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Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study.

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Resting-state fMRI (rs-fMRI) successfully identified reproducible Parkinson's disease (PD) brain patterns (fPDRP) across sites, offering a non-invasive alternative to PET scans for disease assessment.

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Area of Science:

  • Neuroimaging
  • Medical Physics
  • Neurology

Background:

  • Metabolic imaging, like PET, detects disease patterns but involves radiation exposure.
  • Parkinson's disease-related pattern (PDRP) is a validated metabolic topography.
  • Non-invasive methods are sought for disease network detection.

Purpose of the Study:

  • To validate a non-invasive resting-state fMRI (rs-fMRI) derived Parkinson's disease pattern (fPDRP) across different patient populations and sites.
  • To compare the reproducibility of fPDRP topography and expression between two independent cohorts.
  • To assess the correlation of fPDRP expression with clinical motor disability in Parkinson's disease patients.

Main Methods:

  • Utilized independent component analysis (ICA) and bootstrap resampling on rs-fMRI data.
  • Validated the fPDRPNS pattern in a new cohort from Cologne, Germany, and identified a local pattern, fPDRPCOL.
  • Compared topographical similarity and expression levels between fPDRPNS and fPDRPCOL, and correlated with clinical motor scores.

Main Results:

  • fPDRPNS and fPDRPCOL showed topographical similarity, with key contributions from the putamen, globus pallidus, pons, cerebellum, and thalamus.
  • Expression levels of both fPDRP patterns were significantly correlated within each patient group.
  • Abnormal elevations in fPDRPCOL core expression were observed in PD patients compared to controls, and correlations with motor disability were significant.

Conclusions:

  • rs-fMRI derived fPDRP networks are reproducible across different patient populations, clinical sites, and scanning platforms.
  • This non-invasive rs-fMRI approach offers a viable alternative to metabolic PET for quantitative assessment of disease networks in Parkinson's disease.
  • The findings support the use of rs-fMRI for clinical disease monitoring and research.