Voxel-based QSM analysis as an imaging biomarker for mild cognitive impairment in Parkinson disease

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K17148
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 52040:Radiological sciences-related
• Research Institution: Nagoya City University
• Principal Investigator: Uchida Yuto 名古屋市立大学, 医薬学総合研究院(医学), 研究員 (20834261)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: パーキンソン病 / 認知症 / 脳画像解析 / MRI / 定量的磁化率画像

Outline of Final Research Achievements

Quantitative susceptibility mapping (QSM) has been developed as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. In our research, the association of cerebral susceptibility values with cognitive impairments in Parkinson’s disease was investigated using various QSM techniques. We first developed the voxel based QSM analysis. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood-brain barrier function in clinical settings. Finally, we developed the machine learning model trained with QSM, which could successfully detect mild cognitive impairment in Parkinson’s disease.

Free Research Field

神経内科学

Academic Significance and Societal Importance of the Research Achievements

パーキンソン病に伴う認知機能障害の画像学的早期診断法の開発と臨床応用という二つの目標達成に向けて，研究成果を国際論文として複数報告した本研究の学術的・社会的意義は大きい．一方，パーキンソン病に伴う認知機能障害の責任病巣・表現型は多様性を示すことから，集団を対象とした探索的解析では診断困難な例が一定数存在することが明らかとなった．今後は，個体脳ごとに異なる磁化率分布や時空間進展パターンを抽出し，高精度な早期診断モデルと個別化医療への展開を進める．具体的には，これまでに開発した画像を学習データとした機械学習を活用することで，パーキンソン病に伴う認知機能障害の早期発見モデルの構築を目指す．