Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis

Objective To assess whether it is feasible to establish specific cut-off values able to discriminate 'physiological' or 'pathological' brain volume rates in patients with multiple sclerosis (MS). Methods The study was based on the analysis of longitudinal MRI data sets of patients with MS (n=206, 87% relapsing-remitting, 7% secondary progressive and 6% primary progressive) and healthy controls (HC; n=35). Brain atrophy rates were computed over a mean follow-up of 7.5 years (range 1-12) for patients with MS and 6.3 years (range 1-12.5) for HC with the SIENA software and expressed as annualised per cent brain volume change (PBVC/y). A weighted (on the follow-up length) receiver operating characteristic analysis and the area under the curve (AUC) were used for statistics. Results The weighted PBVC/y was -0.51±0.27% in patients with MS and -0.27±0.15% in HC (p<0.0001). There was a significant age-related difference in PBVC/y between HC older and younger than 35 years of age ( p=0.02), but not in patients with MS (p=0.8). The cutoff of PBVC/y, as measured by SIENA that could maximise the accuracy in discriminating patients with MS from HC, was -0.37%, with 67% sensitivity and 80% specificity. According to the observed distribution, values of PBVC/y as measured by SIENA that could define a pathological range were above -0.52% with 95% specificity, above -0.46% with 90% specificity and above -0.40% with 80% specificity. Conclusions Our evidence-based criteria provide values able to discriminate the presence or absence of 'pathological' brain volume loss in MS with high specificity. Such results could be of great value in a clinical setting, particularly in assessing treatment efficacy in MS

Improving the Characterization of Radiologically Isolated Syndrome Suggestive of Multiple Sclerosis

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