Year: 2025
Type: article
Abstract: This review synthesizes current evidence on the relationship between structural brain changes and driving safety in cognitively healthy older adults. Using magnetic resonance imaging (MRI) structural biomarkers—such as white matter hyperintensities (WMH), brain atrophy (BA), and regional gray matter volumes (rGMVs)—recent studies have demonstrated that even mild or asymptomatic alterations are associated with impaired driving behavior and increased crash risk. Emerging machine learning models that incorporate rGMVs have achieved high accuracy and specificity in identifying high-risk drivers, though sensitivity and precision remain limited when relying solely on structural MRI data. Japan’s Brain Dock system, an MRI-based brain healthcare screening program developed uniquely in Japan, provides a valuable infrastructure for large-scale neuroimaging-based risk assessment. Importantly, structural MRI biomarkers can be influenced by lifestyle improvements, such as quitting smoking and reducing alcohol consumption, as well as by the treatment of lifestyle-related diseases, including diabetes and hypertension. Overall, this review highlights the potential of neuroimaging-informed approaches to identify at-risk drivers and to support targeted preventive strategies, thereby contributing to both brain healthcare program and traffic safety in aging societies.
Authors: Kaechang Park, Handityo Aulia Putra
Language: English
Topic: Older Adults Driving Studies
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,290
Awards: Proposal of brain medical evidence for the continuation or surrender of driver's licenses for the elderly, Investigation of older drivers' aging effects of cognitive function on driving behavior, Traffic accident prediction method for elderly drivers using machine learning of MRI brain structure and DR safe driving confirmation behavior, 脳MRIデータに基づくあおり運転ドライバー事前判別法, 脳ドックの大規模MRIデータを用いた疲労感の脳神経基盤探求
OpenAlex ID: W7116759598