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タイトル: Identifying and reverting the adverse effects of white matter hyperintensities on cortical surface analyses
著者: Oi, Yuki
Hirose, Masakazu
Togo, Hiroki  kyouindb  KAKEN_id
Yoshinaga, Kenji
Akasaka, Thai
Okada, Tomohisa
Aso, Toshihiko
Takahashi, Ryosuke  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-1407-9640 (unconfirmed)
Glasser, Matthew F.
Hayashi, Takuya
Hanakawa, Takashi  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-3267-8214 (unconfirmed)
著者名の別形: 大井, 由貴
廣瀬, 正和
東口, 大樹
吉永, 健二
赤坂, 太
岡田, 知久
麻生, 俊彦
髙橋, 良輔
林, 拓也
花川, 隆
キーワード: White matter hyperintensities
Human connectome project
Neuroanatomy
Brain
Magnetic resonance imaging
Cortical surface analysis
発行日: 1-Nov-2023
出版者: Elsevier BV
誌名: NeuroImage
巻: 281
論文番号: 120377
抄録: The Human Connectome Project (HCP)-style surface-based brain MRI analysis is a powerful technique that allows precise mapping of the cerebral cortex. However, the strength of its surface-based analysis has not yet been tested in the older population that often presents with white matter hyperintensities (WMHs) on T2-weighted (T2w) MRI (hypointensities on T1w MRI). We investigated T1-weighted (T1w) and T2w structural MRI in 43 healthy middle-aged to old participants. Juxtacortical WMHs were often misclassified by the default HCP pipeline as parts of the gray matter in T1w MRI, leading to incorrect estimation of the cortical surfaces and cortical metrics. To revert the adverse effects of juxtacortical WMHs, we incorporated the Brain Intensity AbNormality Classification Algorithm into the HCP pipeline (proposed pipeline). Blinded radiologists performed stereological quality control (QC) and found a decrease in the estimation errors in the proposed pipeline. The superior performance of the proposed pipeline was confirmed using an originally-developed automated surface QC based on a large database. Here we showed the detrimental effects of juxtacortical WMHs for estimating cortical surfaces and related metrics and proposed a possible solution for this problem. The present knowledge and methodology should help researchers identify adequate cortical surface biomarkers for aging and age-related neuropsychiatric disorders.
記述: ありふれた脳の白質病変がMRI画像解析を悪化させていた --従来手法に機械学習を組み入れた改善手法の開発--. 京都大学プレスリリース. 2023-10-02.
著作権等: © 2023 The Author(s). Published by Elsevier Inc.
This is an open access article under the CC BY license.
URI: http://hdl.handle.net/2433/285323
DOI(出版社版): 10.1016/j.neuroimage.2023.120377
PubMed ID: 37714391
関連リンク: https://www.kyoto-u.ac.jp/ja/research-news/2023-10-02-0
出現コレクション:学術雑誌掲載論文等

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