Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI.

ABSTRACT:

Objectives

To develop and validate an artificial intelligence algorithm to decide on the necessity of dynamic contrast-enhanced sequences (DCE) in prostate MRI.

Methods

This study was approved by the institutional review board and requirement for study-specific informed consent was waived. A convolutional neural network (CNN) was developed on 300 prostate MRI examinations. Consensus of two expert readers on the necessity of DCE acted as reference standard. The CNN was validated in a separate cohort of 100 prostate MRI examinations from the same vendor and 31 examinations from a different vendor. Sensitivity/specificity were calculated using ROC curve analysis and results were compared to decisions made by a radiology technician.

Results

The CNN reached a sensitivity o

SUBMITTER: Hotker AM 

PROVIDER: S-EPMC8353049 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature