Development and validation of an MRI-based model to predict response to chemoradiotherapy for rectal cancer. Issue 3 (March 2018)

• Record Type: Journal Article
• Authors: Bulens, Philippe; Couwenberg, Alice; Haustermans, Karin; Debucquoy, Annelies; Vandecaveye, Vincent; Philippens, Marielle; Zhou, Mu; Gevaert, Olivier; Intven, Martijn
• Is Part Of: Radiotherapy and oncology. Volume 126:Issue 3(2018)
• Page Start: 437
• Page End: 442
• Publication Date: 2018-03
• Subjects: Rectal cancer -- Chemoradiotherapy -- Response prediction -- MRI -- DWI; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2018.01.008
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: 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.