Clinical correlations of brain lesion distribution in multiple sclerosis

Research output: Contribution to journalJournal articleResearchpeer-review

  • M M Vellinga
  • J J G Geurts
  • Rostrup, Egill
  • B M J Uitdehaag
  • C H Polman
  • F Barkhof
  • H Vrenken
PURPOSE: To explore relations between spatial distribution of multiple sclerosis (MS) lesions, and disability. In MS, the presence of asymptomatic brain lesions challenges the prediction of disability based on conventional brain MRI. Hypothesizing that symptomatology may partly be determined by lesion location, this retrospective study explored relations between lesion location and disability using voxelwise analyses in standard space. MATERIALS AND METHODS: Using nonparametric permutation-based statistics, voxelwise lesion probability on T2 lesion masks was related to expanded disability status scale (EDSS) and MS functional composite (MSFC) subdomain scores and demographic characteristics of 325 MS patients. To identify statistically significant locations, a cluster-forming threshold of 3.1 was used. RESULTS: In clusters in the periventricular region, lesion probability correlated significantly (P < 0.001) with disability and disease duration, and was higher in progressive than in relapsing disease. When controlled for lesion load (LL), no significant clusters survived. Presence and number of spinal cord lesions did not correlate with lesion probability in any location, and did not influence correlations with disability when included in its analyses. CONCLUSION: Periventricular lesions were related to disability. LL influenced relations between disability and lesion probability throughout the brain, suggesting interplay between lesional burden and its location in determining disability in MS.
Original languageEnglish
JournalJournal of Magnetic Resonance Imaging
Volume29
Issue number4
Pages (from-to)768-73
Number of pages5
ISSN1053-1807
DOIs
Publication statusPublished - 2009

Bibliographical note

Keywords: Adult; Brain Mapping; Cross-Sectional Studies; Disability Evaluation; Female; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Middle Aged; Multiple Sclerosis; Retrospective Studies; Statistics, Nonparametric

ID: 21336966