Control of ventricular unloading using an electrocardiogram-synchronized pulsatile ventricular assist device under high stroke ratios.

Pulsatile ventricular assist devices (pVADs) yield a blood flow that imitates the pulsatile flow of the heart and, therefore, could diminish the adverse events related to the continuous flow provided by the ventricular assist devices that are commonly used. However, their intrinsic characteristics of larger size and higher weight set a burden to their implantation, that along with the frequent mechanical failures and thrombosis events, reduce the usage of pVADs in the clinical environment. In this study, we investigated the possibility to reduce the pump size by using high pump stroke ratios while maintaining the ability to control the hemodynamics of the cardiovascular system (CVS). In vitro and in vivo experiments were conducted with a custom pVAD implemented on a hybrid mock circulation system and in five sheep, respectively. The actuation of the pVAD was synchronized with the heartbeat. Variations of the pump stroke ratio, time delay between the pump stroke and the heart stroke, as well as duration of the pump systole in respect to the total cardiac cycle duration were used to evaluate the effects of various pump settings on the hemodynamics of the CVS. The results suggest that by varying the operating settings of the pVAD, a pulsatile flow that provides physiological hemodynamic parameters, as well as a control over the hemodynamic parameters, can be achieved. Additionally, by employing high pump stroke ratios, the size of the pVAD can be significantly reduced; however, at those high pump stroke ratios, the effect of the other pump parameters diminishes.

Performance and Reliable Operation of Physiological Controllers Under Various Cardiovascular Models: In Silico and In Vitro Study.

The evaluation of control schemes for left ventricular assist devices (LVADs) requires the utilization of an appropriate model of the human cardiovascular system. Given that different patients and experimental data yield varying performance of the cardiovascular models (CVMs) and their respective parameters, it becomes crucial to assess the reliable operation of controllers. This study aims to assess the performance and reliability of various LVAD controllers using two state-of-the-art CVMs, with a specific focus on the impact of interpatient variability. Extreme test cases were employed for evaluation, incorporating both in silico and in vitro experiments. The differences observed in response between the studied CVMs can be attributed to variations in their structures and parameters. Specifically, the model with smaller compartments exhibits higher overload rates, whereas the other model demonstrates increased sensitivity to changes in preload and afterload, resulting in more frequent suction events (34.2% vs. 8.5% for constant speed mode). These findings along with the varying response of the tested controllers highlight the influence of the selected CVM emphasizing the need to test each LVAD controller with multiple CVMs or, at least, a range of parameter sets. This approach ensures sufficient evaluation of the controller's efficacy in addressing interpatient variability.

Performance and Robustness of Physiological Controllers With Integrated Pressure Sensors on Inflow Cannula.

The control of left ventricular assist devices (LVADs) requires sensors and/or estimators to account for the physiological state of the patient and apply advanced controllers. Sensor characteristics are a challenge when using implantable pressure sensors because they influence the quality of physiological control and the robustness of the controlled system. The objective of this work is to investigate the performance and robustness of LVAD controllers that operate based on LVAD integrated pressure sensors. Four pressure-based LVAD controllers are tested with a HeartMate 3 that has an integrated pressure sensor. Controller sensitivity as well as robustness to sensor drift and noise are evaluated based on controller response to large changes in preload and afterload. A fail-safe strategy for sensor failure used also to investigate the reliable operation of the LVAD in realistic conditions. All tested controllers are sensitive to drifting pressure signals, which can lead to unstable behavior. The results show that two controllers are robust to noise. The other two controllers show high deviation and oscillation in cardiac output even for small noise. Additionally, a noticeable difference of the controller's response between simulated and measured pressure input was observed, indicating the need for a robust controller design. Reliable operation even in the event of a sensor failure was achieved on the basis of a fail-safe control system.

Continuous Monitoring of Blood Pressure and Vascular Hemodynamic Properties With Miniature Extravascular Hall-Based Magnetic Sensor.

Continuous measurement of vascular and hemodynamic parameters could improve monitoring of disease progression and enable timely clinical decision making and therapy surveillance in patients suffering from cardiovascular diseases. However, no reliable extravascular implantable sensor technology is currently available. Here, we report the design, characterization, and validation of an extravascular, magnetic flux sensing device capable of capturing the waveforms of the arterial wall diameter, arterial circumferential strain, and arterial pressure without restricting the arterial wall. The implantable sensing device, comprising a magnet and a magnetic flux sensing assembly, both encapsulated in biocompatible structures, has shown to be robust, with temperature and cyclic-loading stability. Continuous and accurate monitoring of arterial blood pressure and vascular properties was demonstrated with the proposed sensor in vitro with a silicone artery model and validated in vivo in a porcine model mimicking physiologic and pathologic hemodynamic conditions. The captured waveforms were further used to deduce the respiration frequency, the duration of the cardiac systolic phase, and the pulse wave velocity. The findings of this study not only suggest that the proposed sensing technology is a promising platform for accurate monitoring of arterial blood pressure and vascular properties, but also highlight the necessary changes in the technology and the implantation procedure to allow the translation of the sensing device in the clinical setting.

In-vitro investigation of endothelial monolayer retention on an inflow VAD cannula inside a beating heart phantom.

Ventricular assist devices (VADs) provide an alternative solution to heart transplantation for patients with end-stage heart failure. Insufficient hemocompatibility of VAD components can result in severe adverse events, such as thromboembolic stroke, and readmissions. To enhance VAD hemocompatibility, and avoid thrombus formation, surface modification techniques and endothelialization strategies are employed. In this work, a free form patterning topography is selected to facilitate the endothelialization of the outer surface of the inflow cannula (IC) of a commercial VAD. An endothelialization protocol for convoluted surfaces such as the IC is produced, and the retainment of the endothelial cell (EC) monolayer is evaluated. To allow this evaluation, a dedicated experimental setup is developed to simulate realistic flow phenomena inside an artificial, beating heart phantom with a VAD implanted on its apex. The procedural steps of mounting the system result to the impairment of the EC monolayer, which is further compromised by the developed flow and pressure conditions, as well as by the contact with the moving inner structures of the heart phantom. Importantly, the EC monolayer is better maintained in the lower part of the IC, which is more susceptible to thrombus formation and may therefore aid in minimizing the hemocompatibility related adverse events after the VAD implantation.

Physiologic Data-Driven Iterative Learning Control for Left Ventricular Assist Devices.

Continuous flow ventricular assist devices (cfVADs) constitute a viable and increasingly used therapy for end-stage heart failure patients. However, they are still operating at a fixed-speed mode that precludes physiological cfVAD response and it is often related to adverse events of cfVAD therapy. To ameliorate this, various physiological controllers have been proposed, however, the majority of these controllers do not account for the lack of pulsatility in the cfVAD operation, which is supposed to be beneficial for the physiological function of the cardiovascular system. In this study, we present a physiological data-driven iterative learning controller (PDD-ILC) that accurately tracks predefined pump flow trajectories, aiming to achieve physiological, pulsatile, and treatment-driven response of cfVADs. The controller has been extensively tested in an in-silico environment under various physiological conditions, and compared with a physiologic pump flow proportional-integral-derivative controller (PF-PIDC) developed in this study as well as the constant speed (CS) control that is the current state of the art in clinical practice. Additionally, two treatment objectives were investigated to achieve pulsatility maximization and left ventricular stroke work (LVSW) minimization by implementing copulsation and counterpulsation pump modes, respectively. Under all experimental conditions, the PDD-ILC as well as the PF-PIDC demonstrated highly accurate tracking of the reference pump flow trajectories, outperforming existing model-based iterative learning control approaches. Additionally, the developed controllers achieved the predefined treatment objectives and resulted in improved hemodynamics and preload sensitivities compared to the CS support.

Pressure and Bernoulli-Based Flow Measurement via a Tapered Inflow VAD Cannula.

OBJECTIVE: Currently available ventricular assist devices provide continuous flow and do not adapt to the changing needs of patients. Physiological control algorithms have been proposed that adapt the pump speed based on the left ventricular pressure. However, so far, no clinically used pump can acquire this pressure. Therefore, for the validation of physiological control concepts in vivo, a system that can continuously and accurately provide the left ventricular pressure signal is needed. METHODS: We demonstrate the integration of two pressure sensors into a tapered inflow cannula compatible with the HeartMate 3 (HM3) ventricular assist device. Selective laser melting was used to incorporate functional elements with a small footprint and therefore retain the geometry, function and implantability of the original cannula. The system was tested on a hybrid mock circulation system. Static and simulated physiological flow and pressure profiles were used to evaluate the combined pressure and flow sensing capabilities of the modified cannula. RESULTS: The cannula prototypes enabled continuous pressure measurements at two points of their inner wall in the range of -100 and 200 mmHg. The developed, Bernoulli-based, two sensor model improved the accuracy of the measured simulated left ventricular pressure by eliminating the influence of flow inside the cannula. This method reduced the flow induced pressure uncertainty from up to 7.6 mmHg in single sensor measurements to 0.3 mmHg. Additionally, the two-sensor system and model enable the measurement of the blood flow through the pump with an accuracy of -0.14 ± 0.04 L/min, without dedicated flow sensors.

Building an interdisciplinary program of cardiovascular research at the Swiss Federal Institute of Technology- the ETHeart story.

In this backstory, researchers from Swiss Federal Institute of Technology (ETH Zurich) who initiated an interdisciplinary program to generate innovative solutions for different cardiovascular diseases, such as myocardial infarction, valvular replacement, and movement-based rehabilitation therapy, discuss the benefits and challenges of interdisciplinary research.

Cardiac Output Estimation: Online Implementation for Left Ventricular Assist Device Support.

OBJECTIVE: We present a novel pipeline that consists of various algorithms for the estimation of the cardiac output (CO) during ventricular assist devices (VADs) support using a single pump inlet pressure (PIP) sensor as well as pump intrinsic signals. METHODS: A machine learning (ML) model was constructed for the prediction of the aortic valve opening status. When a closed aortic valve is detected, the estimated CO equals the estimated pump flow. Otherwise, the estimated CO equals the sum of the estimated pump flow and the aortic valve flow, estimated via a Kalman-filter approach. Both the pathophysiological conditions and the pump speed of an in-vitro test bench were adjusted in various combinations to evaluate the performance of the pipeline, as well as the individual estimators. RESULTS: The ML model yielded a Matthews correlation coefficient of 0.771, a sensitivity of 0.913 and a specificity of 0.871. An overall CO root mean square error (RMSE) of 0.69 L/min was achieved. Replacing the pump flow and aortic pressure estimators with sensors would decrease the RMSE below 0.5 L/min. CONCLUSION: The performance of the proposed pipeline is considered the state of the art for VADs with an integrated PIP sensor. The effect of the individual estimators on the overall performance of the pipeline was thoroughly investigated and their limitations were identified for future research. SIGNIFICANCE: The clinical application of the proposed solution could provide the clinicians with essential information about the interaction between the patient's heart and the VAD to further improve the VAD therapy.

Continuous Heart Volume Monitoring by Fully Implantable Soft Strain Sensor.

Cardiothoracic open-heart surgery has revolutionized the treatment of cardiovascular disease, the leading cause of death worldwide. After the surgery, hemodynamic and volume management can be complicated, for example in case of vasoplegia after endocarditis. Timely treatment is crucial for outcomes. Currently, treatment decisions are made based on heart volume, which needs to be measured manually by the clinician each time using ultrasound. Alternatively, implantable sensors offer a real-time window into the dynamic function of our body. Here it is shown that a soft flexible sensor, made with biocompatible materials, implanted on the surface of the heart, can provide continuous information of the heart volume after surgery. The sensor works robustly for a period of two days on a tensile machine. The accuracy of measuring heart volume is improved compared to the clinical gold standard in vivo, with an error of 7.1 mL for the strain sensor versus impedance and 14.0 mL versus ultrasound. Implanting such a sensor would provide essential, continuous information on heart volume in the critical time following the surgery, allowing early identification of complications, facilitating treatment, and hence potentially improving patient outcome.