Libera Fresiello

A modular computational circulatory model applicable to VAD testing and training.

Aim of this work was to develop a modular computational model able to interact with ventricular assist devices (VAD) for research and educational applications. The lumped parameter model consists of five functional modules (left and right ventricles, systemic, pulmonary, and coronary circulation) that are easily replaceable if necessary. The possibility of interacting with VADs is achieved via interfaces acting as impedance transformers. This last feature was tested using an electrical VAD model. Tests were aimed at demonstrating the possibilities and verifying the behavior of interfaces when testing VADs connected in different ways to the circulatory system. For these reasons, experiments were performed in a purely numerical mode, simulating a caval occlusion, and with the model interfaced to an external left-VAD (LVAD) in two different ways: with atrioaortic and ventriculoaortic connection. The caval occlusion caused the leftward shift of the LV p–v loop, along with the drop in arterial and ventricular pressures. A narrower LV p–v loop and cardiac output and aortic pressure rise were the main effects of atrioaortic assistance. A wider LV p–v loop and a ventricular average volume drop were the main effects of ventricular-aortic assistance. Results coincided with clinical and experimental data attainable in the literature. The model will be a component of a hydronumerical model designed to be connected to different types of VADs. It will be completed with autonomic features, including the baroreflex and a more detailed coronary circulation model.

Reproduction of Continuous Flow Left Ventricular Assist Device Experimental Data by Means of a Hybrid Cardiovascular Model With Baroreflex Control

Long-term mechanical circulatory assistance opened new problems in ventricular assist device-patient interaction, especially in relation to autonomic controls. Modeling studies, based on adequate models, could be a feasible approach of investigation. The aim of this work is the exploitation of a hybrid (hydronumerical) cardiovascular simulator to reproduce and analyze in vivo experimental data acquired during a continuous flow left ventricular assistance. The hybrid cardiovascular simulator embeds three submodels: a computational cardiovascular submodel, a computational baroreflex submodel, and a hydronumerical interface submodel. The last one comprises two impedance transformers playing the role of physical interfaces able to provide a hydraulic connection with specific cardiovascular sites (in this article, the left atrium and the ascending/descending aorta). The impedance transformers are used to connect a continuous flow pump for partial left ventricular support (Synergy Micropump, CircuLite, Inc., Saddlebrooke, NJ, USA) to the hybrid cardiovascular simulator. Data collected from five animals in physiological, pathological, and assisted conditions were reproduced using the hybrid cardiovascular simulator. All parameters useful to characterize and tune the hybrid cardiovascular simulator to a specific hemodynamic condition were extracted from experimental data. Results show that the simulator is able to reproduce animal-specific hemodynamic status both in physiological and pathological conditions, to reproduce cardiovascular left ventricular assist device (LVAD) interaction and the progressive unloading of the left ventricle for different pump speeds, and to investigate the effects of the LVAD on baroreflex activity. Results in chronic heart failure conditions show that an increment of LVAD speed from 20 000 to 22 000 rpm provokes a decrement of left ventricular flow of 35% (from 2 to 1.3 L/min). Thanks to its flexibility and modular structure, the simulator is a platform potentially useful to test different assist devices, thus providing clinicians additional information about LVAD therapy strategy.

Simulation of apical and atrio-aortic VAD in patients with transposition or congenitally corrected transposition of the great arteries

Purpose VADs could be used for transportation of the great arteries (TGA) and for congenitally corrected transposition (ccTGA) treatment. A cardiovascular numerical model (NM) may offer a useful clinical support in these complex physiopathologies. This work aims at developing and preliminarily verifying a NM of ccTGA and TGA interacting with VADs. Methods Hemodynamic data were collected at the baseline (BL) and three months (FUP) after apical (atrio-aortic) VAD implantation in a TGA (ccTGA) patient and used in a lumped parameter NM to simulate the patients physiopathology. Measured (MS) and simulated (SIM) data were compared. Results MS and SIM data are in accordance at the BL and at FUP. Cardiac output (l/min): BL_m = 2.9 ± 0.4, BL_s = 3.0 ± 0.3; FUP_m = 4.2 ± 0.2, FUP_s = 4.1 ± 0.1. Right atrial pressure (mmHg): BL_m = 21.4 ± 4.1, BL_s = 18.5 ± 4.5; FUP_m = 13 ± 4, FUP_s = 14.8 ± 3.6. Pulmonary arterial pressure (mmHg): BL_m = 56 ± 6.3, BL_s = 57 ± 2, FUP_m = 37.5 ± 7.5, FUP_s = 35.5 ± 5.9. Systemic arterial pressure (mmHg): BL_m = 71 ± 2, BL_s = 74.6 ± 2.1; FUP_m = 84 ± 9, FUP_s = 81.9 ± 9.8. Conclusions NM can simulate the effect of a VAD in complex physiopathologies, with the inclusion of changes in circulatory parameters during the acute phase and at FUP. The simulation of differently assisted physiopathologies offers a useful support for clinicians.

A cardiovascular simulator tailored for training and clinical uses

OBJECTIVE In the present work a cardiovascular simulator designed both for clinical and training use is presented. METHOD The core of the simulator is a lumped parameter model of the cardiovascular system provided with several modules for the representation of baroreflex control, blood transfusion, ventricular assist device (VAD) therapy and drug infusion. For the training use, a Pre-Set Disease module permits to select one or more cardiovascular diseases with a different level of severity. For the clinical use a Self-Tuning module was implemented. In this case, the user can insert patients specific data and the simulator will automatically tune its parameters to the desired hemodynamic condition. The simulator can be also interfaced with external systems such as the Specialist Decision Support System (SDSS) devoted to address the choice of the appropriate level of VAD support based on the clinical characteristics of each patient. RESULTS The Pre-Set Disease module permits to reproduce a wide range of pre-set cardiovascular diseases involving heart, systemic and pulmonary circulation. In addition, the user can test different therapies as drug infusion, VAD therapy and volume transfusion. The Self-Tuning module was tested on six different hemodynamic conditions, including a VAD patient condition. In all cases the simulator permitted to reproduce the desired hemodynamic condition with an error<10%. CONCLUSIONS The cardiovascular simulator could be of value in clinical arena. Clinicians and students can utilize the Pre-Set Diseases module for training and to get an overall knowledge of the pathophysiology of common cardiovascular diseases. The Self-Tuning module is prospected as a useful tool to visualize patients status, test different therapies and get more information about specific hemodynamic conditions. In this sense, the simulator, in conjunction with SDSS, constitutes a support to clinical decision - making.

Hybrid model analysis of intra-aortic balloon pump performance as a function of ventricular and circulatory parameters.

We investigated the effects of the intra-aortic balloon pump (IABP) on endocardial viability ratio (EVR), cardiac output (CO), end-systolic (V(es)) and end-diastolic (V(ed)) ventricular volumes, total coronary blood flow (TCBF), and ventricular energetics (external work [EW], pressure-volume area [PVA]) under different ventricular (E(max) and diastolic stiffness) and circulatory (arterial compliance) parameters. We derived a hybrid model from a computational model, which is based on merging computational and hydraulic submodels. The lumped parameter computational submodel consists of left and right hearts and systemic, pulmonary, and coronary circulations. The hydraulic submodel includes part of the systemic arterial circulation, essentially a silicone rubber tube representing the aorta, which contains a 40-mL IAB. EVR, CO, V(es), and V(ed), TCBF and ventricular energetics (EW, PVA) were analyzed against the ranges of left ventricular E(max) (0.3-0.5-1 mm Hg/cm(3)) and diastolic stiffness V(stiffness) (≈0.08 and ≈0.3 mm Hg/cm(3), obtained by changing diastolic stiffness constant) and systemic arterial compliance (1.8-2.5 cm(3)/mm Hg). All experiments were performed comparing the selected variables before and during IABP assistance. Increasing E(maxl) from 0.5 to 2 mm Hg/cm(3) resulted in IABP assistance producing lower percentage changes in the selected variables. The changes in ventricular diastolic stiffness strongly influence both absolute value of EVR and its variations during IABP (71 and 65% for lower and higher arterial compliance, respectively). V(ed) and V(es) changes are rather small but higher for lower E(max) and higher V(stiffness). Lower E(max) and higher V(stiffness) resulted in higher TCBF and CO during IABP assistance (∼35 and 10%, respectively). The use of this hybrid model allows for testing real devices in realistic, stable, and repeatable circulatory conditions. Specifically, the presented results show that IABP performance is dependent, at least in part, on left ventricular filling, ejection characteristics, and arterial compliance. It is possible in this way to simulate patient-specific conditions and predict the IABP performance at different values of the circulatory or ventricular parameters. Further work is required to study the conditions for heart recovery modeling, baroreceptor controls, and physiological feedbacks.

Towards a personalized and dynamic CRT-D. A computational cardiovascular model dedicated to therapy optimization.

BACKGROUND In spite of cardiac resynchronization therapy (CRT) benefits, 25-30% of patients are still non responders. One of the possible reasons could be the non optimal atrioventricular (AV) and interventricular (VV) intervals settings. Our aim was to exploit a numerical model of cardiovascular system for AV and VV intervals optimization in CRT. METHODS A numerical model of the cardiovascular system CRT-dedicated was previously developed. Echocardiographic parameters, Systemic aortic pressure and ECG were collected in 20 consecutive patients before and after CRT. Patient data were simulated by the model that was used to optimize and set into the device the intervals at the baseline and at the follow up. The optimal AV and VV intervals were chosen to optimize the simulated selected variable/s on the base of both echocardiographic and electrocardiographic parameters. RESULTS Intervals were different for each patient and in most cases, they changed at follow up. The model can well reproduce clinical data as verified with Bland Altman analysis and T-test (p > 0.05). Left ventricular remodeling was 38.7% and left ventricular ejection fraction increasing was 11% against the 15% and 6% reported in literature, respectively. CONCLUSIONS The developed numerical model could reproduce patients conditions at the baseline and at the follow up including the CRT effects. The model could be used to optimize AV and VV intervals at the baseline and at the follow up realizing a personalized and dynamic CRT. A patient tailored CRT could improve patients outcome in comparison to literature data.

A Model of the Cardiorespiratory Response to Aerobic Exercise in Healthy and Heart Failure Conditions.

The physiological response to physical exercise is now recognized as an important tool which can aid the diagnosis and treatment of cardiovascular diseases. This is due to the fact that several mechanisms are needed to accommodate a higher cardiac output and a higher oxygen delivery to tissues. The aim of the present work is to provide a fully closed loop cardiorespiratory simulator reproducing the main physiological mechanisms which arise during aerobic exercise. The simulator also provides a representation of the impairments of these mechanisms in heart failure condition and their effect on limiting exercise capacity. The simulator consists of a cardiovascular model including the left and right heart, pulmonary and systemic circulations. This latter is split into exercising and non-exercising regions and is controlled by the baroreflex and metabolic mechanisms. In addition, the simulator includes a respiratory model reproducing the gas exchange in lungs and tissues, the ventilation control and the effects of its mechanics on the cardiovascular system. The simulator was tested and compared to the data in the literature at three different workloads whilst cycling (25, 49 and 73 watts). The results show that the simulator is able to reproduce the response to exercise in terms of: heart rate (from 67 to 134 bpm), cardiac output (from 5.3 to 10.2 l/min), leg blood flow (from 0.7 to 3.0 l/min), peripheral resistance (from 0.9 to 0.5 mmHg/(cm3/s)), central arteriovenous oxygen difference (from 4.5 to 10.8 ml/dl) and ventilation (6.1–25.5 l/min). The simulator was further adapted to reproduce the main impairments observed in heart failure condition, such as reduced sensitivity of baroreflex and metabolic controls, lower perfusion to the exercising regions (from 0.6 to 1.4 l/min) and hyperventilation (from 9.2 to 40.2 l/min). The simulator we developed is a useful tool for the description of the basic physiological mechanisms operating during exercise. It can reproduce how these mechanisms interact and how their impairments could limit exercise performance in heart failure condition. The simulator can thus be used in the future as a test bench for different therapeutic strategies aimed at improving exercise performance in cardiopathic subjects.

A modeling tool to study the combined effects of drug administration and LVAD assistance in pathophysiological circulatory conditions

The aim of this work is to develop a tool to study the effect of sodium nitroprusside (SNP) on hemodynamics in conjunction with baroreflex and mechanical circulatory assistance. To this aim, a numerical model of the pharmacodynamic effect of SNP was developed and inserted into a cardiovascular circulatory model integrated with baroreflex and LVAD (continuous flow pump with atrio-aortic connection) sub-models. The experiments were carried out in two steps. In the first step the model was verified comparing simulations with experimental data acquired from mongrel dogs on mean arterial pressure (MAP), cardiac output (CO), heart rate (HR), peripheral resistance, and left ventricular properties. In the second step, the combined action of SNP and mechanical circulatory assistance was studied. Data were measured at pump off and at pump on (20000 rpm and 24000 rpm). At pump off, with a 2.5 μg/kg per min SNP infusion in heart failure condition, the MAP was reduced by approximately 8%, CO and HR increased by about 16% and 18%, respectively. In contrast, during assistance (24000 rpm) the changes in MAP, CO and HR were around −9%, +12%, and +20%, respectively. Furthermore, the effects of the drug on hemodynamic parameters at different heart conditions were significantly different. Thus, the model provides insight into the complex interactions between baroreflex, drug infusion, and LVAD and could be a support for clinical decision-making in cardiovascular pathologies.

A Gaussian Mixture Model to detect suction events in rotary blood pumps

In this paper, we introduce a new suction detection approach based on online learning of a Gaussian Mixture Model (GMM) with constrained parameters to model the reduction in pump flow signals baseline during suction events. A novel three-step methodology is employed: i) signal windowing, ii) GMM based classification and iii) GMM parameter adaptation. More specifically, the first 5 second segment is used for the parameter initialization and the consequent 1 second windows are classified and used for model adaptation. The proposed approach has been tested in simulation (pump flow) signals and satisfactory results have been obtained.

Exercise physiology in chronic mechanical circulatory support patients: vascular function and beyond.

Purpose of review The majority of patients currently implanted with left ventricular assist devices have the expectation of support for more than 2 years. As a result, survival alone is no longer a sufficient distinctive for this technology, and there have been many studies within the last few years examining functional capacity and exercise outcomes. Recent findings Despite strong evidence for functional class improvements and increases in simple measures of walking distance, there remains incomplete normalization of exercise capacity, even in the presence of markedly improved resting hemodynamics. Reasons for this remain unclear. Despite current pumps being run at a fixed speed, it is widely recognized that pump outputs significantly increase with exercise. The mechanism of this increase involves the interaction between preload, afterload, and the intrinsic pump function curves. The role of the residual heart function is also important in determining total cardiac output, as well as whether the aortic valve opens with exercise. Interactions with the vasculature, with skeletal muscle blood flow and the state of the autonomic nervous system are also likely to be important contributors to exercise performance. Summary Further studies examining optimization of pump function with active pump speed modulation and options for optimization of the overall patient condition are likely to be needed to allow left ventricular assist devices to be used with the hope of full functional physiological recovery.