Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis

Volume: 46, Issue: 12, Pages: 5647 - 5658
Published: Aug 31, 2021
Abstract
To evaluate if machine learning (ML) of radiomic features extracted from apparent diffusion coefficient (ADC) and T2-weighted (T2W) MRI can predict prostate cancer (PCa) diagnosis in Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 category 3 lesions. This multi-institutional review board-approved retrospective case–control study evaluated 158 men with 160 PI-RADS category 3 lesions (79 peripheral zone, 81 transition zone)...
Paper Details
Title
Utility of machine learning of apparent diffusion coefficient (ADC) and T2-weighted (T2W) radiomic features in PI-RADS version 2.1 category 3 lesions to predict prostate cancer diagnosis
Published Date
Aug 31, 2021
Volume
46
Issue
12
Pages
5647 - 5658
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