Artificial Intelligence-Based Assessment of Indices of Right Ventricular Function.


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
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

2698-2702

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Shuo Liu (S)

Department of Anesthesiology, Peking University People's Hospital, Beijing, China; Echo Lab, Beth Israel Deaconess Medical Center, Boston, MA.

Ruma Bose (R)

Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA. Electronic address: rbose@bidmc.harvard.edu.

Andaleeb Ahmed (A)

Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Andrew Maslow (A)

Division of Cardiac Anesthesia, Rhode Island Hospital, Providence, RI.

Yi Feng (Y)

Department of Anesthesiology, Peking University People's Hospital, Beijing, China.

Aidan Sharkey (A)

Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Yanick Baribeau (Y)

Echo Lab, Beth Israel Deaconess Medical Center, Boston, MA.

Feroze Mahmood (F)

Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Robina Matyal (R)

Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA.

Kamal Khabbaz (K)

Cardiothoracic Surgery, Beth Israel Deaconess Medical Center, Boston, MA.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH