脳画像データハーモナイゼーションにおける統計学的解析方法
Saved in:
| Published in | 日本磁気共鳴医学会雑誌 Vol. 42; no. 1; pp. 1 - 14 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Japanese |
| Published |
日本磁気共鳴医学会
15.02.2022
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0914-9457 2434-0499 |
| DOI | 10.2463/jjmrm.2021-1740 |
Cover
| Author | 川口, 淳 |
|---|---|
| Author_xml | – sequence: 1 fullname: 川口, 淳 organization: 佐賀大学医学部地域医療科学教育研究センター |
| BookMark | eNo9kL1KA0EcxBdRMMbUPsXF3b29vd1SQvyAgE2sl73LRnMkUe7SWOY2oMRCBbWwsFAxglhIEBEDPsyffDyGXBSbmWEGpvitoMX2YdsgtEZwkTLurkdRK24VKabEIT7DCyhHmcsczKRcRDksCXMk8_xlVEiSRoA9waQrKMmh6qw3nF59je052BOwI0i_IcsjsPdg-5A-Qjqa9x9gB2CH0H2Bbh-6l5CeTd_fZs-n49en6W1vNniY3F1Mbj4nw-tVtFTXzcQU_jyP9jbL1dK2U9nd2iltVJyIYqkdjqnkIaOCUmm04ITVNPPDUHueCEzAQ-NJU8c-C2SNu6amNfENF1QQT-vAD9w8Kv_-RklH7xt1FDdaOj5WOu40wqZRcyqKUUUyyeiojM7_Hh7oWEXa_QFP_34K |
| ContentType | Journal Article |
| Copyright | 2022 一般社団法人日本磁気共鳴医学会 |
| Copyright_xml | – notice: 2022 一般社団法人日本磁気共鳴医学会 |
| DOI | 10.2463/jjmrm.2021-1740 |
| DeliveryMethod | fulltext_linktorsrc |
| EISSN | 2434-0499 |
| EndPage | 14 |
| ExternalDocumentID | article_jjmrm_42_1_42_2021_1740_article_char_ja |
| GroupedDBID | ALMA_UNASSIGNED_HOLDINGS JSF RJT |
| ID | FETCH-LOGICAL-j209a-60296c428229ea8614da47cca558beb6ce59ef074b9d63edaa17e682815aab7b3 |
| ISSN | 0914-9457 |
| IngestDate | Wed Sep 03 06:30:41 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 1 |
| Language | Japanese |
| License | https://creativecommons.org/licenses/by-nc-nd/4.0/deed.ja |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-j209a-60296c428229ea8614da47cca558beb6ce59ef074b9d63edaa17e682815aab7b3 |
| OpenAccessLink | https://www.jstage.jst.go.jp/article/jjmrm/42/1/42_2021-1740/_article/-char/ja |
| PageCount | 14 |
| ParticipantIDs | jstage_primary_article_jjmrm_42_1_42_2021_1740_article_char_ja |
| PublicationCentury | 2000 |
| PublicationDate | 2022/02/15 |
| PublicationDateYYYYMMDD | 2022-02-15 |
| PublicationDate_xml | – month: 02 year: 2022 text: 2022/02/15 day: 15 |
| PublicationDecade | 2020 |
| PublicationTitle | 日本磁気共鳴医学会雑誌 |
| PublicationTitleAlternate | 日磁医誌 |
| PublicationYear | 2022 |
| Publisher | 日本磁気共鳴医学会 |
| Publisher_xml | – name: 日本磁気共鳴医学会 |
| References | 8) Pinto MS, Paolella R, Billiet T, Dyck PV, Guns PJ, Jeurissen B, Ribbens A, Dekker AJd, Sijbers J : Harmonization of brain diffusion MRI : concepts and methods. Front Neurosci 2020 ; 14 : 396 16) Yu M, Linn KA, Cook PA, et al. : Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data. Hum Brain Mapp. 2018 ; 39 : 4213-4227 3) Sudlow C, Gallacher J, Allen N, et al. : UK biobank : an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 2015 ; 12 : e1001779 5) Wachinger C, Rieckmann A, Pölsterl S, et al. : Detect and correct bias in multi-site neuroimaging datasets. Med Image Anal 2021 ; 67 : 101879 22) Tax CM, Grussu F, Kaden E, et al. : Cross-scanner and cross-protocol diffusion MRI data harmonisation : A benchmark database and evaluation of algorithms. NeuroImage 2019 ; 195 : 285-299 7) Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly K, Irizarry RA : Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet 2010 ; 11 : 733-739 14) Fortin JP, Cullen N, Sheline YI, et al. : Harmonization of cortical thickness measurements across scanners and sites. Neuroimage 2018 ; 167 : 104-120 11) 根本清貴：すぐできるVBM精神・神経疾患の脳画像解析．東京：学研メディカル秀潤社，2014 2) Jack CR Jr, Bernstein MA, Fox NC, et al. : The alzheimer's disease neuroimaging initiative (ADNI) : MRI methods. J Magn Reson Imaging 2008 ; 27 : 685-691 9) Johnson WE, Li C, Rabinovic A : Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 2007 ; 8 : 118-127 23) Dewey BE, Zhao C, Reinhold JC, et al. : DeepHarmony : A deep learning approach to contrast harmonization across scanner changes. Magn Reson Imaging 2019 ; 64 : 160-170 21) 山下隆義：イラストで学ぶ ディープラーニング 改訂第2版．東京：講談社，2018 1) Nichols TE, Das S, Eickhoff SB, et al. : Best practices in data analysis and sharing in neuroimaging using MRI. Nat neurosci 2017 ; 20 : 299-303 15) Fortin JP, Parker D, Tunc B, et al. : Harmonization of multi-site diffusion tensor imaging data. Neuroimage 2017 ; 161 : 149-170 10) 川口, 淳 : メタアナリシスと脳画像解析．神経治療 2017 ; 34 : 229-234 17) Yamashita A, Yahata N, Itahashi T, et al. : Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias. PLoS Biol. 2019 ; 17 : e3000042 18) Radua J, Vieta E, Shinohara R, et al. : Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA. NeuroImage 2020 ; 218 : 116956 4) Smith SM, Nichols TE : Statistical challenges in “Big Data” human neuroimaging. Neuron 2018 ; 97 : 263-268 24) Dinsdale NK, Jenkinson M, Namburete A IL. : Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal. Neuroimage 2021 ; 228 : 117689 13) Kawaguchi A : Multivariate Analysis for Neuroimaging Data. Florida : CRC Press, 2021 19) Pomponio R, Erus G, Habes M, et al. : Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage 2020 ; 208 : 116450 6) Alfaro-Almagro F, McCarthy P, Afyouni S, Andersson JLR, Bastiani M, Miller KL, Nichols TE, Smith SM : Confound modelling in UK Biobank brain imaging. Neuroimage 2021 ; 224 : 117002 12) 川口, 淳 : 脳MRIデータの統計解析．計量生物学 2013 ; 33 : 145-174 20) Beer JC, Tustison NJ, Cook PA, et al. : Longitudinal ComBat : A method for harmonizing longitudinal multi-scanner imaging data. NeuroImage 2020 ; 220 : 117129 |
| References_xml | – reference: 7) Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly K, Irizarry RA : Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet 2010 ; 11 : 733-739 – reference: 23) Dewey BE, Zhao C, Reinhold JC, et al. : DeepHarmony : A deep learning approach to contrast harmonization across scanner changes. Magn Reson Imaging 2019 ; 64 : 160-170 – reference: 17) Yamashita A, Yahata N, Itahashi T, et al. : Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias. PLoS Biol. 2019 ; 17 : e3000042 – reference: 21) 山下隆義：イラストで学ぶ ディープラーニング 改訂第2版．東京：講談社，2018 – reference: 2) Jack CR Jr, Bernstein MA, Fox NC, et al. : The alzheimer's disease neuroimaging initiative (ADNI) : MRI methods. J Magn Reson Imaging 2008 ; 27 : 685-691 – reference: 3) Sudlow C, Gallacher J, Allen N, et al. : UK biobank : an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 2015 ; 12 : e1001779 – reference: 19) Pomponio R, Erus G, Habes M, et al. : Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage 2020 ; 208 : 116450 – reference: 9) Johnson WE, Li C, Rabinovic A : Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 2007 ; 8 : 118-127 – reference: 13) Kawaguchi A : Multivariate Analysis for Neuroimaging Data. Florida : CRC Press, 2021 – reference: 12) 川口, 淳 : 脳MRIデータの統計解析．計量生物学 2013 ; 33 : 145-174 – reference: 11) 根本清貴：すぐできるVBM精神・神経疾患の脳画像解析．東京：学研メディカル秀潤社，2014 – reference: 20) Beer JC, Tustison NJ, Cook PA, et al. : Longitudinal ComBat : A method for harmonizing longitudinal multi-scanner imaging data. NeuroImage 2020 ; 220 : 117129 – reference: 15) Fortin JP, Parker D, Tunc B, et al. : Harmonization of multi-site diffusion tensor imaging data. Neuroimage 2017 ; 161 : 149-170 – reference: 14) Fortin JP, Cullen N, Sheline YI, et al. : Harmonization of cortical thickness measurements across scanners and sites. Neuroimage 2018 ; 167 : 104-120 – reference: 16) Yu M, Linn KA, Cook PA, et al. : Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data. Hum Brain Mapp. 2018 ; 39 : 4213-4227 – reference: 1) Nichols TE, Das S, Eickhoff SB, et al. : Best practices in data analysis and sharing in neuroimaging using MRI. Nat neurosci 2017 ; 20 : 299-303 – reference: 10) 川口, 淳 : メタアナリシスと脳画像解析．神経治療 2017 ; 34 : 229-234 – reference: 24) Dinsdale NK, Jenkinson M, Namburete A IL. : Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal. Neuroimage 2021 ; 228 : 117689 – reference: 22) Tax CM, Grussu F, Kaden E, et al. : Cross-scanner and cross-protocol diffusion MRI data harmonisation : A benchmark database and evaluation of algorithms. NeuroImage 2019 ; 195 : 285-299 – reference: 8) Pinto MS, Paolella R, Billiet T, Dyck PV, Guns PJ, Jeurissen B, Ribbens A, Dekker AJd, Sijbers J : Harmonization of brain diffusion MRI : concepts and methods. Front Neurosci 2020 ; 14 : 396 – reference: 5) Wachinger C, Rieckmann A, Pölsterl S, et al. : Detect and correct bias in multi-site neuroimaging datasets. Med Image Anal 2021 ; 67 : 101879 – reference: 6) Alfaro-Almagro F, McCarthy P, Afyouni S, Andersson JLR, Bastiani M, Miller KL, Nichols TE, Smith SM : Confound modelling in UK Biobank brain imaging. Neuroimage 2021 ; 224 : 117002 – reference: 18) Radua J, Vieta E, Shinohara R, et al. : Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA. NeuroImage 2020 ; 218 : 116956 – reference: 4) Smith SM, Nichols TE : Statistical challenges in “Big Data” human neuroimaging. Neuron 2018 ; 97 : 263-268 |
| SSID | ssib058493821 ssib044754443 ssib002004297 ssj0003314441 |
| Score | 2.2705474 |
| SourceID | jstage |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | Bayes estimation bias correction data sharing general linear model machine learning |
| Title | 脳画像データハーモナイゼーションにおける統計学的解析方法 |
| URI | https://www.jstage.jst.go.jp/article/jjmrm/42/1/42_2021-1740/_article/-char/ja |
| Volume | 42 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| ispartofPNX | 日本磁気共鳴医学会雑誌, 2022/02/15, Vol.42(1), pp.1-14 |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3Na9VAEA-1XryIouI3PbjH1CS72Y-LkLzmUYR6aqG3kH3JOzywSmkvHoS-FJR6UMF68OBBxQriQYqI-MA_ZunHn-HM5qPP1oNVL2HY2Z397c4mOxN2Zh3nRuZnNO8p4Wov6Lmsr3N4pZR0-zIvuNAhFz0MFJ67w2cX2O3FcHHixObYqaXVFT3de_DbuJK_0SqUgV4xSvYYmm2FQgHQoF94gobh-Uc6JokkkpGYkkQQBURMkpBISmSXJNQSoibijiUCEres7q8sSqKgYUV15Yg1rTpH5DSSo7YLagmfRHFN1HJ8ovy6lYwRahyS2EfwEeCXiDmaIRG3o4hwRMgSJAKBnKiEKM8SnMQKCeioujKzsaotF-qHluiQqIOiIts11veQizNT9atQQsxsSaeetBoAwwECBqijYgsbkACk9l8y1oWhqxnbuoudwCK1vcC46PhPFPC_8UqXsF32_x3m-H9Wn7mKVVm4pwtbFjCKp3-qm6GabYgFR163ak_xx4yTKuD28LYXMI7pNwaDu8uYXCHwXfAzvYMdvj13Wa_U1NZMWZD6-MAWKbZIGz5G_KUDcDtOBkLY0w9zD5MDq85aMa3Viikj2VgWRTBpFW3Cr9EgohS8dnuHbDsZVZItxH3zEGqwBAfgFzVnKq2ZN3_GOV37Z1NRBfGsMzHIzjnz--vbey--75RPTfnIlCMz_GGQHpnyjSk3zPCdGY5s-VdTbply26x9NGsbZu25GT7Z-_J5_8PjnU_v916t72-93X39bPflt93tzfPOQjeZ78y69XUk7iDwVOZyL1C8x_DctSoyCXZtnjEBX8AwlLrQHAMaiz6Y5FrlnBZ5lvmi4DKQfphlWmh6wZlcurdUXHSm4AOZcaFEpqVgPVrIPve518-5pkyDA3PJuVVNQnq_yjmTHlNzl_9VwBXn1MF7ctWZXFleLa6B-b2ir9vF8BP1_bc7 |
| linkProvider | ISSN International Centre |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E8%84%B3%E7%94%BB%E5%83%8F%E3%83%87%E3%83%BC%E3%82%BF%E3%83%8F%E3%83%BC%E3%83%A2%E3%83%8A%E3%82%A4%E3%82%BC%E3%83%BC%E3%82%B7%E3%83%A7%E3%83%B3%E3%81%AB%E3%81%8A%E3%81%91%E3%82%8B%E7%B5%B1%E8%A8%88%E5%AD%A6%E7%9A%84%E8%A7%A3%E6%9E%90%E6%96%B9%E6%B3%95&rft.jtitle=%E6%97%A5%E6%9C%AC%E7%A3%81%E6%B0%97%E5%85%B1%E9%B3%B4%E5%8C%BB%E5%AD%A6%E4%BC%9A%E9%9B%91%E8%AA%8C&rft.au=%E5%B7%9D%E5%8F%A3%2C+%E6%B7%B3&rft.date=2022-02-15&rft.pub=%E6%97%A5%E6%9C%AC%E7%A3%81%E6%B0%97%E5%85%B1%E9%B3%B4%E5%8C%BB%E5%AD%A6%E4%BC%9A&rft.issn=0914-9457&rft.eissn=2434-0499&rft.volume=42&rft.issue=1&rft.spage=1&rft.epage=14&rft_id=info:doi/10.2463%2Fjjmrm.2021-1740&rft.externalDocID=article_jjmrm_42_1_42_2021_1740_article_char_ja |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0914-9457&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0914-9457&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0914-9457&client=summon |