title: Improving the characterization of radiologically isolated syndrome suggestive of multiple sclerosis.
abstract: OBJECTIVE
  To improve the characterization of asymptomatic subjects with brain magnetic resonance imaging (MRI) abnormalities highly suggestive of multiple sclerosis (MS), a condition named as "radiologically isolated syndrome" (RIS).
  
  
  METHODS
  Quantitative MRI metrics such as brain volumes and magnetization transfer (MT) were assessed in 19 subjects previously classified as RIS, 20 demographically-matched relapsing-remitting MS (RRMS) patients and 20 healthy controls (HC). Specific measures were: white matter (WM) lesion volumes (LV), total and regional brain volumes, and MT ratio (MTr) in lesions, normal-appearing WM (NAWM) and cortex.
  
  
  RESULTS
  LV was similar in RIS and RRMS, without differences in distribution and frequency at lesion mapping. Brain volumes were similarly lower in RRMS and RIS than in HC (p<0.001). Lesional-MTr was lower in RRMS than in RIS (p = 0.048); NAWM-MTr and cortical-MTr were similar in RIS and HC and lower (p<0.01) in RRMS. These values were particularly lower in RRMS than in RIS in the sensorimotor and memory networks. A multivariate logistic regression analysis showed that 13/19 RIS had ≥70% probability of being classified as RRMS on the basis of their brain volume and lesional-MTr values.
  
  
  CONCLUSIONS
  Macroscopic brain damage was similar in RIS and RRMS. However, the subtle tissue damage detected by MTr was milder in RIS than in RRMS in clinically relevant brain regions, suggesting an explanation for the lack of clinical manifestations of subjects with RIS. This new approach could be useful for narrowing down the RIS individuals with a high risk of progression to MS.
authors.affiliation: Department of Neurological and Behavioral Sciences, University of Siena, Siena, Italy. destefano@unisi.it
authors.forename: Nicola
authors.initials: N
authors.lastname: De Stefano
authors.forename: Maria Laura
authors.initials: ML
authors.lastname: Stromillo
authors.forename: Francesca
authors.initials: F
authors.lastname: Rossi
authors.forename: Marco
authors.initials: M
authors.lastname: Battaglini
authors.forename: Antonio
authors.initials: A
authors.lastname: Giorgio
authors.forename: Emilio
authors.initials: E
authors.lastname: Portaccio
authors.forename: Bahia
authors.initials: B
authors.lastname: Hakiki
authors.forename: Gianmichele
authors.initials: G
authors.lastname: Malentacchi
authors.forename: Claudio
authors.initials: C
authors.lastname: Gasperini
authors.forename: Mario
authors.initials: M
authors.lastname: Santangelo
authors.forename: Maria Letizia
authors.initials: ML
authors.lastname: Bartolozzi
authors.forename: Maria Pia
authors.initials: MP
authors.lastname: Sormani
authors.forename: Antonio
authors.initials: A
authors.lastname: Federico
authors.forename: Maria Pia
authors.initials: MP
authors.lastname: Amato
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D016022:Case-Control Studies; D003952:Diagnostic Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000175:diagnosis* / Q000473:pathology; D012044:Regression Analysis