Meta-analysis of diffusion tensor imaging studies in schizophrenia

Schizophr Res. 2009 Mar;108(1-3):3-10. doi: 10.1016/j.schres.2008.11.021. Epub 2009 Jan 6.

Abstract

The objective of the study was to identify whether there are consistent regional white matter changes in schizophrenia. A systematic search was conducted for voxel-based diffusion tensor imaging fractional anisotropy studies of patients with schizophrenia (or related disorders) in relation to comparison groups. The authors carried out meta-analysis of the co-ordinates of fractional anisotropy differences. For the meta-analysis they used the Activation Likelihood Estimation (ALE) method hybridized with the rank approach used in Genome Scan Meta-Analysis (GSMA). This system detects three-dimensional conjunctions of co-ordinates from multiple studies and permits the weighting of studies in relation to sample size. Fifteen articles were identified for inclusion in the meta-analysis, including a total of 407 patients with schizophrenia and 383 comparison subjects. The studies reported fractional anisotropy reductions at 112 co-ordinates in schizophrenia and no fractional anisotropy increases. Over all studies, significant reductions were present in two regions: the left frontal deep white matter and the left temporal deep white matter. The first region, in the left frontal lobe, is traversed by white matter tracts interconnecting the frontal lobe, thalamus and cingulate gyrus. The second region, in the temporal lobe, is traversed by white matter tracts interconnecting the frontal lobe, insula, hippocampus-amygdala, temporal and occipital lobe. This suggests that two networks of white matter tracts may be affected in schizophrenia, with the potential for 'disconnection' of the gray matter regions which they link.

Publication types

  • Meta-Analysis

MeSH terms

  • Anisotropy
  • Brain / pathology
  • Brain Mapping
  • Databases, Factual / statistics & numerical data
  • Diffusion Magnetic Resonance Imaging / methods*
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Schizophrenia / diagnosis*