Measuring progression of cerebral white matter lesions on MRI: visual rating and volumetrics

Neurology. 2004 May 11;62(9):1533-9. doi: 10.1212/01.wnl.0000123264.40498.b6.

Abstract

Objective: To evaluate the concordance of a volumetric method for measuring white matter lesion (WML) change with visual rating scales.

Methods: The authors selected a stratified sample of 20 elderly people (mean age 72 years, range 61 to 88 years) with an MRI examination at baseline and at 3-year follow-up from the community-based Rotterdam Scan Study (RSS). Four raters assessed WML change with four different visual rating scales: the Fazekas scale, the Scheltens scale, the RSS scale, and a new visual rating scale that was designed to measure change in WML. The authors assessed concordance with a volumetric method with scatter plots and correlations, and interobserver agreement with intraclass correlation coefficients.

Results: For assessment of change in WML, the Fazekas, Scheltens, and periventricular part of the RSS scale showed little correlation with volumetrics, and low interobserver agreement. The authors' new WML change scale and the subcortical part of the RSS scale showed good correlation with volumetrics. After additional training, the new WML change scale showed good interobserver agreement for measuring WML change.

Conclusions: Commonly used visual rating scales are not well suited for measuring change in white matter lesion severity. The authors' new white matter lesion change scale is more accurate and precise, and may be of use in studies focusing on progression of white matter lesions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Brain / pathology*
  • Brain Diseases / diagnosis
  • Brain Diseases / pathology*
  • Diagnosis, Computer-Assisted / statistics & numerical data
  • Disease Progression
  • Follow-Up Studies
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging / statistics & numerical data*
  • Middle Aged
  • Observer Variation
  • Research Design
  • Sensitivity and Specificity
  • Severity of Illness Index