Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using multi-modality imaging prostate-specific membrane antigen (PSMA) PET and CT Radiomics

Cao, YufengSutera, PhilipSilva Mendes, WilliamYousefi, BardiaHrinivich, TomDeek, MatthewPhillips, RyanSong, DanielKiess, Ana PonceCem Guler, OzanTorun, NeseReyhan, MehmetSawant, AmitMarchionni, LuigiSimone, Nicole L.Tran, Phuoc T.Onal, CemRen, Lei2024-07-292024-07-292024-07-22http://hdl.handle.net/10713/22615American Association of Physicists in Medicine, July 22, 2024.en-USAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Metastasis.BiomarkersDiagnostic ImagingPositron-Emission TomographyTomography, X-Ray ComputedSurvival AnalysisMachine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using multi-modality imaging prostate-specific membrane antigen (PSMA) PET and CT RadiomicsPoster/Presentation