Principal component and volume of interest analyses in depressed patients imaged by 99mTc-HMPAO SPET: a methodological comparison

    loading  Checking for direct PDF access through Ovid

Abstract

Previous regional cerebral blood flow (rCBF) studies on patients with unipolar major depressive disorder (MDD) have analysed clusters of voxels or single regions and yielded conflicting results, showing either higher or lower rCBF in MDD as compared to normal controls (CTR). The aim of this study was to assess rCBF distribution changes in 68 MDD patients, investigating the data set with both volume of interest (VOI) analysis and principal component analysis (PCA). The rCBF distribution in 68 MDD and 66 CTR, at rest, was compared. Technetium-99m d,l-hexamethylpropylene amine oxime single-photon emission tomography was performed and the uptake in 27 VOIs, bilaterally, was assessed using a standardising brain atlas. Data were then grouped into factors by means of PCA performed on rCBF of all 134 subjects and based on all 54 VOIs. VOI analysis showed a significant group × VOI × hemisphere interaction (P<0.001). rCBF in eight VOIs (in the prefrontal, temporal, occipital and central structures) differed significantly between groups at the P<0.05 level. PCA identified 11 anatomo-functional regions that interacted with groups (P<0.001). As compared to CTR, MDD rCBF was relatively higher in right associative temporo-parietal-occipital cortex (P<0.01) and bilaterally in prefrontal (P<0.005) and frontal cortex (P<0.025), anterior temporal cortex and central structures (P<0.05 and P<0.001 respectively). Higher rCBF in a selected group of MDD as compared to CTR at rest was found using PCA in five clusters of regions sharing close anatomical and functional relationships. At the single VOI level, all eight regions showing group differences were included in such clusters. PCA is a data-driven method for recasting VOIs to be used for group evaluation and comparison. The appearance of significant differences absent at the VOI level emphasises the value of analysing the relationships among brain regions for the investigation of psychiatric disease.

Related Topics

    loading  Loading Related Articles