Automated reading of handheld echocardiograms is feasible and shows strong agreement with high-resolution echocardiography - Results from the PAVE project

Background

We recently showed that population data-based machine-learning can improve the automated echocardiographic quantification of cardiac structure and function. The respective gain in accuracy and precision strengthens the confidence into automated echocardiographic readings and carries potential for applications in various settings.

Purpose

We applied the automated detector to high-resolution standard echocardiograms and to echocardiograms acquired with a handheld device.

Methods and Results

PAVE (Pathology-oriented reading of echocardiography) is a cooperation project between University Hospital Wuerzburg (UKW) and Tomtec Imaging Systems using an established federated machine-learning environment. We recruited 2043 patients (mean age 64±16, 44% women) presenting at the UKW for transthoracic echocardiography (TTE). After high-resolution standard TTE (Vivid E95, GE) trained sonographers acquired images with a handheld ultrasound device (Lumify 2.0, Philips) according to a pre-specified protocol. Images of both modalities were loaded into the analysis platform of the Academic CoreLab Ultrasound-based Cardiovascular Imaging (TomtecArena®, Tomtec, Germany). For the current analysis, we selected n=51 random patients (mean age 65±16, 39% women) from the PAVE cohort. Reading of high-resolution and handheld TTE, respectively, was performed by a trained sonographer (>14 days apart and blinded to the reading results) as well as by the automated detector.

We here present first results regarding 2D (parasternal long axis) measurements of interventricular septum (IVS), left ventricular diameter (LVD) and posterior wall thickness (PW) at end-diastole from manual CoreLab reading (CL) and automated detector reading (AD) of high-resolution TTE (11.3±4.1mm, 10.9±2.5mm; 48.3±8.1mm, 49.5±7.4mm; PW 9.3±3.2mm, 10.0±1.7mm) as well as of the respective handheld echocardiograms (IVS 10.7±3.4mm, 11.0±2.2mm; LVD 47.7±7.4mm, 48.3±6.6mm; PW 9.7±2.7mm, 10.2±1.6mm). The agreement between measurements performed in high-resolution and handheld TTE was assessed using Bland-Altman analysis (Table 1; Figure 1).

Conclusions

The application of an automated detector to handheld TTE was feasible and led to measurement values in the same range but with higher agreement of measurements when compared to human reading. Our results await extension to further echocardiographic parameters and confirmation in larger cohorts but suggest that automated echocardiographic reading might become a valuable tool in patient care. Accurate automated reading of handheld TTE might extend applicability of echocardiography to non-expert settings.