Ventricular Suction Research Articles

A multi-objective physiological control system for continuous-flow left ventricular assist device with non-invasive physiological feedback

In order to enable continuous-flow left ventricular assist device (CFLVAD) to adjust pump speed adaptively in response to changes in ventricular load, we developed a multi-objective physiological control system for CFLVAD with non-invasive physiological feedback mechanism, and proposed a multi-objective hierarchical control (MOHC) strategy to coordinate three controllers. A model-based estimation method was utilized to gain the physiological feedback variables. Suction prevention controller, regurgitation prevention controller, and physiological pulsatility controller were developed and applied to achieve the objectives: preventing left ventricular suction, preventing pump regurgitation, pump flow adaptive adjustment, and enhancing vascular pulsatility. The constraint conditions of feedback variables and controller priority were used to implement multi-objective hierarchical control. The preload and afterload were increased or decreased to simulate the scenarios of the sharp increase in left ventricular flow, the sharp decrease in left ventricular flow, and the rest-exercise-rest. The performance of MOHC was evaluated by subjecting it to three scenarios and compared with that of constant speed control (CSC) and pulsatile varying speed control (PVSC). The simulation results show that the linear correlation between the filtered and actual feedback variables was as high as 99.9%. Compared with CSC and PVSC, MOHC can avoid ventricular suction and pump regurgitation when the left ventricular flow changed rapidly. During rest or exercise, MOHC provided more adequate physiological perfusion and enhances greater vascular pulsatility than CSC and PVSC. MOHC can adjust the CFLVAD pump speed in response to changes in ventricular load.

Physiological control for left ventricular assist devices based on deep reinforcement learning.

The improvement of controllers of left ventricular assist device (LVAD) technology supporting heart failure (HF) patients has enormous impact, given the high prevalence and mortality of HF in the population. The use of reinforcement learning for control applications in LVAD remains minimally explored. This work introduces a preload-based deep reinforcement learning control for LVAD based on the proximal policy optimization algorithm. The deep reinforcement learning control is built upon data derived from a deterministic high-fidelity cardiorespiratory simulator exposed to variations of total blood volume, heart rate, systemic vascular resistance, pulmonary vascular resistance, right ventricular end-systolic elastance, and left ventricular end-systolic elastance, to replicate realistic inter- and intra-patient variability of patients with a severe HF supported by LVAD. The deep reinforcement learning control obtained in this work is trained to avoid ventricular suction and allow aortic valve opening by using left ventricular pressure signals: end-diastolic pressure, maximum pressure in the left ventricle (LV), and maximum pressure in the aorta. The results show controller obtained in this work, compared to the constant speed LVAD alternative, assures a more stable end-diastolic volume (EDV), with a standard deviation of 5 mL and 9 mL, respectively, and a higher degree of aortic flow, with an average flow of 1.1 L/min and 0.9 L/min, respectively. This work implements a deep reinforcement learning controller in a high-fidelity cardiorespiratory simulator, resulting in increases of flow through the aortic valve and increases of EDV stability, when compared to a constant speed LVAD strategy.

Performance study of dual heart assisted control system based on SL-SMC physiological combination controller.

The main challenges of Biventricular Assist Devices (BiVAD) as a treatment modality for patients with Bicardiac heart failure heart failure are the balance of systemic blood flow during changes in physiological activity and the prevention of ventricular suction. In this study, a model of the Biventricular Circulatory System (BCS) was constructed and a physiological combination controller based on Starling-Like controller and Sliding Mode Controller (SMC) was proposed. The effects of the physiological controller on the hemodynamics of the BCS were investigated by simulating two sets of physiological state change experiments: elevated pulmonary artery resistance and resting-exercise, with constant speed (CS) control and combined Starling-like and PI control (SL-PI) as controllers. Simulation and experimental results showed that the Starling-like and Sliding Mode Control (SL-SMC) physiological combination controller was effective in preventing the occurrence of ventricular suction, providing higher cardiac output, maintain balance of systemic blood flow, and have higher response speed and robustness in the face of physiological state changes.

Novel closed-loop control system of dual rotary blood pumps in total artificial heart based on the circulatory equilibrium framework: a proof-of-concept in vivo study.

Total artificial heart (TAH) using dual rotary blood pumps (RBPs) is a potential treatment for end-stage heart failure. A well-noted challenge with RBPs is their low sensitivity to preload, which can lead to venous congestion and ventricular suction. To address this issue, we have developed an innovative closed-loop control system of dual RBPs in TAH. This system emulates the Frank-Starling law of the heart in controlling RBPs while monitoring stressed blood volume (V) based on the circulatory equilibrium framework. We validated the system in in-vivo experiments. In 9 anesthetized dogs, we prepared a TAH circuit using 2 centrifugal-type RBPs. We first investigated whether the flow and inlet atrial pressure in each RBP adhered to a logarithmic Frank-Starling curve. We then examined whether the RBP flows and atrial pressures were maintained stably during aortic occlusion (AO) and pulmonary cannula stenosis (PS), whether averaged flow of dual RBPs and bilateral atrial pressures were controlled to their predefined target values for a specific V, and whether this system could maintain the atrial pressures within predefined control ranges under significant changes in V. This system effectively emulated the logarithmic Frank-Starling curve. It robustly stabilized the flow and atrial pressures during AO and PS without venous congestion or ventricular suction, accurately achieved target values in averaged flow and atrial pressures, and efficaciously maintained these pressures within the control ranges. This system controls dual RBPs in TAH accurately and stably. This system may accelerate clinical application of TAH with dual RBPs.

An in silico analysis of unsteady flow structures in a microaxial blood pump under a pulsating rotation speed

Background and objectiveVentricular assist devices (VADs) are generally designed to perform continuous flow. However, it has been proven that continuous flow, which is not a physiological hemodynamic state, may cause severe complications such as gastrointestinal bleeding, pulmonary hypertension, and ventricular suction. For these reasons, many pulsating blood pump control strategies have been proposed and have the potential for application in percutaneous ventricular assist devices (pVADs) or microaxial blood pumps. A few cases report extra hemolysis when introducing pulsating speed, while none involve blood pumps. This research's primary purpose is to evaluate the potential hemolysis of pVAD under pulsating flow conditions. MethodsFirst, the pulsating flow state is deduced using a heart failure model and varying speed. The heart model is established according to the pathology state collected from a clinical check. The rotation speed and boundary physical state are set to fit the heart failure model. The computational fluid dynamics (CFD) method with the hemolysis prediction model is performed. Furthermore, we used proper orthogonal decomposition (POD) analysis to reconstruct the flow field and obtain more details about shearing and transporting effects. Results(1) As a variable rotational speed was introduced, no significant gain in hemolysis accumulation appeared in pVAD. This is quite different from long-term implantable VADs. (2) Pulsation affects hemolysis mainly through pressure (or normal stress). Variable rotational speed affects hemolysis mainly through flow instability. (3) Variable rotational speed will increase the instability and influence hemolysis by transporting and shearing effects, while the transporting effect is more significant. ConclusionsThe unsteady flow state will affect the spatial distribution of hemolysis, which should be taken into account during control strategy and impeller shape design.

The impact of aortic valve regurgitation on the combination therapy of VA-ECMO and Imeplla support in severe cardiogenic shock: a simulation study

Background: The utilization of a combination of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) and Impella, ECPELLA, has become widespread among patients with cardiogenic shock. The utilization of VA-ECMO in the presence of aortic regurgitation (AR) can result in significant left ventricular (LV) distention. Additionally, the implantation of Impella via the aortic valve frequently induces AR clinically. We established a simulation model and evaluated the impact of AR on hemodynamics under ECPELLA. Furthermore, assuming that the reverse flow of AR is strongly determined by aortic pressure (AP) level, we simulated a scenario where AP was further decreased. Methods: We employed Simulink® (Mathworks, Inc.). The systemic and pulmonary circulations were modeled using a 5-element resistance-capacitance network. Four cardiac chambers were represented by time-varying elastance. We compared the aortic regurgitant flow (Far), total systemic flow (Ftotal), and LV pressure-volume relationship under various severities of AR and varying Impella (0-3.7 L/min) and VA-ECMO (0-5 L/min) flows. AR grades were adjusted by the regurgitant resistance and classified as mild, moderate, and severe, mimicking a clinical scenario. Results: Without AR, ECMO significantly increased Ftotal and raised LV end-diastolic pressure (LVEDP). Impella increased Ftotal and decreased LVEDP. The concomitant presence of AR exacerbated the increase of LVEDP by ECMO and the reduction of LVEDP by Impella. Under ECPELLA support (VA-ECMO: 3 L/min) with mild AR, the increase of Impella support (1 to 3.5 L) increased Ftotal and Far, while decreasing LVEDP, indicating the prevention of AR-induced LV distention. Additionally, the presence of mild AR prevented the Impella-induced left ventricular suction that is commonly observed under ECPELLA support with high-flow VA-ECMO. In the case of moderate AR, while the hemodynamic trends were similar to those observed under mild AR, Impella was unable to prevent the increment of LVEDP to a critical level (< 20 mmHg). However, by decreasing AP through reducing resistance (e.g. vasodilators), both Far and LVEDP were dramatically reduced and Ftotal was increased under ECPELLA support. Conclusion: The concomitant presence of AR in ECPELLA condition increased LV load, while prevented LV suction. The use of vasodilator in ECPELLA with AR could attenuate AR, increase systemic perfusion, and reduce LV load. The optimal control of Impella and VA-ECMO flows and AP can maximize the hemodynamic and LV unloading impacts of ECPELLA. no funding This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

A sensorless, physiologic feedback control strategy to increase vascular pulsatility for rotary blood pumps

Continuous flow rotary blood pumps (RBP) operating clinically at constant rotational speeds cannot match cardiac demand during varying physical activities, are susceptible to suction, diminish vascular pulsatility, and have an increased risk of adverse events. A sensorless, physiologic feedback control strategy for RBP was developed to mitigate these limitations. The proposed algorithm used intrinsic pump speed to obtain differential pump speed (ΔRPM). The proposed gain-scheduled proportional-integral controller, switching of setpoints between a higher pump speed differential setpoint (ΔRPMHr) and a lower pump speed differential setpoint (ΔRPMLr), generated pulsatility and physiologic perfusion, while avoiding suction. The switching between ΔRPMHr and ΔRPMLr setpoints occurred when the measured ΔRPM reached the pump differential reference setpoint. In-silico tests were implemented to assess the proposed algorithm during rest, exercise, a rapid 3-fold pulmonary vascular resistance increase, rapid change from exercise to rest, and compared with maintaining a constant pump speed setpoint. The proposed control algorithm augmented aortic pressure pulsatility to over 35 mmHg during rest and around 30 mmHg during exercise. Significantly, ventricular suction was avoided, and adequate cardiac output was maintained under all simulated conditions. The performance of the sensorless algorithm using estimation was similar to the performance of sensor-based method. This study demonstrated that augmentation of vascular pulsatility was feasible while avoiding ventricular suction and providing physiological pump outflows. Augmentation of vascular pulsatility can minimize adverse events that have been associated with diminished pulsatility. Mock circulation and animal studies would be conducted to validate these results.

Abstract 11115: Impella Preserves Systemic, Coronary, and Cerebral Blood Flows During Ventricular Fibrillation by Establishing the Acute Fontan Circulation

Introduction: The ventricular fibrillation (VF) often occurs in acute heart failure patients with Impella support, percutaneous transvalvular left ventricular assist device. Although Impella can preserve blood pressure in some VF patients, the hemodynamic mechanism of Impella during VF remains unclear. Aim: In this study, we examined the impact of Impella on hemodynamics and cerebral and coronary blood flows in a goat model of VF. We also addressed the optimal blood volume status to maintain the Impella circulation during VF. Methods: In six goats, we inserted Impella CP via the left carotid artery. We simultaneously recorded right (RAP) and left atrial pressure (LAP), central blood pressure at ascending aorta (CBP), and the blood flows of pulmonary artery (PA), left coronary circumflex artery (LCX), and right carotid artery (CA). The VF was induced by direct current. We compared the impact of Impella support level (P0, P4 and P8) on hemodynamics and each blood flow. Under P8-Impella supported VF condition, we withdrew blood continuously and observed the left ventricular (LV) suction point at which a frequent negative LV pressure occurred. Results: As shown in Fig. 1 and 2, Impella maintained hemodynamics flow-dependently, indicating the establishment of acute Fontan circulation. In P8-Impella support, systemic (PA flow), LCX and CA blood flows were preserved by 50.1±27.7, 50.7±12.5 and 67.3±5.6%. from baseline, respectively. The blood volume reduction induced the suction of Impella (Fig. 3) at RAP below 9.9±1.9 mmHg. Conclusions: Impella establishes the acute Fontan circulation and preserves hemodynamics including coronary and cerebral blood flows during VF. The optimal blood volume status should be considered to maintain the Impella operation during VF.

Cardiac hemodynamics and ventricular stiffness of sea-run cherry salmon (Oncorhynchus masou masou) differ critically from those of landlocked masu salmon.

Ventricular diastolic mechanical properties are important determinants of cardiac function and are optimized by changes in cardiac structure and physical properties. Oncorhynchus masou masou is an anadromous migratory fish of the Salmonidae family, and several ecological studies on it have been conducted; however, the cardiac functions of the fish are not well known. Therefore, we investigated ventricular diastolic function in landlocked (masu salmon) and sea-run (cherry salmon) types at 29-30 months post fertilization. Pulsed-wave Doppler echocardiography showed that the atrioventricular inflow waveforms of cherry salmon were biphasic with early diastolic filling and atrial contraction, whereas those of masu salmon were monophasic with atrial contraction. In addition, end-diastolic pressure-volume relationship analysis revealed that the dilatability per unit myocardial mass of the ventricle in cherry salmon was significantly suppressed compared to that in masu salmon, suggesting that the ventricle of the cherry salmon was relatively stiffer (relative ventricular stiffness index; p = 0.0263). Contrastingly, the extensibility of cardiomyocytes, characterized by the expression pattern of Connectin isoforms in their ventricles, was similar in both types. Histological analysis showed that the percentage of the collagen accumulation area in the compact layer of cherry salmon increased compared with that of the masu salmon, which may contribute to ventricle stiffness. Although the heart mass of cherry salmon was about 11-fold greater than that of masu salmon, there was no difference in the morphology of the isolated cardiomyocytes, suggesting that the heart of the cherry salmon grows by cardiomyocyte proliferation, but not cell hypertrophy. The cardiac physiological function of the teleosts varies with differences in their developmental processes and life history. Our multidimensional analysis of the O. masou heart may provide a clue to the process by which the heart acquires a biphasic blood-filling pattern, i.e., a ventricular diastolic suction.

Potential of Medical Management to Mitigate Suction Events in Ventricular Assist Device Patients.

Ventricular suction is a common adverse event in ventricular assist device (VAD) patients and can be due to multiple underlying causes. The aim of this study is to analyze the potential of different therapeutic interventions to mitigate suction events induced by different pathophysiological conditions. To do so, a suction module was embedded in a cardiovascular hybrid (hydraulic-computational) simulator reproducing the entire cardiovascular system. An HVAD system (Medtronic) was connected between a compliant ventricular apex and a simulated aorta. Starting from a patient profile with severe dilated cardiomyopathy, four different pathophysiological conditions leading to suction were simulated: hypovolemia (blood volume: -900 ml), right ventricular failure (contractility -70%), hypotension (systemic vascular resistance: 8.3 Wood Units), and tachycardia (heart rate:185 bpm). Different therapeutic interventions such as volume infusion, ventricular contractility increase, vasoconstriction, heart rate increase, and pump speed reduction were simulated. Their effects were compared in terms of general hemodynamics and suction mitigation. Each intervention elicited a different effect on the hemodynamics for every pathophysiological condition. Pump speed reduction mitigated suction but did not ameliorate the hemodynamics. Administering volume and inducing a systemic vasoconstriction were the most efficient interventions in both improving the hemodynamics and mitigating suction. When simulating volume infusion, the cardiac powers increased, respectively, by 38%, 25%, 42%, and 43% in the case of hypovolemia, right ventricular failure, hypotension, and tachycardia. Finally, a management algorithm is proposed to identify a therapeutic intervention suited for the underlying physiologic condition causing suction.

Fully Elman Neural Network: A Novel Deep Recurrent Neural Network Optimized by an Improved Harris Hawks Algorithm for Classification of Pulmonary Arterial Wedge Pressure.

Heart failure (HF) is one of the most prevalent life-threatening cardiovascular diseases in which 6.5 million people are suffering in the USA and more than 23 million worldwide. Mechanical circulatory support of HF patients can be achieved by implanting a left ventricular assist device (LVAD) into HF patients as a bridge to transplant, recovery or destination therapy and can be controlled by measurement of normal and abnormal pulmonary arterial wedge pressure (PAWP). While there are no commercial long-term implantable pressure sensors to measure PAWP, real-time non-invasive estimation of abnormal and normal PAWP becomes vital. In this work, first an improved Harris Hawks optimizer algorithm called HHO+ is presented and tested on 24 unimodal and multimodal benchmark functions. Second, a novel fully Elman neural network (FENN) is proposed to improve the classification performance. Finally, four novel 18-layer deep learning methods of convolutional neural networks (CNNs) with multi-layer perceptron (CNN-MLP), CNN with Elman neural networks (CNN-ENN), CNN with fully Elman neural networks (CNN-FENN), and CNN with fully Elman neural networks optimized by HHO+ algorithm (CNN-FENN-HHO+) for classification of abnormal and normal PAWP using estimated HVAD pump flow were developed and compared. The estimated pump flow was derived by a non-invasive method embedded into the commercial HVAD controller. The proposed methods are evaluated on an imbalanced clinical dataset using 5-fold cross-validation. The proposed CNN-FENN-HHO+ method outperforms the proposed CNN-MLP, CNN-ENN and CNN-FENN methods and improved the classification performance metrics across 5-fold cross-validation with an average sensitivity of 79%, accuracy of 78% and specificity of 76%. The proposed methods can reduce the likelihood of hazardous events like pulmonary congestion and ventricular suction for HF patients and notify identified abnormal cases to the hospital, clinician and cardiologist for emergency action, which can diminish the mortality rate of patients with HF.

Idiopathic Central Diabetes Insipidus as an Etiology of Left Ventricular Suction and Ventricular Arrhythmias

<h3>Introduction</h3> Left ventricular assist device (LVAD) implantation has increased in patients with end-stage heart failure. Left ventricular suction is a known complication of LVAD therapy, with etiologies including hypovolemia, sepsis and ventricular arrhythmias. Prompt recognition of the underlying cause is crucial in the management and prevention of suction events. <h3>Case Report</h3> A 59-year-old male with non-ischemic cardiomyopathy status post LVAD and ventricular tachycardia (VT) presented with shocks from his implantable defibrillator. He noted 2-3 weeks of low flow alarms and daily suction events with associated lightheadedness and dizziness. On admission, device interrogation revealed two episodes of successfully terminated VT. His antiarrhythmic therapy and device settings were adjusted by the electrophysiology team. On day two of hospitalization, he had ventricular fibrillation associated with a suction event. He was noted to have increased urine output despite holding diuresis. LVAD speed was decreased and he was given intravenous fluids, however right heart catheterization revealed very low filling pressures despite these interventions. He continued to have polyuria despite liberalization of fluid intake and suction alarms with associated ventricular ectopy. Urine studies revealed low urine osmolality of 266 mOsm/Kg and urine sodium of 41 mmol/L. Hypertonic saline challenge resulted in hypernatremia and improved but suboptimal urine concentration. Workup for causes of nephrogenic diabetes insipidus (DI) was unrevealing. Computed tomography of the sella did not reveal any pituitary abnormalities. He was started on desmopressin and urine output appropriately decreased. He had no further ventricular arrhythmias, though he continued to have intermittent suction alarms associated with positional changes. <h3>Summary</h3> Treatment of left ventricular suction events includes correction of underlying etiology, maintaining preload, reducing LVAD speed and management of complications including ventricular arrhythmias. Our patient's suction events and ventricular arrhythmias were presumed secondary to hypovolemia in the setting of central DI and polyuria, which improved with treatment with desmopressin. In review of literature, this is the first documented case of diabetes insipidus resulting in suction events and ventricular arrhythmias.

Determinants of altered left ventricular suction in pre-capillary pulmonary hypertension.

Although the left ventricular (LV) dysfunction in pre-capillary pulmonary hypertension (PH) has been recently recognized, the mechanism of LV dysfunction in this entity is not completely understood. We thus aimed to elucidate the determinants of intraventricular pressure difference (IVPD), a measure of LV suction, in pre-capillary PH. Right heart catheterization and echocardiography were performed in 86 consecutive patients with pre-capillary PH (57 ± 18 years, 85% female). IVPD was determined using colour M-mode Doppler to integrate the Euler equation. In overall, IVPD was reduced compared to previously reported value in normal subjects. In univariable analyses, QRS duration (P = 0.028), LV ejection fraction (P = 0.006), right ventricular (RV) end-diastolic area (P < 0.001), tricuspid annular plane systolic excursion (P = 0.004), and LV early-diastolic eccentricity index (P = 0.009) were associated with IVPD. In the multivariable analyses, RV end-diastolic area and LV eccentricity index independently determined the IVPD. Aberrant ventricular interdependence caused by RV enlargement could impair the LV suction. This study first applied echocardiographic IVPD, a reliable marker of LV diastolic suction, to investigate the mechanism of LV diastolic dysfunction in pre-capillary PH.

A Flow Sensor-Based Suction-Index Control Strategy for Rotary Left Ventricular Assist Devices.

Rotary left ventricular assist devices (LVAD) have emerged as a long-term treatment option for patients with advanced heart failure. LVADs need to maintain sufficient physiological perfusion while avoiding left ventricular myocardial damage due to suction at the LVAD inlet. To achieve these objectives, a control algorithm that utilizes a calculated suction index from measured pump flow (SIMPF) is proposed. This algorithm maintained a reference, user-defined SIMPF value, and was evaluated using an in silico model of the human circulatory system coupled to an axial or mixed flow LVAD with 5–10% uniformly distributed measurement noise added to flow sensors. Efficacy of the SIMPF algorithm was compared to a constant pump speed control strategy currently used clinically, and control algorithms proposed in the literature including differential pump speed control, left ventricular end-diastolic pressure control, mean aortic pressure control, and differential pressure control during (1) rest and exercise states; (2) rapid, eight-fold augmentation of pulmonary vascular resistance for (1); and (3) rapid change in physiologic states between rest and exercise. Maintaining SIMPF simultaneously provided sufficient physiological perfusion and avoided ventricular suction. Performance of the SIMPF algorithm was superior to the compared control strategies for both types of LVAD, demonstrating pump independence of the SIMPF algorithm.

Loss of apical suction assessed by noninvasive pressure differences and twist in acute heart failure: a novel method using vector flow mapping

Abstract Background Early diastolic intraventricular pressure difference (IVPD) reflects left ventricular (LV) apical suction, and IVPD is closely related to cardiac function, especially LV twist. Vector Flow Mapping (VFM) allows visualization of regional pressure distribution and noninvasive quantification of IVPD. The purpose of the present study was to investigate if and how IVPDs are related to LV twist in a model of acute heart failure (HF). Methods In 15 open-chest dogs, HF was induced by intracoronary injection of microspheres. The HF model was classified into two groups based on the LV end-diastolic pressure (LVEDP) (group1: LVEDP&amp;lt;18 mmHg (n=10), group2: LVEDP≥18 mmHg (n=8)). Color Doppler images from apical long-axis views were acquired at baseline and during HF. From these images, pressure differences (ΔP) were calculated along the LV inflow tract throughout the cardiac cycle. For the purpose of this study, the differences between apex and base during isovolumic relaxation time (ΔPIRT) and rapid early inflow period (ΔPE) were used for analyses. Furthermore, apical and basal short axis high frame rate 2D images were acquired, and peak rotation and peak twist were analyzed. Results LVEDP was 7±9, 14±2, 21±3 mmHg for baseline, group1 HF, and group2 HF, respectively. Pressure differences (both ΔPIRT and ΔPE) were visibly changed by the increase of LVEDP (Figure), and the magnitude of ΔPIRT, ΔPE and peak twist decreased significantly with the severity of heart failure. There were significant relationships between pressure differences (ΔPIRT and ΔPE) and dP/dtmin, tau, EF and peak twist (Table). In multivariate analyses, tau and peak twist were independent predictors for ΔPIRT and peak twist was independent predictor for ΔPE. Conclusion VFM analysis is feasible to noninvasively assess the IVPDs in acute heart failure. The IVPDs are closely related to the twisting motion of the LV, and reflect loss of apical suction during severe HF. Funding Acknowledgement Type of funding sources: None. VFM images of pressure differencesCorrelations of pressure differences

Intraventricular flow visualization in different heart failure stages with blood pump support in a mock circulatory loop

The intraventricular blood flow changed by blood pump flow dynamics may correlate with thrombosis and ventricular suction. The flow velocity, distribution of streamlines, vorticity, and standard deviation of velocity inside a left ventricle failing to different extents throughout the cardiac cycle when supported by an axial blood pump were measured by particle image velocimetry (PIV) in this study. The results show slower and static flow velocities existed in the central region of the left ventricle near the mitral valve and aortic valve and that were not sensitive to left ventricular (LV) failure degree or LV pressure. Strong vorticity located near the inner LV wall around the LV apex and the blood pump inlet was not sensitive to LV failure degree or LV pressure. Higher standard deviation of the blood velocity at the blood pump inlet decreased with increasing LV failure degree, whereas the standard deviation of the velocity near the atrium increased with increasing intraventricular pressure. The experimental results demonstrated that the risk of thrombosis inside the failing left ventricle is not related to heart failure degree. The "washout" performance of the strong vorticity near the inner LV wall could reduce the thrombotic potential inside the left ventricle and was not related to heart failure degree. The vorticity near the aortic valve was sensitive to LV failure degree but not to LV pressure. We concluded that the risk of blood damage caused by adverse flow inside the left ventricle decreased with increasing LV pressure.

Adaptive Sensorless Control of LVAD Using Deep Convolutional Neural Network

Purpose Left ventricular assist devices (LVADs) play a vital role for end-stage heart failure (HF) patients during destination therapy. However, the speed of LVADs are set at a constant speed mode which can result in insufficient perfusion and hazardous events such as ventricular suction and pulmonary congestion. A preload-based physiological control system, a “smart pump”, can be employed to adjust the LVAD speed automatically and therefore improve prefusion and deal with the hazardous events. Although most of these physiological control systems require direct measurement of preload, long-term implantation of a pressure sensor can lead to drift or thrombus formation. Preload can instead be estimated using pump intrinsic variables. This study presents a sensorless control of LVAD across different patient conditions without relying on any implantable sensors. Methods An adaptive preload-based physiological controller was employed to adjust the speed of HeartWare HVAD pump to handle interpatient and intrapatient variations using a computer simulation. A deep convolutional neural network (CNN) model was designed to estimated preload based on the 600 samples of pump flow in real-time mode. The proposed CNN model was trained and validated on 100 different patient conditions and tested over new 30 patient conditions and a range of changes to the cardiovascular system, including changes in PVR, SVR and rest to exercise. Finally, the physiological controller and preload estimator were combined to create a sesnorless preload-based physiological control system for LVADs. Results Preload was accurately estimated using the proposed deep convolutional neural network model, which was successfully trained, tested and validated using computer simulation data. The results for all scenarios show the correlation coefficient of 0.97 and RMSE of 0.84 (mmHg). Furthermore, the sesnorless preload-based physiological control was able to prevent ventricular suction and pulmonary congestions over new 30 patients. Conclusion The sesnorless preload-based physiological control can be useful for estimation of preload and control of LVAD speed in a real-time mode for HF patients without implantation of pressure sensors. This controller can improve the HF patients’ quality of lives and lifespan by increasing perfusion, preventing suction and congestion.

A Sensorless Control System for an Implantable Heart Pump Using a Real-Time Deep Convolutional Neural Network.

Left ventricular assist devices (LVADs) are mechanical pumps, which can be used to support heart failure (HF) patients as bridge to transplant and destination therapy. To automatically adjust the LVAD speed, a physiological control system needs to be designed to respond to variations of patient hemodynamics across a variety of clinical scenarios. These control systems require pressure feedback signals from the cardiovascular system. However, there are no suitable long-term implantable sensors available. In this study, a novel real-time deep convolutional neural network (CNN) for estimation of preload based on the LVAD flow was proposed. A new sensorless adaptive physiological control system for an LVAD pump was developed using the full dynamic form of model free adaptive control (FFDL-MFAC) and the proposed preload estimator to maintain the patient conditions in safe physiological ranges. The CNN model for preload estimation was trained and evaluated through 10-fold cross validation on 100 different patient conditions and the proposed sensorless control system was assessed on a new testing set of 30 different patient conditions across six different patient scenarios. The proposed preload estimator was extremely accurate with a correlation coefficient of 0.97, root mean squared error of 0.84 mmHg, reproducibility coefficient of 1.56 mmHg, coefficient of variation of 14.44%, and bias of 0.29 mmHg for the testing dataset. The results also indicate that the proposed sensorless physiological controller works similarly to the preload-based physiological control system for LVAD using measured preload to prevent ventricular suction and pulmonary congestion. This study shows that the LVADs can respond appropriately to changing patient states and physiological demands without the need for additional pressure or flow measurements.

A Compliant Model of the Ventricular Apex to Study Suction in Ventricular Assist Devices.

Ventricular suction is a frequent adverse event in patients with a ventricular assist device (VAD). This study presents a suction module (SM) embedded in a hybrid (hydraulic-computational) cardiovascular simulator suitable for the testing of VADs and related suction events. The SM consists of a compliant latex tube reproducing a simplified ventricular apex. The SM is connected on one side to a hydraulic chamber of the simulator reproducing the left ventricle, and on the other side to a HeartWare HVAD system. The SM is immersed in a hydraulic chamber with a controllable pressure to occlude the compliant tube and activate suction. Two patient profiles were simulated (dilated cardiomyopathy and heart failure with preserved ejection fraction), and the circulating blood volume was reduced stepwise to obtain different preload levels. For each simulated step, the following data were collected: HVAD flow, ventricular pressure and volume, and pressure at the inflow cannula. Data collected for the two profiles and for decreasing preload levels evidenced suction profiles differing in terms of frequency (intermittent vs. every heart beat), amplitude (partial or complete stoppage of the HVAD flow), and shape. Indeed different HVAD flow patterns were observed for the two patient profiles because of the different mechanical properties of the simulated ventricles. Overall, the HVAD flow patterns showed typical indicators of suctions observed in clinics. Results confirmed that the SM can reproduce suction phenomena with VAD under different pathophysiological conditions. As such, the SM can be used in the future to test VADs and control algorithms aimed at preventing suction phenomena.

A 3-dimensional-printed left ventricle model incorporated into a mock circulatory loop to investigate hemodynamics inside a severely failing ventricle supported by a blood pump.

Intraventricular blood stasis is a design consideration for continuous flow blood pumps and might contribute to adverse events such as thrombosis and ventricular suction. However, the blood flow inside left ventricles (LVs) supported by blood pumps is still unclear. In vitro experiments were conducted to imitate how the hydraulic performance of an axial blood pump affects the intraventricular blood flow of a severe heart failure patient, such as velocity distribution, vorticity, and standard deviation of velocity. In this study, a silicone model of the LV was constructed from the computed tomography data of one patient with heart failure and was 3D printed. Then, intraventricular flow was visualized by particle image velocimetry equipment within a mock circulation loop. The results showed that the axial blood pump suctions most of the blood in a severely failing LV, there was an altered flow status within the LV, and blood stasis appeared in the central region of the LV. Some blood may be suctioned from the aortic valve to the blood pump because the patient's native heart was severely failing. Blood stasis at the LV center may cause thrombosis in the LV. The vortex flow near the inner wall of the LV can thoroughly wash the left ventricular cavity.