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Functional MRI in Multiple System Atrophy: A Promising Biomarker for Clinical Applications.

Shuying Xiao1,2, Yuchuan Ding3, Alexander Weiss3

  • 1Department of Neurology, Beijing Luhe Hospital, Capital Medical University, Beijing, People's Republic of China.

Neuropsychiatric Disease and Treatment
|February 25, 2026
PubMed
Summary
This summary is machine-generated.

Functional magnetic resonance imaging (fMRI) shows promise for diagnosing multiple system atrophy (MSA) subtypes and distinguishing it from Parkinson's disease (PD) and progressive supranuclear palsy (PSP). This neuroimaging technique offers insights into disease progression and treatment evaluation.

Keywords:
brain networksfunctional connectivityneurodegenerationsynucleinopathy

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Area of Science:

  • Neuroimaging
  • Neurodegenerative Diseases
  • Biomarker Discovery

Background:

  • Multiple system atrophy (MSA) presents diagnostic challenges due to clinical heterogeneity and α-synuclein pathology.
  • Functional magnetic resonance imaging (fMRI) offers potential for enhanced diagnostic precision by identifying network connectivity abnormalities.
  • fMRI may reflect underlying pathological changes and provide mechanistic insights into MSA.

Purpose of the Study:

  • To explore the utility of resting-state fMRI (rs-fMRI) and task-based fMRI (t-fMRI) in characterizing MSA subtypes and differentiating it from related disorders.
  • To assess fMRI's potential in evaluating treatment effects and understanding disease progression.
  • To highlight the need for standardized protocols and larger trials for robust fMRI biomarker development.

Main Methods:

  • Utilized resting-state fMRI (rs-fMRI) to analyze network connectivity patterns in different MSA subtypes (MSA-P and MSA-C).
  • Investigated rs-fMRI's ability to differentiate MSA from Parkinson's disease (PD) and progressive supranuclear palsy (PSP) based on cerebellar-cortical connectivity.
  • Considered task-based fMRI (t-fMRI) for assessing motor network integration.

Main Results:

  • Rs-fMRI identified distinct connectivity patterns for MSA-P (basal ganglia-cortical disruption) and MSA-C (cerebellar-cortical disconnection).
  • Rs-fMRI successfully distinguished MSA from PD and PSP by revealing characteristic cerebellar-cortical network disruptions.
  • Task-based fMRI indicated impairments in motor network integration.

Conclusions:

  • fMRI serves as a promising tool for MSA subtype classification and differential diagnosis from PD and PSP.
  • fMRI provides insights into symptom-specific network dysfunction and aids in evaluating therapeutic interventions.
  • Future research should focus on large, multicenter trials with standardized protocols to establish reliable fMRI biomarkers for MSA.