Gray matter MRI differentiates neuromyelitis optica from multiple sclerosis using random forest

Neurology. 2016 Dec 6;87(23):2463-2470. doi: 10.1212/WNL.0000000000003395. Epub 2016 Nov 2.

Abstract

Objective: We tested whether brain gray matter (GM) imaging measures can differentiate between multiple sclerosis (MS) and neuromyelitis optica (NMO) using random-forest classification.

Methods: Ninety participants (25 patients with MS, 30 patients with NMO, and 35 healthy controls [HCs]) were studied in Tehran, Iran, and 54 (24 patients with MS, 20 patients with NMO, and 10 HCs) in Padua, Italy. Participants underwent brain T1 and T2/fluid-attenuated inversion recovery MRI. Volume, thickness, and surface of 50 cortical GM regions and volumes of the deep GM nuclei were calculated and used to construct 3 random-forest models to classify patients as either NMO or MS, and separate each patient group from HCs. Clinical diagnosis was the gold standard against which the accuracy was calculated.

Results: The classifier distinguished patients with MS, who showed greater atrophy especially in deep GM, from those with NMO with an average accuracy of 74% (sensitivity/specificity: 77/72; p < 0.01). When we used thalamic volume (the most discriminating GM measure) together with the white matter lesion volume, the accuracy of the classification of MS vs NMO was 80%. The classifications of MS vs HCs and NMO vs HCs achieved higher accuracies (92% and 88%).

Conclusions: GM imaging biomarkers, automatically obtained from clinical scans, can be used to distinguish NMO from MS, even in a 2-center setting, and may facilitate the differential diagnosis in clinical practice.

Classification of evidence: This study provides Class II evidence that GM imaging biomarkers can distinguish patients with NMO from those with MS.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Atrophy
  • Brain / diagnostic imaging*
  • Diagnosis, Differential
  • Disability Evaluation
  • Female
  • Gray Matter / diagnostic imaging*
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Male
  • Multiple Sclerosis, Relapsing-Remitting / classification
  • Multiple Sclerosis, Relapsing-Remitting / diagnostic imaging*
  • Neuromyelitis Optica / classification
  • Neuromyelitis Optica / diagnostic imaging*
  • Organ Size
  • Retrospective Studies