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Electrical analogue model of the cardiovascular system. The systemic arterial section consists of three RLC elements representing the aortic (RAT, LAT and CAT), thoracic (RTT, LTT and CTT) and abdominal (RABT, LABT and CABT) tract respectively. Ras is the variable systemic peripheral resistance. The systemic venous section consists of two variable resistances (Rvs1 and Rvs2) and a compliance (Cvs). The main (small) pulmonary section is reproduced by a RLC element: Rpam, Lpam and Cpam (Rpas, Lpas and Cpas). The arteriole (capillary) bed behaviour is reproduced by a single resistance Rpar (Rpc). The pulmonary venous section consists of a compliance (Cvp) and a resistance (Rvp). Pt is the mean intrathoracic pressure
Source publication
Background
Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure–volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity...
Citations
... The aim of this study is the comparison between Impella 2.5 and IABP using CARDIOSIM © [7][8][9][10][11][12][13][14] software simulator of the cardiovascular system. Our study may contribute to fill the gap in the limited available data from other studies directly comparing Impella 2.5 with IABP. ...
... The numerical model of the cardiovascular system used to perform our simulations has been previously described [7][8][9][10][11]. The electric analogue of the cardiovascular network described in [12] consists of the following compartments ( Figure 1): ascending and descending aorta with aortic arch, thoracic, upper limbs and head, superior and inferior vena cava, renal and hepatic, splanchnic, abdominal and lower limbs [12]. ...
Cardiogenic shock (CS) is part of a clinical syndrome consisting of acute left ventricular failure causing severe hypotension leading to inadequate organ and tissue perfusion. The most commonly used devices to support patients affected by CS are Intra-Aortic Balloon Pump (IABP), Impella 2.5 pump and Extracorporeal Membrane Oxygenation. The aim of this study is the comparison between Impella and IABP using CARDIOSIM© software simulator of the cardiovascular system. The results of the simulations included baseline conditions from a virtual patient in CS followed by IABP assistance in synchronised mode with different driving and vacuum pressures. Subsequently, the same baseline conditions were supported by the Impella 2.5 with different rotational speeds. The percentage variation with respect to baseline conditions was calculated for haemodynamic and energetic variables during IABP and Impella assistance. The Impella pump driven with a rotational speed of 50,000 rpm increased the total flow by 4.36% with a reduction in left ventricular end-diastolic volume (LVEDV) by ≅15% to ≅30%. A reduction in left ventricular end systolic volume (LVESV) by ≅10% to ≅18% (≅12% to ≅33%) was observed with IABP (Impella) assistance. The simulation outcome suggests that assistance with the Impella device leads to higher reduction in LVESV, LVEDV, left ventricular external work and left atrial pressure-volume loop area compared to IABP support.
... Open repair with the elephant trunk technique [3] under hypothermic circula-41 tory arrest is widely used with satisfactory long-term outcome [4]- [5]. More recently, the 42 frozen elephant trunk technique using the Thoraflex TM (Vascutek, Terumo, Inchinnan, 43 The surgical approach consists of techniques involving different cannulation sites. 62 When central aortic cannulation is not feasible, arterial cannulation through one of the 63 femoral arteries (either directly or via an end-to-side Dacron graft) is appropriate. ...
Aortic disease has a significant impact on quality of life. Involvement of the aortic arch requires preservation of blood supply to the brain during surgery. Deep hypothermic circulatory arrest is an established technique for this purpose although neurological injury remains high. Additional techniques have been used to reduce the risk although controversy still remains. A three-way cannulation approach, including both carotid arteries and the femoral artery or the ascending aorta, has been used successfully for aortic arch replacement and redo procedures. We have de-veloped circuits of the circulation to simulate blood flow during this type of cannulation set up. The aim is to analyse using CARDIOSIM© cardiovascular simulation platform, how the haemodynamic and energetic parameters are affected and the benefit derived with particular reference to the cerebral circulation.
... 0-D models eliminate the variation in space and allow the description of pressure and flow as a function of time in a specific compartment of the circulatory system [13]. Zero-dimensional modelling is widely used particularly for the analysis of average values and the interaction between an assist device and the cardiovascular system [15][16][17]. Although 0-D modelling gives less detailed predictions of pressure and flow waveforms, it has shown great potential and flexibility for clinical application with particular reference to the pathophysiology of heart failure, guidance for patient selection and the hemodynamic impact of device intervention [16,18]. ...
... Zero-dimensional modelling is widely used particularly for the analysis of average values and the interaction between an assist device and the cardiovascular system [15][16][17]. Although 0-D modelling gives less detailed predictions of pressure and flow waveforms, it has shown great potential and flexibility for clinical application with particular reference to the pathophysiology of heart failure, guidance for patient selection and the hemodynamic impact of device intervention [16,18]. A combined approach of lumped-parameter modelling, pressure-volume analysis and modified time-varying elastance has a significant potential for daily use within the constraints of a clinical setting. ...
... Since the first version of CARDIOSIM © , the numerical simulator has been used to carry out studies both on animal models [36] and in a clinical setting [11,16,21,23,37,38]. Figure 4 shows a screen output from one of the latest version of the software platform obtained during the analysis of hemodynamic parameters measured in a clinical setting. Seven patients underwent electrocardiographic and echocardiographic evaluation before and after biventricular pacemaker (Biv) implantation, more specifically 24 hours, seven days and six months following CRT. ...
This review is devoted to present the history of CARDIOSIM© software simulator platform, which was developed in Italy to simulate the human cardiovascular and respiratory system. The first version of CARDIOSIM© was developed at the Institute of Biomedical Technologies of the National Research Council in Rome. The first platform version published in 1991 ran on PC with disk operating system (MS-DOS) and was developed using the Turbo Basic language. The last version runs on PC with Microsoft Windows 10 operating system; it is implemented in Visual Basic and C++ languages. The platform has a modular structure consisting of seven different general sections, which can be assembled to reproduce different pathophysiological conditions. The software simulator can reproduce the most important circulatory phenomena in terms of pressure and volume relationships. It represents the whole circulation using a lumped-parameter model and enables the simulation of different cardiovascular conditions according to Starling’s law of the heart and a modified time-varying elastance model. Different mechanical ventilatory and circulatory devices have been implemented in the platform including thoracic artificial lung, ECMO, IABP, pulsatile and continuous right and left ventricular assist devices, biventricular pacemaker and biventricular assist devices. CARDIOSIM© is used in clinical and educational environment.
... For the purposes of our study, we have assembled the cardiovascular network with the new module of the systemic circulation whilst the behavior of the heart is modelled as described in [3], [4]. The systemic venous section [3], [6] and the entire pulmonary circulation [7], [8], [11], [12] are modelled as described in current literature. We have selected the module presented in [13] for the coronary circulation. ...
Background and Objective
The main indications for right ventricular assist device (RVAD) support are right heart failure after implantation of a left ventricular assist device (LVAD) or early graft failure following heart transplantation. About 30-40% of patients will need RVAD support after LVAD implantation. Pulmonary hypertension is also an indication for right heart assistance. Several types of RVAD generating pulsatile or continuous flow are available on the market. These assist devices can be connected to the cardiovascular system in different ways. We sought to analyse the effects induced by different RVAD connections when right ventricular elastance is modified using a numerical simulator. The analysis was based on the behaviour of both left and right ventricular and atrial loops in the pressure-volume plane.
Methods
New modules of the cardiovascular network and a right ventricular centrifugal pump were implemented in CARDIOSIM © software simulator platform. The numerical pump model generated continuous flow when connected in series or parallel to the right ventricle. When the RVAD was connected in series (parallel), the pump removed blood from the right ventricle (atrium) and ejected it into the pulmonary artery. In our study, we analysed the effects induced by RVAD support on left/right ventricular/atrial loops when right ventricular elastance slope (Ees RIGHT ) changed from 0.3 to 0.8 mmHg/ml with the pump connected either in series or parallel. The effect of low and high rotational pump speed was also addressed.
Results
Percentage changes up to 60% were observed for left ventricular pressure-volume area and external work during in-parallel RVAD support at 4000 rpm with Ees RIGHT = 0.3mmHg/ml. The same pump setting and connection type led to percentage variation up to 20% for left ventricular ESV and up to 25% for left ventricular EDV with Ees RIGHT = 0.3mmHg/ml. Again the same pump setting and connection generated up to 50% change in left atrial pressure-volume loop area (PVLA L-A ) and only 3% change in right atrial pressure-volume loop area (PVLA R-A ) when Ees RIGHT = 0.3mmHg/ml. Percentage variation was lower when Ees RIGHT was increased up to 0.8 mmHg/ml.
Conclusion
Early recognition of right ventricular failure followed by aggressive treatment is desirable to achieve a more favourable outcome. RVAD support remains an option for advanced right ventricular failure although onset of major adverse events may preclude its use.
... Lumped parameter models that incorporate non-invasive personalized cardiac parameters offer a unique way to generate these personalized PV loops in a rapid and non-invasive manner. Additionally, they can be used to study the impact of different treatment options and treatment priorities in a patient-specific manner [28,72,104,105,131]. In recent work, Motamed [42] used a personalized lumped parameter model with a time varying elastance heart model and noninvasive parameters to evaluate how different intervention options would impact the cardiac workload for a patient with multiple valvular diseases based on PV loops (Fig. 4 Panel E). ...
... This same argument can be made for cardiovascular simulation tools which will also require further larger scale clinical studies to truly evaluate the benefits and value added in comparison with traditional techniques and tools [131,200]. In certain cases for example, simpler solutions, such as a fully lumped parameter model may be sufficient as opposed to a multiscale model due to the lower computational cost and ease of automation [8,79]. ...
Cardiovascular (CV) disease impacts tens of millions of people annually and carries a massive global economic burden. Continued advances in medical imaging, hardware and computational efficiency are leading to an increased interest in the field of cardiovascular computational modelling to help combat the devastating impact of CV disease. This review article will focus on a computational modelling technique known as lumped parameter modelling (LPM). Due to its rapid computation time, ease of automation and relative simplicity, LPM holds the potential of aiding in the early diagnosis of CV disease, assisting clinicians in determining personalized and optimal treatments and offering a unique in-silico setting to study cardiac and circulatory diseases. In addition, it is one of the many tools that are needed in the eventual development of patient specific cardiovascular “digital twin” frameworks. This review focuses on how the personalization of cardiovascular lumped parameter models are beginning to impact the field of patient specific cardiovascular care. It presents an in-depth examination of the approaches used to develop current predictive LPM hemodynamic frameworks as well as their applications within the realm of cardiovascular disease. The roles of these models in higher order blood flow (1D/3D) simulations are also explored in addition to the different algorithms used to personalize the models. The article outlines the future directions of this field and the current challenges and opportunities related to the translation of this technology into clinical settings.
... The following three hemodynamics quantification capabilities are required to enable clinicallyuseful computational diagnostic frameworks for patients with C3VD who undergo TAVR. The required quantities are: global hemodynamics metrics advocated by [39][40][41][42][43][44][45][46][47][48][49] as follows: (1) Metrics of circulatory function , e.g., detailed information of the dynamics of the circulatory system, and (2) Metrics of cardiac function , e.g., heart workload and its contribution breakdown of each component of the cardiovascular diseases; local hemodynamics metrics advocated by [ 8 , 13 , 50-54 ] as follows: (3) Cardiac fluid dynamics , e.g., details of the instantaneous 3-D flow, vortex formation, growth, eventual shedding, and their effects on fluid transport and stirring inside the heart. The recent advances in fluid dynamics can enable the development of novel fluid-dynamics methods that can be used as engines of new patient-specific diagnostic tools to sufficiently quantify flow conditions and satisfy the three requirements described above. ...
Aortic stenosis is an acute and chronic cardiovascular disease that often coexists with other complex valvular, ventricular and vascular diseases (C3VD). Transcatheter aortic valve replacement is an emerging less invasive intervention for patients with aortic stenosis. Although hemodynamics quantification is critical for accurate and early diagnosis of aortic stenosis and C3VD, proper diagnostic methods for these diseases are still lacking because fluid-dynamics methods, that can be used as engines of new diagnostic tools, are not well developed yet. As the heart resides in a sophisticated vascular network which imposes a load on the heart, effective diagnosis requires quantifications of the global hemodynamics (metrics of circulatory function and metrics of cardiac function), and of the local hemodynamics (cardiac fluid dynamics). To enable the development of new non-invasive diagnostic methods that can quantify local and global hemodynamics, we developed an innovative computational-mechanics and imaging-based framework that only needs patient data routinely and non-invasively measured in clinics. We not only validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements but also, we demonstrated its diagnostic utility in providing novel analyses and interpretations of clinical data.
... In view of the above considerations and based on the experience developed during the COVID-19 pandemic, we developed numerical simulations to reproduce the interactions occurring in ventilated patients on peripheral VA-ECMO support using CAR-DIOSIM© software [7][8][9][10][11] . The initial task consisted of the implementation of a new module based on a 0-D (lumped parameter) numerical model able to reproduce the behavior of the whole systemic circulation. ...
... The cardiovascular network in CARDIOSIM© software consists of seven modules that can be assembled in different ways [7][8][9][10][11] . The modules are: left and right heart, systemic and pulmonary arterial section, systemic and pulmonary venous section and the Table 1 . ...
Background and Objective
Simulation in cardiovascular medicine may help clinicians understand the important events occurring during mechanical ventilation and circulatory support. During the COVID-19 pandemic, a significant number of patients have required hospital admission to tertiary referral centres for concomitant mechanical ventilation and extracorporeal membrane oxygenation (ECMO). Nevertheless, the management of ventilated patients on circulatory support can be quite challenging. Therefore, we sought to review the management of these patients based on the analysis of haemodynamic and energetic parameters using numerical simulations generated by a software package named CARDIOSIMࣩ.
Methods
New modules of the systemic circulation and ECMO were implemented in CARDIOSIMࣩ platform. This is a modular software simulator of the cardiovascular system used in research, clinical and e-learning environment. The new structure of the developed modules is based on the concept of lumped (0-D) numerical modelling. Different ECMO configurations have been connected to the cardiovascular network to reproduce Veno-Arterial (VA) and Veno-Venous (VV) ECMO assistance. The advantages and limitations of different ECMO cannulation strategies have been considered. We have used literature data to validate the effects of a combined ventilation and ECMO support strategy.
Results
The results have shown that our simulations reproduced the typical effects induced during mechanical ventilation and ECMO assistance. We focused our attention on ECMO with triple cannulation such as Veno-Ventricular-Arterial (VV-A) and Veno-Atrial-Arterial (VA-A) configurations to improve the hemodynamic and energetic conditions of a virtual patient. Simulations of VV-A and VA-A assistance with and without mechanical ventilation have generated specific effects on cardiac output, coupling of arterial and ventricular elastance for both ventricles, mean pulmonary pressure, external work and pressure volume area.
Conclusion
The new modules of the systemic circulation and ECMO support allowed the study of the effects induced by concomitant mechanical ventilation and circulatory support. Based on our clinical experience during the COVID-19 pandemic, numerical simulations may help clinicians with data analysis and treatment optimisation of patients requiring both mechanical ventilation and circulatory support.
... CFD has been applied to non-invasively quantify pressure changes and flow within coronary arteries, based on cardiac computed tomography (CT), as well as other vascular beds (9,10). More recently, CFD has been used to study in patients with advanced heart failure the hemodynamic impact of a possible LVAD implant (11). Models have also assessed the impact of inflow and outflow cannula angulation as well as aortic valve opening on flow patterns, shear stress and thrombotic potential (12)(13)(14)(15). ...
Our current understanding of flow through the circuit of left ventricular assist device (LVAD), left ventricle and ascending aorta remains incompletely understood. Computational fluid dynamics, which allow for analysis of flow in the cardiovascular system, have been used for this purpose, although current simulation models have failed to fully incorporate the interplay between the pulsatile left ventricle and continuous-flow generated by the LVAD. Flow-through the LVAD is dependent on the interaction between device and patient-specific factors with suboptimal flow patterns evoking increased risk of LVAD-related complications. Computational fluid dynamics can be used to analyze how different pump and patient factors affect flow patterns in the left ventricle and the aorta. Computational fluid dynamics simulations were carried out on a patient with a HeartMate II. Simulations were also conducted for theoretical scenarios substituting HeartWare HVAD, HeartMate 3 (HM3) in continuous mode and HM3 with Artificial Pulse. An anatomical model of the patient was reconstructed from computed tomography (CT) images, and the LVAD outflow was used as the inflow boundary condition. The LVAD outflow was calculated separately using a lumped-parameter-model of the systemic circulation, which was calibrated to the patient based on the patient-specific ventricular volume change reconstructed from 4 dimensional computed tomography and pulmonary capillary wedge pressure tracings. The LVADs were implemented in the lumped-parameter-model via published pressure head versus flow (H-Q) curves. To quantify the flushing effect, virtual contrast agent was released in the ascending aorta and its flushing over the cycles was quantified. Shear stress acting on the aortic endothelium and shear rate in the bloodstream were also quantified as indicators of normal/abnormal blood flow, especially the latter being a biomarker of platelet activation and hemolysis. LVAD speeds for the HVAD and HM3 were selected to match flow rates for the patient's HMII (9,000 RPM for HMII, 5,500 RPM for HM3, and 2,200 RPM for HVAD), the cardiac outputs were 5.81 L/min, 5.83 L/min, and 5.92 L/min, respectively. The velocity of blood flow in the outflow cannula was higher in the HVAD than in the two HeartMate pumps with a cycle average (range) of 0.92 m/s (0.78-1.19 m/s), 0.91 m/s (0.86-1.00 m/s), and 1.74 m/s (1.40-2.24 m/s) for HMII, HM3, and HVAD, respectively. Artificial pulse increased the peak flow rate to 9.84 L/min for the HM3 but the overall cardiac output was 5.96 L/min, which was similar to the continuous mode. Artificial pulse markedly decreased blood stagnation in the ascending aorta; after six cardiac cycles, 48% of the blood was flushed out from the ascending aorta under the continuous operation mode while 60% was flushed under artificial pulse. Shear stress and shear rate in the aortic arch were higher with the HVAD compared to the HMII and HM3, respectively (shear stress: 1.76 vs. 1.33 vs. 1.33 Pa, shear rate: 136 vs. 91.5 vs. 89.4 s-1). Pump-specific factors such as LVAD type and programmed flow algorithms lead to unique flow patterns which influence blood stagnation, shear stress, and platelet activation. The pump-patient interaction can be studied using a novel computational fluid dynamics model to better understand and potentially mitigate the risk of downstream LVAD complications.
... Since their first surgical implantation in the 1960s [14], ventricular assist devices play an active role in the treatment of heart failure. The new generation of LVADs use axial or centrifugal rotary pumps [15]. Compared with the first generation of pulsating pumps, the rotary pumps have the advantages of small size, high reliability, and durability. ...
The mathematical modeling of the cardiovascular system is a simple and noninvasive method to comprehend hemodynamics and the operating mechanism of the mechanical circulatory assist device. In this study, a numerical model was developed to simulate hemodynamics under different conditions and to evaluate the operating condition of continuous-flow left ventricular assist device (LVAD). The numerical model consisted of a cardiovascular lumped parameter (CLP) model, a baroreflex model, and an LVAD model. The CLP model was established to simulate the human cardiovascular system including the left heart, right heart, systemic circulation, and pulmonary circulation. The baroreflex model was used to regulate left and right ventricular end-systolic elastances, systemic vascular resistance, and heart rate. The centrifugal pump HeartMate III used as an example to simulate the rotary pump dynamics at different operating speeds. Simulation results show that hemodynamics under normal, left ventricular failure and different levels of pump support conditions can be reproduced by the numerical model. Based on simulation results, HeartMate III operating speed can be maintained between 3600 rpm and 4400 rpm to avoid pump regurgitation and ventricular suction. Additionally, in the simulation system, the HeartMate III operating speed should be between 3600 rpm and 3800 rpm to provide optimal physiological perfusion. Thus, the developed numerical model is a feasible solution to simulate hemodynamics and evaluate the operating condition of continuous-flow LVAD.
... The mathematical description and physical modeling of the human CVS have been proven nowadays to be very useful prerequisite tools for understanding the complex physiological processes and mechanisms of a real system by simplifying it. They have become powerful tools for simulating the hemodynamic properties of CVS and have been playing an increasingly important role in the diagnosis or the treatment of CVDs and in the development of medical devices [94,95,96,97,98]. That is why, with the recent significant improvements in computer technology, modeling based on physical principles has attracted increasing interest. ...
This thesis follows on from a recent study conducted by a few researchers from University of Montpellier, with the aim of proposing to the scientific community an inversion procedure capable of noninvasively estimating patient-specific blood pressure in cerebral arteries. Its first objective is, on the one hand, to examine the accuracy and robustness of the inversion procedure proposed by these researchers with respect to various sources of uncertainty related to the models used, formulated assumptions and patient-specific clinical data, and on the other hand, to set a stopping criterion for the ensemble Kalman filter based algorithm used in their inversion procedure. For this purpose, uncertainty analysis and several sensitivity analyses are carried out. The second objective is to illustrate how machine learning, mainly focusing on convolutional neural networks, can be a very good alternative to the time-consuming and costly inversion procedure implemented by these researchers for cerebral blood pressure estimation.An approach taking into account the uncertainties related to the patient-specific medical images processing and the blood flow model assumptions, such as assumptions about boundary conditions, physical and physiological parameters, is first presented to quantify uncertainties in the inversion procedure outcomes. Uncertainties related to medical images segmentation are modelled using a Gaussian distribution and uncertainties related to modeling assumptions choice are analyzed by considering several possible hypothesis choice scenarii. From this approach, it emerges that the uncertainties on the procedure results are of the same order of magnitude as those related to segmentation errors. Furthermore, this analysis shows that the procedure outcomes are very sensitive to the assumptions made about the model boundary conditions. In particular, the choice of the symmetrical Windkessel boundary conditions for the model proves to be the most relevant for the case of the patient under study.Next, an approach for ranking the parameters estimated during the inversion procedure in order of importance and setting a stopping criterion for the algorithm used in the inversion procedure is presented. The results of this strategy show, on the one hand, that most of the model proximal resistances are the most important parameters for blood flow estimation in the internal carotid arteries and, on the other hand, that the inversion algorithm can be stopped as soon as a certain reasonable convergence threshold for the most influential parameter is reached.Finally, a new numerical platform, based on machine learning and allowing to estimate the patient-specific blood pressure in the cerebral arteries much faster than with the inversion procedure but with the same accuracy, is presented. The application of this platform to the patient-specific data used in the inversion procedure provides noninvasive and real-time estimate of patient-specific cerebral pressure consistent with the inversion procedure estimation.
