Stenosis, defined by a partial or full obstruction of the arteries, is a frequent anomaly in the cardiovascular system. The pressure drop across a stenosis indicates the severity of the pathology. There is currently no non-invasive method to obtain this pressure drop. In this communication, we use four different blood flow models to compute the pressure in an idealized geometry of stenosis: the steady RNSP model, the Multi-Ring model, the 1D model, and algebraic models. We compare these models on a test case under a steady flow. We then developed a gradient-based parameter estimation method to compare the complex models (1D and Multi-Ring) with algebraic formulas. We used the parameter estimation to evaluate the influence of the geometry, wall elasticity and flow parameter on the empirical coefficients of the algebraic formulas.
Aortic cross‐clamping is a common strategy during vascular surgery, however, its instantaneous impact on hemodynamics is unknown. We, therefore, developed two numerical models to estimate the immediate impact of aortic clamping on the vascular properties. To assess the validity of the models, we recorded continuous invasive pressure signals during abdominal aneurysm repair surgery, immediately before and after clamping. The first model is a zero‐dimensional (0D) three‐element Windkessel model, which we coupled to a gradient‐based parameter estimation algorithm to identify patient‐specific parameters such as vascular resistance and compliance. We found a 10% increase in the total resistance and a 20% decrease in the total compliance after clamping. The second model is a nine‐artery network corresponding to an average human body in which we solved the one‐dimensional (1D) blood flow equations. With a similar parameter estimation method and using the results from the 0D model, we identified the resistance boundary conditions of the 1D network. Determining the patient‐specific total resistance and the distribution of peripheral resistances through the parameter estimation process was sufficient for the 1D model to accurately reproduce the impact of clamping on the pressure waveform. Both models gave an accurate description of the pressure wave and had a high correlation (R2 > .95) with experimental blood pressure data.
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