Radiomic features of pretreatment MRI could identify T stage in patients with rectal cancer: Preliminary findings.

Background: Recent studies have shown that magnetic resonance (MR) radiomic analysis is feasible and has some value in identifying tumor characteristics, but there are few data regarding the role of MR-based radiomic features in rectal cancer. Purpose: The aim of this study was to determine whether radiomic features extracted from T2-weighted imaging (T2WI) can identify pathological features in rectal cancer. Study Type: Retrospective study. Population/Subjects: A cohort comprising 119 rectal cancer patients who underwent surgery between January 2015 and November 2016. Field Strength/Sequence: 3.0T, axial high-resolution T2-weighted turbo spin echo (TSE) sequence. Assessment: Patients were classified according to pathological features such as T stage, N stage, perineural invasion, histological grade, lymph-vascular invasion, tumor deposits, and circumferential resection margin (CRM). The whole tumor volume (WTV) was distinguished, and segments were quantified on axial high-resolution T2WI by a radiologist. A total of 256 radiomic features were extracted. Statistical Tests: To achieve reliable results, cluster analysis and least absolute shrinkage and selection operator (LASSO) were implemented. In the cluster analysis, the patients were divided into two groups, and chi-square tests were performed to investigate the relationship between the pathological features and the radiomic-based clusters. The area under the curve (AUC) was calculated to evaluate the predictability of the model in the LASSO analysis. Results: The cluster results revealed that patients could be stratified into two groups, and the chi-square test results indicated that the pT stage was correlated with the radiomic feature cluster results (P=0.002). The prediction model AUC for the diagnostic T stage was 0.852 (95% confidence interval: 0.677-1; sensitivity: 79.0%, specificity: 82.0%). Data Conclusion: The use of MRI-derived radiomic features to identify the T stage is feasible in rectal cancer.