Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.
Artificial intelligence
Machine learning
Two-dimensional echocardiography
Journal
The international journal of cardiovascular imaging
ISSN: 1875-8312
Titre abrégé: Int J Cardiovasc Imaging
Pays: United States
ID NLM: 100969716
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
17
03
2023
accepted:
16
09
2023
medline:
4
12
2023
pubmed:
24
10
2023
entrez:
23
10
2023
Statut:
ppublish
Résumé
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recently developed and validated deep learning (DL) algorithm for automated measurements of echocardiographic parameters of left heart chamber size and function can improve the reproducibility and shorten the analysis time, compared to the conventional methodology. The DL algorithm trained to identify standard views and provide automated measurements of 20 standard parameters, was applied to images obtained in 12 randomly selected echocardiographic studies. The resultant measurements were reviewed and revised as necessary by 10 independent expert readers. The same readers also performed conventional manual measurements, which were averaged and used as the reference standard for the DL-assisted approach with and without the manual revisions. Inter-reader variability was quantified using coefficients of variation, which together with analysis times, were compared between the conventional reads and the DL-assisted approach. The fully automated DL measurements showed good agreement with the reference technique: Bland-Altman biases 0-14% of the measured values. Manual revisions resulted in only minor improvement in accuracy: biases 0-11%. This DL-assisted approach resulted in a 43% decrease in analysis time and less inter-reader variability than the conventional methodology: 2-3 times smaller coefficients of variation. In conclusion, DL-assisted approach to analysis of echocardiographic images can provide accurate left heart measurements with the added benefits of improved reproducibility and time savings, compared to conventional methodology.
Identifiants
pubmed: 37872467
doi: 10.1007/s10554-023-02960-5
pii: 10.1007/s10554-023-02960-5
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2507-2516Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature B.V.
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