Aims: This study sought to examine the feasibility, accuracy and reproducibility of a novel, fully automated 2D transthoracic echocardiography (2D TTE) parasternal long axis (PLAX) view aortic measurements quantification software compared to board-certified cardiologists in controlled clinical setting.
Methods and results: Aortic Annulus (AoA), Aortic Sinus (AoS), Sinotubular Junction (STJ) and Proximal Ascending Aorta (AAo) diameter measurements were performed retrospectively on each of 58 subjects in two different ways: twice using a fully automated software (Ligence Heart version 2) and twice manually by three cardiologists (ORG) and one expert cardiologist (EC). Out of 58 studies AoA was measured in 54 (93%), AoS in 55 (95%), STJ in 55 (95%) and AAo in 54 (93%) studies. Automated measurements had a stronger correlation with EC when compared to ORG with the largest correlation difference of .1 for STJ measurements and lowest difference of .01 for AoS measurements. Automated software was in higher agreement with ground truth intervals (ORG measurements mean +- SEM) in three out of four measurements.
Conclusion: Fully automated 2D TTE PLAX view aortic measurements using a novel AI-based quantification software are feasible and yield results that are in close agreement with what experienced readers measure manually while providing better reproducibility. This approach may prove to have important clinical implications in the automation of the aortic root and ascending aorta assessment to improve workflow efficiency.
Keywords: aorta; artificial intelligence; automated measurements; deep learning; echocardiography.
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