Dynamic modeling of the outlet of a pulsatile pump incorporating a flow-dependent resistance

Real-time regurgitation estimation in percutaneous left ventricular assist device fully supported condition using an unscented Kalman filter

Objective.Significant aortic regurgitation is a common complication following left ventricular assist device (LVAD) intervention, and existing studies have not attempted to monitor regurgitation signals and undertake preventive measures during full support. Regurgitation is an adverse event that can lead to inadequate left ventricular unloading, insufficient peripheral perfusion, and repeated episodes of heart failure. Moreover, regurgitation occurring during full support due to pump position offset cannot be directly controlled through control algorithms. Therefore, accurate estimation of regurgitation during percutaneous left ventricular assist device (PLVAD) full support is critical for clinical management and patient safety.Approach.An estimation system based on the regurgitation model is built in this paper, and the unscented Kalman filter estimator (UKF) is introduced as an estimation approach. Three offset degrees and three heart failure states are considered in the investigation. Using the mock circulatory loop experimental platform, compare the regurgitation estimated by the UKF algorithm with the actual measured regurgitation; the errors are analyzed using standard confidence intervals of ±2 SDs, and the effectiveness of the mentioned algorithms is thus assessed. The generalization ability of the proposed algorithm is verified by setting different heart failure conditions and different rotational speeds. The root mean square error and correlation coefficient between the estimated and actual values are quantified and the statistical significance of accuracy differences in estimation is illustrated using one-way analysis of variance (One-Way ANOVA), which in turn assessed the accuracy and stability of the UKF algorithm.Main results.The research findings demonstrate that the regurgitation estimation system based on the regurgitation model and UKF can relatively accurately estimate the regurgitation status of patients during PLVAD full support, but the effect of myocardial contractility on the estimation accuracy still needs to be taken into account.Significance.The proposed estimation method in this study provides essential reference information for clinical practitioners, enabling them to promptly manage potential complications arising from regurgitation. By sensitively detecting LVAD adverse events, valuable insights into the performance and reliability of the LVAD device can be obtained, offering crucial feedback and data support for device improvement and optimization.

Cerebral aneurysm flow diverter modeled as a thin inhomogeneous porous medium in hemodynamic simulations

Rapid and accurate simulation of cerebral aneurysm flow modifications by flow diverters (FDs) can help improving patient-specific intervention and predicting treatment outcome. However, when FD devices are explicitly represented in computational fluid dynamics (CFD) simulations, flow around the stent wires must be resolved, leading to high computational cost. Classic porous medium (PM) methods can reduce computational expense but cannot capture the inhomogeneous FD wire distribution once implanted on a cerebral artery and thus cannot accurately model the post-stenting aneurysmal flow. We report a novel approach that models the FD flow modification as a thin inhomogeneous porous medium (iPM). It improves over the classic PM approaches in two ways. First, the FD is more appropriately treated as a thin screen, which is more accurate than the classic 3D-PM-based Darcy-Forchheimer relation. Second, pressure drop is calculated cell-by-cell using the local FD geometric parameters across an inhomogeneous PM. We applied the iPM technique to simulating the post-stenting hemodynamics of three patient-specific aneurysms. To test its accuracy and speed, we compared the results from the iPM technique against CFD simulations with explicit FD devices. The iPM CFD ran 500% faster than the explicit CFD while achieving 94%-99% accuracy; thus, iPM is a promising clinical bedside modeling tool to assist endovascular interventions with FD and stents.

Modeling left ventricular dynamics using a switched system approach based on a modified atrioventricular piston unit

The contribution of the longitudinal atrioventricular plane displacement to ventricular pumping has drawn more and more attentions. In this paper, differential equations of the left ventricle (LV) are derived via the atrioventricular piston concept. The contribution of left ventricular radial function to blood flow was converted to an equivalent coefficient. A systemic circulatory model incorporating the modified atrioventricular piston unit was developed on a switched system form by adding some state-dependent switching planes. Simulation results prove that the end-systolic pressure volume relationship of the model with a changing systemic arterial resistance is approximately linear and insensitive to perturbations in afterload. Then the LV model was validated using a data fitting method. A pressure-volume loop from a patient undergoing routine diagnostic cardiac catheterization with LV angiography was used as measurements. Model parameters and the trapezoidal profile of contraction forces were adjusted by a trial method. The root mean squared error between the measured and estimated LV pressure is 2.99 mmHg. The LV compliance is 0.34 ml/mmHg. The ratio between left ventricular and left atrial cross-section is 1.8. Therefore, parameter values used in the modified LV model match physiological data. The model can reproduce the realistic pressure-flow relationship in the LV chamber.

Simulation as a preoperative planning approach in advanced heart failure patients. A retrospective clinical analysis

BACKGROUND

Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates.

RESULTS

We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM^© was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process.

CONCLUSIONS

Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.

Simulation as a preoperative planning approach in advanced heart failure patients. A retrospective clinical analysis

BACKGROUND

Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates.

RESULTS

We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM© was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process.

CONCLUSIONS

Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.