1
|
Karasawa T, Saikawa J, Munaka T, Kobayashi T. Homogeneous B0 coil design method for open-access ultra-low field magnetic resonance imaging: A simulation study. Magn Reson Imaging 2024; 112:128-135. [PMID: 38986889 DOI: 10.1016/j.mri.2024.07.006] [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: 03/26/2024] [Revised: 06/10/2024] [Accepted: 07/03/2024] [Indexed: 07/12/2024]
Abstract
A multimodal brain function measurement system integrating functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) is expected to be a tool that will provide new insights into neuroscience. To integrate fMRI and MEG, an ultra-low-field MRI (ULF-MRI) scanner that can generate a static magnetic field (B0) with an electromagnetic coil and turn off the B0 during MEG measurements is desirable. While electromagnetic B0 coil has the above advantages, it also has a trade-off between size and the broadness of the magnetic field homogeneity. In this study, we proposed a method for designing a B0 multi-stage circular coil arrangement that determines the number of coils required to maximize magnetic field homogeneity and minimize the total wiring length of the coils. The optimized multi-stage coil arrangement had an external shape of 600 mm in diameter and a maximum height of 600 mm, with an aperture of 600 mm in diameter and 300 mm in height. The magnetic field homogeneity was <100 ppm over a 210 mm diameter spherical volume (DSV). Compared to a previous two coil pairs arrangement with the same magnetic field homogeneity, the diameter was 1/1.9 times smaller, indicating that the newly designed B0 coil arrangement realized a smaller size and wider magnetic field homogeneity.
Collapse
Affiliation(s)
- Tomohiro Karasawa
- Technology Research Laboratory, Shimadzu corporation, 3-9-4, Hikaridai, Seika-cho, Soraku-gun 619-0237, Japan
| | - Jiro Saikawa
- Technology Research Laboratory, Shimadzu corporation, 3-9-4, Hikaridai, Seika-cho, Soraku-gun 619-0237, Japan
| | - Tatsuya Munaka
- Technology Research Laboratory, Shimadzu corporation, 3-9-4, Hikaridai, Seika-cho, Soraku-gun 619-0237, Japan
| | - Tetsuo Kobayashi
- Office of Institutional Advancement and Communications, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, Japan.
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
Roth BJ. Can MRI Be Used as a Sensor to Record Neural Activity? SENSORS (BASEL, SWITZERLAND) 2023; 23:1337. [PMID: 36772381 PMCID: PMC9918955 DOI: 10.3390/s23031337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/17/2023] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review attempts to answer the following question: Can MRI be used as a sensor to directly record neural behavior? It considers MRI sensing of electrical activity in the heart and in peripheral nerves before turning to the central topic: recording of brain activity. The primary hypothesis is that bioelectric current produced by a nerve or muscle creates a magnetic field that influences the magnetic resonance signal, although other mechanisms for detection are also considered. Recent studies have provided evidence that using MRI to sense neural activity is possible under ideal conditions. Whether it can be used routinely to provide functional information about brain processes in people remains an open question. The review concludes with a survey of artificial intelligence techniques that have been applied to functional MRI and may be appropriate for MRI sensing of neural activity.
Collapse
Affiliation(s)
- Bradley J Roth
- Department of Physics, Oakland University, Rochester, MI 48309, USA
| |
Collapse
|
4
|
Raman S, Gold GE, Rosen MS, Sveinsson B. Automatic estimation of knee effusion from limited MRI data. Sci Rep 2022; 12:3155. [PMID: 35210490 PMCID: PMC8873489 DOI: 10.1038/s41598-022-07092-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 02/10/2022] [Indexed: 01/17/2023] Open
Abstract
Knee effusion is a common comorbidity in osteoarthritis. To quantify the amount of effusion, semi quantitative assessment scales have been developed that classify fluid levels on an integer scale from 0 to 3. In this work, we investigated the use of a neural network (NN) that used MRI Osteoarthritis Knee Scores effusion-synovitis (MOAKS-ES) values to distinguish physiologic fluid levels from higher fluid levels in MR images of the knee. We evaluate its effectiveness on low-resolution images to examine its potential in low-field, low-cost MRI. We created a dense NN (dNN) for detecting effusion, defined as a nonzero MOAKS-ES score, from MRI scans. Both the training and performance evaluation of the network were conducted using public radiological data from the Osteoarthritis Initiative (OAI). The model was trained using sagittal turbo-spin-echo (TSE) MR images from 1628 knees. The accuracy was compared to VGG16, a commonly used convolutional classification network. Robustness of the dNN was assessed by adding zero-mean Gaussian noise to the test images with a standard deviation of 5-30% of the maximum test data intensity. Also, inference was performed on a test data set of 163 knees, which includes a smaller test set of 36 knees that was also assessed by a musculoskeletal radiologist and the performance of the dNN and the radiologist compared. For the larger test data set, the dNN performed with an average accuracy of 62%. In addition, the network proved robust to noise, classifying the noisy images with minimal degradation to accuracy. When given MRI scans with 5% Gaussian noise, the network performed similarly, with an average accuracy of 61%. For the smaller 36-knee test data set, assessed both by the dNN and by a radiologist, the network performed better than the radiologist on average. Classifying knee effusion from low-resolution images with a similar accuracy as a human radiologist using neural networks is feasible, suggesting automatic assessment of images from low-cost, low-field scanners as a potentially useful assessment tool.
Collapse
Affiliation(s)
- Sandhya Raman
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Garry E Gold
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Matthew S Rosen
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Bragi Sveinsson
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
5
|
Ueda H, Ito Y, Oida T, Taniguchi Y, Kobayashi T. Magnetic resonance imaging simulation with spin-lock preparations to detect tiny oscillatory magnetic fields. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 324:106910. [PMID: 33482529 DOI: 10.1016/j.jmr.2020.106910] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/27/2020] [Accepted: 12/25/2020] [Indexed: 06/12/2023]
Abstract
Spin-lock preparation was studied to detect tiny oscillatory magnetic fields such as a neural magnetic field without the blood oxygen level-dependent effect. This approach is a direct measurement and independent of static magnetic field strength. Accordingly, it is anticipated as a feasible functional magnetic resonance imaging (fMRI) in low and ultra-low-field MRI. Several reports have been published on spin-lock preparation but reports on imaging simulation are rare. Research in this area can assist in investigating magnetic resonance signal changes and, accordingly, can help to develop new spin-lock methods. In this study, we propose an imaging simulation method with an analytical solution using the Bloch equation. To demonstrate the feasibility of our proposed method, we compared simulated images with experimental results in which the number of sub-voxels and the amplitude and phase of the target oscillatory magnetic fields varied. In addition, we also applied graphics processing unit parallel computing and investigated the feasibility of avoiding an impracticable calculation time by doing so.
Collapse
Affiliation(s)
- Hiroyuki Ueda
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan.
| | - Yosuke Ito
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
| | - Takenori Oida
- Central Research Laboratory, Hamamatsu Photonics K.K., Japan
| | - Yo Taniguchi
- Research & Development Group, Hitachi, Ltd., Japan
| | - Tetsuo Kobayashi
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
| |
Collapse
|
6
|
Sogabe T, Ueda H, Ito Y, Taniguchi Y, Kobayashi T. Dependence of stimulus-induced rotary saturation on the direction of target oscillating magnetic fields: A phantom and simulation study. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 321:106849. [PMID: 33128915 DOI: 10.1016/j.jmr.2020.106849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 09/23/2020] [Accepted: 10/09/2020] [Indexed: 06/11/2023]
Abstract
Several noninvasive techniques for the direct measurement of the neuronal activity using magnetic resonance imaging (MRI) have recently been reported. As a promising candidate, we focus on a spin-lock MRI sequence (i.e., stimulus-induced rotary saturation (SIRS)) directly measuring a tiny oscillating magnetic field. Previous phantom studies on SIRS have applied the target oscillating magnetic field parallel to the direction of the static magnetic field B0. However, in practice, the neuromagnetic fields are not always aligned in the same direction as in such a condition. This study investigates the MR signal changes during SIRS when the target magnetic field direction is not the same as that of the B0 field through both phantom experiments and Bloch simulations. The experimental results indicate that only the target magnetic field component along the B0 field affects the signal change, indicating that SIRS has partial sensitivity, even if the target magnetic fields are tilted from the B0 field. Furthermore, the simulation results show good agreements with the experimental results. These results clarify the sensitivity direction of SIRS-based fMRI and lead to the possibility that the direction of the generated neuromagnetic fields can be estimated, such that we can separate directional information from the other information contained in neuromagnetic fields (e.g., phase information).
Collapse
Affiliation(s)
- Tomoyuki Sogabe
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
| | - Hiroyuki Ueda
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
| | - Yosuke Ito
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan
| | - Yo Taniguchi
- Research & Development Group, Hitachi, Ltd., Japan
| | - Tetsuo Kobayashi
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto-daigaku Katsura, Nishikyo-ku, Kyoto 615-8510, Japan.
| |
Collapse
|