Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis

Bruno Alfano, Arturo Brunetti, Michele Larobina, Mario Quarantelli, Enrico Tedeschi, Andrea Ciarmiello, Eugenio M. Covelli, Marco Salvatore

Research output: Contribution to journalArticlepeer-review

Abstract

A fully automated magnetic resonance (MR) segmentation method for identification and volume measurement of demyelinated white matter has been developed. Spin-echo MR brain scans were performed in 38 patients with multiple sclerosis (MS) and in 46 healthy subjects. Segmentation of normal tissues and white matter lesions (WML) was obtained, based on their relaxation rates and proton density maps. For WML identification, additional criteria included three-dimensional (3D) lesion shape and surrounding tissue composition. Segmented images were generated, and normal brain tissues and WML volumes were obtained. Sensitivity, specificity, and reproducibility of the method were calculated, using the WML identified by two neuroradiologists as the gold standard. The average volume of 'abnormal' white matter in normal subjects (false positive) was 0.11 ml (range 0-0.59 ml). In MS patients the average WML volume was 31.0 ml (range 1.1-132.5 ml), with a sensitivity of 87.3%. In the reproducibility study, the mean SD of WML volumes was 2.9 ml. The procedure appears suitable for monitoring disease changes over time. (C) 2000 Wiley-Liss, Inc.

Original languageEnglish
Pages (from-to)799-807
Number of pages9
JournalJournal of Magnetic Resonance Imaging
Volume12
Issue number6
DOIs
Publication statusPublished - 2000

Keywords

  • Brain
  • Multiple sclerosis
  • Segmentation
  • Volume measurement

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Fingerprint

Dive into the research topics of 'Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis'. Together they form a unique fingerprint.

Cite this