostic value under unshielded conditions using a single sensing coil. In particular, the EMI elimination outperforms the state-of-the-art deep learning methods and numerical computation methods. In addition, 2 × super-resolution (DDSRNet) and denoising (SwinIR) techniques enable further improvements in imaging speed and quality. DISCUSSION The proposed strategy enables low-field mobile MRI scanners to achieve fast, high-quality imaging under unshielded conditions using minimal hardware resources, which has great significance for the widespread deployment of low-field mobile MRI scanners.
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Affiliation(s)
- Lei Li
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qingyuan He
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Shufeng Wei
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
| | - Huixian Wang
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
| | - Zheng Wang
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
| | - Zhao Wei
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
| | - Hongyan He
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
| | - Ce Xiang
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wenhui Yang
- Institute of Electrical Engineering Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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Zhao Y, Xiao L, Hu J, Wu EX. Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction. Magn Reson Med 2024; 92:112-127. [PMID: 38376455 DOI: 10.1002/mrm.30046] [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: 05/08/2023] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP). METHODS Deep-DSP is proposed to directly predict EMI-free MR signals. During scanning, MRI receive coil and EMI sensing coils simultaneously sample data within two windows (i.e., for MR data and EMI characterization data acquisition, respectively). Afterward, a residual U-Net model is trained using synthetic MRI receive coil data and EMI sensing coil data acquired during EMI signal characterization window, to predict EMI-free MR signals from signals acquired by MRI receive and EMI sensing coils. The trained model is then used to directly predict EMI-free MR signals from data acquired by MRI receive and sensing coils during the MR signal-acquisition window. This strategy was evaluated on an ultralow-field 0.055T brain MRI scanner without any RF shielding and a 1.5T whole-body scanner with incomplete RF shielding. RESULTS Deep-DSP accurately predicted EMI-free MR signals in presence of strong EMI. It outperformed recently developed EDITER and convolutional neural network methods, yielding better EMI elimination and enabling use of few EMI sensing coils. Furthermore, it could work well without dedicated EMI characterization data. CONCLUSION Deep-DSP presents an effective EMI elimination strategy that outperforms existing methods, advancing toward truly portable and patient-friendly MRI. It exploits electromagnetic coupling between MRI receive and EMI sensing coils as well as typical MR signal characteristics. Despite its deep learning nature, Deep-DSP framework is computationally simple and efficient.
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Affiliation(s)
- Yujiao Zhao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, People's Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Linfang Xiao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, People's Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Jiahao Hu
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, People's Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, People's Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, People's Republic of China
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Chinedozi ID, Boskamp E, Darby Z, Kang JK, Rando H, Sair H, Pitt J, Wilcox C, Kim BS, Khanduja S, Whitman G, Cho SM. Point-of-Care Bedside Brain Magnetic Resonance Imaging Is Safe in Extracorporeal Membrane Oxygenation Patients With Swan Ganz Catheters: A Phantom Experiment and Single Center Experience. J Surg Res 2024; 299:290-297. [PMID: 38788465 DOI: 10.1016/j.jss.2024.04.045] [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: 09/12/2023] [Revised: 03/05/2024] [Accepted: 04/22/2024] [Indexed: 05/26/2024]
Abstract
INTRODUCTION More than 1.2 million pulmonary artery catheters (PACs) are used in cardiac patients per annum within the United States. However, it is contraindicated in traditional 1.5 and 3T magnetic resonance imaging (MRI) scans. We aimed to test preclinical and clinical safety of using this imaging modality given the potential utility of needing it in the clinical setting. METHODS We conducted two phantom experiments to ensure that the electromagnetic field power deposition associated with bare and jacketed PACs was safe and within the acceptable limit established by the Food and Drug Administration. The primary end points were the safety and feasibility of performing Point-of-Care (POC) MRI without imaging-related adverse events. We performed a preclinical computational electromagnetic simulation and evaluated these findings in nine patients with PACs on veno-arterial extracorporeal membrane oxygenation. RESULTS The phantom experiments showed that the baseline point specific absorption rate through the head averaged 0.4 W/kg. In both the bare and jacketed catheters, the highest net specific absorption rates were at the neck entry point and tip but were negligible and unlikely to cause any heat-related tissue or catheter damage. In nine patients (median age 66, interquartile range 42-72 y) with veno-arterial extracorporeal membrane oxygenation due to cardiogenic shock and PACs placed for close hemodynamic monitoring, POC MRI was safe and feasible with good diagnostic imaging quality. CONCLUSIONS Adult ECMO patients with PACs can safely undergo point-of-care low-field (64 mT) brain MRI within a reasonable timeframe in an intensive care unit setting to assess for acute brain injury that might otherwise be missed with conventional head computed tomography.
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Affiliation(s)
| | | | - Zachary Darby
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Jin Kook Kang
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Hannah Rando
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Haris Sair
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - John Pitt
- Hyperfine Research, Guilford, Connecticut
| | | | - Bo Soo Kim
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Shivalika Khanduja
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Glenn Whitman
- Division of Cardiac Surgery, Johns Hopkins University, Baltimore, Maryland
| | - Sung-Min Cho
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland.
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Seghier ML, Maalej N. Rescue equipment should include portable medical imaging systems. Sci Bull (Beijing) 2024; 69:1819-1822. [PMID: 38755086 DOI: 10.1016/j.scib.2024.04.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates; Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
| | - Nabil Maalej
- Physics Department, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
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Zong F, Wang L, Liu H, Xue B, Bai R, Liu Y. A genetic optimisation and iterative reconstruction framework for sparse multi-dimensional diffusion-relaxation correlation MRI. Comput Biol Med 2024; 175:108508. [PMID: 38678941 DOI: 10.1016/j.compbiomed.2024.108508] [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: 11/22/2023] [Revised: 04/11/2024] [Accepted: 04/21/2024] [Indexed: 05/01/2024]
Abstract
Multi-dimensional diffusion-relaxation correlation (DRC) magnetic resonance imaging (MRI) techniques have recently been developed to investigate tissue microstructures. Sub-voxel tissue heterogeneity is resolved from the local correlation distributions of relaxation time and molecular diffusivity. However, the implementation of these techniques considerably increases the total acquisition time, and simply reducing the scan time may be at the expense of detailed structural resolution. To overcome these limitations, an optimised framework was proposed for acquiring microstructural maps of the human brain on a clinically feasible timescale. First, the acquisition parameters of the multi-dimensional DRC MRI method were sparsely optimised using a genetic algorithm with a fitness function according to the spectral resolution of the correlation map, hardware requirements, and total scan time. Next, the acquired DRC MRI data were processed using a proposed numerical algorithm based on the dynamic inverse Laplace transform (ILT). Prior knowledge from one-dimensional data was then utilised in the iterative procedure to improve the spectral resolution. Finally, the proposed framework was validated using Monte Carlo simulations and experimental data acquired from healthy participants on an MRI scanner. The results demonstrated that the suggested approach is feasible for offering high-resolution DRC maps that correspond to distinct microstructures with a limited amount of optimised acquisition data from two-dimensional DRC sampling space. By significantly reducing scan time while retaining structural resolution, this approach may enable multi-dimensional DRC MRI to be more widely used for quantitative evaluation in biological and medical settings.
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Affiliation(s)
- Fangrong Zong
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
| | - Lixian Wang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Huabing Liu
- Beijing Limecho Technology Co., Ltd., Beijing, 102200, China
| | - Bing Xue
- School of Engineering and Computer Science, Victoria University of Wellington, Victoria, 6140, New Zealand
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310020, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310030, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Post and Telecommunication, Beijing, 100876, China.
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Zhao Y, Ding Y, Lau V, Man C, Su S, Xiao L, Leong ATL, Wu EX. Whole-body magnetic resonance imaging at 0.05 Tesla. Science 2024; 384:eadm7168. [PMID: 38723062 DOI: 10.1126/science.adm7168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 03/19/2024] [Indexed: 05/31/2024]
Abstract
Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.
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Affiliation(s)
- Yujiao Zhao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Ye Ding
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Vick Lau
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Christopher Man
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Shi Su
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Linfang Xiao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Alex T L Leong
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
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Yang Z, Chan YM, Chan DSH, Wu C, Wang Z, Jiang Y, Liu D, Xia Z, Zhang L, Cai Y, Wong CY. A Biomineralized Bifunctional Patient-Friendly Nanosystem for Sustained Glucose Monitoring and Control in Diabetes. SMALL METHODS 2024:e2400159. [PMID: 38697928 DOI: 10.1002/smtd.202400159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/04/2024] [Indexed: 05/05/2024]
Abstract
Regular blood glucose monitoring and control is necessary for people with type 1 or advanced type 2 diabetes, yet diagnosing and treating patients with diabetes in an accurate, sustained and patient-friendly manner remains limited. Here, a glucose-responsive bifunctional nanosystem (PGOxMns) is constructed via one-pot biomineralisation of manganese dioxide with glucose oxidase and ε-poly-L-lysine. Under hyperglycaemic conditions, the cascade reactions that occur when glucose interacts with PGOxMns can trigger the production of Mn(II), which enhances the magnetic resonance imaging signal. Simultaneously, manganese dioxide catalyses the decomposition of toxic hydrogen peroxide into oxygen, which also maintains glucose oxidase (GOx) activity. In an in vivo model of diabetes, PGOxMns is used to monitor glucose levels (0-20 mm) and allowed identification of diabetic mice via T1-weighted MRI. Furthermore, PGOxMns is found to have a high insulin-loading capacity (83.6%), likely due to its positive charge. A single subcutaneous injection of insulin-loaded nanosystem (Ins-PGOxMns) into diabetic mice resulted in a rapid and efficient response to a glucose challenge and prolonged blood glucose level control (< 200 mg dL-1) for up to 50 h. Overall, this proof-of-concept study demonstrates the feasibility of using biomineralised nanosystems to develop patient-friendly strategies for glucose monitoring and control.
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Affiliation(s)
- Zhe Yang
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Yuen-Man Chan
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Daniel Shiu-Hin Chan
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Chengnan Wu
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Zimeng Wang
- Department of Mathematics and Information Technology, Education University of Hong Kong, Tai Po, New Territories, Hong Kong SAR, 999077, China
| | - Yuxin Jiang
- Department of Anesthesiology, Affiliated Hospital of Guangdong Medical University, Guangdong, 524023, China
| | - Danyong Liu
- Department of Anesthesiology, Affiliated Hospital of Guangdong Medical University, Guangdong, 524023, China
| | - Zhengyuan Xia
- Department of Anesthesiology, Affiliated Hospital of Guangdong Medical University, Guangdong, 524023, China
- Department of Anesthesiology, The First Affiliated Hospital of Jinan University, Guangdong, 510632, China
| | - Li Zhang
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
| | - Yin Cai
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, 999077, China
| | - Chun-Yuen Wong
- Department of Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong SAR, 999077, China
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Chaban YV, Vosshenrich J, McKee H, Gunasekaran S, Brown MJ, Atalay MK, Heye T, Markl M, Woolen SA, Simonetti OP, Hanneman K. Environmental Sustainability and MRI: Challenges, Opportunities, and a Call for Action. J Magn Reson Imaging 2024; 59:1149-1167. [PMID: 37694980 DOI: 10.1002/jmri.28994] [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: 07/14/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/12/2023] Open
Abstract
The environmental impact of magnetic resonance imaging (MRI) has recently come into focus. This includes its enormous demand for electricity compared to other imaging modalities and contamination of water bodies with anthropogenic gadolinium related to contrast administration. Given the pressing threat of climate change, addressing these challenges to improve the environmental sustainability of MRI is imperative. The purpose of this review is to discuss the challenges, opportunities, and the need for action to reduce the environmental impact of MRI and prepare for the effects of climate change. The approaches outlined are categorized as strategies to reduce greenhouse gas (GHG) emissions from MRI during production and use phases, approaches to reduce the environmental impact of MRI including the preservation of finite resources, and development of adaption plans to prepare for the impact of climate change. Co-benefits of these strategies are emphasized including lower GHG emission and reduced cost along with improved heath and patient satisfaction. Although MRI is energy-intensive, there are many steps that can be taken now to improve the environmental sustainability of MRI and prepare for the effects of climate change. On-going research, technical development, and collaboration with industry partners are needed to achieve further reductions in MRI-related GHG emissions and to decrease the reliance on finite resources. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Yuri V Chaban
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jan Vosshenrich
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Hayley McKee
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Suvai Gunasekaran
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Maura J Brown
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael K Atalay
- Department of Diagnostic Imaging, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Tobias Heye
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
| | - Sean A Woolen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | | | - Kate Hanneman
- Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada
- Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
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10
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de Vos B, Remis RF, Webb AG. Characterization of concomitant gradient fields and their effects on image distortions using a low-field point-of-care Halbach-based MRI system. Magn Reson Med 2024; 91:828-841. [PMID: 37749850 DOI: 10.1002/mrm.29879] [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: 05/15/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 09/27/2023]
Abstract
PURPOSE Concomitant gradient fields have been extensively studied at clinical field strengths. However, their effects have not yet been modeled for low-field point-of-care (POC) systems. The purpose of this work is to characterize the effects associated with concomitant fields for POC Halbach-array-based systems. METHODS The concomitant fields associated with a cylindrical gradient coils designed for a transverseB 0 $$ {B}_0 $$ and a signal model including the tilting effect of the effective magnetic field are derived. The formalism is used to simulate and predict concomitant field related distortions. A 46-mT Halbach-array-based system with a maximum gradient strength of 15 mT/m is used to verify the model using two-dimensional spin-echo sequences. RESULTS The simulations and experimental results are in good agreement with the derived equations. The fundamental characteristics of the concomitant field equations are different to conventional MRI systems: Image distortions occur primarily in the transverse directions and a cross-term only exists when applying transverse gradient pulses simultaneously. CONCLUSION The level of image warping in the frequency encoding direction is insignificant for the POC systems discussed here. However, when trying to achieve short echo-times by using strong phase encoding and readout-dephasing gradients, the combination can result in image warping and blurring which should be accounted for in image interpretation.
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Affiliation(s)
- Bart de Vos
- Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands
| | - Rob F Remis
- Micro-electronics, Signal Processing Systems, Delft University of Technology, Delft, The Netherlands
| | - Andrew G Webb
- Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands
- Micro-electronics, Terahertz Sensing, Delft University of Technology, Delft, The Netherlands
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11
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Pitarch C, Ungan G, Julià-Sapé M, Vellido A. Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology. Cancers (Basel) 2024; 16:300. [PMID: 38254790 PMCID: PMC10814384 DOI: 10.3390/cancers16020300] [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: 11/09/2023] [Revised: 12/28/2023] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. This paper reviews in detail some of the most recent advances in the use of Deep Learning in this field, from the broader topic of the development of Machine-Learning-based analytical pipelines to specific instantiations of the use of Deep Learning in neuro-oncology; the latter including its use in the groundbreaking field of ultra-low field magnetic resonance imaging.
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Affiliation(s)
- Carla Pitarch
- Department of Computer Science, Universitat Politècnica de Catalunya (UPC BarcelonaTech) and Intelligent Data Science and Artificial Intelligence (IDEAI-UPC) Research Center, 08034 Barcelona, Spain;
- Eurecat, Digital Health Unit, Technology Centre of Catalonia, 08005 Barcelona, Spain
| | - Gulnur Ungan
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain; (G.U.); (M.J.-S.)
- Centro de Investigación Biomédica en Red (CIBER), 28029 Madrid, Spain
| | - Margarida Julià-Sapé
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain; (G.U.); (M.J.-S.)
- Centro de Investigación Biomédica en Red (CIBER), 28029 Madrid, Spain
| | - Alfredo Vellido
- Department of Computer Science, Universitat Politècnica de Catalunya (UPC BarcelonaTech) and Intelligent Data Science and Artificial Intelligence (IDEAI-UPC) Research Center, 08034 Barcelona, Spain;
- Centro de Investigación Biomédica en Red (CIBER), 28029 Madrid, Spain
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12
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Islam KT, Zhong S, Zakavi P, Chen Z, Kavnoudias H, Farquharson S, Durbridge G, Barth M, McMahon KL, Parizel PM, Dwyer A, Egan GF, Law M, Chen Z. Improving portable low-field MRI image quality through image-to-image translation using paired low- and high-field images. Sci Rep 2023; 13:21183. [PMID: 38040835 PMCID: PMC10692211 DOI: 10.1038/s41598-023-48438-1] [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: 08/22/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023] Open
Abstract
Low-field portable magnetic resonance imaging (MRI) scanners are more accessible, cost-effective, sustainable with lower carbon emissions than superconducting high-field MRI scanners. However, the images produced have relatively poor image quality, lower signal-to-noise ratio, and limited spatial resolution. This study develops and investigates an image-to-image translation deep learning model, LoHiResGAN, to enhance the quality of low-field (64mT) MRI scans and generate synthetic high-field (3T) MRI scans. We employed a paired dataset comprising T1- and T2-weighted MRI sequences from the 64mT and 3T and compared the performance of the LoHiResGAN model with other state-of-the-art models, including GANs, CycleGAN, U-Net, and cGAN. Our proposed method demonstrates superior performance in terms of image quality metrics, such as normalized root-mean-squared error, structural similarity index measure, peak signal-to-noise ratio, and perception-based image quality evaluator. Additionally, we evaluated the accuracy of brain morphometry measurements for 33 brain regions across the original 3T, 64mT, and synthetic 3T images. The results indicate that the synthetic 3T images created using our proposed LoHiResGAN model significantly improve the image quality of low-field MRI data compared to other methods (GANs, CycleGAN, U-Net, cGAN) and provide more consistent brain morphometry measurements across various brain regions in reference to 3T. Synthetic images generated by our method demonstrated high quality both quantitatively and qualitatively. However, additional research, involving diverse datasets and clinical validation, is necessary to fully understand its applicability for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.
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Affiliation(s)
- Kh Tohidul Islam
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
| | - Shenjun Zhong
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Australian National Imaging Facility, Brisbane, QLD, Australia
| | - Parisa Zakavi
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | - Zhifeng Chen
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia
| | - Helen Kavnoudias
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Radiology, Alfred Hospital, Melbourne, VIC, Australia
| | | | - Gail Durbridge
- Herston Imaging Research Facility, University of Queensland, Brisbane, QLD, Australia
| | - Markus Barth
- School of Information Technology and Electrical Engineering and Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Katie L McMahon
- School of Clinical Science, Herston Imaging Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
| | - Paul M Parizel
- David Hartley Chair of Radiology, Department of Radiology, Royal Perth Hospital, Perth, WA, Australia
- Medical School, University of Western Australia, Perth, WA, Australia
| | - Andrew Dwyer
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Radiology, Alfred Hospital, Melbourne, VIC, Australia
| | - Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia
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13
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Qi Z, Bopp MHA, Nimsky C, Chen X, Xu X, Wang Q, Gan Z, Zhang S, Wang J, Jin H, Zhang J. A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note. Bioengineering (Basel) 2023; 10:1290. [PMID: 38002414 PMCID: PMC10669875 DOI: 10.3390/bioengineering10111290] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 11/01/2023] [Indexed: 11/26/2023] Open
Abstract
Mixed Reality Navigation (MRN) is pivotal in augmented reality-assisted intelligent neurosurgical interventions. However, existing MRN registration methods face challenges in concurrently achieving low user dependency, high accuracy, and clinical applicability. This study proposes and evaluates a novel registration method based on a laser crosshair simulator, evaluating its feasibility and accuracy. A novel registration method employing a laser crosshair simulator was introduced, designed to replicate the scanner frame's position on the patient. The system autonomously calculates the transformation, mapping coordinates from the tracking space to the reference image space. A mathematical model and workflow for registration were designed, and a Universal Windows Platform (UWP) application was developed on HoloLens-2. Finally, a head phantom was used to measure the system's target registration error (TRE). The proposed method was successfully implemented, obviating the need for user interactions with virtual objects during the registration process. Regarding accuracy, the average deviation was 3.7 ± 1.7 mm. This method shows encouraging results in efficiency and intuitiveness and marks a valuable advancement in low-cost, easy-to-use MRN systems. The potential for enhancing accuracy and adaptability in intervention procedures positions this approach as promising for improving surgical outcomes.
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Affiliation(s)
- Ziyu Qi
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany;
| | - Miriam H. A. Bopp
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany;
- Center for Mind, Brain and Behavior (CMBB), 35043 Marburg, Germany
| | - Christopher Nimsky
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany;
- Center for Mind, Brain and Behavior (CMBB), 35043 Marburg, Germany
| | - Xiaolei Chen
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
| | - Xinghua Xu
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
| | - Qun Wang
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
| | - Zhichao Gan
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
- Medical School of Chinese PLA, Beijing 100853, China
| | - Shiyu Zhang
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
- Medical School of Chinese PLA, Beijing 100853, China
| | - Jingyue Wang
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
- Medical School of Chinese PLA, Beijing 100853, China
| | - Haitao Jin
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
- Medical School of Chinese PLA, Beijing 100853, China
- NCO School, Army Medical University, Shijiazhuang 050081, China
| | - Jiashu Zhang
- Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China; (X.C.); (X.X.); (Q.W.); (Z.G.); (S.Z.); (J.W.); (H.J.)
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14
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Fan Q, Xiong W, Zhou H, Yang J, Feng J, Li Z, Wu L, Hu F, Duan X, Li B, Fan J, Xu Y, Chen X, Shen Z. An AND Logic Gate for Magnetic-Resonance-Imaging-Guided Ferroptosis Therapy of Tumors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2305932. [PMID: 37717205 DOI: 10.1002/adma.202305932] [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: 06/19/2023] [Revised: 09/14/2023] [Indexed: 09/18/2023]
Abstract
To improve the magnetic resonance imaging (MRI) efficiency and ferroptosis therapy efficacy of exceedingly small magnetic iron oxide nanoparticles (IO, <5 nm) for tumors via enhancing the sensitivity of tumor microenvironment (TME) responsiveness, inspired by molecular logic gates, a self-assembled IO with an AND logic gate function is designed and constructed. Typically, cystamine (CA) is conjugated onto the end of poly(2-methylthio-ethanol methacrylate) (PMEMA) to generate PMEMA-CA. The PMEMA-CA is grafted onto the surface of brequinar (BQR)-loaded IO to form IO-BQR@PMEMA. The self-assembled IO-BQR@PMEMA (SA-IO-BQR@PMEMA) is obtained due to the hydrophobicity of PMEMA. The carbon-sulfur single bond of PMEMA-CA can be oxidized by reactive oxygen species (ROS) in the TME to a thio-oxygen double bond, resulting in the conversion from being hydrophobic to hydrophilic. The disulfide bond of PMEMA-CA can be broken by the glutathione (GSH) in the TME, leading to the shedding of PMEMA from the IO surface. Under the dual actions of ROS and GSH in TME (i.e., AND logic gate), SA-IO-BQR@PMEMA can be disassembled to release IO, Fe2+/3+ , and BQR. In vitro and in vivo results demonstrate the AND logic gate function and mechanism, the high T1 MRI performance and exceptional ferroptosis therapy efficacy for tumors, and the excellent biosafety of SA-IO-BQR@PMEMA.
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Affiliation(s)
- Qingdeng Fan
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Wei Xiong
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Huimin Zhou
- Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Jing Yang
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Jie Feng
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Zongheng Li
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Lihe Wu
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Fang Hu
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Xiaopin Duan
- Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Bo Li
- Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Junbing Fan
- Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Yikai Xu
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
| | - Xiaoyuan Chen
- Departments of Diagnostic Radiology Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Clinical Imaging Research Centre, Nanomedicine Translational Research Program, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, 119228, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, 138673, Singapore
| | - Zheyu Shen
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai South Road, Baiyun, Guangzhou, Guangdong, 510515, China
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15
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Mazurek MH, Parasuram NR, Peng TJ, Beekman R, Yadlapalli V, Sorby-Adams AJ, Lalwani D, Zabinska J, Gilmore EJ, Petersen NH, Falcone GJ, Sujijantarat N, Matouk C, Payabvash S, Sze G, Schiff SJ, Iglesias JE, Rosen MS, de Havenon A, Kimberly WT, Sheth KN. Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke. Stroke 2023; 54:2832-2841. [PMID: 37795593 PMCID: PMC11103256 DOI: 10.1161/strokeaha.123.043146] [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: 03/20/2023] [Accepted: 09/13/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND Neuroimaging is essential for detecting spontaneous, nontraumatic intracerebral hemorrhage (ICH). Recent data suggest ICH can be characterized using low-field magnetic resonance imaging (MRI). Our primary objective was to investigate the sensitivity and specificity of ICH on a 0.064T portable MRI (pMRI) scanner using a methodology that provided clinical information to inform rater interpretations. As a secondary aim, we investigated whether the incorporation of a deep learning (DL) reconstruction algorithm affected ICH detection. METHODS The pMRI device was deployed at Yale New Haven Hospital to examine patients presenting with stroke symptoms from October 26, 2020 to February 21, 2022. Three raters independently evaluated pMRI examinations. Raters were provided the images alongside the patient's clinical information to simulate real-world context of use. Ground truth was the closest conventional computed tomography or 1.5/3T MRI. Sensitivity and specificity results were grouped by DL and non-DL software to investigate the effects of software advances. RESULTS A total of 189 exams (38 ICH, 89 acute ischemic stroke, 8 subarachnoid hemorrhage, 3 primary intraventricular hemorrhage, 51 no intracranial abnormality) were evaluated. Exams were correctly classified as positive or negative for ICH in 185 of 189 cases (97.9% overall accuracy). ICH was correctly detected in 35 of 38 cases (92.1% sensitivity). Ischemic stroke and no intracranial abnormality cases were correctly identified as blood-negative in 139 of 140 cases (99.3% specificity). Non-DL scans had a sensitivity and specificity for ICH of 77.8% and 97.1%, respectively. DL scans had a sensitivity and specificity for ICH of 96.6% and 99.3%, respectively. CONCLUSIONS These results demonstrate improvements in ICH detection accuracy on pMRI that may be attributed to the integration of clinical information in rater review and the incorporation of a DL-based algorithm. The use of pMRI holds promise in providing diagnostic neuroimaging for patients with ICH.
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Affiliation(s)
- Mercy H. Mazurek
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | | | - Teng J. Peng
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | | | - Annabel J. Sorby-Adams
- Department of Neurology, Division of Neurocritical Care, Massachusetts General Hospital, Boston, MA, USA
| | - Dheeraj Lalwani
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Julia Zabinska
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Emily J. Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Nils H. Petersen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Guido J. Falcone
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | | | - Charles Matouk
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Sam Payabvash
- Department of Radiology, Yale University School of Medicine, New Haven, CT, USA
| | - Gordon Sze
- Department of Radiology, Yale University School of Medicine, New Haven, CT, USA
| | - Steven J. Schiff
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Yale Center for Brain & Mind Heath, Yale School of Medicine, New Haven, CT, USA
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew S. Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Adam de Havenon
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - W. Taylor Kimberly
- Department of Neurology, Division of Neurocritical Care, Massachusetts General Hospital, Boston, MA, USA
| | - Kevin N. Sheth
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
- Yale Center for Brain & Mind Heath, Yale School of Medicine, New Haven, CT, USA
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16
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Guo X, Dye J. Modern Prehospital Screening Technology for Emergent Neurovascular Disorders. Adv Biol (Weinh) 2023; 7:e2300174. [PMID: 37357150 DOI: 10.1002/adbi.202300174] [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: 05/05/2023] [Revised: 05/14/2023] [Indexed: 06/27/2023]
Abstract
Stroke is a serious neurological disease and a significant contributor to disability worldwide. Traditional in-hospital imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) remain the standard modalities for diagnosing stroke. The development of prehospital stroke detection devices may facilitate earlier diagnosis, initiation of stroke care, and ultimately better patient outcomes. In this review, the authors summarize the features of eight stroke detection devices using noninvasive brain scanning technology. The review summarizes the features of stroke detection devices including portable CT, MRI, transcranial Doppler ultrasound , microwave tomographic imaging, electroencephalography, near-infrared spectroscopy, volumetric impedance phaseshift spectroscopy, and cranial accelerometry. The technologies utilized, the indications for application, the environments indicated for application, the physical features of the eight stroke detection devices, and current commercial products are discussed. As technology advances, multiple portable stroke detection instruments exhibit the promising potential to expedite the diagnosis of stroke and enhance the time taken for treatment, ultimately aiding in prehospital stroke triage.
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Affiliation(s)
- Xiaofan Guo
- Department of Neurology, Loma Linda University, Loma Linda, CA, 92354, USA
| | - Justin Dye
- Department of Neurosurgery, Loma Linda University, Loma Linda, CA, 92354, USA
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17
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Campbell-Washburn AE, Keenan KE, Hu P, Mugler JP, Nayak KS, Webb AG, Obungoloch J, Sheth KN, Hennig J, Rosen MS, Salameh N, Sodickson DK, Stein JM, Marques JP, Simonetti OP. Low-field MRI: A report on the 2022 ISMRM workshop. Magn Reson Med 2023; 90:1682-1694. [PMID: 37345725 PMCID: PMC10683532 DOI: 10.1002/mrm.29743] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 04/21/2023] [Accepted: 05/17/2023] [Indexed: 06/23/2023]
Abstract
In March 2022, the first ISMRM Workshop on Low-Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low-field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low-field MRI within traditional radiology practices, other point-of-care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low-field portable systems that are purpose-built for clinical decision-making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value.
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Affiliation(s)
- Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Kathryn E Keenan
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Peng Hu
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - John P Mugler
- Department of Radiology & Medical Imaging, Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Andrew G Webb
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | | | - Kevin N Sheth
- Division of Neurocritical Care and Emergency Neurology, Departments of Neurology and Neurosurgery, and the Yale Center for Brain and Mind Health, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jürgen Hennig
- Dept.of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthew S Rosen
- Massachusetts General Hospital, A. A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, USA
- Department of Physics, Harvard University, Cambridge, Massachusetts, USA
| | - Najat Salameh
- Center for Adaptable MRI Technology (AMT Center), Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Daniel K Sodickson
- Department of Radiology, NYU Langone Health, New York, New York, USA
- Center for Advanced Imaging Innovation and Research, NYU Langone Health, New York, New York, USA
| | - Joel M Stein
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Orlando P Simonetti
- Division of Cardiovascular Medicine, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA
- Department of Radiology, The Ohio State University, Columbus, Ohio, USA
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18
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Shoghli A, Chow D, Kuoy E, Yaghmai V. Current role of portable MRI in diagnosis of acute neurological conditions. Front Neurol 2023; 14:1255858. [PMID: 37840918 PMCID: PMC10576557 DOI: 10.3389/fneur.2023.1255858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 09/06/2023] [Indexed: 10/17/2023] Open
Abstract
Neuroimaging is an inevitable component of the assessment of neurological emergencies. Magnetic resonance imaging (MRI) is the preferred imaging modality for detecting neurological pathologies and provides higher sensitivity than other modalities. However, difficulties such as intra-hospital transport, long exam times, and availability in strict access-controlled suites limit its utility in emergency departments and intensive care units (ICUs). The evolution of novel imaging technologies over the past decades has led to the development of portable MRI (pMRI) machines that can be deployed at point-of-care. This article reviews pMRI technologies and their clinical implications in acute neurological conditions. Benefits of pMRI include timely and accurate detection of major acute neurological pathologies such as stroke and intracranial hemorrhage. Additionally, pMRI can be potentially used to monitor the progression of neurological complications by facilitating serial measurements at the bedside.
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Affiliation(s)
| | | | | | - Vahid Yaghmai
- Department of Radiological Sciences, School of Medicine, University of California, Irvine, Irvine, CA, United States
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19
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Man C, Lau V, Su S, Zhao Y, Xiao L, Ding Y, Leung GK, Leong AT, Wu EX. Deep learning enabled fast 3D brain MRI at 0.055 tesla. SCIENCE ADVANCES 2023; 9:eadi9327. [PMID: 37738341 PMCID: PMC10516503 DOI: 10.1126/sciadv.adi9327] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 08/21/2023] [Indexed: 09/24/2023]
Abstract
In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single average three-dimensional (3D) encoding with 2D partial Fourier sampling, reducing the scan time of T1- and T2-weighted imaging protocols to 2.5 and 3.2 minutes, respectively. The 3D deep learning leverages the homogeneous brain anatomy available in high-field human brain data to enhance image quality, reduce artifacts and noise, and improve spatial resolution to synthetic 1.5-mm isotropic resolution. Our method successfully overcomes low-signal barrier, reconstructing fine anatomical structures that are reproducible within subjects and consistent across two protocols. It enables fast and quality whole-brain MRI at 0.055 tesla, with potential for widespread biomedical applications.
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Affiliation(s)
- Christopher Man
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Vick Lau
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Shi Su
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Yujiao Zhao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Linfang Xiao
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Ye Ding
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Gilberto K. K. Leung
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Alex T. L. Leong
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Ed X. Wu
- Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
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20
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Shan S, Gao Y, Liu PZY, Whelan B, Sun H, Dong B, Liu F, Waddington DEJ. Distortion-corrected image reconstruction with deep learning on an MRI-Linac. Magn Reson Med 2023; 90:963-977. [PMID: 37125656 PMCID: PMC10860740 DOI: 10.1002/mrm.29684] [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: 09/26/2022] [Revised: 03/29/2023] [Accepted: 04/11/2023] [Indexed: 05/02/2023]
Abstract
PURPOSE MRI is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearities (GNLs) limit anatomical accuracy, potentially compromising the quality of tumor treatments. In addition, slow MR acquisition and reconstruction limit the potential for effective image guidance. Here, we demonstrate a deep learning-based method that rapidly reconstructs distortion-corrected images from raw k-space data for MR-guided radiotherapy applications. METHODS We leverage recent advances in interpretable unrolling networks to develop a Distortion-Corrected Reconstruction Network (DCReconNet) that applies convolutional neural networks (CNNs) to learn effective regularizations and nonuniform fast Fourier transforms for GNL-encoding. DCReconNet was trained on a public MR brain dataset from 11 healthy volunteers for fully sampled and accelerated techniques, including parallel imaging (PI) and compressed sensing (CS). The performance of DCReconNet was tested on phantom, brain, pelvis, and lung images acquired on a 1.0T MRI-Linac. The DCReconNet, CS-, PI-and UNet-based reconstructed image quality was measured by structural similarity (SSIM) and RMS error (RMSE) for numerical comparisons. The computation time and residual distortion for each method were also reported. RESULTS Imaging results demonstrated that DCReconNet better preserves image structures compared to CS- and PI-based reconstruction methods. DCReconNet resulted in the highest SSIM (0.95 median value) and lowest RMSE (<0.04) on simulated brain images with four times acceleration. DCReconNet is over 10-times faster than iterative, regularized reconstruction methods. CONCLUSIONS DCReconNet provides fast and geometrically accurate image reconstruction and has the potential for MRI-guided radiotherapy applications.
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Affiliation(s)
- Shanshan Shan
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNew South WalesAustralia
- State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD‐X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education InstitutionsSoochow UniversitySuzhouJiangsuChina
- Department of Medical PhysicsIngham Institute of Applied Medical ResearchLiverpoolNew South WalesAustralia
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneQueenslandAustralia
| | - Yang Gao
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneQueenslandAustralia
- School of Computer Science and EngineeringCentral South UniversityChangshaHunanChina
| | - Paul Z. Y. Liu
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNew South WalesAustralia
- Department of Medical PhysicsIngham Institute of Applied Medical ResearchLiverpoolNew South WalesAustralia
| | - Brendan Whelan
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNew South WalesAustralia
- Department of Medical PhysicsIngham Institute of Applied Medical ResearchLiverpoolNew South WalesAustralia
| | - Hongfu Sun
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneQueenslandAustralia
| | - Bin Dong
- Department of Medical PhysicsIngham Institute of Applied Medical ResearchLiverpoolNew South WalesAustralia
| | - Feng Liu
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneQueenslandAustralia
| | - David E. J. Waddington
- ACRF Image X Institute, Sydney School of Health Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNew South WalesAustralia
- Department of Medical PhysicsIngham Institute of Applied Medical ResearchLiverpoolNew South WalesAustralia
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21
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Kimberly WT, Sorby-Adams AJ, Webb AG, Wu EX, Beekman R, Bowry R, Schiff SJ, de Havenon A, Shen FX, Sze G, Schaefer P, Iglesias JE, Rosen MS, Sheth KN. Brain imaging with portable low-field MRI. NATURE REVIEWS BIOENGINEERING 2023; 1:617-630. [PMID: 37705717 PMCID: PMC10497072 DOI: 10.1038/s44222-023-00086-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/06/2023] [Indexed: 09/15/2023]
Abstract
The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.
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Affiliation(s)
- W Taylor Kimberly
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Annabel J Sorby-Adams
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew G Webb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
| | - Ritvij Bowry
- Departments of Neurosurgery and Neurology, McGovern Medical School, University of Texas Health Neurosciences, Houston, TX, USA
| | - Steven J Schiff
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Adam de Havenon
- Division of Vascular Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Francis X Shen
- Harvard Medical School Center for Bioethics, Harvard law School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Gordon Sze
- Department of Radiology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Pamela Schaefer
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and AI Laboratory, Massachusetts Institute of Technology, Boston, MA, USA
| | - Matthew S Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin N Sheth
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
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22
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Theilenberg S, Shang Y, Ghazouani J, Kumaragamage C, Nixon TW, McIntyre S, Vaughan JT, Parkinson B, Garwood M, de Graaf RA, Juchem C. Design and realization of a multi-coil array for B 0 field control in a compact 1.5T head-only MRI scanner. Magn Reson Med 2023; 90:1228-1241. [PMID: 37145035 PMCID: PMC10330274 DOI: 10.1002/mrm.29692] [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: 12/17/2022] [Revised: 03/27/2023] [Accepted: 04/14/2023] [Indexed: 05/06/2023]
Abstract
PURPOSE To design and implement a multi-coil (MC) array for B0 field generation for image encoding and simultaneous advanced shimming in a novel 1.5T head-only MRI scanner. METHODS A 31-channel MC array was designed following the unique constraints of this scanner design: The vertically oriented magnet is very short, stopping shortly above the shoulders of a sitting subject, and includes a window for the subject to see through. Key characteristics of the MC hardware, the B0 field generation capabilities, and thermal behavior, were optimized in simulations prior to its construction. The unit was characterized via bench testing. B0 field generation capabilities were validated on a human 4T MR scanner by analysis of experimental B0 fields and by comparing images for several MRI sequences acquired with the MC array to those acquired with the system's linear gradients. RESULTS The MC system was designed to produce a multitude of linear and nonlinear magnetic fields including linear gradients of up to 10 kHz/cm (23.5 mT/m) with MC currents of 5 A per channel. With water cooling it can be driven with a duty cycle of up to 74% and ramp times of 500 μs. MR imaging experiments encoded with the developed multi-coil hardware were largely artifact-free; residual imperfections were predictable, and correctable. CONCLUSION The presented compact multi-coil array is capable of generating image encoding fields with amplitudes and quality comparable to clinical systems at very high duty cycles, while additionally enabling high-order B0 shimming capabilities and the potential for nonlinear encoding fields.
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Affiliation(s)
- Sebastian Theilenberg
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Yun Shang
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Jalal Ghazouani
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Chathura Kumaragamage
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - Terence W. Nixon
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - Scott McIntyre
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - J. Thomas Vaughan
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
- Department of Radiology, Columbia University Medical Center, New York, NY, United States
| | - Ben Parkinson
- Robinson Research Institute, Victoria University of Wellington, Wellington, New Zealand
| | - Mike Garwood
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
- Department of Radiology, Columbia University Medical Center, New York, NY, United States
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Frija G, Salama DH, Kawooya MG, Allen B. A paradigm shift in point-of-care imaging in low-income and middle-income countries. EClinicalMedicine 2023; 62:102114. [PMID: 37560257 PMCID: PMC10406955 DOI: 10.1016/j.eclinm.2023.102114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/03/2023] [Accepted: 07/06/2023] [Indexed: 08/11/2023] Open
Abstract
The concept of primary healthcare is now regarded as crucial for enhancing access to healthcare services in low-income and middle-income countries (LMICs). Technological advancements that have made many medical imaging devices smaller, lighter, portable and more affordable, and infrastructure advancements in power supply, Internet connectivity, and artificial intelligence, are all increasing the feasibility of POCI (point-of care imaging) in LMICs. Although providing imaging services at the same time as the clinic visit represents a paradigm shift in the way imaging care is typically provided in high-income countries where patients are typically directed to dedicated imaging centres, a POCI model is often the only way to provide timely access to imaging care for many patients in LIMCs. To address the growing burden of non-communicable diseases such as cancer and heart disease, bringing advanced imaging tools to the POCI will be necessary. Strategies tailored to the countries' specific needs, including training, safety and quality, will be of the utmost importance.
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Affiliation(s)
- Guy Frija
- Université Paris-Cité, 12 Rue de l’Ecole de Médecine, 75005, Paris, France
| | - Dina H. Salama
- Radiology and Medical Imaging Technology Department, Misr University for Science and Technology, Cairo, Egypt
| | - Michael G. Kawooya
- Department of Radiology, Ernest Cook Ultrasound Research and Education Institute (ECUREI), Kampala, Uganda
| | - Bibb Allen
- Department of Radiology, Grandview Medical Center, Birmingham, AL, USA
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24
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Park D, Bascuñán J, Lee W, Iwasa Y. Conceptual Design of a Portable, Solid-Nitrogen-Cooled 0.5-T/560-mm Point-of-Care MRI Magnet. IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY : A PUBLICATION OF THE IEEE SUPERCONDUCTIVITY COMMITTEE 2023; 33:4400304. [PMID: 37638131 PMCID: PMC10456986 DOI: 10.1109/tasc.2023.3242228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
We describe the conceptual design of a portable, liquid-helium-free, all-REBCO, 0.5-T/560-mm point-of-care magnetic resonance imaging (MRI) magnet. It is free from an external power supply and a refrigeration system during operation. In our portable MRI magnet, we use a detachable "cryocirculator" that circulates, in a closed circuit, cold working fluid, and most importantly for portability, it can be readily coupled to or decoupled from the magnet, in contrast, a conventional cryocooler is mechanically attached to the magnet. Another unique feature of our system is a volume of solid nitrogen (SN2) in the cold chamber that adds enough thermal mass to the magnet in the 30-36-K operating temperature range, enabling it to maintain its field over a period of, for this system, ≥10 hours, plenty enough for this portable MRI system, uncoupled from its cryocirculator, to perform its mission before it needs recooling.
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Affiliation(s)
- Dongkeun Park
- Francis Bitter Magnet Laboratory (FBML)/Plasma Science and Fusion Center (PSFC), Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Juan Bascuñán
- Francis Bitter Magnet Laboratory (FBML)/Plasma Science and Fusion Center (PSFC), Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Wooseung Lee
- FBML/PSFC, MIT, Cambridge, MA 02139, USA.; Gwangju Center, Korea Basic Science Institute, Buk-gu, Gwangju, 611856, South Korea
| | - Yukikazu Iwasa
- Francis Bitter Magnet Laboratory (FBML)/Plasma Science and Fusion Center (PSFC), Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
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25
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Sarty GE. Concept for gradient-free MRI on twin natural slices. MAGMA (NEW YORK, N.Y.) 2023; 36:671-686. [PMID: 36417013 DOI: 10.1007/s10334-022-01047-x] [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: 12/20/2021] [Revised: 10/23/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVE The design of an MRI for use in space requires that the hardware be kept to an absolute minimum in terms of mass, complexity, and power. In addition, NASA requirements are that the external stray field needs to be less than 3.2 Gauss, 7 cm from the MRI enclosure. THEORY RF encoding designs with Halbach magnets offer the best chance of meeting those requirements. Spatially non-uniform magnetic fields with foliations of isomagnetic surfaces, or natural slices, may be used to provide slice selection, and to reduce further the hardware complexity, for TRansmit Array Spatial Encoding (TRASE) Magnetic Resonance Imaging (MRI) or potentially for other radio frequency (RF) encoding methods. The design of such non-uniform magnetic fields in a Halbach configuration with built-in axial gradients leads to pairs of isomagnetic surfaces centered on either side of a central maximum field strength slice. If TRASE images from slices other than the central isomagnetic surface are desired, then the Nuclear Magnetic Resonance (NMR) signals originating from the twin natural slices must be separated during image reconstruction. Here, a design for simultaneously imaging on twin slices in such an inhomogeneous magnetic field using multiple receiver coils with spatially varying RF profiles is described mathematically and numerical simulation examples are given. DESIGN APPROACH To achieve RF encoding on the natural slices, at least three TRASE transmit coils are required. Here a solution with twisted solenoid coils is given. To achieve the twin slice separation at least two receive coils are required. Here a solution with two solenoids is given. DISCUSSION The MRI design presented here uses a combination of RF encoding (TRASE), a spatial encoding magnetic field (SEM, pairs of natural slices) and receive coil spatial profiles to encode enough information into the NMR signal for image slice reconstruction. The design presented here enables using Halbach magnets with a built-in axial gradient to be used for MRI. CONCLUSION The result is a new gradient-free TRASE MRI design capable of imaging pairs of electronically selectable axial slices.
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Affiliation(s)
- Gordon E Sarty
- Division of Biomedical Engineering and the quanTA Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
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26
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Oberdick SD, Jordanova KV, Lundstrom JT, Parigi G, Poorman ME, Zabow G, Keenan KE. Iron oxide nanoparticles as positive T 1 contrast agents for low-field magnetic resonance imaging at 64 mT. Sci Rep 2023; 13:11520. [PMID: 37460669 DOI: 10.1038/s41598-023-38222-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 07/05/2023] [Indexed: 07/20/2023] Open
Abstract
We have investigated the efficacy of superparamagnetic iron oxide nanoparticles (SPIONs) as positive T1 contrast agents for low-field magnetic resonance imaging (MRI) at 64 millitesla (mT). Iron oxide-based agents, such as the FDA-approved ferumoxytol, were measured using a variety of techniques to evaluate T1 contrast at 64 mT. Additionally, we characterized monodispersed carboxylic acid-coated SPIONs with a range of diameters (4.9-15.7 nm) in order to understand size-dependent properties of T1 contrast at low-field. MRI contrast properties were measured using 64 mT MRI, magnetometry, and nuclear magnetic resonance dispersion (NMRD). We also measured MRI contrast at 3 T to provide comparison to a standard clinical field strength. SPIONs have the capacity to perform well as T1 contrast agents at 64 mT, with measured longitudinal relaxivity (r1) values of up to 67 L mmol-1 s-1, more than an order of magnitude higher than corresponding r1 values at 3 T. The particles exhibit size-dependent longitudinal relaxivities and outperform a commercial Gd-based agent (gadobenate dimeglumine) by more than eight-fold at physiological temperatures. Additionally, we characterize the ratio of transverse to longitudinal relaxivity, r2/r1 and find that it is ~ 1 for the SPION based agents at 64 mT, indicating a favorable balance of relaxivities for T1-weighted contrast imaging. We also correlate the magnetic and structural properties of the particles with models of nanoparticle relaxivity to understand generation of T1 contrast. These experiments show that SPIONs, at low fields being targeted for point-of-care low-field MRI systems, have a unique combination of magnetic and structural properties that produce large T1 relaxivities.
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Affiliation(s)
- Samuel D Oberdick
- Department of Physics, University of Colorado, Boulder, CO, 80309, USA.
- National Institute of Standards and Technology, Boulder, CO, 80305, USA.
| | | | - John T Lundstrom
- Department of Physics, University of Colorado, Boulder, CO, 80309, USA
- National Institute of Standards and Technology, Boulder, CO, 80305, USA
| | - Giacomo Parigi
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019, Sesto Fiorentino, Italy
- Department of Chemistry "Ugo Schiff", University of Florence, Via Della Lastruccia 3, 50019, Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Via Luigi Sacconi 6, 50019, Sesto Fiorentino, Italy
| | | | - Gary Zabow
- National Institute of Standards and Technology, Boulder, CO, 80305, USA
| | - Kathryn E Keenan
- National Institute of Standards and Technology, Boulder, CO, 80305, USA
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27
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Abbas A, Hilal K, Rasool AA, Zahidi UF, Shamim MS, Abbas Q. Low-field magnetic resonance imaging in a boy with intracranial bolt after severe traumatic brain injury: illustrative case. JOURNAL OF NEUROSURGERY. CASE LESSONS 2023; 6:CASE23225. [PMID: 37392768 PMCID: PMC10555635 DOI: 10.3171/case23225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 05/24/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND Conventional magnetic resonance imaging (cMRI) is sensitive to motion and ferromagnetic material, leading to suboptimal images and image artifacts. In many patients with neurological injuries, an intracranial bolt (ICB) is placed for monitoring intracranial pressure (ICP). Repeated imaging (computed tomography [CT] or cMRI) is frequently required to guide management. A low-field (0.064-T) portable magnetic resonance imaging (pMRI) machine may provide images in situations that were previously considered contraindications for cMRI. OBSERVATIONS A 10-year-old boy with severe traumatic brain injury was admitted to the pediatric intensive care unit, and an ICB was placed. Initial head CT showed a left-sided intraparenchymal hemorrhage with intraventricular dissection and cerebral edema with mass effect. Repeated imaging was required to assess the brain structure because of continually fluctuating ICP. Transferring the patient to the radiology suite was risky because of his critical condition and the presence of an ICB; hence, pMRI was performed at the bedside. Images obtained were of excellent quality without any ICB artifact, guiding the decision to continue to manage the patient conservatively. The child later improved and was discharged from the hospital. LESSONS pMRI can be used to obtain excellent images at the bedside in patients with an ICB, providing useful information for better management of patients with neurological injuries.
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Selvaganesan K, Wan Y, Ha Y, Wu B, Hancock K, Galiana G, Constable RT. Magnetic resonance imaging using a nonuniform Bo (NuBo) field-cycling magnet. PLoS One 2023; 18:e0287344. [PMID: 37319289 PMCID: PMC10270621 DOI: 10.1371/journal.pone.0287344] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 06/02/2023] [Indexed: 06/17/2023] Open
Abstract
Magnetic resonance imaging (MRI) is a powerful noninvasive diagnostic tool with superior soft tissue contrast. However, access to MRI is limited since current systems depend on homogeneous, high field strength main magnets (B0-fields), with strong switchable gradients which are expensive to install and maintain. In this work we propose a new approach to MRI where imaging is performed in an inhomogeneous field using radiofrequency spatial encoding, thereby eliminating the need for uniform B0-fields and conventional cylindrical gradient coils. The proposed technology uses an innovative data acquisition and reconstruction approach by integrating developments in field cycling, parallel imaging and non-Fourier based algebraic reconstruction. The scanner uses field cycling to image in an inhomogeneous B0-field; in this way magnetization is maximized during the high field polarization phase, and B0 inhomogeneity effects are minimized by using a low field during image acquisition. In addition to presenting the concept, this work provides experimental verification of a long-lived spin echo signal, spatially varying resolution, as well as both simulated and experimental 2D images. Our initial design creates an open MR system that can be installed in a patient examination table for body imaging (e.g., breast or liver) or built into a wall for weighted-spine imaging. The proposed system introduces a new class of inexpensive, open, silent MRIs that could be housed in doctor's offices much like ultrasound is today, making MRI more widely accessible.
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Affiliation(s)
- Kartiga Selvaganesan
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America
| | - Yuqing Wan
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America
| | - Yonghyun Ha
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America
| | - Baosong Wu
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America
| | - Kasey Hancock
- Department of Electrical Engineering, Yale University, New Haven, CT, United States of America
| | - Gigi Galiana
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America
| | - R. Todd Constable
- Department of Biomedical Engineering, Yale University, New Haven, CT, United States of America
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America
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29
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Jordanova KV, Martin MN, Ogier SE, Poorman ME, Keenan KE. In vivo quantitative MRI: T 1 and T 2 measurements of the human brain at 0.064 T. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01095-x. [PMID: 37208553 PMCID: PMC10386946 DOI: 10.1007/s10334-023-01095-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/03/2023] [Accepted: 04/19/2023] [Indexed: 05/21/2023]
Abstract
OBJECTIVE To measure healthy brain [Formula: see text] and [Formula: see text] relaxation times at 0.064 T. MATERIALS AND METHODS [Formula: see text] and [Formula: see text] relaxation times were measured in vivo for 10 healthy volunteers using a 0.064 T magnetic resonance imaging (MRI) system and for 10 test samples on both the MRI and a separate 0.064 T nuclear magnetic resonance (NMR) system. In vivo [Formula: see text] and [Formula: see text] values are reported for white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) for automatic segmentation regions and manual regions of interest (ROIs). RESULTS [Formula: see text] sample measurements on the MRI system were within 10% of the NMR measurement for 9 samples, and one sample was within 11%. Eight [Formula: see text] sample MRI measurements were within 25% of the NMR measurement, and the two longest [Formula: see text] samples had more than 25% variation. Automatic segmentations generally resulted in larger [Formula: see text] and [Formula: see text] estimates than manual ROIs. DISCUSSION [Formula: see text] and [Formula: see text] times for brain tissue were measured at 0.064 T. Test samples demonstrated accuracy in WM and GM ranges of values but underestimated long [Formula: see text] in the CSF range. This work contributes to measuring quantitative MRI properties of the human body at a range of field strengths.
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Affiliation(s)
- Kalina V Jordanova
- Physical Measurement Laboratory, National Institute of Standards and Technology, NIST, Boulder, CO, USA.
| | - Michele N Martin
- Physical Measurement Laboratory, National Institute of Standards and Technology, NIST, Boulder, CO, USA
| | - Stephen E Ogier
- Physical Measurement Laboratory, National Institute of Standards and Technology, NIST, Boulder, CO, USA
- Department of Physics, University of Colorado Boulder, Boulder, CO, USA
| | | | - Kathryn E Keenan
- Physical Measurement Laboratory, National Institute of Standards and Technology, NIST, Boulder, CO, USA
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de Vos B, Remis RF, Webb AG. An integrated target field framework for point-of-care halbach array low-field MRI system design. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01093-z. [PMID: 37208554 PMCID: PMC10386967 DOI: 10.1007/s10334-023-01093-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/18/2023] [Accepted: 04/16/2023] [Indexed: 05/21/2023]
Abstract
OBJECTIVE Low-cost low-field point-of-care MRI systems are used in many different applications. System design has correspondingly different requirements in terms of imaging field-of-view, spatial resolution and magnetic field strength. In this work an iterative framework has been created to design a cylindrical Halbach-based magnet along with integrated gradient and RF coils that most efficiently fulfil a set of user-specified imaging requirements. METHODS For efficient integration, target field methods are used for each of the main hardware components. These have not been used previously in magnet design, and a new mathematical model was derived accordingly. These methods result in a framework which can design an entire low-field MRI system within minutes using standard computing hardware. RESULTS Two distinct point-of-care systems are designed using the described framework, one for neuroimaging and the other for extremity imaging. Input parameters are taken from literature and the resulting systems are discussed in detail. DISCUSSION The framework allows the designer to optimize the different hardware components with respect to the desired imaging parameters taking into account the interdependencies between these components and thus give insight into the influence of the design choices.
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Affiliation(s)
- Bart de Vos
- C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, Netherlands.
| | - Rob F Remis
- Signal Processing Systems, Delft University of Technology, Delft, Netherlands
| | - Andrew G Webb
- C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, Netherlands
- Signal Processing Systems, Delft University of Technology, Delft, Netherlands
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31
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Martin MN, Jordanova KV, Kos AB, Russek SE, Keenan KE, Stupic KF. Relaxation measurements of an MRI system phantom at low magnetic field strengths. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01086-y. [PMID: 37209233 PMCID: PMC10386925 DOI: 10.1007/s10334-023-01086-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/23/2023] [Accepted: 03/29/2023] [Indexed: 05/22/2023]
Abstract
OBJECTIVE Temperature controlled T1 and T2 relaxation times are measured on NiCl2 and MnCl2 solutions from the ISMRM/NIST system phantom at low magnetic field strengths of 6.5 mT, 64 mT and 550 mT. MATERIALS AND METHODS The T1 and T2 were measured of five samples with increasing concentrations of NiCl2 and five samples with increasing concentrations of MnCl2. All samples were scanned at 6.5 mT, 64 mT and 550 mT, at sample temperatures ranging from 10 °C to 37 °C. RESULTS The NiCl2 solutions showed little change in T1 and T2 with magnetic field strength, and both relaxation times decreased with increasing temperature. The MnCl2 solutions showed an increase in T1 and a decrease in T2 with increasing magnetic field strength, and both T1 and T2 increased with increasing temperature. DISCUSSION The low field relaxation rates of the NiCl2 and MnCl2 arrays in the ISMRM/NIST system phantom are investigated and compared to results from clinical field strengths of 1.5 T and 3.0 T. The measurements can be used as a benchmark for MRI system functionality and stability, especially when MRI systems are taken out of the radiology suite or laboratory and into less traditional environments.
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Affiliation(s)
- Michele N Martin
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA.
| | - Kalina V Jordanova
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Anthony B Kos
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Stephen E Russek
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Kathryn E Keenan
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
| | - Karl F Stupic
- U.S. Department of Commerce, National Institute of Standards and Technology, 325 Broadway, Boulder, CO, 80305, USA
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Webb A, O'Reilly T. Tackling SNR at low-field: a review of hardware approaches for point-of-care systems. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01100-3. [PMID: 37202656 PMCID: PMC10386948 DOI: 10.1007/s10334-023-01100-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 05/03/2023] [Accepted: 05/09/2023] [Indexed: 05/20/2023]
Abstract
OBJECTIVE To review the major hardware components of low-field point-of-care MRI systems which affect the overall sensitivity. METHODS Designs for the following components are reviewed and analyzed: magnet, RF coils, transmit/receive switches, preamplifiers, data acquisition system, and methods for grounding and mitigating electromagnetic interference. RESULTS High homogeneity magnets can be produced in a variety of different designs including C- and H-shaped as well as Halbach arrays. Using Litz wire for RF coil designs enables unloaded Q values of ~ 400 to be reached, with body loss representing about 35% of the total system resistance. There are a number of different schemes to tackle issues arising from the low coil bandwidth with respect to the imaging bandwidth. Finally, the effects of good RF shielding, proper electrical grounding, and effective electromagnetic interference reduction can lead to substantial increases in image signal-to-noise ratio. DISCUSSION There are many different magnet and RF coil designs in the literature, and to enable meaningful comparisons and optimizations to be performed it would be very helpful to determine a standardized set of sensitivity measures, irrespective of design.
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Affiliation(s)
- Andrew Webb
- Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands.
| | - Thomas O'Reilly
- Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
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Guo T, He W, Wan C, Zhang Y, Xu Z. NMR Magnetometer Based on Dynamic Nuclear-Polarization for Low-Strength Magnetic Field Measurement. SENSORS (BASEL, SWITZERLAND) 2023; 23:4663. [PMID: 37430578 DOI: 10.3390/s23104663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 04/29/2023] [Accepted: 05/09/2023] [Indexed: 07/12/2023]
Abstract
Nuclear magnetic resonance (NMR) magnetometers are considered due to their ability to map magnetic fields with high precision and calibrate other magnetic field measurement devices. However, the low signal-to-noise ratio of low-strength magnetic fields limits the precision when measuring magnetic fields below 40 mT. Therefore, we developed a new NMR magnetometer that combines the dynamic nuclear polarization (DNP) technique with pulsed NMR. The dynamic pre-polarization technique enhances the SNR under a low magnetic field. Pulsed NMR was used in conjunction with DNP to improve measurement accuracy and speed. The efficacy of this approach was validated through simulation and analysis of the measurement process. Next, a complete set of equipment was constructed, and we successfully measured magnetic fields of 30 mT and 8 mT with an accuracy of only 0.5 Hz (11 nT) at 30 mT (0.4 ppm) and 1 Hz (22 nT) at 8mT (3 ppm).
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Affiliation(s)
- Taoning Guo
- School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Wei He
- School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Cai Wan
- School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Yuxiang Zhang
- School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Zheng Xu
- School of Electrical Engineering, Chongqing University, Chongqing 400044, China
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Haskell MW, Nielsen JF, Noll DC. Off-resonance artifact correction for MRI: A review. NMR IN BIOMEDICINE 2023; 36:e4867. [PMID: 36326709 PMCID: PMC10284460 DOI: 10.1002/nbm.4867] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/25/2022] [Accepted: 11/01/2022] [Indexed: 06/06/2023]
Abstract
In magnetic resonance imaging (MRI), inhomogeneity in the main magnetic field used for imaging, referred to as off-resonance, can lead to image artifacts ranging from mild to severe depending on the application. Off-resonance artifacts, such as signal loss, geometric distortions, and blurring, can compromise the clinical and scientific utility of MR images. In this review, we describe sources of off-resonance in MRI, how off-resonance affects images, and strategies to prevent and correct for off-resonance. Given recent advances and the great potential of low-field and/or portable MRI, we also highlight the advantages and challenges of imaging at low field with respect to off-resonance.
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Affiliation(s)
- Melissa W Haskell
- Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
- Hyperfine Research, Guilford, Connecticut, USA
| | | | - Douglas C Noll
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
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Negnevitsky V, Vives-Gilabert Y, Algarín JM, Craven-Brightman L, Pellicer-Guridi R, O'Reilly T, Stockmann JP, Webb A, Alonso J, Menküc B. MaRCoS, an open-source electronic control system for low-field MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 350:107424. [PMID: 37001194 DOI: 10.1016/j.jmr.2023.107424] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 02/20/2023] [Accepted: 03/13/2023] [Indexed: 05/10/2023]
Abstract
Every magnetic resonance imaging (MRI) device requires an electronic control system that handles pulse sequences and signal detection and processing. Here we provide details on the architecture and performance of MaRCoS, a MAgnetic Resonance COntrol System developed by an open international community of low-field MRI researchers. MaRCoS is inexpensive and can handle cycle-accurate sequences without hard length limitations, rapid bursts of events, and arbitrary waveforms. It has also been readily adapted to meet the requirements of the various academic and private institutions participating in its development. We describe the MaRCoS hardware, firmware and software that enable all of the above, including a Python-based graphical user interface for pulse sequence implementation, data processing and image reconstruction.
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Affiliation(s)
| | - Yolanda Vives-Gilabert
- Intelligent Data Analysis Laboratory, Department of Electronic Engineering, Universitat de València, Valencia, Spain
| | - José M Algarín
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV), Valencia, Spain
| | - Lincoln Craven-Brightman
- Massachusetts General Hospital, A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Rubén Pellicer-Guridi
- Asociación de Investigación MPC, Manuel de Lardizábal 5, Donostia-San Sebastián 20018, Spain
| | - Thomas O'Reilly
- Department of Radiology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333, Netherlands
| | - Jason P Stockmann
- Massachusetts General Hospital, A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Andrew Webb
- Department of Radiology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333, Netherlands
| | - Joseba Alonso
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV), Valencia, Spain
| | - Benjamin Menküc
- University of Applied Sciences and Arts Dortmund, Sonnenstr. 96, Dortmund 44139, Germany.
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36
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Wei S, Wei Z, Wang Z, Wang H, He Q, He H, Li L, Yang W. Optimization design of a permanent magnet used for a low field (0.2 T) movable MRI system. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01090-2. [PMID: 37081246 DOI: 10.1007/s10334-023-01090-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVE To design a lightweight permanent magnet for a lowfield movable head imaging MRI system. MATERIALS AND METHODS To reduce the weight of the magnet, the pole pieces, anti-eddy current plates, and shimming rings were removed, and the distance between the two vertical yokes was shortened as much as possible. To compensate for the magnetic field deformation caused by the shortened distance between two vertical iron yokes, two side magnetic poles were added to the vertical yokes. The magnetic field distributions in magnetic poles, the iron yoke, and the spherical imaging region were simulated. Phantom and in vivo head imaging were conducted with a lowfield movable MRI prototype scanner equipped with the proposed permanent magnet. RESULTS A permanent magnet with a center field of 0.19815 T, a homogeneity of 46 ppm over the 20 cm spherical imaging region, and a weight of 654 kg have been achieved. Acceptable images of a phantom and a human brain have been acquired with the prototype MRI scanner. DISCUSSION The proposed permanent magnet design significantly reduces the magnet's weight compared with the conventional magnet structure and shows promise in promoting the development of lowfield compact MRI systems.
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Affiliation(s)
- Shufeng Wei
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
| | - Zhao Wei
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
| | - Zheng Wang
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
| | - Huixian Wang
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
| | - Qingyuan He
- Peking University Third Hospital, Beijing, 100191, China
| | - Hongyan He
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lei Li
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wenhui Yang
- Department of Electromagnetic Detection and Imaging Research, Institute of Electrical Engineering, Chinese Academy of Sciences, Zhongguancun Beiertiao NO.6, Beijing, 100190, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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Zhao H, Liu Z, Tang J, Gao B, Qin Q, Li J, Zhou Y, Yao P, Xi Y, Lin Y, Qian H, Wu H. Energy-efficient high-fidelity image reconstruction with memristor arrays for medical diagnosis. Nat Commun 2023; 14:2276. [PMID: 37081008 PMCID: PMC10119144 DOI: 10.1038/s41467-023-38021-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 04/06/2023] [Indexed: 04/22/2023] Open
Abstract
Medical imaging is an important tool for accurate medical diagnosis, while state-of-the-art image reconstruction algorithms raise critical challenges in massive data processing for high-speed and high-quality imaging. Here, we present a memristive image reconstructor (MIR) to greatly accelerate image reconstruction with discrete Fourier transformation (DFT) by computing-in-memory (CIM) with memristor arrays. A high-accuracy quasi-analogue mapping (QAM) method and generic complex matrix transfer (CMT) scheme was proposed to improve the mapping precision and transfer efficiency, respectively. High-fidelity magnetic resonance imaging (MRI) and computed tomography (CT) image reconstructions were demonstrated, achieving software-equivalent qualities and DICE scores after segmentation with nnU-Net algorithm. Remarkably, our MIR exhibited 153× and 79× improvements in energy efficiency and normalized image reconstruction speed, respectively, compared to graphics processing unit (GPU). This work demonstrates MIR as a promising high-fidelity image reconstruction platform for future medical diagnosis, and also largely extends the application of memristor-based CIM beyond artificial neural networks.
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Affiliation(s)
- Han Zhao
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Zhengwu Liu
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Jianshi Tang
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China.
- Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, 100084, China.
| | - Bin Gao
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
- Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, 100084, China
| | - Qi Qin
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Jiaming Li
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Ying Zhou
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Peng Yao
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Yue Xi
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - Yudeng Lin
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
| | - He Qian
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
- Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, 100084, China
| | - Huaqiang Wu
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China
- Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, 100084, China
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Parsa J, Webb A. Specific absorption rate (SAR) simulations for low-field (< 0.1 T) MRI systems. MAGMA (NEW YORK, N.Y.) 2023:10.1007/s10334-023-01073-3. [PMID: 36933091 PMCID: PMC10386976 DOI: 10.1007/s10334-023-01073-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 01/19/2023] [Accepted: 02/23/2023] [Indexed: 03/19/2023]
Abstract
OBJECTIVE To simulate the magnetic and electric fields produced by RF coil geometries commonly used at low field. Based on these simulations, the specific absorption rate (SAR) efficiency can be derived to ensure safe operation even when using short RF pulses and high duty cycles. METHODS Electromagnetic simulations were performed at four different field strengths between 0.05 and 0.1 T, corresponding to the lower and upper limits of current point-of-care (POC) neuroimaging systems. Transmit magnetic and electric fields, as well as transmit efficiency and SAR efficiency were simulated. The effects of a close-fitting shield on the EM fields were also assessed. SAR calculations were performed as a function of RF pulse length in turbo-spin echo (TSE) sequences. RESULTS Simulations of RF coil characteristics and B1+ transmit efficiencies agreed well with corresponding experimentally determined parameters. Overall, the SAR efficiency was, as expected, higher at the lower frequencies studied, and many orders of magnitude greater than at conventional clinical field strengths. The tight-fitting transmit coil results in the highest SAR in the nose and skull, which are not thermally sensitive tissues. The calculated SAR efficiencies showed that only when 180° refocusing pulses of duration ~ 10 ms are used for TSE sequences does SAR need to be carefully considered. CONCLUSION This work presents a comprehensive overview of the transmit and SAR efficiencies for RF coils used for POC MRI neuroimaging. While SAR is not a problem for conventional sequences, the values derived here should be useful for RF intensive sequences such as T1ρ, and also demonstrate that if very short RF pulses are required then SAR calculations should be performed.
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Affiliation(s)
- Javad Parsa
- C.J. Gorter MRI Centre, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Percuros B.V., Leiden, The Netherlands
| | - Andrew Webb
- C.J. Gorter MRI Centre, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
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Krishnamoorthy S, Paulraj S, Selvaraj NP, Ragupathy B, Arumugam S. A novel approach for neural networks based diagnosis and grading of stroke in tumor-affected brain MRIs. NETWORK (BRISTOL, ENGLAND) 2023; 34:190-220. [PMID: 37352128 DOI: 10.1080/0954898x.2023.2225601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/28/2023] [Accepted: 06/11/2023] [Indexed: 06/25/2023]
Abstract
Recognition and diagnosis of stroke from magnetic resonance Image (MRIs) are significant for medical procedures in therapeutic standards. The primary goal of this scheme is the discovery of stroke in tumour locale in brain tissues influenced image. The probability of stroke is categorized on brain tumour influenced images into mild, moderate, or serious cases. The mild and moderate phases of stroke are recognized as "Ahead of schedule" findings and serious cases are distinguished as "Advance" determination. The proposed Glioblastoma brain tumour recognition strategy used the Multifaceted Brain Tumour Image Segmentation test open-access dataset for evaluating the presentation. The brain images are classified utilizing the Deep Neural Networks classification algorithm as normal and abnormal images. The tumour region is segmented from the identified set of abnormal images using the normalized graph cut algorithm. The stroke likelihood is identified using the Deep Neural Networks by analysing the proximity of tumour section in brain matters. The proposed stroke analysis framework accurately groups 10 images as "Right on time" stroke probability images and accomplishes 90% order rate. The proposed stroke prediction framework effectively characterizes images as "Advance" stroke probability images and accomplishes 90% characterization rate.
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Affiliation(s)
| | - Sivakumar Paulraj
- School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
| | - Nagendra Prabhu Selvaraj
- Department of Computational Intelligence, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
| | - Balakumaresan Ragupathy
- Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India
| | - Selvapandian Arumugam
- Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India
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Guallart‐Naval T, O'Reilly T, Algarín JM, Pellicer‐Guridi R, Vives‐Gilabert Y, Craven‐Brightman L, Negnevitsky V, Menküc B, Galve F, Stockmann JP, Webb A, Alonso J. Benchmarking the performance of a low-cost magnetic resonance control system at multiple sites in the open MaRCoS community. NMR IN BIOMEDICINE 2023; 36:e4825. [PMID: 36097704 PMCID: PMC10078257 DOI: 10.1002/nbm.4825] [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: 03/22/2022] [Revised: 08/15/2022] [Accepted: 08/26/2022] [Indexed: 05/15/2023]
Abstract
PURPOSE To describe the current properties and capabilities of an open-source hardware and software package that is being developed by many sites internationally with the aim of providing an inexpensive yet flexible platform for low-cost MRI. METHODS This article describes three different setups from 50 to 360 mT in different settings, all of which used the MaRCoS console for acquiring data, and different types of software interface (custom-built GUI or Pulseq overlay) to acquire it. RESULTS Images are presented both from phantoms and in vivo from healthy volunteers to demonstrate the image quality that can be obtained from the MaRCoS hardware/software interfaced to different low-field magnets. CONCLUSIONS The results presented here show that a number of different sequences commonly used in the clinic can be programmed into an open-source system relatively quickly and easily, and can produce good quality images even at this early stage of development. Both the hardware and software will continue to develop, and it is an aim of this article to encourage other groups to join this international consortium.
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Affiliation(s)
- Teresa Guallart‐Naval
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M)Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV)ValenciaSpain
- Tesoro Imaging S.L.ValenciaSpain
| | - Thomas O'Reilly
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - José M. Algarín
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M)Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV)ValenciaSpain
| | | | - Yolanda Vives‐Gilabert
- Intelligent Data Analysis Laboratory, Department of Electronic EngineeringUniversitat de ValènciaValenciaSpain
| | | | | | - Benjamin Menküc
- University of Applied Sciences and Arts DortmundDortmundGermany
| | - Fernando Galve
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M)Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV)ValenciaSpain
| | - Jason P. Stockmann
- Massachusetts General Hospital, A. A. Martinos Center for Biomedical ImagingCharlestownMAUSA
| | - Andrew Webb
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Joseba Alonso
- MRILab, Institute for Molecular Imaging and Instrumentation (i3M)Spanish National Research Council (CSIC) and Universitat Politècnica de València (UPV)ValenciaSpain
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Arnold TC, Freeman CW, Litt B, Stein JM. Low-field MRI: Clinical promise and challenges. J Magn Reson Imaging 2023; 57:25-44. [PMID: 36120962 PMCID: PMC9771987 DOI: 10.1002/jmri.28408] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/11/2022] [Accepted: 08/12/2022] [Indexed: 02/03/2023] Open
Abstract
Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high-field devices remain expensive to install and operate, making them scarce outside of high-income countries and major population centers. Low-field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low-field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low-field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low-field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI-guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low-field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Thomas Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Colbey W. Freeman
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Brian Litt
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Joel M. Stein
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Bian H, Wang J, Hong C, Liu L, Ji R, Cao S, Abdalla AN, Chen X. GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:194-207. [PMID: 36698653 PMCID: PMC9841998 DOI: 10.1364/boe.479343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/28/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
Limited to the power of the light source in ophthalmic optical coherence tomography (OCT), the signal-to-noise ratio (SNR) of the reconstructed images is usually lower than OCT used in other fields. As a result, improvement of the SNR is required. The traditional method is averaging several images at the same lateral position. However, the image registration average costs too much time, which limits its real-time imaging application. In response to this problem, graphics processing unit (GPU)-side kernel functions are applied to accelerate the reconstruction of the OCT signals in this paper. The SNR of the images reconstructed from different numbers of A-scans and B-scans were compared. The results demonstrated that: 1) There is no need to realize the axial registration with every A-scan. The number of the A-scans used to realize axial registration is suitable to set as ∼25, when the A-line speed was set as ∼12.5kHz. 2) On the basis of ensuring the quality of the reconstructed images, the GPU can achieve 43× speedup compared with CPU.
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Affiliation(s)
- Haiyi Bian
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Jingtao Wang
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
| | - Chengjian Hong
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
| | - Lei Liu
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Rendong Ji
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Suqun Cao
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Ahmed N. Abdalla
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Xinjian Chen
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
- State Key Laboratory of Radiation Medicine and Protection, Soochow University, 215123, Suzhou, China
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Liang TO, Koh YH, Qiu T, Li E, Yu W, Huang SY. High-performance permanent magnet array design by a fast genetic algorithm (GA)-based optimization for low-field portable MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 345:107309. [PMID: 36335876 DOI: 10.1016/j.jmr.2022.107309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 08/21/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
Lightweight and compact permanent magnet arrays (PMAs) are suitable for portable dedicated magnetic resonance imaging (MRI). It is worth exploring different PMA design possibilities and optimization methods with an adequate balance between weight, size, and performance, in addition to Halbach arrays and C-shaped/H-shaped magnets which are widely used. In this paper, the design and optimization of a sparse high-performance inward-outward ring-pair PMA consisting of magnet cuboids is presented for portable imaging of the brain. The design is lightweight (151kg) and compact (inner bore diameter: 270mm, outer diameter: 616mm, length: 480mm, 5-Gauss range: 1840×1840×2340mm3). The optimization framework is based on the genetic algorithm with a consideration of both field properties and simulated image quality. The resulting PMA design has an average field strength of 101.5 mT and a field pattern with a built-in linear readout gradient. Subtracting the best fit to the linear gradient target resulted in a residual deviation from the target field of 0.76mT and an average linear regression coefficient of 0.85 to the linear gradient. The required radiofrequency bandwidth is 6.9% within a field of view (FoV) with a diameter of 200mm and a length of 125mm. It has a magnetic field generation efficiency of 0.67mT/kg, which is high among the sparse PMAs that were designed for an FoV with a diameter of 200mm. The field can be used to supply gradients in one direction working with gradient coils in the other two directions, or can be rotated to encode signals for imaging with axial slice selection. The encoding capability of the designed PMA was examined through the simulated reconstructed images. The force experienced by each magnet in the design was calculated, and the feasibility of a physical implementation was confirmed. The design can offer an increased field strength, and thus, an increased signal-to-noise ratio. It has a longitudinal field direction that allows the application of technologies developed for solenoidal magnets. This proposed design can be a promising alternative to supplying the main and gradient fields in combination for dedicated portable MRI. Lastly, the design is resulted from a fast genetic algorithm-based optimization in which fast magnetic field calculation was applied and high design flexibility was feasible. Within optimization iterations, image quality metrics were used for the encoding field of a magnet configuration to guide the design of the magnet array.
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Affiliation(s)
- Ting-Ou Liang
- Singapore University of Technology and Design 8 Somapah Road, 487372, Singapore
| | - Yan Hao Koh
- Singapore University of Technology and Design 8 Somapah Road, 487372, Singapore
| | - Tie Qiu
- Singapore University of Technology and Design 8 Somapah Road, 487372, Singapore
| | - Erping Li
- Zhejiang University Hangzhou, Zhejiang Province, China
| | - Wenwei Yu
- Center for Frontier Medical Engineering, Chiba University Inage Ku, Yayoi Cho, 1-33, Chiba 263-8522, Japan
| | - Shao Ying Huang
- Singapore University of Technology and Design 8 Somapah Road, 487372, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore IE Kent Ridge Road, 119228, Singapore.
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di Biase L, Bonura A, Caminiti ML, Pecoraro PM, Di Lazzaro V. Neurophysiology tools to lower the stroke onset to treatment time during the golden hour: microwaves, bioelectrical impedance and near infrared spectroscopy. Ann Med 2022; 54:2658-2671. [PMID: 36154386 PMCID: PMC9542520 DOI: 10.1080/07853890.2022.2124448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Reperfusion therapy administration timing in acute ischaemic stroke is the main determinant of patients' mortality and long-term disability. Indeed, the first hour from the stroke onset is defined the "golden hour", in which the treatment has the highest efficacy and lowest side effects. Delayed ambulance transport, inappropriate triage and difficulty in accessing CT scans lead to delayed onset to treatment time (OTT) in clinical practice. To date brain CT scan is needed to rule out intracranial haemorrhage, which is a major contraindication to thrombolytic therapy. The availability, dimension and portability make CT suitable mainly for intrahospital use, determining further delays in the therapies administration. This review aims at evaluating portable neurophysiology technologies developed with the scope of speeding up the diagnostic phase of acute stroke and, therefore, the initiation of intravenous thrombolysis. Medline databases were explored for studies concerning near infrared spectroscopy (NIRS), bioelectrical impedance spectroscopy (BIS) and Microwave imaging (MWI) as methods for stroke diagnosis. A total of 1368 articles were found, and 12 of these fit with our criteria and were included in the review. For each technology, the following parameters were evaluated: diagnostic accuracy, ability to differentiate ischaemic and haemorrhagic stroke, diagnosis time from stroke onset, portability and technology readiness level (TRL). All the described methods seem to be able to identify acute stroke even though the number of studies is very limited. Low cost and portability make them potentially usable during ambulance transport, possibly leading to a reduction of stroke OTT along with the related huge benefits in terms of patients outcome and health care costs. In addition, unlike standard imaging techniques, neurophysiological techniques could allow continuous monitoring of patients for timely intrahospital stroke diagnosis.KEY MESSAGESFirst hour from the stroke onset is defined the "golden hour", in which the treatment has the highest efficacy and lowest side effects.The delay for stroke onset to brain imaging time is one of the major reasons why only a minority of patients with acute ischaemic stroke are eligible to reperfusion therapies.Neurophysiology techniques (NIRS, BIS and MWI) could have a potential high impact in reducing the time to treatment in stroke patients.
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Affiliation(s)
- Lazzaro di Biase
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di Roma, Roma, Italy.,Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy.,Brain Innovations Laboratory, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Adriano Bonura
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di Roma, Roma, Italy.,Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Maria Letizia Caminiti
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di Roma, Roma, Italy.,Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Pasquale Maria Pecoraro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di Roma, Roma, Italy.,Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Vincenzo Di Lazzaro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology and Neurobiology, Università Campus Bio-Medico di Roma, Roma, Italy.,Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
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Yu P, Wang Y, Xu Y, Wu Z, Zhao Y, Peng B, Wang F, Tang Y, Yang X. Theoretical foundation for designing multilayer Halbach array magnets for benchtop NMR and MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 344:107322. [PMID: 36332512 DOI: 10.1016/j.jmr.2022.107322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 10/21/2022] [Accepted: 10/23/2022] [Indexed: 06/16/2023]
Abstract
Multilayer Halbach array magnets support portable NMR and MRI, but optimizing their design to maximize performance and minimize the use of expensive magnet materials is challenging. This is partly because our theoretical understanding of such arrays is incomplete and computationally intensive. Here we provide a theoretical description of the magnetic field distribution and we demonstrate that inhomogeneity is greatest along the z axis in multilayer Halbach array magnets. This allows the configuration of the multilayer Halbach array magnets to be optimized in a way that takes into account homogeneity, magnet volume, and magnetic flux density. At the same time, our description simplifies the design of multilayer array magnets, while accommodating the possibility of different outer radii, lengths for each layer array, or the presence of separation between the rings. We validated the theoretical description in simulations of a three-layer Halbach array magnet, then with a prototype three-layer 1-T Halbach array magnet. After adjusting the position of magnet blocks in the neighboring rings, we achieved homogeneity of 220 ppm for a standard 5 mm NMR tube while the inner diameter of the magnet is 20 mm. Our work provides a theoretical foundation for designing multilayer Halbach array magnets to maximize homogeneity and minimize the use of magnet materials.
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Affiliation(s)
- Peng Yu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China; Jinan Guoke Medical Technology Development Co., Ltd., Jinan 250101, China
| | - Ya Wang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Yajie Xu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Zhongyi Wu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Ying Zhao
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Bowen Peng
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Feng Wang
- School of Electronic and Information Engineering, Changchun University of Science and Technology, 130022 Changchun, China
| | - Yuguo Tang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
| | - Xiaodong Yang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
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Abhyankar N, Agrawal A, Campbell J, Maly T, Shrestha P, Szalai V. Recent advances in microresonators and supporting instrumentation for electron paramagnetic resonance spectroscopy. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:101101. [PMID: 36319314 PMCID: PMC9632321 DOI: 10.1063/5.0097853] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 08/13/2022] [Indexed: 06/16/2023]
Abstract
Electron paramagnetic resonance (EPR) spectroscopy characterizes the magnetic properties of paramagnetic materials at the atomic and molecular levels. Resonators are an enabling technology of EPR spectroscopy. Microresonators, which are miniaturized versions of resonators, have advanced inductive-detection EPR spectroscopy of mass-limited samples. Here, we provide our perspective of the benefits and challenges associated with microresonator use for EPR spectroscopy. To begin, we classify the application space for microresonators and present the conceptual foundation for analysis of resonator sensitivity. We summarize previous work and provide insight into the design and fabrication of microresonators as well as detail the requirements and challenges that arise in incorporating microresonators into EPR spectrometer systems. Finally, we provide our perspective on current challenges and prospective fruitful directions.
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Affiliation(s)
| | - Amit Agrawal
- Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Jason Campbell
- Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
| | - Thorsten Maly
- Bridge12 Technologies, Inc., Natick, Massachusetts 01760, USA
| | | | - Veronika Szalai
- Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
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47
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Portable NMR for quantification of breast density in vivo: Proof-of-concept measurements and comparison with quantitative MRI. Magn Reson Imaging 2022; 92:212-223. [PMID: 35843446 DOI: 10.1016/j.mri.2022.07.004] [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: 03/22/2022] [Revised: 06/17/2022] [Accepted: 07/11/2022] [Indexed: 11/23/2022]
Abstract
Mammographic Density (MD) is the degree of radio-opacity of the breast in an X-ray mammogram. It is determined by the Fibroglandular: Adipose tissue ratio. MD has major implications in breast cancer risk and breast cancer chemoprevention. This study aimed to investigate the feasibility of accurate, low-cost quantification of MD in vivo without ionising radiation. We used single-sided portable nuclear magnetic resonance ("Portable NMR") due to its low cost and the absence of radiation-related safety concerns. Fifteen (N = 15) healthy female volunteers were selected for the study and underwent an imaging routine consisting of 2D X-ray mammography, quantitative breast 3T MRI (Dixon and T1-based 3D compositional breast imaging), and 1D compositional depth profiling of the right breast using Portable NMR. For each participant, all the measurements were made within 3-4 h of each other. MRI-determined tissue water content was used as the MD-equivalent quantity. Portable NMR depth profiles of tissue water were compared with the equivalent depth profiles reconstructed from Dixon and T1-based MR images, which were used as the MD-equivalent reference standard. The agreement between the depth profiles acquired using Portable NMR and the reconstructed reference-standard profiles was variable but overall encouraging. The agreement was somewhat inferior to that seen in breast tissue explant measurements conducted in vitro, where quantitative micro-CT was used as the reference standard. The lower agreement in vivo can be attributed to an uncertainty in the positioning of the Portable NMR sensor on the breast surface and breast compression in Portable NMR measurements. The degree of agreement between Portable NMR and quantitative MRI is encouraging. While the results call for further development of quantitative Portable NMR, they demonstrate the in-principle feasibility of Portable NMR-based quantitative compositional imaging in vivo and show promise for the development of safe and low-cost protocols for quantification of MD suitable for clinical applications.
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48
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Shen S, Kong X, Meng F, Wu J, He Y, Guo P, Xu Z. An optimized quadrature RF receive coil for very-low-field (50.4 mT) magnetic resonance brain imaging. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 342:107269. [PMID: 35905530 DOI: 10.1016/j.jmr.2022.107269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 06/13/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
The radiofrequency (RF) receive coil is a direct probe for magnetic resonance imaging (MRI), and its performance determines the quality of MRI results. The RF coil employed for low-field MRI has a low working frequency, which makes its characteristic different from the RF coil exploited for conventional clinic MRI and may result in a different optimum RF coil configuration. To design and optimize a head RF receive coil for a very-low-field (50.4 mT) MRI system, we investigated the relationship between the structure and performance of the RF coil. Specifically, we focused on a quadrature RF coil consisting of a saddle coil and a modified Helmholtz coil wound around the surface of an elliptical cylinder. First, we evaluated the efficiency and RF magnetic field inhomogeneity of one-loop RF coil and determined the optimum dimension for saddle coil and modified Helmholtz RF coil. Then, we further studied the performance of the optimum-dimension RF coil from the perspective of the number of RF coil loops and revealed that the number of loops of RF coil for very-low-field MRI was a remarkable feature influencing the alternative current (AC) resistance of the RF coil and therefore make the SNR increase first and then decrease with the number of RF coil loops. We finally obtained the optimum number of loops for the saddle coil, modified Helmholtz coil, and fabricated a quadrature RF coil. The performance of the quadrature coil was evaluated through CuSO4 phantom imaging and in vivo human brain imaging. In phantom imaging, the SNR of quadrature RF coil increased by about 40% compared with that of single-channel RF coil.
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Affiliation(s)
- Sheng Shen
- State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China
| | - Xiaohan Kong
- State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China
| | - Fanqin Meng
- State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China
| | - Jiamin Wu
- Shenzhen Academy of Aerospace Technology, 6 Keji South 10th Road, Nanshan District, Shenzhen C4, 518057, China; Harbin Institute of Technology, 92 Xi Da Zhi Jie, Harbin 150001, Nangang Qu, China
| | - Yucheng He
- Shenzhen Academy of Aerospace Technology, 6 Keji South 10th Road, Nanshan District, Shenzhen C4, 518057, China
| | - Pan Guo
- School of Physics and Electronic Engineering, Chongqing Normal University, Chongqing 401331, China
| | - Zheng Xu
- State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044, China.
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49
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Lang M, Rapalino O, Huang S, Lev MH, Conklin J, Wald LL. Emerging Techniques and Future Directions: Fast and Portable Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2022; 30:565-582. [PMID: 35995480 DOI: 10.1016/j.mric.2022.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Fast MRI and portable MRI are emerging as promising technologies to improve the speed, efficiency, and availability of MR imaging. Fast MRI methods are increasingly being adopted to create screening protocols for the diagnosis and management of acute pathology in the emergency department. Faster imaging can facilitate timely diagnosis, reduce motion artifacts, and improve departmental MR operations. Point-of-care and portable MRI are emerging technologies that require radiologists to reenvision the role of MRI as a tool with greater accessibility, fewer siting constraints, and the ability to provide valuable diagnostic information at the bedside. Recently introduced commercially available pulse sequences and new MRI scanners are bringing these technologies closer to the patient's clinical setting, and we expect their use to only increase over the coming decade. This article provides an overview of these emerging technologies for emergency radiologists.
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Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Susie Huang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
| | - Lawrence L Wald
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
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50
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Guallart-Naval T, Algarín JM, Pellicer-Guridi R, Galve F, Vives-Gilabert Y, Bosch R, Pallás E, González JM, Rigla JP, Martínez P, Lloris FJ, Borreguero J, Marcos-Perucho Á, Negnevitsky V, Martí-Bonmatí L, Ríos A, Benlloch JM, Alonso J. Portable magnetic resonance imaging of patients indoors, outdoors and at home. Sci Rep 2022; 12:13147. [PMID: 35907975 PMCID: PMC9338984 DOI: 10.1038/s41598-022-17472-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 07/26/2022] [Indexed: 12/25/2022] Open
Abstract
Mobile medical imaging devices are invaluable for clinical diagnostic purposes both in and outside healthcare institutions. Among the various imaging modalities, only a few are readily portable. Magnetic resonance imaging (MRI), the gold standard for numerous healthcare conditions, does not traditionally belong to this group. Recently, low-field MRI technology companies have demonstrated the first decisive steps towards portability within medical facilities and vehicles. However, these scanners' weight and dimensions are incompatible with more demanding use cases such as in remote and developing regions, sports facilities and events, medical and military camps, or home healthcare. Here we present in vivo images taken with a light, small footprint, low-field extremity MRI scanner outside the controlled environment provided by medical facilities. To demonstrate the true portability of the system and benchmark its performance in various relevant scenarios, we have acquired images of a volunteer's knee in: (i) an MRI physics laboratory; (ii) an office room; (iii) outside a campus building, connected to a nearby power outlet; (iv) in open air, powered from a small fuel-based generator; and (v) at the volunteer's home. All images have been acquired within clinically viable times, and signal-to-noise ratios and tissue contrast suffice for 2D and 3D reconstructions with diagnostic value. Furthermore, the volunteer carries a fixation metallic implant screwed to the femur, which leads to strong artifacts in standard clinical systems but appears sharp in our low-field acquisitions. Altogether, this work opens a path towards highly accessible MRI under circumstances previously unrealistic.
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Affiliation(s)
| | - José M Algarín
- Institute for Molecular Imaging and Instrumentation, Spanish National Research Council, 46022, Valencia, Spain
- Institute for Molecular Imaging and Instrumentation, Universitat Politècnica de València, 46022, Valencia, Spain
| | - Rubén Pellicer-Guridi
- PhysioMRI Tech S.L., 46022, Valencia, Spain
- Asociación de investigación MPC, 20018, San Sebastián, Spain
| | - Fernando Galve
- Institute for Molecular Imaging and Instrumentation, Spanish National Research Council, 46022, Valencia, Spain
- Institute for Molecular Imaging and Instrumentation, Universitat Politècnica de València, 46022, Valencia, Spain
| | - Yolanda Vives-Gilabert
- PhysioMRI Tech S.L., 46022, Valencia, Spain
- Intelligent Data Analysis Laboratory, Department of Electronic Engineering, Universitat de València, 46100, Burjassot, Spain
| | | | - Eduardo Pallás
- Institute for Molecular Imaging and Instrumentation, Spanish National Research Council, 46022, Valencia, Spain
- Institute for Molecular Imaging and Instrumentation, Universitat Politècnica de València, 46022, Valencia, Spain
| | | | | | | | | | | | | | | | - Luis Martí-Bonmatí
- Medical Imaging Department, Hospital Universitari i Politècnic La Fe, 46026, Valencia, Spain
| | | | - José M Benlloch
- Institute for Molecular Imaging and Instrumentation, Spanish National Research Council, 46022, Valencia, Spain
- Institute for Molecular Imaging and Instrumentation, Universitat Politècnica de València, 46022, Valencia, Spain
| | - Joseba Alonso
- Institute for Molecular Imaging and Instrumentation, Spanish National Research Council, 46022, Valencia, Spain.
- Institute for Molecular Imaging and Instrumentation, Universitat Politècnica de València, 46022, Valencia, Spain.
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