Delta radiomics for rectal cancer response prediction using low field magnetic resonance guided radiotherapy: an external validation.

INTRODUCTION: A recent study performed on 16 locally advanced rectal cancer (LARC) patients treated using magnetic resonance guided radiotherapy (MRgRT) has identified two delta radiomics features as predictors of clinical complete response (cCR) after neoadjuvant radio-chemotherapy (nCRT). This study aims to validate these features (ΔLleast and Δglnu) on an external larger dataset, expanding the analysis also for pathological complete response (pCR) prediction. METHODS: A total of 43 LARC patients were enrolled: Gross Tumour Volume (GTV) was delineated on T2/T1* MR images acquired during MRgRT and the two delta features were calculated. Receiver Operating Characteristic (ROC) curve analysis was performed on the 16 cases of the original study and the best cut-off value was identified. The performance of ΔLleast and Δglnu was evaluated at the best cut-off value. RESULTS: On the original dataset of 16 patients, ΔLleast reported an AUC of 0.81 for cCR and 0.93 for pCR, while Δglnu 0.72 and 0.54 respectively. The best cut-off values of ΔLleast was 0.73 for both outcomes, while Δglnu reported 0.54 for cCR and 0.93 for pCR. At the external validation, ΔLleast showed an accuracy of 81% for cCR and 79% for pCR, while Δglnu reported 63% for cCR and 40% for pCR. CONCLUSION: The accuracy of ΔLleast in predicting cCR and pCR is significantly higher than those obtained considering Δglnu, but inferior if compared with other image-based biomarker, such as the early-regression index. Studies with larger cohorts of patients are recommended to further investigate the role of delta radiomic features in MRgRT.

External Validation of Early Regression Index (ERITCP) as Predictor of Pathologic Complete Response in Rectal Cancer Using Magnetic Resonance-Guided Radiation Therapy.

PURPOSE: Tumor control probability (TCP)-based early regression index (ERITCP) is a radiobiological parameter that showed promising results in predicting pathologic complete response (pCR) on T2-weighted 1.5 T magnetic resonance (MR) images of patients with locally advanced rectal cancer. This study aims to validate the ERITCP in the context of low-tesla MR-guided radiation therapy, using images acquired with different magnetic field strength (0.35 T) and image contrast (T2/T1). Furthermore, the optimal timing for pCR prediction was estimated, calculating the ERI index at different biologically effective dose (BED) levels. METHODS AND MATERIALS: Fifty-two patients with locally advanced rectal cancer treated with neoadjuvant chemoradiation therapy were enrolled in this multi-institutional retrospective study. For each patient, a 0.35 T T2/T1-weighted MR image was acquired during simulation and on each treatment day. Gross tumor volume was contoured according to International Commission on Radiation Units Report 83 guidelines. According to the original definition, ERITCP was calculated considering the residual tumor volume at BED = 25 Gy. ERI was also calculated in correspondence with several BED levels: 13, 21, 32, 40, 46, 54, 59, and 67. The predictive performance of the different ERI indices were evaluated in terms of receiver operating characteristic curve. The robustness of ERITCP with respect to the interobserver variability was also evaluated considering 2 operators and calculating the intraclass correlation index. RESULTS: Fourteen patients showed pCR. ERITCP correctly 47 of 52 cases (accuracy = 90%), showing good results in terms of sensitivity (86%), specificity (92%), negative predictive value (95%), and positive predictive value (80%). The analysis at different BED levels shows that the best predictive performance is obtained when this parameter is calculated at BED = 25 Gy (area under the curve = 0.93). ERITCP results are robust with respect to interobserver variability (intraclass correlation index = 0.99). CONCLUSIONS: This study confirmed the validity and the robustness of ERITCP as a pCR predictor in the context of low-tesla MR-guided radiation therapy and indicate 25 Gy as the best BED level to perform predictions.