Artificial Intelligence-Based Assessment of Indices of Right Ventricular Function.
artificial intelligence
echocardiography
right ventricle
strain
vendor-neutral strain
Journal
Journal of cardiothoracic and vascular anesthesia
ISSN: 1532-8422
Titre abrégé: J Cardiothorac Vasc Anesth
Pays: United States
ID NLM: 9110208
Informations de publication
Date de publication:
Oct 2020
Oct 2020
Historique:
received:
10
11
2019
revised:
10
01
2020
accepted:
14
01
2020
pubmed:
14
3
2020
medline:
28
4
2021
entrez:
14
3
2020
Statut:
ppublish
Résumé
Echocardiographic assessment of right ventricular (RV) function is based largely on visual estimation of tricuspid annulus and motion of the free wall. Regional strain analysis has provided an objective measure of myocardial performance assessment, but is limited in use by vendor-specific software. The study was designed to investigate statistical correlation between RV region-specific strain and echocardiographic parameters of RV function using a vendor-neutral RV-specific strain assessment program. This is a retrospective study. Tertiary hospital. One hundred seven patients undergoing coronary artery bypass graft, valve repair or replacement, or a combination of procedures. None. One hundred seven patients underwent comprehensive echocardiographic of RV function intraoperatively. Off-line analysis of global, longitudinal, and septal strain was performed using a vendor-neutral software. The 2 values were compared statistically. All pairs demonstrated strong statistical significance; the strongest relationships were between (1) RV fractional area change (FAC) (%)-RV longitudinal strain (r RV function can be assessed objectively by strain analyses across different platforms using the artificial intelligence-based vendor-neutral strain analysis software. There is a statistically significant correlation between strain values and conventional 2-dimensional echocardiographic parameters of RV function.
Identifiants
pubmed: 32165105
pii: S1053-0770(20)30085-9
doi: 10.1053/j.jvca.2020.01.024
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2698-2702Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.