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Wan C, He W, Littin S, Lange T, Zaitsev M, Xu Z. Preliminary Exploration of T 1ρ and T 2 Mapping in Porcine Articular Cartilage Using Very-Low-Field Magnetic Resonance Imaging. IEEE Trans Biomed Eng 2024; 71:3302-3311. [PMID: 38935473 DOI: 10.1109/tbme.2024.3420174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
OBJECTIVE The high prevalence of osteoarthritis emphasizes the need for a cost-effective and accessible method for its early diagnosis. Recently, the portability and affordability of very-low-field (VLF) magnetic resonance imaging (MRI, 10-100 mT) have caused it to gain popularity. Nevertheless, there is insufficient evidence to quantify early degenerative changes in cartilage using VLF MRI. This study assessed the potential of T1ρ and T2 mapping for detecting degenerative changes in porcine cartilage specimens using a 50 mT MRI scanner. METHODS T2- and T1ρ-weighted images were acquired using a 50 mT MRI scanner with 2D spin-echo and triple-refocused T1ρ preparation sequences. MRI scans of porcine cartilage were also acquired using a 3 T MRI scanner for comparison. A mono-exponential algorithm was applied to fit a series of T2- and T1ρ-weighted images. T2 values for CuSO4·5H2O solutions measured via Carr-Purcell-Meiboom-Gill (CPMG) and spin-echo sequences were compared to verify the algorithm's reliability. The nonparametric Kruskal-Wallis statistical test was used to compare T2 and T1ρ values. Experimental repeatability was assessed using the root-mean-square of the coefficient of variation (rmsCV). RESULTS T2 values of the CuSO4·5H2O solutions obtained using the spin-echo sequence showed differences within 2.3% of those obtained using the CPMG sequence, indicating the algorithm's reliability. The T1ρ values for varying concentrations of agarose gel solutions were higher than the T2 values. Furthermore, 50 mT and 3 T MRI results showed that both the T1ρ and T2 values were significantly higher for porcine cartilage degraded for 6 h vs intact cartilage, with p-values of 0.006 and 0.01, respectively. Our experimental results showed good reproducibility (rmsCV < 8%). CONCLUSION We demonstrated the feasibility of quantitative cartilage imaging via T2 and T1ρ mapping at 50 mT MRI for the first time.
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Ren Q, Lang Y, Jia Y, Xiao X, Liu Y, Kong X, Jin R, He Y, Zhang J, You JW, Sha WEI, Pang Y. High-Q metasurface signal isolator for 1.5T surface coil magnetic resonance imaging on the go. OPTICS EXPRESS 2024; 32:8751-8762. [PMID: 38571125 DOI: 10.1364/oe.514806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/24/2024] [Indexed: 04/05/2024]
Abstract
The combination of surface coils and metamaterials remarkably enhance magnetic resonance imaging (MRI) performance for significant local staging flexibility. However, due to the coupling in between, impeded signal-to-noise ratio (SNR) and low-contrast resolution, further hamper the future growth in clinical MRI. In this paper, we propose a high-Q metasurface decoupling isolator fueled by topological LC loops for 1.5T surface coil MRI system, increasing the magnetic field up to fivefold at 63.8 MHz. We have employed a polarization conversion mechanism to effectively eliminate the coupling between the MRI metamaterial and the radio frequency (RF) surface transmitter-receiver coils. Furthermore, a high-Q metasurface isolator was achieved by taking advantage of bound states in the continuum (BIC) for extremely high-resolution MRI and spectroscopy. An equivalent physical model of the miniaturized metasurface design was put forward through LC circuit analysis. This study opens up a promising route for the easy-to-use and portable surface coil MRI scanners.
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He J, Kong X, Xu Z. Improving the SNR of UMR sensor using LC resonator. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 356:107580. [PMID: 37924681 DOI: 10.1016/j.jmr.2023.107580] [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] [Revised: 10/23/2023] [Accepted: 10/26/2023] [Indexed: 11/06/2023]
Abstract
Single-sided or unilateral magnetic resonance (UMR) technology has various benefits, such as an open structure, low cost, portability, and nondestructive measurement, in contrast to the conventional closed magnet structure. UMR is widely used in material analysis, well logging, and biomedicine. However, its development is constrained by its poor signal-to-noise ratio (SNR). To enhance the SNR of UMR sensor, a surface coil of LC resonator is added on the Radio Frequency (RF) coil. First, a method of calculating the current in the RF coil including LC resonator is derived. Next, the equivalent AC resistance of the coil is calculated using the partial-element equivalent-circuit (PEEC) method. Finally, the SNR of a UMR sensor incorporating LC resonator is analyzed, and its sensitivity map is provided. Experimental comparisons are made between the UMR sensor with and without a LC resonator. Results show that the SNR of the UMR can be enhanced by up to three times after the LC resonator is loaded. The SNR improves within 30 mm of the coil surface, and this beneficial effect steadily diminishes as the distance increases. This study offers a useful method for improving the signal of UMR sensors.
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Affiliation(s)
- Jiali He
- School of Electrical Engineering, Chongqing University, Chongqing, China
| | - Xiaohan Kong
- Graduate School of Information Science and Technology, Hokkaido University, Sapporo 060-0814, Japan
| | - Zheng Xu
- School of Electrical Engineering, Chongqing University, Chongqing, China.
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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: 11] [Impact Index Per Article: 5.5] [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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