title: Magnetization transfer MRI metrics predict the accumulation of disability 8 years later in patients with multiple sclerosis.
abstract: In multiple sclerosis, the relationship between conventional MRI findings and the clinical evolution of the disease is weak. Magnetization transfer (MT) MRI can provide markers reflecting the more disabling features of multiple sclerosis pathology. The aim of the present study was to assess the value of MT MRI quantities and their short-term changes in predicting the long-term accumulation of disability in multiple sclerosis patients. Conventional and MT MRI scans of the brain were obtained at baseline and after 12 months in 73 patients, who were followed prospectively with clinical visits for a median period of 8 years. At baseline and at 12 months, T2-hyperintense and T1-hypointense lesion volume, normalized brain volume [with grey (GM) and white matter (WM) fractions] and average lesion MT ratio (MTR) were measured. At the two time points, metrics derived from the MTR histograms of the whole-brain parenchyma, GM and normal-appearing WM were also computed. A multivariate analysis, adjusted for follow-up duration, was performed to establish which variables were significant predictors of long-term neurological deterioration. At the end of follow-up, 44 patients (60%) showed a significant disability worsening. A multivariable model included baseline GM MTR histogram peak height [P = 0.029, odds ratio (OR) = 0.97], and average lesion MTR percentage change after 12 months (P = 0.016, OR = 0.88) as independent predictors of disability worsening at 8 years (r2 = 0.28). The discriminating ability of such a model in predicting the individual patients' outcome was 66%. MT MRI provides useful prognostic markers for the prediction of the long-term evolution of multiple sclerosis. This study also suggests that GM damage is one of the key factors associated with disability accumulation in this 'white matter' condition.
authors.affiliation: Neuroimaging Research Unit, San Raffaele Scientific Institute, Milan, Italy.
authors.forename: Federica
authors.initials: F
authors.lastname: Agosta
authors.forename: Marco
authors.initials: M
authors.lastname: Rovaris
authors.forename: Elisabetta
authors.initials: E
authors.lastname: Pagani
authors.forename: Maria Pia
authors.initials: MP
authors.lastname: Sormani
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Comi
authors.forename: Massimo
authors.initials: M
authors.lastname: Filippi
mesh_terms: D001921:Brain / Q000473:pathology*; D016022:Case-Control Studies; D018450:Disease Progression; D005500:Follow-Up Studies; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D009103:Multiple Sclerosis / Q000175:diagnosis*; D011336:Probability; D011379:Prognosis; D011446:Prospective Studies