Treatment planning computed tomography radiomics for predicting treatment outcomes and haematological toxicities in locally advanced cervical cancer treated with radiotherapy: A retrospective cohort study

Objective We evaluated whether radiomic features extracted from planning computed tomography (CT) scans predict clinical end points in patients with locally advanced cervical cancer (LACC) undergoing intensity‐modulated radiation therapy and brachytherapy. Design A retrospective cohort study. Setting Xiangya Hospital of Central South University, Changsha, Hunan, China. Population Two hundred and fifty‐seven LACC patients who were treated with intensity‐modulated radiotherapy from 2014 to 2017. Methods Patients were allocated into the training/validation sets (3:1 ratio) using proportional random sampling, resulting in the same proportion of groups in the two sets. We extracted 254 radiomic features from each of the gross target volume, pelvis and sacral vertebrae. The sequentially backward elimination support vector machine algorithm was used for feature selection and end point prediction. Main outcomes and measures Clinical end points include tumour complete response (CR), 5‐year overall survival (OS), anaemia, and leucopenia. Results A combination of ten clinicopathological parameters and 34 radiomic features performed best for predicting CR (validation balanced accuracy: 80.8%). The validation balanced accuracy of 54 radiomic features was 85.8% for OS, and their scores can stratify patients into the low‐risk and high‐risk groups (5‐year OS: 95.5% versus 36.4%, p