Development and validation of an MRI-based model to predict response to chemoradiotherapy for rectal cancer.

Background And Purpose: To safely implement organ preserving treatment strategies for patients with rectal cancer, well-considered selection of patients with favourable response is needed. In this study, we develop and validate an MRI-based response predicting model.

Methods: A multivariate model using T2-volumetric and DWI parameters before and 6 weeks after chemoradiation (CRT) was developed using a cohort of 85 rectal cancer patients and validated in an external cohort of 55 patients that underwent preoperative CRT.

Results: Twenty-two patients (26%) achieved ypT0-1N0 response in the development cohort versus 13 patients (24%) in the validation cohort. Two T2-volumetric parameters (ΔVolume% and Sphere_post) and two DWI parameters (ADC_avg_post and ADCratio_avg) were retained in a model predicting (near-)complete response (ypT0-1N0). In the development cohort, this model had a good predictive performance (AUC = 0.89; 95% CI 0.80-0.98). Validation of the model in an external cohort resulted in a similar performance (AUC = 0.88 95% CI 0.79-0.98).

Conclusion: An MRI-based prediction model of (near-)complete pathological response following CRT in rectal cancer patients, shows a high predictive performance in an external validation cohort. The clinically relevant features in the model make it an interesting tool for implementation of organ-preserving strategies in rectal cancer.