title: MRI as a marker for disease heterogeneity in multiple sclerosis.
abstract: BACKGROUND
  Whereas recent data from imaging studies challenge the prevailing notion that multiple sclerosis (MS) is purely an inflammatory disease, pathologic studies suggest differences in the disease processes between individual patients with MS. The ability to dissect the pathophysiologic disease heterogeneity, if it indeed exists, by methodologies that can be applied in vivo is important both for the development of new therapeutics and for the ability to identify the optimal therapy for an individual patient.
  
  
  OBJECTIVE
  To design a stratification algorithm for patients with MS based on accepted MRI measurements reflective of inflammation and axonal damage/tissue loss and to assess if such MS subgroups retain their intergroup differences long term.
  
  
  METHODS
  Mathematical modeling was used to select three discriminatory MRI measures for clinical outcome based on the cross-sectional analysis of 71 patients with untreated MS and tested general applicability of the stratification scheme on the independent longitudinal cohort of 71 MS patients.
  
  
  RESULTS
  By consecutive employment of MRI measures reflective of inflammation and tissue loss, the authors were able to separate MS patients into four clinically meaningful subgroups. The analysis of the longitudinal confirmatory cohort demonstrated persistence of the intergroup differences in selected MRI measures for 8 years.
  
  
  CONCLUSIONS
  The inflammatory activity and destructiveness of the multiple sclerosis process are to some degree independent of each other, and the successive evaluation of both of these variables can strengthen prediction of clinical outcome in individual patients.
authors.affiliation: Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892-1400, USA. bielekob@ninds.nih.gov
authors.forename: B
authors.initials: B
authors.lastname: Bielekova
authors.forename: N
authors.initials: N
authors.lastname: Kadom
authors.forename: E
authors.initials: E
authors.lastname: Fisher
authors.forename: N
authors.initials: N
authors.lastname: Jeffries
authors.forename: J
authors.initials: J
authors.lastname: Ohayon
authors.forename: N
authors.initials: N
authors.lastname: Richert
authors.forename: T
authors.initials: T
authors.lastname: Howard
authors.forename: C N
authors.initials: CN
authors.lastname: Bash
authors.forename: J A
authors.initials: JA
authors.lastname: Frank
authors.forename: L
authors.initials: L
authors.lastname: Stone
authors.forename: R
authors.initials: R
authors.lastname: Martin
authors.forename: G
authors.initials: G
authors.lastname: Cutter
authors.forename: H F
authors.initials: HF
authors.lastname: McFarland
mesh_terms: D000328:Adult; D000465:Algorithms; D001369:Axons / Q000473:pathology; D015415:Biomarkers; D002490:Central Nervous System / Q000473:pathology / Q000503:physiopathology; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D003937:Diagnosis, Differential; D018450:Disease Progression; D005260:Female; D006801:Humans; D007249:Inflammation / Q000175:diagnosis / Q000503:physiopathology; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009103:Multiple Sclerosis / Q000145:classification* / Q000175:diagnosis* / Q000503:physiopathology; D011237:Predictive Value of Tests; D011379:Prognosis; D014855:Wallerian Degeneration / Q000175:diagnosis* / Q000503:physiopathology
chemical_list: D015415:Biomarkers