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MRI-Based Radiomics Input for Prediction of 2-Year Disease Recurrence in Anal Squamous Cell Carcinoma

Nicolas Giraud 1 Olivier Saut 2, 3, 4 Thomas Aparicio 5 Philippe Ronchin 6 Louis-Arnaud Bazire 7 Emilie Barbier 8 Claire Lemanski 9 Xavier Mirabel 10 Pierre-Luc Etienne 11 Astrid Lièvre 12 Wulfran Cacheux 13 Ariane Darut-Jouve 14 Christelle de La Fouchardière 15 Arnaud Hocquelet 16 Hervé Trillaud 16 Thomas Charleux 1 Gilles Breysacher 17 Delphine Argo-Leignel 18 Alexandre Tessier 19 Nicolas Magné 20 Meher Ben Abdelghani 21 Côme Lepage 22 Véronique Vendrely 1 
Abstract : Purpose: Chemo-radiotherapy (CRT) is the standard treatment for non-metastatic anal squamous cell carcinomas (ASCC). Despite excellent results for T1-2 stages, relapses still occur in around 35% of locally advanced tumors. Recent strategies focus on treatment intensification, but could benefit from a better patient selection. Our goal was to assess the prognostic value of pre-therapeutic MRI radiomics on 2-year disease control (DC). Methods: We retrospectively selected patients with non-metastatic ASCC treated at the CHU Bordeaux and in the French FFCD0904 multicentric trial. Radiomic features were extracted from T2-weighted pre-therapeutic MRI delineated sequences. After random division between training and testing sets on a 2:1 ratio, univariate and multivariate analysis were performed on the training cohort to select optimal features. The correlation with 2-year DC was assessed using logistic regression models, with AUC and accuracy as performance gauges, and the prediction of disease-free survival using Cox regression and Kaplan-Meier analysis. Results: A total of 82 patients were randomized in the training (n = 54) and testing sets (n = 28). At 2 years, 24 patients (29%) presented relapse. In the training set, two clinical (tumor size and CRT length) and two radiomic features (FirstOrder_Entropy and GLCM_JointEnergy) were associated with disease control in univariate analysis and included in the model. The clinical model was outperformed by the mixed (clinical and radiomic) model in both the training (AUC 0.758 versus 0.825, accuracy of 75.9% versus 87%) and testing (AUC 0.714 versus 0.898, accuracy of 78.6% versus 85.7%) sets, which led to distinctive high and low risk of disease relapse groups (HR 8.60, p = 0.005). Conclusion: A mixed model with two clinical and two radiomic features was predictive of 2-year disease control after CRT and could contribute to identify high risk patients amenable to treatment intensification with view of personalized medicine.
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https://hal.inria.fr/hal-03428535
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Submitted on : Thursday, November 18, 2021 - 11:45:23 AM
Last modification on : Tuesday, November 22, 2022 - 2:26:16 PM
Long-term archiving on: : Saturday, February 19, 2022 - 6:50:45 PM

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Nicolas Giraud, Olivier Saut, Thomas Aparicio, Philippe Ronchin, Louis-Arnaud Bazire, et al.. MRI-Based Radiomics Input for Prediction of 2-Year Disease Recurrence in Anal Squamous Cell Carcinoma. Cancers, 2021, 13 (2), pp.193. ⟨10.3390/cancers13020193⟩. ⟨hal-03428535⟩

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