Artificial intelligence can detect left ventricular dilatation on contrast-enhanced thoracic computer tomography relative to cardiac magnetic resonance imaging.

ABSTRACT:

Objectives

To assess the diagnostic accuracy of an automated algorithm to detect left ventricular (LV) dilatation on non-ECG gated CT, using cardiac magnetic resonance (CMR) as reference standard.

Methods

Consecutive patients with contrast-enhanced CT thorax and CMR within 31 days (2016-2020) were analysed (n = 84). LV dilatation was defined against age-, sex- and body surface area-specific values for CMR. CTs underwent automated artificial intelligence(AI)-derived analysis that segmented ventricular chambers, presenting maximal LV diameter and volume. Area under the receiver operator curve (AUC-ROC) analysis identified CT thresholds with ≥90% sensitivity and highest specificity and ≥90% specificity with highest sensitivity. Youden's Index was used to identify thresho

SUBMITTER: Asif A 

PROVIDER: S-EPMC9815728 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature