Back to Search Start Over

In Silico Modelling of Aortic Strain and Strain Rate in Aortic Coarctation Treated with Stent Angioplasty with Comparison to Clinical Cohorts

Authors :
Nicholas Gaddum
Des Dillon-Murphy
Richard Arm
Isma Rafiq
Radomir Chabiniok
Gareth Morgan
Tobias Schaeffter
Tarique Hussain
Source :
Applications in Engineering Science, Vol 12, Iss , Pp 100123- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

ABSTRACT: Objective: Treatment of aortic coarctation has seen a shift from traditional surgical repair to the use of aortic stents. The aim of this study was to assess the impact upon hemodynamics and arterial strain when aortic coarctation is treated with a stent using an experimental coarctation model, and to confirm any findings in a clinical cohort using MRI. Methods: An experimental patient model included a silicone arterial tree, and ventricular stroke profile was derived from patient MRI data. Pressure, flow and aortic strain was measured before and after stent placement in the model. A clinical study comprised of strain measurements using MRI in two patient cohorts; those treated with a stent, and those treated with surgical repair. Results: Before stent placement, peak strain decreased as the pulse propagated away from the aortic valve. After stent placement however, peak strain was amplified as it approached the stent, despite peak systolic pressure having dropped by 20 mmHg. Introduction of the stent caused an almost three fold increase in aortic strain rate to 150%.s − 1. Echoing these results the stented patient group's strain increased from 28% +/- 14% in the ascending aorta to 43% +/- 24% (p < 0.05) pre-coarctation. This was not seen in those with surgical repair of coarctation, (ascending aorta 40% +/- 22% compared to the pre-coarctation aorta strain 38% +/- 20%, p = 0.81). Conclusions: Despite a reduced systolic pressure gradient through a stented coarctation, dramatic increases in strain and strain rate could attribute subsequent pathologies in the aorta proximally.

Details

Language :
English
ISSN :
26664968
Volume :
12
Issue :
100123-
Database :
Directory of Open Access Journals
Journal :
Applications in Engineering Science
Publication Type :
Academic Journal
Accession number :
edsdoj.15daba03c50043d890d161b6b40baa5b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.apples.2022.100123