Head-to-head comparison between biparametric and multiparametric MRI for the diagnosis of prostate cancer: a systematic review and meta-analysis

S Woo, CH Suh, SY Kim, JY Cho… - American Journal of …, 2018 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study was to perform a systematic review and meta-
analysis of a head-to-head comparison between the performance of biparametric MRI …

Active surveillance for prostate cancer: current evidence and contemporary state of practice

JJ Tosoian, HB Carter, A Lepor, S Loeb - Nature Reviews Urology, 2016 - nature.com
Prostate cancer remains one of the most commonly diagnosed malignancies worldwide.
Early diagnosis and curative treatment seem to improve survival in men with unfavourable …

Variability of the positive predictive value of PI-RADS for prostate MRI across 26 centers: experience of the society of abdominal radiology prostate cancer disease …

AC Westphalen, CE McCulloch, JM Anaokar, S Arora… - Radiology, 2020 - pubs.rsna.org
Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active
surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) …

Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment

P Schelb, S Kohl, JP Radtke, M Wiesenfarth… - Radiology, 2019 - pubs.rsna.org
Background Men suspected of having clinically significant prostate cancer (sPC)
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …

[HTML][HTML] Weakly-supervised convolutional neural networks for multimodal image registration

Y Hu, M Modat, E Gibson, W Li, N Ghavami… - Medical image …, 2018 - Elsevier
One of the fundamental challenges in supervised learning for multimodal image registration
is the lack of ground-truth for voxel-level spatial correspondence. This work describes a …

[HTML][HTML] Prostate imaging-reporting and data system steering committee: PI-RADS v2 status update and future directions

AR Padhani, J Weinreb, AB Rosenkrantz, G Villeirs… - European urology, 2019 - Elsevier
Abstract Context The Prostate Imaging-Reporting and Data System (PI-RADS) v2 analysis
system for multiparametric magnetic resonance imaging (mpMRI) detection of prostate …

What are we missing? False-negative cancers at multiparametric MR imaging of the prostate

S Borofsky, AK George, S Gaur, M Bernardo, MD Greer… - Radiology, 2018 - pubs.rsna.org
Purpose To characterize clinically important prostate cancers missed at multiparametric
(MP) magnetic resonance (MR) imaging. Materials and Methods The local institutional …

[HTML][HTML] Prostate magnetic resonance imaging interpretation varies substantially across radiologists

GA Sonn, RE Fan, P Ghanouni, NN Wang… - European urology …, 2019 - Elsevier
Background Multiparametric magnetic resonance imaging (mpMRI) interpreted by experts is
a powerful tool for diagnosing prostate cancer. However, the generalizability of published …

Radiomic machine learning for characterization of prostate lesions with MRI: comparison to ADC values

D Bonekamp, S Kohl, M Wiesenfarth, P Schelb… - Radiology, 2018 - pubs.rsna.org
Purpose To compare biparametric contrast-free radiomic machine learning (RML), mean
apparent diffusion coefficient (ADC), and radiologist assessment for characterization of …

The value of PSA density in combination with PI-RADS™ for the accuracy of prostate cancer prediction

FA Distler, JP Radtke, D Bonekamp, C Kesch… - The Journal of …, 2017 - auajournals.org
Purpose: Multiparametric magnetic resonance imaging has an emerging role in prostate
cancer diagnostics. In addition, clinical information is a reliable predictor of significant …