Artificial Intelligence at the Intersection of Pathology and Radiology in Prostate Cancer

Overview

Journal Diagn Interv Radiol

Publisher Galenos Publishing House

Date 2019 May 8

PMID 31063138

Citations 33

Authors

Stephnie A Harmon

Sena Tuncer

Thomas Sanford

Peter L Choyke

Baris Turkbey

Affiliations

Soon will be listed here.

Abstract

Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle biopsies sampled throughout the prostate gland. Multiparametric magnetic resonance imaging (mpMRI) has become a well-established clinical tool for detecting and localizing prostate cancer. However, both pathologic and radiologic assessment suffer from poor reproducibility among readers. Artificial intelligence (AI) methods show promise in aiding the detection and assessment of imaging-based tasks, dependent on the curation of high-quality training sets. This review provides an overview of recent advances in AI applied to mpMRI and digital pathology in prostate cancer which enable advanced characterization of disease through combined radiology-pathology assessment.

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