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.

Despite 50 years of research to assess the intra-aortic balloon pump (IABP) effects on patients' hemodynamics, some issues related to the effects of this therapy are still not fully understood. One of these issues is the effect of IABP, its inflation timing and duration on peripheral circulation autonomic controls. This work provides a systematic analysis of IABP effects on baroreflex using a cardiovascular hybrid model, which consists of computational and hydraulic submodels. The work also included a baroreflex computational model that was connected to a hydraulic model with a 40-cm(3) balloon. The IABP was operated at different inflation trigger timings (-0.14 to 0.31 s) and inflation durations (0.05-0.45 s), with time of the dicrotic notch being taken as t = 0. Baroreflex-dependent parameters-afferent and efferent pathway activity, heart rate, peripheral resistance, and venous tone-were evaluated at each of the inflation trigger times and durations considered. Balloon early inflation (0.09 s before the dicrotic notch) with inflation duration of 0.25 s generated a maximum net increment of afferent pathway activity of 10%, thus leading to a decrement of efferent sympathetic activity by 15.3% compared with baseline values. These times also resulted in a reduction in peripheral resistance and heart rate by 4 and 4.3% compared with baseline value. We conclude that optimum IABP triggering time results in positive effects on peripheral circulation autonomic controls. Conversely, if the balloon is not properly timed, peripheral resistance and heart rate may even increase, which could lead to detrimental outcomes.

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.

Considering the lack of donors, ventricular assist devices (VADs) could be an alternative to heart transplantation for failing Fontan patients, in spite of the lack of experience and the complex anatomy and physiopathology of these patients. Considering the high number of variables that play an important role such as type of Fontan failure, type of VAD connection, and setting (right VAD [RVAD], left VAD [LVAD], or biventricular VAD [BIVAD]), a numerical model could be useful to support clinical decisions. The aim of this article is to develop and test a lumped parameter model of the cardiovascular system simulating and comparing the VAD effects on failing Fontan. Hemodynamic and echocardiographic data of 10 Fontan patients were used to simulate the baseline patients' condition using a dedicated lumped parameter model. Starting from the simulated baseline and for each patient, a systolic dysfunction, a diastolic dysfunction, and an increment of the pulmonary vascular resistance were simulated. Then, for each patient and for each pathology, the RVAD, LVAD, and BIVAD implantations were simulated. The model can reproduce patients' baseline well. In the case of systolic dysfunction, the LVAD unloads the single ventricle and increases the cardiac output (CO) (35%) and the arterial systemic pressure (Pas) (25%). With RVAD, a decrement of inferior vena cava pressure (Pvci) (39%) was observed with 34% increment of CO, but an increment of the single ventricle external work (SVEW). With the BIVAD, an increment of Pas (29%) and CO (37%) was observed. In the case of diastolic dysfunction, the LVAD increases CO (42%) and the RVAD decreases the Pvci, while both increase the SVEW. In the case of pulmonary vascular resistance increment, the highest CO (50%) and Pas (28%) increment is obtained with an RVAD with the highest decrement of Pvci (53%) and an increment of the SVEW but with the lowest VAD power consumption. The use of numerical models could be helpful in this innovative field to evaluate the effect of VAD implantation on Fontan patients to support patient and VAD type selection personalizing the assistance.