To investigate age- and sex-related changes in choroid plexus (CP) volume in healthy adults, as well as its association with the volumes of other brain regions, and explore the relationship of CP volume changes with degenerative brain alterations.

A total of 320 healthy subjects aged between 18 and 85 years were prospectively recruited in Physical Examination Center of First Affiliated Hospital to Army Medical University during August 2023 and February 2024. These participants were randomly divided into 7.0T and 3.0T groups, with 160 people in each group. After all of them underwent sagittal three-dimensional structural MPRAGE scans of magnetic resonance imaging (MRI) at 3.0T or 7.0T, FreeSurfer 6.0 segmentation software was employed to obtain the volumes of CP and other brain regions automatically. Spearman analysis was applied to analyze the correlation of CP volume with age. Independent sample t-test analysis was applied to analyze the differences in CP volume between genders. Partial correlation analysis was performed to analyze the correlation between CP volume and the volumes of other brain regions.

A total of 311 subjects were included in the study. The results from both 3.0T and 7.0T MRI showed that CP volume was positively correlated with age (3.0T: r=0.462, P < 0.001; 7.0T: r=0.539, P < 0.001). The males had significantly larger CP volume than the females (3.0T: 1.4±0.47 vs 1.08±0.39 mL, P < 0.001; 7.0T: 2.43±0.68 vs 1.98±0.38 mL, P < 0.001). In addition, 3.0T MRI revealed there was a significant positive correlation of CP volume with the volumes of white matter hyperintensities (WMH) and cerebrospinal fluid (P < 0.001), as well as a negative correlation with the volumes of gray matter, white matter, hippocampus and thalamus (P < 0.05).

CP volume is increased with ageing, with gender differences, independent of field strength and resolution. CP volume is correlated with WMH, hippocampus and other brain regions, suggesting that increment in CP volume is involved in age-related degenerative changes in the brain. Changes in CP volume might be regarded as a new imaging marker for the neurodegenerative changes.

To develop a CT radiomics-based prediction model for prognosis of pancreatic ductal adenocarcinoma (PDAC) in order to provide evidence for individualized treatment decisions.

A retrospective study was carried on 118 PDAC patients admitted in the First Affiliated Hospital of Army Medical University between January 2020 and December 2023. They were assigned into a training group (n=83) and a validation group (n=35) at a 7∶3 ratio. ITK-SNAP software was used to perform 3-D segmentation on the preoperatively enhanced arterial phase CT images, and radiomic features were extracted using pyradiomics. High-reproducibility features were selected through ICC analysis (>0.85), and core features were determined using LASSO regression to construct the Rad-score. Cox regression analysis was employed to develop both a radiomics model and a model integrating radiomic and clinical features for predicting overall survival in PDAC patients. Receiver operating characteristic (ROC) curves and calibration curves were plotted to evaluate the prognostic models for survival prediction.

From 1453 extracted radiomic features, 7 core features were finally selected to construct the Rad-score. The radiomics prediction model based on the Rad-score achieved an AUC value of 0.796 (95%CI: 0.702~0.890) and 0.744 (95%CI: 0.589~0.899) for 1-year survival prediction in the training and validation groups, respectively. The integrated model combining 2 types of features together demonstrated improved performance with an AUC value of 0.906 (95%CI: 0.842~0.970) and 0.872 (95%CI: 0.753~0.992) in the 2 groups. Calibration curve analysis indicated good prediction accuracy for both models.

Both the CT radiomics-based model and the integrated model incorporating clinical features demonstrate good predictive performance for survival outcomes.