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アイテム
Beyond case-control study in neuroimaging for psychiatric disorders: Harmonizing and utilizing the brain images from multiple sites
http://hdl.handle.net/10061/0002001187
http://hdl.handle.net/10061/0002001187733d3e5a-5b25-4375-a5c1-2a1a384ba3f9
| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||||||
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| 公開日 | 2025-10-03 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Beyond case-control study in neuroimaging for psychiatric disorders: Harmonizing and utilizing the brain images from multiple sites | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Magnetic resonance image | |||||||||||||||
| キーワード | ||||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Harmonization | |||||||||||||||
| キーワード | ||||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Life-course trajectory | |||||||||||||||
| キーワード | ||||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Normative modeling | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| アクセス権 | ||||||||||||||||
| アクセス権 | open access | |||||||||||||||
| 著者 |
Koike, Shinsuke
× Koike, Shinsuke
× 田中, 沙織
× Hayashi, Takuya
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| 抄録 | ||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | Recent magnetic resonance imaging (MRI) research has advanced our understanding of brain pathophysiology in psychiatric disorders. This progress necessitates re-evaluation of the diagnostic system for psychiatric disorders based on MRI-based biomarkers, with implications for precise clinical diagnosis and optimal therapeutics. To achieve this goal, large-scale multi-site studies are essential to develop a standardized MRI database, with the analysis of several thousands of images and the incorporation of new data. A critical challenge in these studies is to minimize sampling and measurement biases in MRI studies to accurately capture the diversity of disease-derived biomarkers. Various techniques have been employed to consolidate datasets from multiple sites in case-control studies. Traveling subject harmonization stands out as a powerful tool that can differentiate measurement bias from sample variety and sampling bias. A non-linear statistical model for a normative trajectory across the lifespan also strengthens the database to mitigate sampling bias from known factors such as age and sex. These approaches can enhance the alterations between psychiatric disorders and integrate new data and follow-up scans into existing life-course trajectory, enhancing the reliability of machine learning classification and subtyping. Although this approach has been developed using T1-weighted structural image features, future research may extend this framework to other modalities and measures. The required sample size and methodological establishment are needed for future investigations, leading to novel insights into the brain pathophysiology of psychiatric disorders and the development of optimal therapeutics for bedside clinical applications. Sharing big data and their findings also need to be considered. | |||||||||||||||
| 書誌情報 |
en : Neuroscience and biobehavioral reviews 巻 171, ページ数 14, 発行日 2025-04-01 |
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| 出版者 | ||||||||||||||||
| 出版者 | Elsevier | |||||||||||||||
| ISSN | ||||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||||
| 収録物識別子 | 1873-7528 | |||||||||||||||
| 出版者版DOI | ||||||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||
| 関連識別子 | https://doi.org/10.1016/j.neubiorev.2025.106063 | |||||||||||||||
| 出版者版URI | ||||||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||||||
| 識別子タイプ | URI | |||||||||||||||
| 関連識別子 | https://www.sciencedirect.com/science/article/pii/S0149763425000636 | |||||||||||||||
| 権利 | ||||||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/ | |||||||||||||||
| 権利情報 | © 2025 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | |||||||||||||||
| 著者版フラグ | ||||||||||||||||
| 出版タイプ | NA | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Society for the Promotion of Science (JSPS) | |||||||||||||||
| 研究課題番号 | JP24K02378 | |||||||||||||||
| 研究課題番号URI | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-24K02378/ | |||||||||||||||
| 研究課題名 | 脳画像10,000データから精神疾患機械学習器の複数作成と臨床応用 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Society for the Promotion of Science (JSPS) | |||||||||||||||
| 研究課題番号 | JP23H03877 | |||||||||||||||
| 研究課題番号URI | https://kaken.nii.ac.jp/ja/grant/KAKENHI-PUBLICLY-23H03877/ | |||||||||||||||
| 研究課題名 | 生涯にわたる大規模脳構造画像データセットを利活用した新たな脳画像解析手法の提案 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP18dm0307004 | |||||||||||||||
| 研究課題名 | 人生ステージに沿った健常および精神・神経疾患の統合MRIデータベースの構築にもとづく国際脳科学連携 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP18dm0307006 | |||||||||||||||
| 研究課題名 | マルチモーダル神経画像・高精度標準化解析による種間比較霊長類脳コネクトーム解明研究 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP22dm0307002 | |||||||||||||||
| 研究課題名 | 縦断的MRIデータに基づく成人期気分障害と関連疾患の神経回路の解明 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP23tm0524002 | |||||||||||||||
| 研究課題名 | ブレインアトラス創生による精神神経疾患のシングルセル・ゲノム創薬 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP23wm0625001 | |||||||||||||||
| 研究課題名 | 脳データ統合プラットフォームの開発と活用による脳機能と疾患病態の解明 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Agency for Medical Research and Development (AMED) | |||||||||||||||
| 研究課題番号 | JP24wm0625302 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Science and Technology Agency (JST) | |||||||||||||||
| 研究課題番号 | JPMJMS2021 | |||||||||||||||
| 研究課題番号URI | https://projectdb.jst.go.jp/grant/JST-PROJECT-20320124/ | |||||||||||||||
| 研究課題名 | 複雑臓器制御系の数理的包括理解と超早期精密医療への挑戦 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | Japan Science and Technology Agency (JST) | |||||||||||||||
| 研究課題番号 | JPMJFR231Q | |||||||||||||||
| 研究課題番号URI | https://projectdb.jst.go.jp/grant/JST-PROJECT-24013930/ | |||||||||||||||
| 研究課題名 | ヒト脳磁気共鳴画像で観察される精神疾患脳皮質体積変化の解明 | |||||||||||||||
| 助成情報 | ||||||||||||||||
| 助成機関名 | World Premier International-International Research Center for Neurointelligence (WPI-IRCN) | |||||||||||||||
