大脳白質病変の定量化

Quantitative Assessment of White Matter Lesions

大脳白質病変は行動記憶障害を引き起こし，重篤な疾患の要因になり得る。この大脳白質病変を定量的に評価することで，関連する疾患の発症率を効率的に抑えることが可能となる。学術，商業，自動化の観点から，人工知能を活用した画像診断が有用なアプローチとなり得ることを発見した。さらに，年齢，生活習慣，ストレスなどが病変形成の主要因であり，モニタリングや治療に活用できることが明らかになった。

Abstract

Cerebral White Matter Lesions (CWMLs) contribute to normal human behavioral and memory impairments, leading to life-threatening diseases and disorders. Quantitative assessment is crucial to enable accurate microstructural diagnosis and to mitigate associated morbidity. In this review, we examined contemporary trends and available strategies across scientific, commercial, and automation domains, and identified neuroimaging assisted by Artificial Intelligence (AI) as a promising approach for advancing CWML evaluation. In addition, brain docking with voxel-based morphometry techniques indicate that age, lifestyle, and stress are major contributors to CWML formation and may serve as useful parameters for monitoring and therapeutic planning. Our study may help guide future research into the microstructural-level pathological mechanisms of CWML and the development of real-time diagnosis.