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CT-Based Radiomics and Deep Learning for BRCA Mutation and Progression-Free Survival Prediction in Ovarian Cancer Using a Multicentric Dataset.

Giacomo AvesaniHuong Elena TranGiulio CammarataFrancesca BottaSara RaimondiLuca RussoSalvatore PersianiMatteo BonattiTiziana TagliaferriMiriam DolciamiVeronica CelliLuca BoldriniJacopo LenkowiczPaola PricoloFederica TomaoStefania Maria Rita RizzoNicoletta ColomboLucia ManganaroAnna FagottiGiovanni ScambiaBenedetta GuiRiccardo Manfredi
Published in: Cancers (2022)
In our multicentric dataset, representative of a real-life clinical scenario, we could not find a good radiomic predicting model for PFS and BRCA mutational status, with both traditional radiomics and deep learning, but the combination of clinical and radiomic models improved model performance for the prediction of BRCA mutation. These findings highlight the need for standardization through the whole radiomic pipelines and robust multicentric external validations of results.
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