Harnessing routine MRI for the early screening of Parkinson’s disease: a multicenter machine learning study using T2-weighted FLAIR imaging

Harnessing routine MRI for the early screening of Parkinson’s disease: a multicenter machine learning study using T2-weighted FLAIR imaging

Abstract Objective To explore the potential of radiomics features derived from T2-weighted fluid-attenuated inversion recovery (T2W FLAIR) images to distinguish idiopathic Parkinson’s disease (PD) patients from healthy controls (HCs). Methods T2W FLAIR images from 1727 subjects were retrospectively...

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Bibliographic Details
Main Authors: Junyan Fu, Hongyi Chen, Chengling Xu, Zhongzheng Jia, Qingqing Lu, Haiyan Zhang, Yue Hu, Kun Lv, Jun Zhang, Daoying Geng
Format: Article
Language:English
Published: SpringerOpen 2025-04-01
Series:Insights into Imaging
Subjects:
Parkinson’s disease
Machine learning
Magnetic resonance imaging
Substantia nigra
Putamen
Online Access:https://doi.org/10.1186/s13244-025-01961-3
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https://doi.org/10.1186/s13244-025-01961-3

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