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Multicenter data harmonization for regional brain atrophy and application in multiple sclerosis.

Elisabetta Pagani1, Loredana Storelli1, Patrizia Pantano2,3

  • 1Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.

Journal of Neurology
|September 24, 2022
PubMed
Summary
This summary is machine-generated.

Harmonizing multicenter MRI data using subsampling improves the accuracy of brain atrophy analysis in multiple sclerosis (MS). This method enhances the robustness of findings, identifying key areas like the thalamus and cerebellum affected in MS patients.

Keywords:
HarmonizationMulticenterMultiple sclerosisRegional atrophyVBM

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Area of Science:

  • Neuroimaging
  • Biostatistics
  • Neurology

Background:

  • Assessing regional brain atrophy is crucial in multiple sclerosis (MS) for clinical relevance.
  • Analyzing large, multicenter datasets for MS research is challenging due to data variability.

Purpose of the Study:

  • To compare data harmonization methods for correcting center effects in multicenter neuroimaging studies.
  • To investigate regional gray matter (GM) volume differences in relapsing-remitting MS using a large multicenter dataset.

Main Methods:

  • Voxel-based morphometry (VBM) was applied to MRI scans from 466 MS patients and 279 healthy controls (HC).
  • Four methods were compared to correct for center effects: no correction, statistical modeling, ComBat, and subsampling.
  • Gray matter atrophy was assessed in MS patients versus HC and correlated with clinical disability and T2 lesion volume.

Main Results:

  • The subsampling harmonization method most effectively reduced statistical model residuals (2.98 vs. 5.03 without correction).
  • Multicenter analysis revealed atrophy in the thalami, deep GM nuclei, cerebellum, and cortical regions in MS patients.
  • Thalamic atrophy was consistently detected across single-center analyses, while other regions varied.

Conclusions:

  • Subsampling-based harmonization is superior for reducing statistical residuals and enhancing multicenter data analysis robustness.
  • Multicenter findings, particularly regarding thalamic and cerebellar atrophy, are more reliable than single-center results.
  • The study underscores the value of large, harmonized, multicenter data repositories for advancing MS research.