Philippe Bulens1, Alice Couwenberg2, Karin Haustermans3, Annelies Debucquoy1, Vincent Vandecaveye4, Marielle Philippens2, Mu Zhou5, Olivier Gevaert5, Martijn Intven2. 1. Department of Radiation Oncology, University Hospital Leuven, Belgium. 2. Department of Radiation Oncology, University Medical Center Utrecht, The Netherlands. 3. Department of Radiation Oncology, University Hospital Leuven, Belgium. Electronic address: karin.haustermans@uzleuven.be. 4. Department of Radiology, University Hospital Leuven, Belgium. 5. Stanford Center for Biomedical Informatics Research, Stanford University, USA.
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.
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 cancerpatients 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 cancerpatients, 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.
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