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JNNP: Application of gray matter volume model to predict disability progression and cognitive deterioration in patients with multiple sclerosis

 Last Update: 2021-05-08
 Source: Internet
 Author: User

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Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system.

Neurodegeneration is manifested by brain atrophy, which can be measured by MRI.

Independent component analysis (ICA) is a powerful data-driven technique that has been used to identify brain networks on structural MRI.

Use MRI and baseline and longitudinal data from the extended disability status scale, nine-hole Peg test (9HPT) and symbolic digital mode test (SDMT) in clinical trials of 988 SPMS patients.

Visual representation of image analysis

Consensus other region out of a total of 15 kinds of characteristic variations GM.

consensus

Stable independent component analysis (ICA) component.

In short, some covariant GM regional models are more predictive of disability progression than single-region or whole-brain measurements.

ColatoE ,StuttersJ ,TurC ColatoEColato StuttersJStutters TurCTur, et albmj.

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