18F-FDG PET/MR影像组学特征与宫颈癌PD-L1表达的相关性研究OA北大核心CSTPCD

Objective:To explore the correlation between 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/MR radiomic features and the expression of programmed death-ligand 1 (PD-L1) in cervical cancer. Materials and Methods:A retrospective analysis was conducted on 26 cervical cancer patients who underwent 18F-FDG PET/MR scans at Shengjing Hospital,China Medical University,from May 2017 to July 2023. Regions of interest (ROIs) were delineated on the images of the primary lesions in PET,T1WI,and T2WI. Each cross-sectional image containing an ROI for each patient was treated as a sample. Based on sampling and staining of surgical specimens,the samples were divided into a positive group (n=233,73.97％) and a negative group (n=82,26.03％). Radiomic features were extracted from the images using first-order statistics. Independent sample t-tests or Mann-Whitney U tests were used to compare the differences in feature parameters between the two groups. The correlation between image feature parameters and PD-L1 expression was analyzed. The samples were randomly divided into training and testing sets in a 7:3 ratio. Radiomic features with statistically significant differences were used as parameters to establish PET radiomic models,MR radiomic models,and PET/MR combined models through logistic regression. The diagnostic performance of each model for PD-L1 expression was evaluated using the area under the curve (AUC) analysis of receiver operating characteristic (ROC) curves. Results:The 15 first-order statistical features of PET images,including 10Percentile (P<0.01),90Percentile (P<0.01),Energy (P<0.01),Interquartile Range (P<0.01),and others,exhibit a strong correlation with PD-L1 expression. Similarly,the T1WI image parameters,such as 10Percentile (P<0.01),90Percentile (P<0.05),Maximum (P<0.05),Mean (P<0.01),and nine other first-order statistical features,show a strong correlation with PD-L1 expression. Additionally,the T2WI image parameters,including Entropy (P<0.05),Skewness (P<0.01),Energy (P<0.05),Interquartile Range (P<0.01),and eight other first-order statistical features,demonstrate a strong correlation with PD-L1 expression. Conclusions:18F-FDG PET/MR radiomic features show a strong correlation with the differential expression of PD-L1 in cervical cancer. The PET/MR radiomic model demonstrates better performance in predicting PD-L1 expression,providing a potential clinical tool for assessing PD-L1 expression in cervical cancer patients to optimize individualized treatment plans and improve patient prognosis.