医用画像の定量化と標準化：QIBA/J-QIBAの概説と組織緩和時間定量化の動向
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| Published in | 日本磁気共鳴医学会雑誌 Vol. 40; no. 4; pp. 143 - 148 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
日本磁気共鳴医学会
15.11.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0914-9457 2434-0499 |
| DOI | 10.2463/jjmrm.2020-1720 |
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| Author | 青木, 茂樹 萩原, 彰文 立石, 宇貴秀 藤田, 翔平 |
|---|---|
| Author_xml | – sequence: 1 fullname: 萩原, 彰文 organization: 順天堂大学医学部放射線診断学講座 – sequence: 1 fullname: 藤田, 翔平 organization: 東京大学医学系研究科生体物理医学専攻 – sequence: 1 fullname: 立石, 宇貴秀 organization: 東京医科歯科大学大学院医歯学総合研究科画像診断・核医学分野 – sequence: 1 fullname: 青木, 茂樹 organization: 順天堂大学医学部放射線診断学講座 |
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| Copyright | 2020 一般社団法人日本磁気共鳴医学会 |
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| References | 4) https://qibawiki.rsna.org/images/9/90/QIBA_Profile_Stages-20160210.pdf 9) Blystad I, Håkansson I, Tisell A, et al. : Quantitative MRI for analysis of active multiple sclerosis lesions without gadolinium-based contrast agent. AJNR Am J Neuroradiol 2016 ; 37 : 94-100 1) Biomarkers Definitions Working Group : Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001 ; 69 : 89-95 3) https://qibawiki.rsna.org/images/6/63/QIBA_DWIProfile_Consensus_Dec2019_Final.pdf 7) Warntjes JBM, Leinhard OD, West J, Lundberg P : Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magn Reson Med 2008 ; 60 : 320-329 8) Hagiwara A, Hori M, Cohen-Adad J, et al. : Linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative multidynamic multiecho sequence for rapid simultaneous relaxometry at 3 T: A validation study with a standardized phantom and healthy controls. Invest Radiol 2019 ; 54 : 39-47 12) Jiang Y, Ma D, Keenan KE, Stupic KF, Gulani V, Griswold MA : Repeatability of magnetic resonance fingerprinting T1 and T2 estimates assessed using the ISMRM/NIST MRI system phantom. Magn Reson Med 2017 ; 78 : 1452-1457 19) Hagiwara A, Fujita S, Ohno Y, Aoki S : Variability and standardization of quantitative imaging: monoparametric to multiparametric quantification, radiomics, and artificial intelligence. Invest Radiol. doi:10.1097/RLI.0000000000000666 (online ahead of print 13) Kato Y, Ichikawa K, Okudaira K, et al. : Comprehensive evaluation of B1+-corrected FISP-based magnetic resonance fingerprinting: accuracy, repeatability and reproducibility of T1 and T2 relaxation times for ISMRM/NIST system phantom and volunteers. Magn Reson Med Sci. doi:10.2463/mrms.mp.2019-0016. (online ahead of print 14) Badve C, Yu A, Dastmalchian S, et al. : MR fingerprinting of adult brain tumors: initial experience. AJNR Am J Neuroradiol 2017 ; 38 : 492-499 18) Panda A, O'Connor G, Lo WC, et al. : Targeted biopsy validation of peripheral zone prostate cancer characterization with magnetic resonance fingerprinting and diffusion mapping. Invest Radiol 2019 ; 54 : 485-493 5) Damadian R : Tumor detection by nuclear magnetic resonance. Science 1971 ; 171 : 1151-1153 2) Poste G : Bring on the biomarkers. Nature 2011 ; 469 : 156-157 17) Taniguchi Y, Yokosawa S, Shirai T, et al. : Fast 3D multi parameter mapping of relaxation times and susceptibility using partially RF-spoiled gradient echo at 3T. Joint Annual Meeting ISMRM-ESMRMB 2018 ; 5630 10) Fujita S, Hagiwara A, Hori M, et al. : Three-dimensional high-resolution simultaneous quantitative mapping of the whole brain with 3D-QALAS: An accuracy and repeatability study. Magn Reson Imaging 2019 ; 63 : 235-243 15) Ma D, Jiang Y, Chen Y, et al. : Fast 3D magnetic resonance fingerprinting for a whole-brain coverage. Magn Reson Med 2018 ; 79 : 2190-2197 6) Barbosa S, Blumhardt LD, Roberts N, Lock T, Edwards RH : Magnetic resonance relaxation time mapping in multiple sclerosis: normal appearing white matter and the “invisible” lesion load. Magn Reson Imaging 1994 ; 12 : 33-42 11) Ma D, Gulani V, Seiberlich N, et al. : Magnetic resonance fingerprinting. Nature 2013 ; 495 : 187-192 16) Cao X, Ye H, Liao C, Li Q, He H, Zhong J : Fast 3D brain MR fingerprinting based on multi-axis spiral projection trajectory. Magn Reson Med 2019 ; 82 : 289-301 |
| References_xml | – reference: 5) Damadian R : Tumor detection by nuclear magnetic resonance. Science 1971 ; 171 : 1151-1153 – reference: 9) Blystad I, Håkansson I, Tisell A, et al. : Quantitative MRI for analysis of active multiple sclerosis lesions without gadolinium-based contrast agent. AJNR Am J Neuroradiol 2016 ; 37 : 94-100 – reference: 17) Taniguchi Y, Yokosawa S, Shirai T, et al. : Fast 3D multi parameter mapping of relaxation times and susceptibility using partially RF-spoiled gradient echo at 3T. Joint Annual Meeting ISMRM-ESMRMB 2018 ; 5630 – reference: 19) Hagiwara A, Fujita S, Ohno Y, Aoki S : Variability and standardization of quantitative imaging: monoparametric to multiparametric quantification, radiomics, and artificial intelligence. Invest Radiol. doi:10.1097/RLI.0000000000000666 (online ahead of print) – reference: 8) Hagiwara A, Hori M, Cohen-Adad J, et al. : Linearity, bias, intrascanner repeatability, and interscanner reproducibility of quantitative multidynamic multiecho sequence for rapid simultaneous relaxometry at 3 T: A validation study with a standardized phantom and healthy controls. Invest Radiol 2019 ; 54 : 39-47 – reference: 18) Panda A, O'Connor G, Lo WC, et al. : Targeted biopsy validation of peripheral zone prostate cancer characterization with magnetic resonance fingerprinting and diffusion mapping. Invest Radiol 2019 ; 54 : 485-493 – reference: 6) Barbosa S, Blumhardt LD, Roberts N, Lock T, Edwards RH : Magnetic resonance relaxation time mapping in multiple sclerosis: normal appearing white matter and the “invisible” lesion load. Magn Reson Imaging 1994 ; 12 : 33-42 – reference: 7) Warntjes JBM, Leinhard OD, West J, Lundberg P : Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magn Reson Med 2008 ; 60 : 320-329 – reference: 3) https://qibawiki.rsna.org/images/6/63/QIBA_DWIProfile_Consensus_Dec2019_Final.pdf – reference: 12) Jiang Y, Ma D, Keenan KE, Stupic KF, Gulani V, Griswold MA : Repeatability of magnetic resonance fingerprinting T1 and T2 estimates assessed using the ISMRM/NIST MRI system phantom. Magn Reson Med 2017 ; 78 : 1452-1457 – reference: 15) Ma D, Jiang Y, Chen Y, et al. : Fast 3D magnetic resonance fingerprinting for a whole-brain coverage. Magn Reson Med 2018 ; 79 : 2190-2197 – reference: 11) Ma D, Gulani V, Seiberlich N, et al. : Magnetic resonance fingerprinting. Nature 2013 ; 495 : 187-192 – reference: 14) Badve C, Yu A, Dastmalchian S, et al. : MR fingerprinting of adult brain tumors: initial experience. AJNR Am J Neuroradiol 2017 ; 38 : 492-499 – reference: 13) Kato Y, Ichikawa K, Okudaira K, et al. : Comprehensive evaluation of B1+-corrected FISP-based magnetic resonance fingerprinting: accuracy, repeatability and reproducibility of T1 and T2 relaxation times for ISMRM/NIST system phantom and volunteers. Magn Reson Med Sci. doi:10.2463/mrms.mp.2019-0016. (online ahead of print) – reference: 2) Poste G : Bring on the biomarkers. Nature 2011 ; 469 : 156-157 – reference: 10) Fujita S, Hagiwara A, Hori M, et al. : Three-dimensional high-resolution simultaneous quantitative mapping of the whole brain with 3D-QALAS: An accuracy and repeatability study. Magn Reson Imaging 2019 ; 63 : 235-243 – reference: 1) Biomarkers Definitions Working Group : Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001 ; 69 : 89-95 – reference: 4) https://qibawiki.rsna.org/images/9/90/QIBA_Profile_Stages-20160210.pdf – reference: 16) Cao X, Ye H, Liao C, Li Q, He H, Zhong J : Fast 3D brain MR fingerprinting based on multi-axis spiral projection trajectory. Magn Reson Med 2019 ; 82 : 289-301 |
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| Title | 医用画像の定量化と標準化：QIBA/J-QIBAの概説と組織緩和時間定量化の動向 |
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