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Advancements in diffusion kurtosis imaging for assessing microstructural alterations in the brain associated with Parkinson's disease
FU Jiajie  WANG Song  ZHAO Qiufeng 

DOI:10.12015/issn.1674-8034.2026.07.016.


[Abstract] Parkinson's disease (PD) has insidious early manifestations, and conventional magnetic resonance imaging (MRI) is limited in detecting brain microstructural abnormalities. Therefore, sensitive and noninvasive imaging methods are urgently needed for early identification and disease assessment. Diffusion kurtosis imaging (DKI) can quantify the non-Gaussian diffusion characteristics of water molecules and sensitively reflect the complexity and heterogeneity of brain tissue microstructure, showing important value in recent studies of PD-related brain microstructural changes. However, current findings remain inconsistent because of differences in sample size, disease stage, clinical subtype, scanning protocols, and post-processing methods, highlighting the need for a systematic review. This article first outlines the technical principles and major parameters of DKI, and then focuses on its applications in gray matter nuclei, white matter fiber tracts, neural circuits, and the glymphatic system in PD. The potential value of DKI combined with artificial intelligence (AI) in auxiliary diagnosis and clinical phenotyping is also discussed. Finally, this review analyzes the current research limitations and future directions, aiming to provide references for the in-depth research and clinical application of DKI in PD.
[Keywords] Parkinson's disease；magnetic resonance imaging；diffusion kurtosis imaging；artificial intelligence；brain microstructure；glymphatic system

FU Jiajie   WANG Song   ZHAO Qiufeng*  

Department of Radiology, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China

Corresponding author: ZHAO Q F, E-mail: qiufengzhao2012@163.com

Conflicts of interest   None.

Received  2026-04-01
Accepted  2026-06-09
DOI: 10.12015/issn.1674-8034.2026.07.016
DOI:10.12015/issn.1674-8034.2026.07.016.

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