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Communication Dans Un Congrès Année : 2021

Mechanistic simulation of tumor response outperforms radiomics predicting recurrence in prostate cancer radiotherapy

Résumé

In prostate cancer radiotherapy, biochemical recurrence has been traditionally predicted using radiomics approaches with however limited performance. The purpose of this work was to use a mechanistic in silico model of tumor growth and response to irradiation to obtain better predictions. A cohort of 76 patients with localized prostate adenocarcinoma having undergone external beam radiotherapy was used. Analogous digital tissues were built from pre-treatment MRI. The prescribed irradiation protocols were simulated using the mechanistic model. Logistic regression was then performed to predict recurrence i) directly from MRI features following a conventional radiomics approach, ii) from intermediate parameters and iii) from the number of tumor cells at t =8 weeks output given by the mechanistic model. Significant improvement in prediction (p-value leq 0.0001) was achieved using the simulation-based marker (AUC =0.85) compared to predictions based on the MRI features without and with oversampling (AUC =0.77 and 0.80, respectively). © 2021 IEEE.
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Dates et versions

hal-03283732 , version 1 (12-07-2021)

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Citer

C. Sosa-Marrero, P. Fontaine, E. Mylona, K. Gnep, A. Hernandez, et al.. Mechanistic simulation of tumor response outperforms radiomics predicting recurrence in prostate cancer radiotherapy. 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, Apr 2021, Nice, France. pp.1-4, ⟨10.1109/ISBI48211.2021.9433997⟩. ⟨hal-03283732⟩
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