A longitudinal multimodal MRI study of the visual network in postoperative delirium

Although structural and functional damage to the brain is considered to be an important neurobiological mechanism of postoperative delirium (POD), alterations in the visual cortical network related to this vulnerability have not yet been determined. In this study, we investigated the impact of alterations in the visual network (VN), as measured by structural and functional magnetic resonance imaging (MRI), on the development of POD. Thirty-six adult patients with frontal glioma who underwent elective craniotomy were recruited. The primary outcome was POD 1–7 days after surgery, as assessed by the Confusion Assessment Method. Cognition before surgery was measured by a battery of neuropsychological tests. Then, we evaluated preoperative and postoperative gray matter volume (GMV) and functional connectivity (FC) alterations by voxel-based morphometry and resting-state functional MRI (rs-fMRI) between the POD and non-POD groups. Multiple logistic regression models were used to investigate the associations between neuroimaging biomarkers and the occurrence of POD. Compared to those in the non-POD group, a decreased GMV in the fusiform gyrus (0.181 [0.018] vs. 0.207 [0.022], FDRp = 0.001) and decreased FC between the fusiform gyrus and VN (0.351 [0.153] vs. 0.610 [0.197], GFRp < 0.001) were observed preoperatively in the POD group, and increased FC between the fusiform gyrus and ventral attentional network (0.538 [0.180] vs. 0.452 [0.184], GFRp = < 0.001) was observed postoperatively in the POD group. According to our multiple logistic regression analysis, age (Odds ratio [OR]: 1.141 [1.015 to 1.282], P = 0.03) and preoperative fusiform-VN FC (OR 0.001 [0.001 to 0.067], P = 0.01) were significantly related to risk of POD. Our findings suggested that preoperative functional disconnectivity between fusiform and VN might be highly involved in the development of POD. These findings may allow for the discovery of additional underlying mechanisms.