Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain.
PLoS One. 2012;7(6):e38299. doi: 10.1371/journal.pone.0038299. Epub 2012 Jun 28.
Melancholic depression is a biologically homogeneous clinical entity in which structural brain alterations have been described. Interestingly, reports of structural alterations in melancholia include volume increases in Cerebro-Spinal Fluid (CSF) spaces. However, there are no previous reports of CSF volume alterations using automated whole-brain voxel-wise approaches, as tissue classification algorithms have been traditionally regarded as less reliable for CSF segmentation. Here we aimed to assess CSF volumetric alterations in melancholic depression and their clinical correlates by means of a novel segmentation algorithm ('new segment', as implemented in the software Statistical Parametric Mapping-SPM8), incorporating specific features that may improve CSF segmentation. A three-dimensional Magnetic Resonance Image (MRI) was obtained from seventy patients with melancholic depression and forty healthy control subjects. Although imaging data were pre-processed with the 'new segment' algorithm, in order to obtain a comparison with previous segmentation approaches, tissue segmentation was also performed with the 'unified segmentation' approach. Melancholic patients showed a CSF volume increase in the region of the left Sylvian fissure, and a CSF volume decrease in the subarachnoid spaces surrounding medial and lateral parietal cortices. Furthermore, CSF increases in the left Sylvian fissure were negatively correlated with the reduction percentage of depressive symptoms at discharge. None of these results were replicated with the 'unified segmentation' approach. By contrast, between-group differences in the left Sylvian fissure were replicated with a non-automated quantification of the CSF content of this region. Left Sylvian fissure alterations reported here are in agreement with previous findings from non-automated CSF assessments, and also with other reports of gray and white matter insular alterations in depressive samples using automated approaches. The reliable characterization of CSF alterations may help in the comprehensive characterization of brain structural abnormalities in psychiatric samples and in the development of etiopathogenic hypotheses relating to the disorders.
忧郁性抑郁症是一种生物学上同质的临床实体，其中已经描述了结构性脑改变。有趣的是，忧郁症的结构性改变报告包括脑脊液（CSF）空间体积增加。然而，以前没有使用自动全脑体素方法报告 CSF 体积改变的报告，因为组织分类算法传统上被认为对 CSF 分割不太可靠。在这里，我们旨在通过一种新的分割算法（“新分割”，如在软件统计参数映射-SPM8 中实现）评估忧郁性抑郁症的 CSF 体积改变及其临床相关性，该算法结合了可能改善 CSF 分割的特定特征。从 70 名患有忧郁性抑郁症的患者和 40 名健康对照中获得了三维磁共振图像（MRI）。尽管成像数据是使用“新分割”算法进行预处理的，但是为了获得与以前的分割方法的比较，还使用“统一分割”方法进行了组织分割。忧郁性患者在左侧大脑裂的区域显示出 CSF 体积增加，并且在围绕内侧和外侧顶叶皮质的蛛网膜下腔中显示出 CSF 体积减少。此外，左侧大脑裂中的 CSF 增加与出院时抑郁症状减少的百分比呈负相关。这些结果均未使用“统一分割”方法复制。相比之下，在左侧大脑裂中的组间差异使用该区域 CSF 含量的非自动定量方法进行了复制。此处报告的左侧大脑裂改变与以前的非自动 CSF 评估结果以及使用自动方法在抑郁样本中对灰白质岛改变的其他报告一致。CSF 改变的可靠特征有助于全面描述精神科样本中的脑结构异常，并发展与该疾病相关的病因假说。
