A Review on white matter changes in Parkinson’s disease detected by diffusion MRI

Abstract

Parkinson’s disease (PD), a progressive neurodegenerative disorder prevalent among the elderly, requires a deeper understanding of brain structural changes for improved diagnosis and treatment. Because of its clinical complexity, early identification of PD remains challenging, with diagnosis often taking up to 2.9 years from when a patient first begins to experience symptoms, with 80.6% accuracy. To address this, integrating computational neuroimaging techniques like diffusion MRI, as it reveals brain structural changes, particularly in white matter. This review focuses on using diffusion MRI to explore white matter alterations in PD, highlighting its role in identifying axonal abnormalities across different stages and subtypes of the disease. By examining major fiber bundles through tractography, analyzing brain networks using graph theory, and applying deep learning techniques for pattern recognition, we review widespread microstructural damage and structural disconnections in key white matter regions using the PRISMA model to examine relevant studies covering the period from 2013 to 2023. Unlike previous reviews, we comprehensively evaluate the white matter changes from both technical and clinical perspectives. These findings suggest paths for future research to enhance our understanding and improve prevention, early diagnosis, and treatment strategies for PD, ultimately advancing the clinical utility of diffusion MRI.