Magnetic Resonance Imaging Radiomics‐Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI‐RADS 3 Lesions

Volume: 54, Issue: 5, Pages: 1466 - 1473
Published: May 10, 2021
Abstract
While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal.To construct and cross-validate a machine learning model based on radiomics features from T2 -weighted imaging (T2 WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2.Single-center...
Paper Details
Title
Magnetic Resonance Imaging Radiomics‐Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI‐RADS 3 Lesions
Published Date
May 10, 2021
Volume
54
Issue
5
Pages
1466 - 1473
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