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.

Purpose: 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. Methods: This multi-ins...

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Bibliographic Details

Published in:	Abdominal Radiology Vol. 46; no. 12; pp. 5647 - 5659
Main Authors:	Lim, Christopher S., Abreu-Gomez, Jorge, Thornhill, Rebecca, James, Nick, Al Kindi, Ahmed, Lim, Andrew S., Schieda, Nicola
Format:	Journal Article
Published:	Springer Nature Dec2021
Online Access:	View this record in EBSCOhost