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

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

ObjectiveTo 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 methodsFifty-nine patient...

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Bibliographic Details
Main Authors: Jinke Xie, Basen Li, Xiangde Min, Peipei Zhang, Chanyuan Fan, Qiubai Li, Liang Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Oncology
Subjects:
magnetic resonance imaging
prostatic neoplasms
Gleason score
active surveillance
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2020.604266/full

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