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Abstract #2375

MRI-based radiomic to predict lipomatous soft tissue tumors malignancy

Benjamin Leporq1, Amine Bouhamama2, Fabrice Lame2, Catherine Bihane2, Michael Sdika1, Jean-Yves Blay3, Frank Pilleul2, and Olivier Beuf4

1CREATIS CNRS UMR 5220; Inserm U1206; INSA-Lyon; UCBL Lyon 1, Université de Lyon, Villeurbanne, France, 2Department of Radiology, Centre de lutte contre le cancer Léon Berard, Lyon, France, 3Department of Oncology, Centre de lutte contre le cancer Léon Berard, Lyon, France, 4CREATIS CNRS UMR 5220; Inserm U1206; INSA-Lyon; UCBL Lyon 1, Université de Lyon, Lyon, France

In this study a MRI-based radiomic method was developed to predict lipomatous soft tissue tumors malignancy. 81 subjects with lipomatous soft tissue tumors whose histology was known and with fat-suppressed T1w contrast enhanced MR images available were retrospectively enrolled to constitute a database. A linear support vector machine was used after learning base dimension reduction to develop the model. Results demonstrate that the evaluation of lipomatous tumor malignancy is feasible with good diagnosis performances using a routinely used MRI acquisition in clinical practice.

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