Development and applications of in-vitro and in-silico models of the cardiovascular system to study the effects of mechanical circulatory support.

Cardiovascular diseases (CVDs) are the leading cause of mortality globally. With ongoing interest in CVDs treatment, preclinical models for drug/therapeutic development that allow for fast iterative research are needed. Owing to the inherent complexity of the cardiovascular system, current in-vitro models of the cardiovascular system fail to replicate many of the physiological aspects of the cardiovascular system. In this dissertation, the main concern is with heart failure (HF). In advanced HF, patients may receive Left Ventricular Assist Devices (LVADs) as a bridge to transplant or destination therapy. However, LVADs have many limitations, including inability to adapt to varying tissue demand conditions, risk of ventricular suction, and diminished arterial pulsatility. To address these issues, this dissertation aims to use and develop computer, cellular, and tissue models of the cardiovascular system. 1) Use an in-silico model of the cardiovascular system to develop a novel control algorithm for LVADs. The control system was rigorously tested and showed adequate perfusion during rest and exercise, protect against ventricular suction under reduced heart preload, and augment arterial pulsatility through pulse modulation without requiring sensor implantation or model-based estimations. 2) While pulsatility augmentation was feasible through the developed control algorithm, the pulse waveform that could normalize the vascular phenotype is unknown. To address this, an endothelial cell-smooth muscle cell microfluidic coculture model was developed to recreate the physiological mechanical stimulants in the vascular wall. The results demonstrated different effects of pulsatile shear stress and stretch on endothelial cells and may indicate that a pulse pressure of at least 30 mmHg is needed to maintain normal endothelial morphology. 3) In order to study the effects of mechanical unloading on the native ventricle, a novel cardiac tissue culture model (CTCM) was developed. CTCM provided physiological electromechanical and humoral stimulation with 25% preload stretch and thyroid and glucocorticoid treatment maintained the cardiac phenotype for 12 days. The device was thoroughly characterized and tested. Results demonstrated improved viability, energy utilization, fibrotic remodeling, and structural integrity compared to available culture systems. The system was also used to reproduce ventricular volume-overload and the results demonstrated hypertrophic and fibrotic remodeling, typical of volume-overload pathology

Control of a rotary blood pump

Implantable rotary blood pumps (RBPs) are an emerging technology designed to provide sufferers of heart failure with a viable treatment option which improves their medical prognosis and quality of life. The broad aim of this thesis is to address the need for a pump control strategy, and develop a solution whereby the implant recipient’s physiological requirements are continuously monitored in a non-invasive manner and met with an appropriate response by the RBP. Employing only the non-invasive signal of instantaneous pump impeller speed to assess flow dynamics, five physiologically significant pumping states have been identified in acute ex vivo porcine experiments (N=6). Two broader states, corresponding to normal and ventricular suction conditions, were readily discernable in clinical data from human implant recipients (N=10). Employing a classification and regression tree (CART) model, an automated real-time algorithm was developed to detect pumping states with a high degree of sensitivity and specificity. Both suction and normal states were detected without error in data from the animal experiments, and with a peak sensitivity/specificity, for detecting suction, of 99.11% / 98.76% in the human patient data. Algorithms to non-invasively estimate RBP flow and differential pressure in both steady- and pulsatile-flow environments were developed. Taking the pump feedback signals of speed and power, together with the blood haematocrit (or equivalent viscosity) level, as input parameters, several estimation models were developed via polynomial surface fitting and/or system identification methods, yielding clinically acceptable results (mean flow errors of 3.09% and 5.49%, and mean pressure errors of 1.80% and 6.47%, for the steady- and pulsatile-flow cases, respectively). An RBP control algorithm based on a non-invasive indicator of the implant recipient’s activity level has been proposed and evaluated in a software simulation environment. An Activity Level Index (ALI) forms the basis of an adaptive control module operating within a hierarchical multi-objective framework which imposes several constraints on the pump’s operating region. Three class IV heart failure cases of varying severity were simulated under rest and exercise conditions, and a comparison with other popular RBP control strategies was performed. Simulations of the proposed control algorithm exhibited the effective intervention of each constraint, resulting in an improved flow response and the maintenance of a safe operating condition, compared with other control modes

Left Ventricular Assist Devices: Engineering Design Considerations

Patients with end-stage congestive heart failure awaiting heart transplantation often wait long periods of time (300 days or more on the average) before a suitable donor heart becomes available. The medical community has placed increased emphasis on the use of Left Ventricular Assist Devices or LVADs that can substitute for, or enhance, the function of the natural heart while the patient is waiting for the heart transplant (Poirier, 1997; Frazier & Myers, 1999). Essentially, a rotary LVAD is a pump that operates continuously directing blood from the left ventricle into the aorta by avoiding the aortic valve. Generally speaking, the goal of the LVAD is to assist the native heart in pumping blood through the circulatory system so as to provide the patient with as close to a normal lifestyle as possible until a donor heart becomes available or, in some cases, until the patient’s heart recovers. In many situations, this means allowing the patient to return home and/or to the workforce

Left Ventricular Assist Devices: Engineering Design Considerations

Patients with end-stage congestive heart failure awaiting heart transplantation often wait long periods of time (300 days or more on the average) before a suitable donor heart becomes available. The medical community has placed increased emphasis on the use of Left Ventricular Assist Devices or LVADs that can substitute for, or enhance, the function of the natural heart while the patient is waiting for the heart transplant (Poirier, 1997; Frazier & Myers, 1999). Essentially, a rotary LVAD is a pump that operates continuously directing blood from the left ventricle into the aorta by avoiding the aortic valve. Generally speaking, the goal of the LVAD is to assist the native heart in pumping blood through the circulatory system so as to provide the patient with as close to a normal lifestyle as possible until a donor heart becomes available or, in some cases, until the patient’s heart recovers. In many situations, this means allowing the patient to return home and/or to the workforce

Suction Detection And Feedback Control For The Rotary Left Ventricular Assist Device

The Left Ventricular Assist Device (LVAD) is a rotary mechanical pump that is implanted in patients with congestive heart failure to help the left ventricle in pumping blood in the circulatory system. The rotary type pumps are controlled by varying the pump motor current to adjust the amount of blood flowing through the LVAD. One important challenge in using such a device is the desire to provide the patient with as close to a normal lifestyle as possible until a donor heart becomes available. The development of an appropriate feedback controller that is capable of automatically adjusting the pump current is therefore a crucial step in meeting this challenge. In addition to being able to adapt to changes in the patient\u27s daily activities, the controller must be able to prevent the occurrence of excessive pumping of blood from the left ventricle (a phenomenon known as ventricular suction) that may cause collapse of the left ventricle and damage to the heart muscle and tissues. In this dissertation, we present a new suction detection system that can precisely classify pump flow patterns, based on a Lagrangian Support Vector Machine (LSVM) model that combines six suction indices extracted from the pump flow signal to make a decision about whether the pump is not in suction, approaching suction, or in suction. The proposed method has been tested using in vivo experimental data based on two different LVAD pumps. The results show that the system can produce superior performance in terms of classification accuracy, stability, learning speed, iv and good robustness compared to three other existing suction detection methods and the original SVM-based algorithm. The ability of the proposed algorithm to detect suction provides a reliable platform for the development of a feedback control system to control the current of the pump (input variable) while at the same time ensuring that suction is avoided. Based on the proposed suction detector, a new control system for the rotary LVAD was developed to automatically regulate the pump current of the device to avoid ventricular suction. The control system consists of an LSVM suction detector and a feedback controller. The LSVM suction detector is activated first so as to correctly classify the pump status as No Suction (NS) or Suction (S). When the detection is “No Suction”, the feedback controller is activated so as to automatically adjust the pump current in order that the blood flow requirements of the patient’s body at different physiological states are met according to the patient’s activity level. When the detection is “Suction”, the pump current is immediately decreased in order to drive the pump back to a normal No Suction operating condition. The performance of the control system was tested in simulations over a wide range of physiological conditions

Estimation and control of the pump pressure rise and flow from intrinsic parameters for a magnetically-levitated axial blood pump

An increase in the number of cardiac patients and a decrease in number of heart donors has triggered the development of artificial heart pump to support the proper functioning of the heart. There is also an increase in demand for smaller sized pumps with long term application. All these factors have stimulated the use of a magnetically-levitated rotary blood pump as Left Ventricular Assistant Devices. The demand of volume and pressure of blood varies from person to person. Moreover, the prevention of cannular ventricle collapse at suction, dependence of pump performance on its inlet, and outlet conditions has necessitated control of the pump. Also, the available invasive pressure and flow transducers limit the use, due to their low reliability, periodic calibration, and assembling problem. In this work, three independent and quantitative non-invasive measurement methods for the estimation of pump parameters from intrinsic parameters were developed, substantiated, and compared. The first method used DC motor current and the motor speed as the inputs to the system. In this method, behavior of brushless DC motor was studied using its working model. Pump speed and bearing current were the inputs for the second estimation technique. In this method, pump performance and impeller behavior were continuously monitored in three axes (X,Y, ). The third method is conceptualized on the output of the Hall Effect sensors, which were used for sensing the position of impeller, and the pump speed. The behavior of the sensor output with the impeller position in four axes (X,Y,Z, ) was developed using a real impeller in model housing. The data were analyzed in Microsoft Excel 2007 and MATLAB using least square estimation techniques and Fourier series expansion. An algorithm for each technique was developed. In addition, the propagation of errors and uncertainties at each step of estimation method were accounted and calculated, with the results for each method compared

Systems and methods for controlling and implantable blood pump

Systems and methods for controlling an implantable pump are provided. For example, the exemplary controller for controlling the implantable pump may only rely on the actuator's current measurement. The controller is robust to pressure and flow changes inside the pump head, and allows fast change of pump's operation point. For example, the controller includes, a two stage, nonlinear position observer module based on a reduced order model of the electromagnetic actuator. The controller includes an algorithm that estimates the position of the moving component of the implantable pump based on the actuator's current measurement and adjusts operation of the pump accordingly. Alternatively, the controller may rely on position measurements and/or velocity estimations.CIFRE avec CORWAV