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Article Dans Une Revue European Journal of Neurology Année : 2017

Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis

Résumé

Background: Assessing survival is a critical issue in patients with Amyotrophic Lateral Sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by MRI and disease progression. Aim of the study was than to determine the predictive added value of multimodal SC MRI on survival. Methods: 49 ALS patients were recruited and clinical data collected. Patients were scored on ALSFRS-R and manual muscle testing. They were followed longitudinally to assess survival. Cervical spinal cord was imaged using 3T MRI system. Cord volume and cross-sectional area (CSA) at each vertebral level were computed. DTI metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. Results: When building a multivariate Cox regression model with clinical and MRI parameters, FA, MTR, and CSA at C2-C3, C4-C5, C5-C6 and C6-C7 vertebral levels were significant. Moreover, hazard ratio (HR) calculated for CSA at C3-C4 and C5-C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had HR very close to 1. Conclusions: We suggest that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, results confirmation in independent bigger cohorts of patients is warranted.
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Dates et versions

hal-01540346 , version 1 (16-06-2017)

Identifiants

Citer

G. Querin, M. M. El Mendili, T. Lenglet, S. Delphine, V. Marchand-Pauvert, et al.. Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis. European Journal of Neurology, 2017, ⟨10.1111/ene.13329⟩. ⟨hal-01540346⟩
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