Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation

Autor: Catherine C. Stowell, Valeria Kallassy, Beth Lane, Jonathan Abbott, Kieran Borgeat, David Connolly, Oriol Domenech, Joanna Dukes‐McEwan, Luca Ferasin, Josefa Fernández Del Palacio, Chris Linney, Jose Novo Matos, Ilaria Spalla, Nuala Summerfield, Tommaso Vezzosi, James P. Howard, Matthew J. Shun‐Shin, Darrel P. Francis, Virginia Luis Fuentes
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Journal of Veterinary Internal Medicine, Vol 38, Iss 2, Pp 922-930 (2024)
Druh dokumentu: article
ISSN: 1939-1676
0891-6640
DOI: 10.1111/jvim.17012
Popis: Abstract Background Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs. Hypothesis A neural network can be trained to measure echocardiographic left ventricular (LV) linear dimensions in dogs. Animals Training dataset: 1398 frames from 461 canine echocardiograms from a single specialist center. Validation: 50 additional echocardiograms from the same center. Methods Training dataset: a right parasternal 4‐chamber long axis frame from each study, labeled by 1 of 18 echocardiographers, marking anterior and posterior points of the septum and free wall. Validation Dataset End‐diastolic and end‐systolic frames from 50 studies, annotated twice (blindly) by 13 experts, producing 26 measurements of each site from each frame. The neural network also made these measurements. We quantified its accuracy as the deviation from the expert consensus, using the individual‐expert deviation from consensus as context for acceptable variation. The deviation of the AI measurement away from the expert consensus was assessed on each individual frame and compared with the root‐mean‐square‐variation of the individual expert opinions away from that consensus. Results For the septum in end‐diastole, individual expert opinions deviated by 0.12 cm from the consensus, while the AI deviated by 0.11 cm (P = .61). For LVD, the corresponding values were 0.20 cm for experts and 0.13 cm for AI (P = .65); for the free wall, experts 0.20 cm, AI 0.13 cm (P
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