Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression?
Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression?
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DOI:
10.1016/j.neuroimage.2008.11.006
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发表时间:
2009-03-01
期刊:
影响因子:
5.7
通讯作者:
Fossati, Philippe
中科院分区:
文献类型:
--
作者:
Bergouignan, Loretxu;Chupin, Marie;Fossati, Philippe
Context: According 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).Objective: The 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.Method: Twenty-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.Results: Using 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