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A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Published on: July 2, 2014
Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume
Loretxu Bergouignan1, Marie Chupin, Yvonne Czechowska
1CNRS UMR, Emotion Center, Department of Psychiatry, Groupe Hospitalier Pitié-Salpétrière, Paris, France. loretxu@alternatiba.org
Neuroimage
|December 17, 2008
Summary
This study found that automated segmentation and VBM-DARTEL are sensitive methods for detecting hippocampal volume reduction in depressed patients, outperforming standard VBM. These techniques aid in understanding depression
Area of Science:
- Neuroimaging
- Psychiatry
- Radiology
Background:
- Meta-analyses indicate a smaller hippocampus in individuals with depression.
- Traditional magnetic resonance imaging (MRI) studies often rely on manual hippocampal segmentation, which is time-consuming and prone to variability.
- Automated methods like voxel-based morphometry (VBM) and automated segmentation offer potential advantages over manual techniques.
Purpose of the Study:
- To compare the sensitivity of manual segmentation, automated segmentation, and VBM in identifying hippocampal structural changes in middle-aged adults with acute depression.
- To evaluate the effectiveness of different VBM normalization methods (standard SPM5 vs. DARTEL) for detecting these changes.
Main Methods:
- Twenty-one middle-aged depressed inpatients and 21 matched controls underwent hippocampal structure analysis.
- Techniques employed included VBM with SPM5 (using standard normalization and DARTEL algorithm) and manual and automated segmentation.
- Region of Interest (ROI) analyses were conducted for VBM.
Main Results:
- VBM with the DARTEL algorithm detected significant hippocampal volume differences between depressed patients and controls.
- Manual segmentation revealed an 11.6% hippocampal volume reduction, and automated segmentation showed a 9.7% reduction, both statistically significant.
- Standard VBM (without DARTEL) failed to detect significant bilateral hippocampal volume differences, while VBM-DARTEL and automated segmentation demonstrated comparable sensitivity.
Conclusions:
- VBM-DARTEL and automated segmentation are sensitive and reliable methods for detecting hippocampal volume changes in depression.
- These automated approaches are suitable for large-scale volumetric studies and can overcome limitations of manual segmentation.
- Automated segmentation may enable detailed analysis of hippocampal subregions, potentially clarifying the pathophysiology of psychiatric disorders.
