MRI-based radiomic to predict lipomatous soft tissue tumors malignancy

Benjamin Leporq (1) , Amine Bouhamama (2) , Fabrice Lame (3) , Catherine Bihane (2) , Michaël Sdika (4, 5, 6) , Jean-Yves Blay (7) , Frank Pilleul (1) , Olivier Beuf (1)

1 RMN et optique : De la mesure au biomarqueur
2 Centre Léon Bérard [Lyon]
3 UAG UFR SM - Université des Antilles et de la Guyane - UFR des sciences médicales
4 Images et Modèles
5 MYRIAD - Modeling & analysis for medical imaging and Diagnosis
6 Service Informatique et développements
7 Service d'Oncologie Médicale

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.

Domaines: Imagerie

Benjamin Leporq, Amine Bouhamama, Fabrice Lame, Catherine Bihane, Michaël Sdika, et al.. MRI-based radiomic to predict lipomatous soft tissue tumors malignancy. 27th Annual meeting of the ISMRM, May 2019, Montréal, Canada. ⟨hal-02266792⟩