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Enhanced CT and MRI Focal Bone Tumor Classification with Machine Learning–based Stratification: A Multicenter Retrospective Study

Astrée Lemore, Nora Vogt, Julien Oster, Edouard Germain, Marc Fauvel, Romain Gillet, François Sirveaux, Béatrice Marie, N. Sans, Marie Faruch, Franck Lapègue, François Lafourcade, Sammy Badr, Anne Cotten, Fadila Mihoubi Bouvier, Sisi Yang, Jean‐Luc Drapé, Maxime Pastor, Yann Thouvenin, Marie Pierre Baron, C. Cyteval, David Fadli, Claire Fournier, Olivier Hauger, Mariem Ben Haj Amor, Nicolas Stacoffe, Sophie Daubié, Jean‐Baptiste Pialat, Jean‐Baptiste Pialat, Stéphane Cherix, Fabio Zanchi, Patrick Omoumi, Alain Blum, Gabriela Hossu, Pedro Augusto Gondim Teixeira

2025Radiology8 citationsDOI

Abstract

A machine learning algorithm using radiologic features from structured reports accurately classified focal bone lesions; Bone Tumor Imaging Reporting and Data System 2.0 was proposed to categorize model outputs into clinically meaningful malignancy risk classes.

Topics & Concepts

MedicineCategorizationMalignancyRadiologyRisk stratificationRetrospective cohort studyArtificial intelligencePathologyInternal medicineComputer scienceRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and ApplicationsAdvanced X-ray and CT Imaging
Enhanced CT and MRI Focal Bone Tumor Classification with Machine Learning–based Stratification: A Multicenter Retrospective Study | Litcius