Performance of a novel artificial intelligence software developed to derive coronary fractional flow reserve values from diagnostic angiograms.

ABSTRACT:

Background

Although invasive measurement of fractional flow reserve (FFR) is recommended to guide revascularization, its routine use is underutilized. Recently, a novel non-invasive software that can instantaneously produce FFR values from the diagnostic angiograms, derived completely from artificial intelligence (AI) algorithms has been developed. We aim to assess the accuracy and diagnostic performance of AI-FFR in a real-world retrospective study.

Methods

Retrospective, three-center study comparing AI-FFR values with invasive pressure wire-derived FFR obtained in patients undergoing routine diagnostic angiography. The accuracy, sensitivity, and specificity of AI-FFR were analyzed.

Results

A total of 304 vessels from 297 patients were included. Mean invasive FFR was

SUBMITTER: Ben-Assa E 

PROVIDER: S-EPMC10602213 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature