A newly proposed cardiovascular system model under-predicted peak pressure drop by 25% and over-predicted mean pressure drop by 7% for severely stenosed aortic valves compared to literature values.
A newly proposed lumped parameter model of aortic stenosis provides more accurate predictions of transvalvular pressure drops compared to previously published models.
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%.
Laubscher et al. (Sat,) conducted a other in Aortic valve stenosis. Newly proposed valve modeling approach vs. Previously published valve models was evaluated on Transvalvular pressure drops (peak and mean). A newly proposed cardiovascular system model under-predicted peak pressure drop by 25% and over-predicted mean pressure drop by 7% for severely stenosed aortic valves compared to literature values.