Quantifying left ventricular myocardial strain in patients with different CAD-RADS levels based on computed tomography feature tracking technology

© 2023. Springer Nature Limited..

To evaluate myocardial strain in patients with different coronary artery disease-reporting and data system (CAD-RADS) levels using the computed tomography (CT) feature tracking technology and to investigate the relationship of myocardial strain with coronary artery calcium scores (CACs) and the degree of coronary artery stenosis. We prospectively enrolled 237 consecutive patients to undergo coronary CT angiography. The participants were divided into the following groups: control (n = 87), CAD-RADS 1 (n = 43), CAD-RADS 2 (n = 43), CAD-RADS 3 (n = 38), and CAD-RADS 4 and above (n = 26). Myocardial strains were analyzed by commercial software, and CACs and coronary stenosis were assessed on post-processing stations. Differences between multiple groups were analyzed using one-way analysis of variance or the Kruskal-Wallis test. Logistic regression were used to analyze the effects of dichotomous variables. As the CAD-RADS level increased, the global circumferential strain (GCS), global longitudinal strain (GLS) and global radial strain (GRS) of the left ventricle based on CT gradually decreased. A significant correlation was observed between global myocardial strain and CACs (GRS: r =  - 0.219, GCS: r = 0.189, GLS: r = 0.491; P < 0.05). The independent predictors of obstructive CAD were age (β = 0.065, odds ratio [OR] = 1.067, P = 0.005), left ventricular ejection fraction (β = 0.145, OR = 1.156, P = 0.047), and GLS (β = 0.232, OR = 1.261, P = 0.01). CT-derived GLS of the left ventricle is correlated with CAD-RADS levels and CACs. It may be a better indicator than CACs to reflect the severity of CAD.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

Scientific reports - 13(2023), 1 vom: 11. Okt., Seite 17199

Sprache:

Englisch

Beteiligte Personen:

Li, Na [VerfasserIn]
Zhang, Lijie [VerfasserIn]
Wu, Hongying [VerfasserIn]
Liu, Jia [VerfasserIn]
Cao, Yukun [VerfasserIn]
Li, Yumin [VerfasserIn]
Yu, Jie [VerfasserIn]
Han, Xiaoyu [VerfasserIn]
Shao, Guozhu [VerfasserIn]
Yang, Ming [VerfasserIn]
Gu, Jin [VerfasserIn]
Chen, Lina [VerfasserIn]
Wang, Jiangtao [VerfasserIn]
Shi, Heshui [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 01.11.2023

Date Revised 19.11.2023

published: Electronic

Citation Status MEDLINE

doi:

10.1038/s41598-023-44530-8

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM363146652