Evaluation of parametrial infiltration in patients with IB‐IIB cervical cancer by a radiomics model integrating features from tumoral and peritumoral regions in 18F‐fluorodeoxy glucose positron emission tomography/MR images

Abstract

AbstractParametrial infiltration (PMI) is an essential factor in staging and planning treatment of cervical cancer. The purpose of this study was to develop a radiomics model for accessing PMI in patients with IB‐IIB cervical cancer using features from 18F‐fluorodeoxy glucose (18F‐FDG) positron emission tomography (PET)/MR images. In this retrospective study, 66 patients with International Federation of Gynecology and Obstetrics stage IB‐IIB cervical cancer (22 with PMI and 44 without PMI) who underwent 18F‐FDG PET/MRI were divided into a training dataset (n = 46) and a testing dataset (n = 20). Features were extracted from both the tumoral and peritumoral regions in 18F‐FDG PET/MR images. Single‐modality and multimodality radiomics models were developed with random forest to predict PMI. The performance of the models was evaluated with F1 score, accuracy, and area under the curve (AUC). The Kappa test was used to observe the differences between PMI evaluated by radiomics‐based models and pathological results. The intraclass correlation coefficient for features extracted from each region of interest (ROI) was measured. Three‐fold crossvalidation was conducted to confirm the diagnostic ability of the features. The radiomics models developed by features from the tumoral region in T2‐weighted images (F1 score = 0.400, accuracy = 0.700, AUC = 0.708, Kappa = 0.211, p = 0.329) and the peritumoral region in PET images (F1 score = 0.533, accuracy = 0.650, AUC = 0.714, Kappa = 0.271, p = 0.202) achieved the best performances in the testing dataset among the four single‐ROI radiomics models. The combined model using features from the tumoral region in T2‐weighted images and the peritumoral region in PET images achieved the best performance (F1 score = 0.727, accuracy = 0.850, AUC = 0.774, Kappa = 0.625, p < 0.05). The results suggest that 18F‐FDG PET/MRI can provide complementary information regarding cervical cancer. The radiomics‐based method integrating features from the tumoral and peritumoral regions in 18F‐FDG PET/MR images gave a superior performance for evaluating PMI.