Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression?

Department of Psychiatry, McGill University, Montreal, PQ, Canada
NeuroImage (Impact Factor: 6.36). 03/2009; 45(1):29-37. DOI: 10.1016/j.neuroimage.2008.11.006
Source: PubMed


ContextAccording to meta-analyses, depression is associated with a smaller hippocampus. Most magnetic resonance imaging (MRI) studies among middle aged acute depressed patients are based on manual segmentation of the hippocampus. Few studies used automated methods such as voxel-based morphometry (VBM) or automated segmentation that can overcome certain drawbacks of manual segmentation (essentially intra- and inter-rater variability and operator time consumption).ObjectiveThe aim of our study was to compare the sensitivity of manual segmentation, automated segmentation and VBM to detect hippocampal structural changes in middle aged acute depressed population.MethodTwenty-one middle aged depressed inpatients and 21 matched controls were compared regarding their hippocampal structure using VBM with SPM5, manual segmentation and an automated segmentation algorithm. The VBM-ROI analysis was performed using two different normalization methods: the standard approach implemented in SPM5 and the most recent DARTEL algorithm.ResultsUsing VBM-DARTEL, when corrected for multiple comparisons, significant volume differences were detected between groups in different regions and more specifically in hippocampus with ROI analyses. Whereas using standard VBM (without DARTEL), ROI analyses did not show bilateral volume between group differences.Significant hippocampal volume reductions between patients and controls were also detected using manual segmentation (− 11.6% volume reduction, p < 0.05) and automated segmentation (− 9.7% volume reduction, p < 0.05). VBM-DARTEL and automated segmentation show equal sensitivity in detecting hippocampal differences in depressed patients, while standard VBM was unable to detect hippocampal changes. Both VBM-DARTEL and automated segmentation could be used to perform large scale volumetric studies in humans. The new automated segmentation technique could further explore and detect hippocampal subpart differences that could be very useful for clarifying physiopathology of psychiatric disorders.

Download full-text


Available from: Martin Lepage,
44 Reads
  • Source
    • "Of these two approaches, VBM offers several advantages over the manual region-of-interest method. VBM is an automated technique that reduces selection bias when measuring differences in gray matter volume because it does not require a priori definition of regions of interest [24]. It also allows the averaging together of MRI scans acquired with the same equipment and imaging parameters [25]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Abnormal brain structure has been reported in obsessive-compulsive disorder (OCD), but findings from these reports have been inconsistent. This study aimed to gain more detailed insights into gray matter structure and correlate this structure with clinical features in patients with drug-naïve OCD using voxel-based morphometry (VBM). Voxel-based morphometry and tools of Diffeomorphic Anatomical Registration through Exponentiated Lie Algebra (DARTEL) were used to investigate structural differences in gray matter volume between 26 drug-naïve OCD patients and 32 healthy controls. Partial correlation analysis was used to analyze associations of gray matter abnormalities with Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores and illness duration. Compared to healthy controls, drug-naïve OCD patients showed significantly smaller gray matter volume in the right dorsolateral prefrontal cortex (DLPFC), left superior temporal gyrus, left precuneus and right precentral gyrus, as well as significantly greater gray matter volume in the left anterior insula and right parahippocampal gyrus (p < 0.05, corrected using the familywise error rate). Y-BOCS scores correlated positively with gray matter volume in the left anterior insula, while they correlated negatively with gray matter volume in the right DLPFC. OCD pathophysiology may involve structural changes in the DLPFC-parietal regions, including the dorsolateral prefrontal cortex, precuneus, superior temporal gyrus and connected limbic structures such as the parahippocampal gyrus and anterior insula. Longitudinal studies are needed that integrate anatomical, functional and diffusion MRI data. Copyright © 2015. Published by Elsevier B.V.
    Behavioural brain research 08/2015; 294. DOI:10.1016/j.bbr.2015.07.061 · 3.03 Impact Factor
  • Source
    • "To assess brain morphology, we employed voxel-based morphometry (VBM) of the MR images of the participants. VBM is a whole-brain, semi-automatic and unbiased technique for characterizing local differences in gray matter, which is as sensitive as manual segmentation, to detect hippocampal volume differences (Bergouignan et al., 2009 "
    [Show abstract] [Hide abstract]
    ABSTRACT: In estrogen-induced synaptic plasticity, a correlation of structure, function and behavior in the hippocampus has been widely established. 17ß-estradiol has been shown to increase dendritic spine density on hippocampal neurons and is accompanied by enhanced long-term potentiation and improved performance of animals in hippocampus-dependent memory tests. After inhibition of aromatase, the final enzyme of estradiol synthesis, with letrozole we consistently found a strong and significant impairment of long-term potentiation (LTP) in female mice as early as after six hours of treatment. LTP impairment was followed by loss of hippocampal spine synapses in the hippocampal CA1 area. Interestingly, these effects were not found in male animals. In the Morris water maze test, chronic administration of letrozole did not alter spatial learning and memory in either female or in male mice. In humans, analogous effects of estradiol on hippocampal morphology and physiology were observed using neuroimaging techniques. However, similar to our findings in mice, an effect of estradiol on memory performance has not been consistently identified/observed. Copyright © 2015. Published by Elsevier Inc.
    Hormones and Behavior 05/2015; 74. DOI:10.1016/j.yhbeh.2015.05.008 · 4.63 Impact Factor
    • "These were then applied to each participant's GM image. The DARTEL toolbox represents one of the highest-ranking registration methods and provides higher sensitivity for voxel-based morphometry (Bergouignan et al. 2009; Klein et al. 2009), as it has been proven in both healthy subjects and AD patients (Cuingnet et al. 2011). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Clinical symptoms observed in Alzheimer's disease (AD) patients may reflect variations within specific large-scale brain networks, modeling AD as a disconnection syndrome. The present magnetic resonance imaging study aims to compare the organization of gray matter structural covariance networks between 109 cognitively unimpaired controls (CTRL) and 109 AD patients positive to beta-amyloid at the early stages of the disease, using voxel-based morphometry. The default-mode network (DMN; medial temporal lobe subsystem) was less extended in AD patients in comparison with CTRL, with a significant decrease in the structural association between the entorhinal cortex and the medial prefrontal and the dorsolateral prefrontal cortices. The DMN (midline core subsystem) was also less extended in AD patients. Trends toward increased structural association were observed in the salience and executive control networks. The observed changes suggest that early disruptions in structural association between heteromodal association cortices and the entorhinal cortex could contribute to an isolation of the hippocampal formation, potentially giving rise to the clinical hallmark of AD, progressive memory impairment. It also provides critical support to the hypothesis that the reduced connectivity within the DMN in early AD is accompanied by an enhancement of connectivity in the salience and executive control networks. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail:
    Cerebral Cortex 05/2015; DOI:10.1093/cercor/bhv105 · 8.67 Impact Factor
Show more