Elucidation of resting state functional networks and integration of white matter microstructural information in dystonia

2023 Fiscal Year Final Research Report

• Project/Area Number: 20K07868
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 52020:Neurology-related
• Research Institution: The University of Tokushima
• Principal Investigator: FUJITA Koji 徳島大学, 大学院医歯薬学研究部(医学域), 講師 (80601765)
• Project Period (FY): 2020-04-01 – 2024-03-31
• Keywords: ジストニア / 磁気共鳴画像

Outline of Final Research Achievements

The diagnosis of dystonia relies primarily on symptomatology, which can be problematic because of the high variability among clinicians. Therefore, there is a need for objective markers that can be utilized for diagnosis and disease assessment. In imaging studies, resting-state functional magnetic resonance imaging (fMRI) is expected to be utilized. However, resting-state fMRI is difficult to quantify on an individual patient level. To solve this problem, the principal investigator has developed a novel method to determine and quantify disease-related networks using independent component analysis and bootstrapping in resting-state fMRI. In this study, the method was applied to dystonia to detect and quantify resting-state functional networks. The independent component analysis-bootstrap method was used to identify the networks and quantify their expression.

Free Research Field

神経内科学

Academic Significance and Societal Importance of the Research Achievements

本研究はジストニアを対象としているが、ジストニアと同様に従来のMRI検査で明らかな異常を認めない多くの神経精神疾患に応用できる可能性がある。例えば、パーキンソン病の診断に直結する所見は従来のMRIでは認めがたい。また、多系統萎縮症、進行性核上性麻痺、大脳皮質基底核症候群などのパーキンソン症候群も、病初期などは従来のMRIで異常を認めないことがしばしばある。これらの疾患では安静時fMRIなどにおける変化が報告されているが、バイオマーカーとしてはいまだ確立していない。したがって、本研究の成果は神経画像バイオマーカーの開発に広く貢献することが見込まれる。