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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

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Neurological disability and brain grey matter atrophy in primary progressive multiple sclerosis are determined by

Theodoros Ladopoulos1,2, Zainab Abbas3, Britta Krieger4

  • 1Department of Neurology, St Josef Hospital, Ruhr University, Gudrunstr. 56, 44791, Bochum, Germany. Theodoros.Ladopoulos@rub.de.

Journal of Neurology
|April 1, 2025
PubMed
Abstract

Insights

Quantitative MRI measures of multiple sclerosis (MS) lesions, not just lesion load, correlate with grey matter atrophy and disability in progressive MS. These findings highlight differences in lesion pathology between MS subtypes.

Area of Science:

  • Neuroimaging
  • Neurology
  • Radiology

Background:

  • Conventional MRI metrics like lesion count and volume in multiple sclerosis (MS) lack specificity and fail to fully explain clinical disability or brain atrophy.
  • Demyelinating plaques show distinct histopathological features across relapsing and progressive MS subtypes.
  • Quantitative MRI offers a more detailed assessment of MS lesions and their impact.

Purpose of the Study:

  • To evaluate microstructural characteristics of MS lesions using quantitative MRI.
  • To investigate the associations between these quantitative MRI parameters, grey matter (GM) atrophy, and clinical disability in different MS subtypes.

Main Methods:

  • 56 control subjects, 121 relapsing-remitting MS (RRMS) patients, and 38 primary progressive MS (PPMS) patients underwent 1.5 T MRI scans and clinical assessments.
  • Lesion and brain segmentation were performed using SAMSEG; relaxation rates and myelin volume fraction were estimated using MDME sequence and SyMRI software.
  • Associations between quantitative MRI parameters (lesional and normal-appearing white matter) with GM atrophy and clinical disability were analyzed.

Main Results:

  • PPMS patients exhibited significantly decreased brain regional volumes and quantitative lesional/NAWM MRI parameters compared to RRMS patients.
  • Quantitative lesional MRI parameters were significantly associated with cortical/deep GM volumes and disability scores in both RRMS and PPMS, particularly in PPMS.
  • Unlike in RRMS, lesion volume alone did not correlate with GM atrophy or clinical disability in the PPMS group.

Conclusions:

  • Quantitative MRI measures of MS lesions, unlike simple lesion load, strongly correlate with clinical disability and GM atrophy in PPMS.
  • These findings suggest distinct lesion pathologies contribute to disease progression in different MS subtypes.
  • Quantitative MRI provides valuable insights into the relationship between lesion characteristics and clinical outcomes in MS.
Keywords:
Advanced neuroimagingEDSSGrey matter atrophyMDMEMRIMultiple sclerosis

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