A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis

Arthur, Amani; Orton, Matthew R; Emsley, Robby; Vit, Sharon; Kelly-Morland, Christian; Strauss, Dirk; Lunn, Jason; Doran, Simon; Lmalem, Hafida; Nzokirantevye, Axelle; Litiere, Saskia; Bonvalot, Sylvie; Haas, Rick; Gronchi, Alessandro; Van Gestel, Dirk; Ducassou, Anne; Raut, Chandrajit P; Meeus, Pierre; Spalek, Mateusz; Hatton, Matthew; Le Pechoux, Cecile; Thway, Khin; Fisher, Cyril; Jones, Robin; Huang, Paul H; Messiou, Christina

doi:10.1016/s1470-2045(23)00462-x

The Lancet Oncology

2023

DOI: 10.1016/s1470-2045(23)00462-x

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A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis

Amani Arthur,

Matthew R Orton,

Robby Emsley

et al.

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Cited by 19 publications

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A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis

Cited by 19 publications

References 26 publications

A radionomics model for the prediction of grade and histological subtype in retroperitoneal sarcoma

A radionomics model for the prediction of grade and histological subtype in retroperitoneal sarcoma

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