| Project/Area Number |
19K07820
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 51030:Pathophysiologic neuroscience-related
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| Research Institution | Shinshu University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
山田 光則 信州大学, 医学部, 特任教授 (30240039)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Project Status |
Completed (Fiscal Year 2023)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2021: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | ALSP / HDLS / 白質脳症 / 遺伝性 / ミクログリア / CSF1R / アストロサイト / 若年性認知症 / 脳画像 / 脳病変ステージ / 腫大軸索 / グリア |
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| Outline of Research at the Start |
ヒト若年性認知症の一つ、腫大神経軸索（スフェロイド）を伴う遺伝性大脳白質変性症（ALSP: adult onset leukoencephalopathy with axonal spheroids and pigmented glia）における（1）脳の神経病理学的ステージごとのCSF1R発現細胞種を同定し、（2）生存患者さんの脳病理ステージ診断を脳画像所見で行うための基準を確立する。
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| Outline of Final Research Achievements |
Settlement of stages of the pathological brain lesions (Oyanagi et al. Brain Pathol 2017) from the findings of brain imaging considered to be inevitably essential for the prognostication in adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP).
MRI images of eight patients with ALSP were analyzed semiquantitatively. White matter degeneration was assessed as a scale of 0 to 4 at six anatomical points, and brain atrophy as a scale 0 to 4 in four anatomical areas. The scores of the two assessments were then summed to give total MRI scores of 0 - 40 points. Based on the scores, the MRI features were classified as Grades (0 - 4). MRI Grades (2 - 4) based on the total MRI scores were well correlated with the pathological lesion Stages (II - IV).
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| Academic Significance and Societal Importance of the Research Achievements |
生存中の遺伝性白質脳症患者の脳MRI画像所見から、その患者の脳の病理ステージ分類を可能とする方法を確立した。すなわち、それぞれの患者さんの脳画像所見を、われわれが見いだした方法によって「脳画像Grade」を確定することにより、それぞれの症例の脳病理Stageを明確に知る事が可能となり、その患者さんの現在の臨床症状の理解と予後の推定と対策策定のために不可欠に重要な情報を提供しうることとなった。
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