Article

Regional deficits in brain volume in schizophrenia: A meta-analysis of voxel-based morphometry studies

Department of Experimental Psychology, University of Oxford, Oxford, England, United Kingdom
American Journal of Psychiatry (Impact Factor: 13.56). 01/2006; 162(12):2233-45. DOI: 10.1176/appi.ajp.162.12.2233
Source: PubMed

ABSTRACT Voxel-based morphometry is a method for detecting group differences in the density or volume of brain matter. The authors reviewed the literature on use of voxel-based morphometry in schizophrenia imaging research to examine the capabilities of this method for clearly identifying specific structural differences in patients with schizophrenia, compared with healthy subjects. The authors looked for consistently reported results of relative deficits in gray and white matter in schizophrenia and evaluated voxel-based morphometry methods in order to propose a future strategy for using voxel-based morphometry in schizophrenia research.
The authors reviewed all voxel-based morphometry studies of schizophrenia that were published to May 2004 (15 studies). The studies included a total of 390 patients with a diagnosis of schizophrenia and 364 healthy volunteers.
Gray and white matter deficits in patients with schizophrenia, relative to healthy comparison subjects, were reported in a total of 50 brain regions. Deficits were reported in two of the 50 regions in more than 50% of the studies and in nine of the 50 regions in one study only. The most consistent findings were of relative deficits in the left superior temporal gyrus and the left medial temporal lobe. Use of a smaller smoothing kernel (4-8 mm) led to detection of a greater number of regions implicated in schizophrenia.
This review implicates the left superior temporal gyrus and the left medial temporal lobe as key regions of structural difference in patients with schizophrenia, compared to healthy subjects. The diversity of regions reported in voxel-based morphometry studies is in part related to the choice of variables in the automated process, such as smoothing kernel size and linear versus affine transformation, as well as to differences in patient groups. Voxel-based morphometry can be used as an exploratory whole-brain approach to identify abnormal brain regions in schizophrenia, which should then be validated by using region-of-interest analyses.

3 Followers
 · 
100 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The notion that schizophrenia patients' (SZ) sense of being detached from external reality is a core feature of the disorder has existed since the early days of its recognition and is still largely emphasized in first person accounts of SZs; however, its etiology, neurophysiological mechanism, and significance for clinical symptoms are unclear. Mind-wandering is a ubiquitous experience of being detached from reality, the underlying neural mechanism of which closely resembles the brain in a resting-state. The resting-state functional magnetic resonance imaging data of 33 SZs and 33 matched healthy controls (CNT) were acquired. All subjects answered the mind-wandering subscale of the Imaginal Processing Inventory Questionnaire. Functional connectivity maps were constructed using 82 regions of interest comprising default-mode, salience, and frontoparietal networks. SZs exhibit significantly higher mind-wandering frequency relative to CNT. The elevated mind-wandering frequency in SZs significantly correlated with positive and general symptom severity. The mind-wandering frequency was inversely correlated with connectivity degree in the right ventromedial prefrontal cortex, the brain region involved in self-experience in SZs. Our results suggest that self-disturbances in SZs can explain SZs' disconnection to the external world, leading to the manifestation of positive psychotic symptoms. This study demonstrates strong preliminary evidence that contributes significantly to resolve the complex relationship between self, world, and the brain of SZs, which may lie at the "core" of psychotic experiences. Copyright © 2015 Elsevier B.V. All rights reserved.
    Schizophrenia Research 04/2015; 165(1). DOI:10.1016/j.schres.2015.03.021 · 4.43 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this longitudinal magnetic resonance (MR) imaging study was to examine the effects of endurance training on hippocampal and grey matter volumes in schizophrenia patients and healthy controls. 20 chronic schizophrenia patients and 21 age- and gender-matched healthy controls underwent 3months of endurance training (30 min, 3 times perweek). 19 additionally recruited schizophrenia patients played table soccer (“foosball” in the USA) over the same period. MR imaging with 3D-volumetric T1-weighted sequences was performed on a 3 T MR scanner at baseline, after 6 weeks and after the 3-month intervention and 3 additional training-free months. In addition to voxel-based morphometry (VBM), we performed manual and automatic delineation of the hippocampus and its substructures. Endurance capacity and psychopathological symptoms were measured as secondary endpoints. No significant increases in the volumes of the hippocampus or hippocampal substructures were observed in schizophrenia patients or healthy controls. However, VBM analyses displayed an increased volume of the left superior, middle and inferior anterior temporal gyri compared to baseline in schizophrenia patients after the endurance training, whereas patients playing table soccer showed increased volumes in the motor and anterior cingulate cortices. After the additional training-free period, the differenceswere no longer present.While endurance capacity improved in exercising patients and healthy controls, psychopathological symptoms did not significantly change. The subtle changes in the left temporal cortex indicate an impact of exercise on brain volumes in schizophrenia. Subsequent studies in larger cohorts are warranted to address the question of response variability of endurance training.
    Schizophrenia Research 02/2015; DOI:10.1016/j.schres.2015.01.005 · 4.43 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. However reported studies in schizophrenic patients vary widely in terms of their methodology and the clinical samples investigated, leading to heterogeneous results. In order to evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls) patients were differentiated from controls with a sensitivity of 80.3% (95%-CI: 76.7 to 83.5%) and a specificity of 80.3% (95%-CI: 76.9 to 83.3%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019) and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% accuracy.
    Neuropsychopharmacology 02/2015; 40(7). DOI:10.1038/npp.2015.22 · 7.83 Impact Factor