Objective: To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods: This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), returnto-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results: The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

Objective: To evaluate the application of laplacian-regularized mean apparent propagator (MAPL)-MRI to brain glioma-induced corticospinal tract (CST) injury. Materials and Methods: This study included 20 patients with glioma adjacent to the CST pathway who had undergone structural and diffusion MRI. The entire CSTs of the affected and healthy sides were reconstructed, and the peritumoral CSTs were manually segmented. The morphological characteristics of the CST (track number, average length, volume, displacement of the affected CST) were examined and the diffusion parameter values, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean squared displacement (MSD), q-space inverse variance (QIV), returnto-origin probability (RTOP), return-to-axis probabilities (RTAP), and return-to-plane probabilities (RTPP) along the entire and peritumoral CSTs, were calculated. The entire and peritumoral CST characteristics of the affected and healthy sides as well as those relative CST characteristics of the patients with motor weakness and normal motor function were compared. Results: The track number, volume, MD, RD, MSD, QIV, RTAP, RTOP, and RTPP of the entire and peritumoral CSTs changed significantly for the affected side, whereas the AD and FA changed significantly only in the peritumoral CST (p < 0.05). In patients with motor weakness, the relative MSD of the entire CST, QIV of the entire and peritumoral CSTs, and the AD, MD, RD of the peritumoral CST were significantly higher, whereas the RTPP of the entire and peritumoral CSTs and the RTOP of the peritumoral CST were significantly lower than those in patients with normal motor function (p < 0.05 for all). In contrast, no significant changes were found in the CST morphological characteristics, FA, or RTAP (p > 0.05 for all). Conclusion MAPL-MRI is an effective approach for evaluating microstructural changes after CST injury. Its sensitivity may improve when using the peritumoral CST features.

Objectives:To identify the risk factors associated with delirium in intensive care unit (ICU) hospitalization of sepsis patients and construct a clinical prediction model to to provide a reference for the prevention and control of delirium in sepsis patients.Methods:Data were collected of sepsis patients admitted in the Intensive Care Unit in the Second Affiliated Hospital of Soochow University from September 2020 to August 2022.The patients were divided into delirium group and non-delirium group according to whether delirium occurred or not. Comparing of the differences in general and clinical data between the two groups, the independent risk factors for delirium were screened by backward stepwise regression method, and the delirium risk prediction model was constructed and evaluated. An independent risk factor analysis for delirium was conducted using a backward stepwise regression approach to identify significant predictors. A delirium risk prediction model was constructed based on the identified risk factors, followed by a comprehensive evaluation of the model's performance.Results:A total of 381 sepsis patients were included in the study, 114 patients (29.9%) developed delirium during the ICU hospitalization. Univariate analysis revealed statistically significant differences ( P< 0.05) between the delirium and non-delirium groups for several factors including age ≥ 65 years, blood transfusion, use of midazolam, use of adrenaline, APACHEⅡ score>15, SOFA score>4, metabolic acidosis, urea>7.1 mmol/L, coagulation disorders, lactate levels, and platelet count. Multivariate analysis identified age ≥ 65 years, use of midazolam, APACHEⅡ score>15, metabolic acidosis, urea>7.1 mmol/L, and coagulation disorders as independent risk factors for delirium in sepsis patients during ICU hospitalization.The predictive model was evaluated with an area under the ROC curve of 0.813, a non-significant Hosmer-Lemeshow goodness-of-fit test ( P=0.957>0.05), and a Brier score of 0.149 (<0.25), indicating good predictive performance and calibration. Clinical decision and impact curves demonstrated the model's favorable clinical applicability. Conclusions:The occurrence of delirium in ICU sepsis patients closely associate with six factors: age ≥ 65 years, use of midazolam, APACHEⅡ score>15, metabolic acidosis, urea>7.1 mmol/L, and coagulation disorders. This sepsis delirium prediction model has good clinical predictive ability and clinical applicability.