Development of artificial intelligence tools for invasive Doppler-based coronary microvascular assessment.

ABSTRACT:

Aims

Coronary flow reserve (CFR) assessment has proven clinical utility, but Doppler-based methods are sensitive to noise and operator bias, limiting their clinical applicability. The objective of the study is to expand the adoption of invasive Doppler CFR, through the development of artificial intelligence (AI) algorithms to automatically quantify coronary Doppler quality and track flow velocity.

Methods and results

A neural network was trained on images extracted from coronary Doppler flow recordings to score signal quality and derive values for coronary flow velocity and CFR. The outputs were independently validated against expert consensus. Artificial intelligence successfully quantified Doppler signal quality, with high agreement with expert consensus (Spearman's rho: 0

SUBMITTER: Seligman H 

PROVIDER: S-EPMC10393887 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature