SS-Detect: Development and Validation of a New Strategy for Source-Based Morphometry in Multiscanner Studies

Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.

Progressive structural damage in sleep-related hypermotor epilepsy

This study aimed to explore the alterations in gray matter volume (GMV) based on high-resolution structural data and the temporal precedence of structural alterations in patients with sleep-related hypermotor epilepsy (SHE). After preprocessing of T1 structural images, the voxel-based morphometry and source-based morphometry (SBM) methods were applied in 60 SHE patients and 56 healthy controls to analyze the gray matter volumetric alterations. Furthermore, a causal network of structural covariance (CaSCN) was constructed using Granger causality analysis based on structural data of illness duration ordering to assess the causal impact of structural changes in abnormal gray matter regions. The GMVs of SHE patients were widely reduced, mainly in the bilateral cerebellums, fusiform gyri, the right angular gyrus, the right postcentral gyrus, and the left parahippocampal gyrus. In addition to those regions, the results of the SBM analysis also found decreased GMV in the bilateral frontal lobes, precuneus, and supramarginal gyri. The analysis of CaSCN showed that along with disease progression, the cerebellum was the prominent node that tended to affect other brain regions in SHE patients, while the frontal lobe was the transition node and the supramarginal gyrus was the prominent node that may be easily affected by other brain regions. Our study found widely affected regions of decreased GMVs in SHE patients; these regions underlie the morphological basis of epileptic networks, and there is a temporal precedence relationship between them.

Decreased gray matter volume is associated with theory of mind deficit in adolescents with schizophrenia

Schizophrenia patients often suffer from deficit in theory of mind (TOM). Prior neuroimaging studies revealed neuroimaging correlates of TOM deficit in adults with schizophrenia, neuroimaging correlates of TOM in adolescents is less well established. This study aimed to investigate gray matter volume (GMV) abnormalities and TOM deficits in schizophrenic adolescents, and examine the relationship between them. Twenty adolescent schizophrenic patients and 25 age, sex-matched healthy controls underwent T1-weighted magnetic resonance imaging (MRI) scans, and were examined for TOM based on the Reading the Mind in the Eyes test (RMET). Univariate voxel-based morphometry (VBM) and multivariate source-based morphometry (SBM) were employed to examine alterations of two GMV phenotypes in schizophrenic adolescents: voxel-wise GMV and covarying structural brain patterns (SBPs). Compared with controls, our results revealed a significant deficit in RMET performance of the patients, Voxel-wise VBM analysis revealed that patients exhibited decreased GMV in bilateral insula, orbitofrontal cortex, and right rolandic operculum, and GMV of these brain regions were positively correlated with RMET performance. Multivariate SBM analysis identified a significantly different between-group SBP comprising of bilateral insula and inferior frontal cortex, bilateral superior temporal cortex, and bilateral lateral parietal cortex and right rolandic operculum. The loading scores of this SBP was positively correlated with RMET performance. This study revealed impairment of TOM ability in schizophrenic adolescents and revealed an association between TOM deficit and decreased GMV in regions which are crucial for social cognition, thereby provided insight and possible target regions for understanding the neural pathology and normalizing TOM deficit in adolescent schizophrenia patients.