Publications by authors named "Robert Salamonsen"

: This review explores the Starling-like physiological control method (SLC) for rotary ventricular assist devices (VADs) for severe heart failure. The SLC, based on mathematical models of the circulation, has two functions modeling each ventricle. The first function controls the output of the VAD to the arterial pool according to Starling's law, while the second function accounts for how the blood returns to the heart from the veins.

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Rotary ventricular assist devices (VADs) operated clinically under constant speed control (CSC) cannot respond adequately to changes in patient cardiac demand, resulting in sub-optimal VAD flow regulation. Starling-like control (SLC) of VADs mimics the healthy ventricular flow regulation and automatically adjusts VAD speed to meet varying patient cardiac demand. The use of a fixed control line (CL - the relationship between ventricular preload and VAD flow) limits the flow regulating capability of the controller, especially in the case of exercise.

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The high cost of ventricular assist devices results in poor cost-effectiveness when used as a short-term bridging solution, thus a low-cost alternative is desirable. The present study aimed to develop an intraventricular balloon pump (IVBP) for short-term circulatory support, and to evaluate the effect of balloon actuation timing on the degree of cardiac support provided to a simulated in vitro severe heart failure (SHF) patient. A silicone IVBP was designed to avoid contact with internal left ventricular (LV) features (ie, papillary muscles, chordae, aortic, and mitral valves) based on LV computed tomography data of 10 SHF patients with dilated cardiomyopathy.

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Rotary blood pumps may be used as ventricular assist devices (VADs) to support patients with end-stage heart failure-'rotary VADs'. Clinically, rotary VADs are operated at a constant speed which is set manually. Due to inadequate haemodynamic monitoring equipment outside of the hospital setting, device speed remains the same for weeks or months at a time, leaving clinicians in the dark, and patients vulnerable to harmful over- or under-pumping events.

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Rotary ventricular assist devices (VADs) are less sensitive to preload than the healthy heart, resulting in inadequate flow regulation in response to changes in patient cardiac demand. Starling-like physiological controllers (SLCs) have been developed to automatically regulate VAD flow based on ventricular preload. An SLC consists of a cardiac response curve (CRC) which imposes a nonlinear relationship between VAD flow and ventricular preload, and a venous return line (VRL) which determines the return path of the controller.

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Control for dual rotary left ventricular assist devices (LVADs) used as a biventricular assist device (BiVAD) is challenging. If the control system fails, flow imbalance between the systemic and the pulmonary circulations would result, subsequently leading to ventricular suction or pulmonary congestion. With the expectation that advanced control approaches such as model predictive control could address the challenges naturally and effectively, we developed a synergistic first principles model predictive controller (MPC) for the BiVAD.

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Rotary ventricular assist devices (VADs) are used to provide mechanical circulatory support. However, their lack of preload sensitivity in constant speed control mode (CSC) may result in ventricular suction or venous congestion. This is particularly true of biventricular support, where the native flow-balancing Starling response of both ventricles is diminished.

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Due to a shortage of donor hearts, rotary left ventricular assist devices (LVADs) are used to provide mechanical circulatory support. To address the preload insensitivity of the constant speed controller (CSC) used in conventional LVADs, we developed a preload-based Starling-like controller (SLC). The SLC emulates the Starling law of the heart to maintain mean pump flow ([Formula: see text]) with respect to mean left ventricular end diastolic pressure (PLVEDm) as the feedback signal.

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Background: Donation after circulatory death (DCD) represents a potential new source of hearts to increase the donor pool. We showed previously that DCD hearts in Greyhound dogs could be resuscitated and preserved by continuous cold crystalloid perfusion but not by cold static storage and could demonstrate excellent contractile and metabolic function on an in vitro system. In the current study, we demonstrate that resuscitated DCD hearts are transplantable.

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Preventing ventricular suction and venous congestion through balancing flow rates and circulatory volumes with dual rotary ventricular assist devices (VADs) configured for biventricular support is clinically challenging due to their low preload and high afterload sensitivities relative to the natural heart. This study presents the in vivo evaluation of several physiological control systems, which aim to prevent ventricular suction and venous congestion. The control systems included a sensor-based, master/slave (MS) controller that altered left and right VAD speed based on pressure and flow; a sensor-less compliant inflow cannula (IC), which altered inlet resistance and, therefore, pump flow based on preload; a sensor-less compliant outflow cannula (OC) on the right VAD, which altered outlet resistance and thus pump flow based on afterload; and a combined controller, which incorporated the MS controller, compliant IC, and compliant OC.

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Introduction: Left ventricular assist devices are crucial in rehabilitation of patients with end-stage heart failure. Whether cardiopulmonary function is enhanced with higher pump output is unknown.

Methods: 10 patients (aged 39±16 years, mean±SD) underwent monitored adjustment of pump speed to determine minimum safe low speed and maximum safe high speed at rest.

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This study in five large greyhound dogs implanted with a VentrAssist left ventricular assist device focused on identification of the precise site and physiological changes induced by or underlying the complication of left ventricular suction. Pressure sensors were placed in left and right atria, proximal and distal left ventricle, and proximal aorta while dual perivascular and tubing ultrasonic flow meters measured blood flow in the aortic root and pump outlet cannula. When suction occurred, end-systolic pressure gradients between proximal and distal regions of the left ventricle on the order of 40-160 mm Hg indicated an occlusive process of variable intensity in the distal ventricle.

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In this study, we evaluate a preload-based Starling-like controller for implantable rotary blood pumps (IRBPs) using left ventricular end-diastolic pressure (PLVED) as the feedback variable. Simulations are conducted using a validated mathematical model. The controller emulates the response of the natural left ventricle (LV) to changes in PLVED.

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The present study investigates the response of implantable rotary blood pump (IRBP)-assisted patients to exercise and head-up tilt (HUT), as well as the effect of alterations in the model parameter values on this response, using validated numerical models. Furthermore, we comparatively evaluate the performance of a number of previously proposed physiologically responsive controllers, including constant speed, constant flow pulsatility index (PI), constant average pressure difference between the aorta and the left atrium, constant average differential pump pressure, constant ratio between mean pump flow and pump flow pulsatility (ratioP I or linear Starling-like control), as well as constant left atrial pressure ( P l a ¯ ) control, with regard to their ability to increase cardiac output during exercise while maintaining circulatory stability upon HUT. Although native cardiac output increases automatically during exercise, increasing pump speed was able to further improve total cardiac output and reduce elevated filling pressures.

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In recent years, extensive studies have been conducted in the area of pumping state detection for implantable rotary blood pumps. However, limited studies have focused on automatically identifying the aortic valve non-opening (ANO) state despite its importance in the development of control algorithms aiming for myocardial recovery. In the present study, we investigated the performance of 14 ANO indices derived from the pump speed waveform using four different types of classifiers, including linear discriminant analysis, logistic regression, back propagation neural network, and k-nearest neighbors (KNN).

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The application of rotary left ventricular (LV) assist devices (LVADs) is expanding from bridge to transplant, to destination and bridge to recovery therapy. Conventional constant speed LVAD controllers do not regulate flow according to preload, and can cause over/underpumping, leading to harmful ventricular suction or pulmonary edema, respectively. We implemented a novel adaptive controller which maintains a linear relationship between mean flow and flow pulsatility to imitate native Starling-like flow regulation which requires only the measurement of VAD flow.

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Clinically adequate implementation of physiological control of a rotary left ventricular assist device requires a sophisticated technique such as the recently proposed method based on the Frank-Starling mechanism. In this mechanism, the stroke volume of the heart increases in response to an increase in the volume of blood filling the left ventricle at the end of diastole. To emulate this process, changes in pump speed need to automatically regulate pump flow to ensure that the combined output of the left ventricle and pump match the output of the right ventricle across changing cardiovascular states.

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In general, patient variability and diverse environmental operation makes physiological control of a left ventricular assist device (LVAD) a complex and complicated problem. In this work, we implement a Starling-like controller which adjusts mean pump flow using pump flow pulsatility as the feedback parameter. The linear relationship between mean pump flow and pump flow pulsatility forms the desired flow of the Starling-like controller.

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This multicenter study examines in detail the spontaneous increase in pump flow at fixed speed that occurs in exercise. Eight patients implanted with the VentrAssist rotary blood pump were subjected to maximal and submaximal cycle ergometry studies, the latter being completed with patients supine and monitored with right heart catheter and echocardiography. Maximal exercise studies conducted in each patient at three different pump speeds on separate days established initially the magnitude and consistency of increases in pump flow that correlated well with changes in heart rate.

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From the moment of creation to the moment of death, the heart works tirelessly to circulate blood, being a critical organ to sustain life. As a non-stopping pumping machine, it operates continuously to pump blood through our bodies to supply all cells with oxygen and necessary nutrients. When the heart fails, the supplement of blood to the body's organs to meet metabolic demands will deteriorate.

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A clinically intuitive physiologic controller is desired to improve the interaction between implantable rotary blood pumps and the cardiovascular system. This controller should restore the Starling mechanism of the heart, thus preventing overpumping and underpumping scenarios plaguing their implementation. A linear Starling-like controller for pump flow which emulated the response of the natural left ventricle (LV) to changes in preload was then derived using pump flow pulsatility as the feedback variable.

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A heart-pump interaction model has been developed based on animal experimental measurements obtained with a rotary blood pump in situ. Five canine experiments were performed to investigate the interaction between the cardiovascular system and the implantable rotary blood pump over a wide range of operating conditions, including variations in cardiac contractility and heart rate, systemic vascular resistance (SVR), and total blood volume (V(total) ). It was observed in our experiments that SVR decreased with increasing mean pump speed under the healthy condition, but was relatively constant during the speed ramp study under reduced cardiac contractility conditions.

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Numerical models, able to simulate the response of the human cardiovascular system (CVS) in the presence of an implantable rotary blood pump (IRBP), have been widely used as a predictive tool to investigate the interaction between the CVS and the IRBP under various operating conditions. The present study investigates the effect of alterations in the model parameter values, that is, cardiac contractility, systemic vascular resistance, and total blood volume on the efficiency of rotary pump assistance, using an optimized dynamic heart-pump interaction model previously developed in our laboratory based on animal experimental measurements obtained from five canines. The effect of mean pump speed and the circulatory perturbations on left and right ventricular pressure volume loops, mean aortic pressure, mean cardiac output, pump assistance ratio, and pump flow pulsatility from both the greyhound experiments and model simulations are demonstrated.

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A physiological control system was developed for a rotary left ventricular assist device (LVAD) in which the target pump flow rate (LVADQ) was set as a function of left atrial pressure (LAP), mimicking the Frank-Starling mechanism. The control strategy was implemented using linear PID control and was evaluated in a pulsatile mock circulation loop using a prototyped centrifugal pump by varying pulmonary vascular resistance to alter venous return. The control strategy automatically varied pump speed (2460 to 1740 to 2700 RPM) in response to a decrease and subsequent increase in venous return.

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Third-generation continuous-flow left ventricular assist devices (LVAD) provide reduced pulsatility flow. We examined the safe working range for LVAD pump speed and the effect on pump output and cardiac function in 13 stable outpatients with VentrAssist-LVAD (Ventracor Ltd, Australia). Pump speed was decreased from a baseline mean of 2,073 ± 86 revolutions per minute (RPM, with corresponding mean flow of 5.

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