echocardiogram

Can artificial intelligence guide novice operators to obtain echocardiographic scans with limited diagnostic utility?

By A. Narang et al

In this prospective, multi-centre diagnostic study by Narang et al, a cohort of 8 nurses without prior ultrasonography experience used artificial intelligence guidance to scan 30 patients each with a 10-view echocardiographic protocol (240 total patients).

Five expert echocardiographers blindly reviewed these scans and felt they were of diagnostic quality for left ventricular size and function in 98.8% of patients, right ventricular size in 92.5%, and presence of pericardial effusion in 98.8%.

Artificial intelligence can extend the reach of echocardiography to assess the 4 basic parameters of left ventricular size and function, right ventricular size, and presence of a nontrivial pericardial effusion to sites with limited expertise.

Read the full open access article on the JAMA website: 
https://jamanetwork.com/journals/jamacardiology/fullarticle/2776714

Watch the videos: 
https://edhub.ama-assn.org/jn-learning/video-player/18585899
https://edhub.ama-assn.org/jn-learning/video-player/18585901

Reference: 
Narang A, Bae R, Hong H, Thomas Y, Surette S, Cadieu C, Chaudhry A, Martin RP, McCarthy PM, Rubenson DS, Goldstein S, Little SH, Lang RM, Weissman NJ, Thomas JD. Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use. JAMA Cardiol. 2021 Jun 1;6(6):624-632. doi: 10.1001/jamacardio.2021.0185. PMID: 33599681; PMCID: PMC8204203.