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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Progressive Gray Matter Atrophy and Abnormal Structural Covariance Network in Ischemic Pontine Stroke
Ying Wei1, Caihong Wang1, Jingchun Liu2
1Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Abstract:
Our aim was to identify the longitudinal changes in gray matter volume (GMV) and secondary alterations of structural covariance after pontine stroke (PS). Structural MRI and behavioral scores were obtained at 1 week, 1 month, 3 months, 6 months in 11 patients with PS. Twenty healthy subjects underwent the same examination only once. We used voxel-based morphometry and seed-based structural covariance to investigate the altered GMV and structural covariance patterns. Furthermore, the associations between the GMV changes and behavioral scores were assessed. With the progression of the disease, GMV decreased significantly in the bilateral cerebellar posterior lobe (ipsilateral Crus II (CBE Crus II_IL) and contralateral Crus I (CBE Crus I_CL)), which were initially detected at the first month and then continued to decrease during the following 6 months. Based on the CBE Crus II_IL and CBE Crus I_CL as seed regions, structural covariance analysis revealed that there were more positively and negatively correlated brain regions in PS group, mainly distributed in the bilateral prefrontal lobe, parietal lobe, temporal lobe, paralimbic system and cerebellum. In addition, PS group showed more additional correlations between these covariant brain regions, and the changes of GMV in these regions were correlated with behavioral scores related to motor and cognitive functions. These findings indicate that PS could lead to significant GMV atrophy in the bilateral cerebellar posterior lobe at the early stage, accompanied by anomalous structural covariance patterns with more covariant brain regions and additional structural connectivity, which may provide useful information for understanding the neurobiological mechanisms of behavioral recovery after PS.
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