Prediction of Pathological Upgrading at Radical Prostatectomy in Prostate Cancer Eligible for Active Surveillance: A Texture Features and Machine Learning-Based Analysis of Apparent Diffusion Coefficient Maps

OBJECTIVE: To evaluate a combination of texture features and machine learning-based analysis of apparent diffusion coefficient (ADC) maps for the prediction of Grade Group (GG) upgrading in Gleason score (GS) ≤6 prostate cancer (PCa) (GG1) and GS 3 + 4 PCa (GG2). MATERIALS AND METHODS: Fifty-nine pa...

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Detalles Bibliográficos
Autores principales: Xie, Jinke, Li, Basen, Min, Xiangde, Zhang, Peipei, Fan, Chanyuan, Li, Qiubai, Wang, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890009/
https://www.ncbi.nlm.nih.gov/pubmed/33614487
http://dx.doi.org/10.3389/fonc.2020.604266

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890009/
https://www.ncbi.nlm.nih.gov/pubmed/33614487
http://dx.doi.org/10.3389/fonc.2020.604266

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