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Altered Brain Volume, Microstructure Metrics and Functional Connectivity Features in Multiple System Atrophy.

Yunxiang Ge1, Weimin Zheng2, Yujia Li1

  • 1Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China.

Frontiers in Aging Neuroscience
|June 6, 2022
PubMed
Summary

Multiple System Atrophy with cerebellar ataxia (MSA-c) shows brain volume, microstructure, and functional connectivity changes. Multimodal MRI identified sensitive biomarkers for diagnosing MSA-c and understanding its neural mechanisms.

Keywords:
extended network-based statisticsmicrostructure metricsmultimodal MRImultiple system atrophysupport vector machine

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Area of Science:

  • Neuroimaging
  • Neurology
  • Biomarkers

Background:

  • Multiple System Atrophy with cerebellar ataxia (MSA-c) is a neurodegenerative disorder.
  • Understanding its specific pathological patterns is crucial for diagnosis and treatment.

Purpose of the Study:

  • To deeply understand volume, microstructure, and functional changes in MSA-c.
  • To identify sensitive neuroimaging biomarkers for MSA-c diagnosis.

Main Methods:

  • Structural MRI (T1-weighted imaging), Diffusion Tensor Imaging (DTI), and functional MRI (BOLD fMRI) were used.
  • Extended Network-Based Statistics (extended-NBS) and Support Vector Machine (SVM) classifier were applied.
  • Correlations between imaging features and UMSARS scores were explored.

Main Results:

  • Significant grey matter atrophy in the cerebellum and white matter abnormalities in the cerebellum and other brain regions were observed.
  • Altered functional connectivity related to cerebellar sub-regions was identified.
  • Specific imaging features were found to be sensitive biomarkers for differentiating MSA-c from healthy controls.

Conclusions:

  • Multimodal neuroimaging provides insights into the neural pathophysiological mechanisms of MSA-c.
  • Identified imaging biomarkers can aid in the diagnosis of MSA-c.