title: Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis.
abstract: OBJECTIVE
  To assess in a large population of patients with clinically isolated syndrome (CIS) the relevance of brain lesion location and frequency in predicting 1-year conversion to multiple sclerosis (MS).
  
  
  METHODS
  In this multicenter, retrospective study, clinical and MRI data at onset and clinical follow-up at 1 year were collected for 1,165 patients with CIS. On T2-weighted MRI, we generated lesion probability maps of white matter (WM) lesion location and frequency. Voxelwise analyses were performed with a nonparametric permutation-based approach (p < 0.05, cluster-corrected).
  
  
  RESULTS
  In CIS patients with hemispheric, multifocal, and brainstem/cerebellar onset, lesion probability map clusters were seen in clinically eloquent brain regions. Significant lesion clusters were not found in CIS patients with optic nerve and spinal cord onset. At 1 year, clinically definite MS developed in 26% of patients. The converting group, despite a greater baseline lesion load compared with the nonconverting group (7 ± 8.1 cm3 vs. 4.6 ± 6.7 cm3, p < 0.001), showed less widespread lesion distribution (18% vs. 25% of brain voxels occupied by lesions). High lesion frequency was found in the converting group in projection, association, and commissural WM tracts, with larger clusters being in the corpus callosum, corona radiata, and cingulum.
  
  
  CONCLUSIONS
  Higher frequency of lesion occurrence in clinically eloquent WM tracts can characterize CIS subjects with different types of onset. The involvement of specific WM tracts, in particular those traversed by fibers involved in motor function and near the corpus callosum, seems to be associated with a higher risk of clinical conversion to MS in the short term.
authors.affiliation: Department of Neurological and Behavioral Sciences, University of Siena, Siena.
authors.forename: Antonio
authors.initials: A
authors.lastname: Giorgio
authors.forename: Marco
authors.initials: M
authors.lastname: Battaglini
authors.forename: Maria Assunta
authors.initials: MA
authors.lastname: Rocca
authors.forename: Alessandro
authors.initials: A
authors.lastname: De Leucio
authors.forename: Martina
authors.initials: M
authors.lastname: Absinta
authors.forename: Ronald
authors.initials: R
authors.lastname: van Schijndel
authors.forename: Alex
authors.initials: A
authors.lastname: Rovira
authors.forename: Mar
authors.initials: M
authors.lastname: Tintoré
authors.forename: Declan
authors.initials: D
authors.lastname: Chard
authors.forename: Olga
authors.initials: O
authors.lastname: Ciccarelli
authors.forename: Christian
authors.initials: C
authors.lastname: Enzinger
authors.forename: Claudio
authors.initials: C
authors.lastname: Gasperini
authors.forename: Jette
authors.initials: J
authors.lastname: Frederiksen
authors.forename: Massimo
authors.initials: M
authors.lastname: Filippi
authors.forename: Frederik
authors.initials: F
authors.lastname: Barkhof
authors.forename: Nicola
authors.initials: N
authors.lastname: De Stefano
mesh_terms: D000328:Adult; D017668:Age of Onset; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D016000:Cluster Analysis; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D009103:Multiple Sclerosis / Q000473:pathology*; D012189:Retrospective Studies