| Project/Area Number |
15K15282
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
General internal medicine(including psychosomatic medicine)
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| Research Institution | University of Occupational and Environmental Health, Japan |
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Principal Investigator |
KODAMA NAOKI 産業医科大学, 医学部, 講師 (10352303)
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 摂食障害 / MRI / 体形の不満 / 機械学習 / 多変量解析 / 脳機能画像 |
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| Outline of Final Research Achievements |
With the goal of elucidating the neurological basis for eating disorders, we took contrast MRI and rsfMRI images and examined the correlation with body dissatisfaction, a key symptom of eating disorders. Using multivariate analysis with a machine learning algorithm, it was possible to distinguish the AN group from the healthy control group with the contrast images (accuracy rate 0.76, χ2 test p=0.003). The calculated results reflected body dissatisfaction, a central symptom of eating disorders. For resting brain activity, the AN group had increased activity from the right parahippocampal gyrus to the amygdala and decreased activity in the right superior parietal lobule and left fusiform gyrus. These findings suggest abnormalities in emotional processing and visual information processing which includes body shape.
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| Academic Significance and Societal Importance of the Research Achievements |
神経性やせ症の患者のMRI画像を機械学習を用いたアルゴリズムで解析した。MRIの画像のみで疾患の有無を判別することができ、脳の萎縮パターンと摂食障害の中核症状である体形の不満とが関連していることが示唆された。また、安静時の脳活動をMRIを使って解析した結果、神経性やせ症の患者には情動の処理や体形を含む視覚情報の処理の異常が有ることが示唆された。
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