Objective:To investigate the value of intratumoral and peritumoral radiomics models based on 18F-FDG PET-CT in predicting epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma and interpret peritumoral radiomics features. Methods:This study was a cross-sectional study. Patients with lung adenocarcinoma who underwent 18F-FDG PET-CT at the Third Affiliated Hospital of Soochow University between January 2018 and April 2022 were retrospectively collected and samplied into a training set (309 cases) and a test set (206 cases) in a 6∶4 ratio randomly. Radiomics features were extracted from the intratumoral and peritumoral regions of interest based on PET and CT images, respectively, and the optimal feature sets were selected. Radiomics models were established using the XGBoost algorithm, and radiomics scores (intratumoral CT label, peritumoral CT label, intratumoral PET label, peritumoral PET label) were calculated. Logistic regression analysis was used to construct a clinical model and a combined model (incorporating PET-CT intratumoral and peritumoral radiomics, clinical features, and CT semantic features). The predictive performance of the models was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Unsupervised clustering, Spearman correlation analysis, and visualization methods were used for the interpretability of peritumoral radiomics features. Results:In both the training and test sets, the AUC value of CT peritumoral labels was greater than that of CT intratumoral labels for predicting EGFR mutation status in lung adenocarcinoma (training set: Z=3.84, P<0.001; test set: Z=1.99, P=0.046). In the test set, the AUC value of PET intratumoral labels (0.684) was slightly higher than that of PET peritumoral labels (0.672) for predicting EGFR mutation status, but the difference was not statistically significant ( P>0.05). The combined model had the highest AUC value for predicting EGFR mutation status of lung adenocarcinoma in both the training and test sets and was significantly better than the clinical model (training set: Z=6.52, P<0.001; test set: Z=2.31, P=0.021). Interpretability analysis revealed that CT peritumoral radiomics features were correlated with CT shape features, and there were significant differences in CT peritumoral features between different EGFR mutation statuses. Conclusions:The value of CT peritumoral labels is superior to that of CT intratumoral labels in predicting EGFR mutation status in lung adenocarcinoma. The predictive performance of the model can be improved by combining PET-CT intratumoral and peritumoral radiomics, clinical features, and CT semantic features.

ObjectiveTo investigate the dietary preference and nutritional knowledge needs of the elderly people who dined at meal service sites. MethodsUsing the form of stratified and convenience sampling method with self-designed questionnaire was used， in November 2021， to select 700 elderly people who dine at meal service sites in 7 jurisdictions in Shanghai were selected， and a self-designed questionnaire was used to investigate the basic information. Results91.64% of the elderly surveyed would eat at relatively fixed meal service sites， and the total Dietary Diversity Score （DDS9） was 3.56±1.46. 41.45% of the elderly with diseases preferred unhealthy cooking methods. Only 8.03% of the surveyed seniors said they were unwilling to accept targeted and personalized nutrition tips and reminders. Multivariate logistic regression analysis showed that the probability reaching the “understanding” level of “Food Guide Pagoda for Chinese Residents” and “Four Principles Recommended by the Core Dietary Guidelines for the Elderly” was different in the elderly with different education levels. The willingness of the elderly to expect to receive different nutrition tips and reminders was related to whether they cared about the corresponding contents. There was a statistically significant difference （P<0.05） among the elderly who were concerned about different health problems in terms of the willingness to receive different nutritional tips. There were significant differences in the proportion of elderly people with different health status for intervention （χ²=5.402， P<0.05）. ConclusionThe elderly who dine at meal service sites are highly dependent on the sites， have a low level of dietary diversification， and do not have a high degree of understanding of nutrition-related knowledge， and have a high demand for targeted nutritional interventions. Nutritional interventions for the sick elderly should be piloted through multiple channels.