MRI index lesion radiomics and machine learning for detection of extraprostatic extension of disease: a multicenter study

OBJECTIVES: To build a machine learning (ML) model to detect extraprostatic extension (EPE) of prostate cancer (PCa), based on radiomics features extracted from prostate MRI index lesions. METHODS: Consecutive MRI exams of patients undergoing radical prostatectomy for PCa were retrospectively collec...

Descripción completa

Detalles Bibliográficos
Autores principales: Cuocolo, Renato, Stanzione, Arnaldo, Faletti, Riccardo, Gatti, Marco, Calleris, Giorgio, Fornari, Alberto, Gentile, Francesco, Motta, Aurelio, Dell’Aversana, Serena, Creta, Massimiliano, Longo, Nicola, Gontero, Paolo, Cirillo, Stefano, Fonio, Paolo, Imbriaco, Massimo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Magnetic Resonance
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452573/
https://www.ncbi.nlm.nih.gov/pubmed/33792737
http://dx.doi.org/10.1007/s00330-021-07856-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452573/
https://www.ncbi.nlm.nih.gov/pubmed/33792737
http://dx.doi.org/10.1007/s00330-021-07856-3

Ejemplares similares