Application of voxelwise analysis in the detection of regions of reduced fractional anisotropy in multiple sclerosis patients

J Magn Reson Imaging. 2007 Sep;26(3):552-6. doi: 10.1002/jmri.21076.

Abstract

Purpose: To investigate the utility of voxelwise analysis in the detection of lesions in the normal appearing white matter (NAWM) of individual multiple sclerosis (MS) patients.

Materials and methods: Diffusion tensor imaging (DTI) was performed on 10 normal controls and six patients with MS lesions. The fractional anisotropy (FA) maps derived from the diffusion-weighted images were then spatially normalized (via an affine transformation) into Montreal Neurological Institute (MNI) space, and the normalized FA map of each of the patients was compared voxelwise with the normalized FA maps of the group of normals in a one-sample t-test (P = 0.0001). Two independent board-certified neuroradiologists reviewed the data.

Results: In the patient data for all six cases, the two reviewers determined detection sensitivities of 72% and 96% for the voxelwise technique based on known fluid-attenuated inversion-recovery (FLAIR) lesions. In addition, between the two reviewers, nine NAWM regions exhibiting FA reductions were identified in the six patients. However, numerous regions of abnormal FA were detected that were attributed to poor intersubject image registration.

Conclusion: Voxelwise analysis of spatially normalized FA maps has the potential to identify regions of FA reduction in lesions and in the NAWM of individual MS patients in a rapid and reproducible fashion. J. Magn. Reson. Imaging 2007;26:552-556. (c) 2007 Wiley-Liss, Inc.

MeSH terms

  • Adult
  • Anisotropy
  • Brain / pathology
  • Diffusion Magnetic Resonance Imaging / methods
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Middle Aged
  • Models, Statistical
  • Multiple Sclerosis / diagnosis*
  • Multiple Sclerosis / diagnostic imaging*
  • Neurology / methods
  • Radiography
  • Reproducibility of Results
  • Sensitivity and Specificity