Windkessel model of hemodynamic state supported by a pulsatile ventricular assist device in premature ventricle contraction

Abstract

BackgroundCounter-pulsation control (CPC) by ventricular assist devices (VADs) is believed to reduce cardiac load and increase coronary perfusion. However, patients with VADs have a higher risk of arrhythmia, which may cause the CPC to fail. Consequently, CPC has not been applied by VADs in clinical practice. The phase-locked loop (PLL) algorithm for CPC is readily implemented in VADs; however, it requires a normal, consistent heartbeat for adequate performance. When an arrhythmia occurs, the algorithm maintains a constant pumping rate despite the unstable heartbeat. Therefore, to apply the PLL algorithm to CPC, the hemodynamic effects of abnormal heartbeats must be analyzed.ObjectivesThis study sought to predict the hemodynamic effects in patients undergoing CPC using VADs, based on electrocardiogram (ECG) data, including a wide range of heart rate (HR) changes caused by premature ventricular contraction (PVC) or other reasons.MethodsA four-element Windkessel hemodynamic model was used to reproduce the patient’s aortic blood pressure in this study. ECG data from 15 patients with severe congestive heart failure were used to assess the effect of the CPC on the patients’ hemodynamic state. The input and output flow characteristics of the pulsatile VAD (LibraHeart I, Cervika, Korea) were measured using an ultrasound blood flow meter (TS410, Transonic, USA), with the aortic pressure maintained at 80–120 mmHg. All other patient conditions were also reproduced.ResultsIn patients with PVCs or normal heartbeats, CPC controlled by a VAD reduced the cardiac load by 20 and 40%, respectively. When the HR was greater for other reasons, such as sinus tachycardia, simultaneous ejection from the heart and VAD was observed; however, the cardiac load was not increased by rapid cardiac contractions resulting from decreased left ventricle volume. These data suggest that the PLL algorithm reduces the cardiac load and maintains consistent hemodynamic changes.

A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

“…Compared with the two-element and three-element Windkessel models, it is more difficult to identify the model parameters of the four-element Windkessel model. Consequently, only a few researchers make use of this model [23, 37, 38].…”

“…Many researchers chose aortic flow as model input [22, 44, 45]. Flow at other positions was selected as model input, such as carotid flow [46], left ventricle flow [23] and mitral valve mean flow [47]. Few researchers chose brachial and radial pressure as model input [48].…”

“…Few researchers chose brachial and radial pressure as model input [48]. For model parameter acquisition, the majority of researchers calculated model parameters by population averaging [22, 23, 44–46, 48] and only a small number of researchers adopted partially individualized model parameters [47].…”

A Beating Heart Testbed for the Evaluation of Robotic Cardiovascular Interventions

“…A left heart simulator was presented by Rabbah et al, which is used for the study of MV mechanics and hemodynamics [18]. Mock loops that used various versions of a Windkessel model have been described by a number researchers [19]- [21]. In these studies, a Windkessel model is used to mimic resistance and compliance of the aorta and arteries of the vascular system.…”

Control of continuum robots for minimally invasive interventions

“…A left heart simulator was presented by Rabbah et al, which is used for the study of MV mechanics and hemodynamics [154]. Mock loops that used various versions of a Windkessel model have been described by a number researchers [155][156][157]. In these studies, a Windkessel model is used to mimic resistance and compliance of the aorta and arteries of the vascular system.…”