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Randomized Controlled Trial
. 2023 Apr;616(7957):520-524.
doi: 10.1038/s41586-023-05947-3. Epub 2023 Apr 5.

Blinded, randomized trial of sonographer versus AI cardiac function assessment

Affiliations
Randomized Controlled Trial

Blinded, randomized trial of sonographer versus AI cardiac function assessment

Bryan He et al. Nature. 2023 Apr.

Abstract

Artificial intelligence (AI) has been developed for echocardiography1-3, although it has not yet been tested with blinding and randomization. Here we designed a blinded, randomized non-inferiority clinical trial (ClinicalTrials.gov ID: NCT05140642; no outside funding) of AI versus sonographer initial assessment of left ventricular ejection fraction (LVEF) to evaluate the impact of AI in the interpretation workflow. The primary end point was the change in the LVEF between initial AI or sonographer assessment and final cardiologist assessment, evaluated by the proportion of studies with substantial change (more than 5% change). From 3,769 echocardiographic studies screened, 274 studies were excluded owing to poor image quality. The proportion of studies substantially changed was 16.8% in the AI group and 27.2% in the sonographer group (difference of -10.4%, 95% confidence interval: -13.2% to -7.7%, P < 0.001 for non-inferiority, P < 0.001 for superiority). The mean absolute difference between final cardiologist assessment and independent previous cardiologist assessment was 6.29% in the AI group and 7.23% in the sonographer group (difference of -0.96%, 95% confidence interval: -1.34% to -0.54%, P < 0.001 for superiority). The AI-guided workflow saved time for both sonographers and cardiologists, and cardiologists were not able to distinguish between the initial assessments by AI versus the sonographer (blinding index of 0.088). For patients undergoing echocardiographic quantification of cardiac function, initial assessment of LVEF by AI was non-inferior to assessment by sonographers.

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Conflict of interest statement

Stanford University is in the process of applying for a patent application covering video-based deep learning models for assessing cardiac function that lists B.H., J.Y.Z. and D.O. as inventors. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Consort diagram.
Screening, randomization and follow-up.
Fig. 2
Fig. 2. Comparison of AI versus sonographer guidance on cardiologist assessment and difference between final versus previous cardiologist assessments.
Dots represent individual studies and lines represent the lines of best fit. MAD, mean absolute difference.

Comment in

References

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