Use of Artificial Intelligence for Acquisition of Limited Echocardiograms: A Randomized Controlled Trial for Educational Outcomes

Abstract

AbstractBackgroundPoint-of-care ultrasound (POCUS) machines may utilize artificial intelligence (AI) to enhance image interpretation and acquisition. This study investigates whether AI-enabled devices improve competency among POCUS novices.MethodsWe conducted a randomized controlled trial at a single academic institution from 2021-2022. Internal medicine trainees (N=43) with limited POCUS experience were randomized to receive a POCUS device with (Echonous, N=22) or without (Butterfly, N=21) AI-functionality for two weeks while on an inpatient rotation. The AI-device provided automatic labeling of cardiac structures, guidance for optimal probe placement to acquire cardiac views, and ejection fraction estimations. Participants were allowed to use the devices at their discretion for patient-related care.The primary outcome was the time to acquire an apical 4-chamber (A4C) image. Secondary outcomes included A4C image quality using the modified Rapid Assessment for Competency in Echocardiography (RACE) scale, correct identification of pathology, and participant attitudes. Measurements were performed at the time of randomization and at two-week follow-up. All scanning assessments were performed on the same standardized patient.ResultsBoth AI and non-AI groups had similar scan times and image quality scores at baseline. At follow-up, the AI group had faster scan times (72 seconds [IQR 38-85] vs. 85 seconds [IQR 54-166]; p=0.01), higher image quality scores (4.5 [IQR 2-5.5] vs. 2 [IQR 1-3]; p<0.01) and correctly identified reduced systolic function more often (85% vs 50%; p=0.02) compared to the non-AI group. Trust in the AI features did not differ between the groups pre- or post-intervention. The AI group did not report increased confidence in their abilities to obtain or interpret cardiac images.ConclusionsPOCUS devices with AI features may improve image acquisition and interpretation by novices. Future studies are needed to determine the extent that AI impacts POCUS learning.