Quantitative assessment of brain glymphatic imaging features using deep learning-based EPVS segmentation and DTI-ALPS analysis in Alzheimer’s disease

BackgroundThis study aimed to quantitatively evaluate brain glymphatic imaging features in patients with Alzheimer’s disease (AD), amnestic mild cognitive impairment (aMCI), and normal controls (NC) by applying a deep learning-based method for the automated segmentation of enlarged perivascular spac...

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Bibliographic Details
Main Authors:	Fenyang Chen, Tiantian Heng, Qi Feng, Rui Hua, Jiaojiao Wu, Feng Shi, Zhengluan Liao, Keyin Qiao, Zhiliang Zhang, Jianliang Miao
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-07-01
Series:	Frontiers in Aging Neuroscience
Subjects:	Alzheimer’s disease amnestic mild cognitive impairment glymphatic system V-shape bottleneck network enlarged perivascular space diffusion tensor imaging along perivascular spaces
Online Access:	https://www.frontiersin.org/articles/10.3389/fnagi.2025.1621106/full
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Quantitative assessment of brain glymphatic imaging features using deep learning-based EPVS segmentation and DTI-ALPS analysis in Alzheimer’s disease

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