Diagnostic accuracy and clinical implications of robotic assisted MRI-US fusion guided target saturation biopsy of the prostate.

MRI-targeted prostate biopsy improves detection of clinically significant prostate cancer (PCa). However, up to 70% of PCa lesions display intralesional tumor heterogeneity. Current target sampling strategies do not yet adequately account for this finding.

Toward a Platform for Structured Data Acquisition in Oncology: A Pilot Study on Prostate Cancer Screening.

Introduction: Physicians spend an ever-rising amount of time to collect relevant information from highly variable medical reports and integrate them into the patient's health condition.

Objectives: We compared synoptic reporting based on data elements to narrative reporting in order to evaluate its capabilities to collect and integrate clinical information.

Methods: We developed a novel system to align medical reporting to data integration requirements and tested it in prostate cancer screening.

Autonomous Detection and Classification of PI-RADS Lesions in an MRI Screening Population Incorporating Multicenter-Labeled Deep Learning and Biparametric Imaging: Proof of Concept.

Background: Opportunistic prostate cancer (PCa) screening is a controversial topic. Magnetic resonance imaging (MRI) has proven to detect prostate cancer with a high sensitivity and specificity, leading to the idea to perform an image-guided prostate cancer (PCa) screening; Methods: We evaluated a prospectively enrolled cohort of 49 healthy men participating in a dedicated image-guided PCa screening trial employing a biparametric MRI (bpMRI) protocol consisting of T2-weighted (T2w) and diffusion weighted imaging (DWI) sequences. Datasets were analyzed both by human readers and by a fully automated artificial intelligence (AI) software using deep learning (DL).