Dynamic simulation of aortic valve stenosis using a lumped parameter cardiovascular system model with flow regime dependent valve pressure loss characteristics. (August 2022)

• Record Type: Journal Article
• Authors: Laubscher, Ryno; van der Merwe, Johan; Liebenberg, Jacques; Herbst, Philip
• Is Part Of: Medical engineering & physics. Volume 106(2022)
• Publication Date: 2022-08
• Subjects: Cardiovascular system -- Aortic stenosis -- Mitral regurgitation -- Lumped parameter modelling -- Valve dynamics -- Valve pressure losses; Biomedical engineering -- Periodicals; Biomedical Engineering -- Periodicals; Physics -- Periodicals; Génie biomédical -- Périodiques; Biomedical engineering; Electronic journals; Periodicals; 610.28
• DOI: 10.1016/j.medengphy.2022.103838
• Languages: English
• ISSNs: 1350-4533

Abstract

Highlights: Multi-compartment lumped parameter modelling of cardiovascular system. Development of 0D geometry dependent heart valve pressure drop model. Comparison of proposed model to state-of-the-art 0D heart valve models. Cardiovascular models applied to study aortic stenosis. Model results for varying degrees of aortic stenosis compared to physiological values. Abstract: Valvular heart diseases are growing concern in impoverished parts of the world, such as Southern-Africa, claiming more than 31 % of total deaths related to cardiovascular diseases. The ability to model the effects of regurgitant and obstructive lesions on the valve body can assist clinicians in preparing personalised treatments. In the present work, a multi-compartment lumped parameter model of the human cardiovascular system is developed, with a newly proposed valve modelling approach which accounts for geometry and flow regime dependent pressure drops along with the valve cusp motion. The model is applied to study various degrees of aortic stenosis using typical human cardiovascular parameters. The predicted transvalvular pressure drops for the different modelling approaches are compared to typical measured mean and peak gradients found in literature for severely stenosed aortic valves. The comparison between the predicted and measured values show that the previously published valve models under predicts expected severely stenosed peak and mean transvalvular pressure drops by approximately 47% and 25% respectively, whereas the newly proposed model under predicts the peak pressure drop by 25% and over predicts mean pressure drop by 7%.