Tumoral and Peritumoral Radiomics with MRI-Combined Clinical Models Predict T Stages of Early Rectal Cancer
Abstract
RATIONALE AND OBJECTIVES: Early and accurate staging of rectal cancer is essential for selecting optimal treatment strategies. This study aimed to evaluate the utility of a combined clinical, tumoral, and peritumoral radiomics model for predicting T1 and T2 rectal cancer staging. MATERIALS AND METHODS: We retrospectively enrolled patients with pathologically confirmed rectal cancer from three medical centers between August 2018 and December 2024. Radiomics features were extracted from both tumoral and peritumoral regions using preoperative magnetic resonance imaging scans. The radiomics model with the highest area under the curve (AUC) was combined with a clinical model to construct a fusion model for distinguishing T1 and T2 stages. RESULTS: A total of 392 patients were included and allocated to a training set (n = 208), an internal test set (n = 90), and an external test set (n = 94). The fusion model (clinical+Com-T2WI) demonstrated robust performance, achieving AUCs of 0.91, 0.82, and 0.88 in the training, internal, and external test sets, respectively. Tumor thickness (P =.034) and tumor length (P
Fields of Study & Subjects
Radiomics and Machine Learning in Medical Imaging
Colorectal Cancer Surgical Treatments
Colorectal and Anal Carcinomas
Publication details
- Journal / source
- Academic Radiology
- Publisher
- Elsevier BV
- Volume
- 33
- Issue
- 4
- Pages
- 1397–1408
- Publication date
- 31 January 2026
- Language
- EN