Interactive simulator for e-Learning environments: a teaching software for health care professionals

Evaluation of Different Cannulation Strategies for Aortic Arch Surgery Using a Cardiovascular Numerical Simulator

Aortic disease has a significant impact on quality of life. The involvement of the aortic arch requires the 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 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 developed circuits of the circulation to simulate blood flow during this type of cannulation set up. The CARDIOSIM© cardiovascular simulation platform was used to analyse the effect on haemodynamic and energetic parameters and the benefit derived in terms of organ perfusion pressure and flow. Our simulation approach based on lumped-parameter modelling, pressure-volume analysis and modified time-varying elastance provides a theoretical background to a three-way cannulation strategy for aortic arch surgery with correlation to the observed clinical practice.

CARDIOSIM©: The First Italian Software Platform for Simulation of the Cardiovascular System and Mechanical Circulatory and Ventilatory Support

This review is devoted to presenting the history of the CARDIOSIM^© software simulator platform, which was developed in Italy to simulate the human cardiovascular and respiratory systems. 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 a PC with a disk operating system (MS-DOS) and was developed using the Turbo Basic language. The latest 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 the most important pathophysiological conditions. One or more zero-dimensional (0-D) modules have been implemented in the platform for each section. The different modules can be assembled to reproduce part or the whole circulation according to Starling’s law of the heart. Different mechanical ventilatory and circulatory devices have been implemented in the platform, including thoracic artificial lungs, ECMO, IABPs, pulsatile and continuous right and left ventricular assist devices, biventricular pacemakers and biventricular assist devices. CARDIOSIM^© is used in clinical and educational environments.

Modeling Mechanical Ventilation In Silico-Potential and Pitfalls

Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to "look inside" the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

Ventricular and Atrial Pressure—Volume Loops: Analysis of the Effects Induced by Right Centrifugal Pump Assistance

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. We sought to study the effects induced by different RVAD connections when right ventricular elastance (EesRIGHT) was modified using numerical simulations based on atrial and ventricular pressure–volume analysis. We considered the effects induced by continuous-flow RVAD support on left/right ventricular/atrial loops when EesRIGHT changed from 0.3 to 0.8 mmHg/mL during in-series or parallel pump connection. Pump rotational speed was also addressed. Parallel RVAD support at 4000 rpm with EesRIGHT = 0.3 mmHg/mL generated percentage changes up to 60% for left ventricular pressure–volume area and external work; up to 20% for left ventricular ESV and up to 25% for left ventricular EDV; up to 50% change in left atrial pressure-volume area (PVLAL-A) and only a 3% change in right atrial pressure–volume area (PVLAR-A). Percentage variation was lower when EesRIGHT = 0.8 mmHg/mL. Early recognition of right ventricular failure followed by aggressive treatment is desirable, so as to achieve a more favourable outcome. RVAD support remains an option for advanced right ventricular failure, although the onset of major adverse events may preclude its use.

Computational Simulator Models and Invasive Hemodynamic Monitoring as Tools for Precision Medicine in Pulmonary Arterial Hypertension

Precision medicine, providing the right therapeutic strategy for the right patient, could revolutionize management and prognosis of patients affected by cardiovascular diseases. Big data and artificial intelligence are pivotal for the realization of this ambitious design. In the setting of pulmonary arterial hypertension (PAH), the use of computational models and data derived from ambulatory implantable hemodynamic monitors could provide useful information for tailored treatment, as requested by precision medicine.

ECMO Assistance during Mechanical Ventilation: Effects Induced on Energetic and Haemodynamic Variables

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 CARDIOSIM©.

METHODS

New modules of the systemic circulation and ECMO were implemented in CARDIOSIM© 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.

In silico study of airway/lung mechanics in normal human breathing

The airway/lung mechanics is usually represented with nonlinear 0-D models based on a pneumatic-electrical analogy. The aim of this work is to provide a detailed description of the human respiratory mechanics in healthy and diseased conditions. The model used for this purpose employs some known constitutive functions of the main components of the respiratory system. We give a detailed mathematical description of these functions and subsequently derive additional key ones. We are interested not only in the main output such as airflow at the mouth or alveolar pressure and volume, but also in other quantities such as resistance and pressure drop across each element of the system and even recoil and compliance of the chest wall. Pathological conditions are simulated by altering the parameters of the constitutive functions. Results show that increased upper airway resistance induces airflow reduction with concomitant narrowing of volume and pressure ranges without affecting lung compliance. Instead, increased elastic recoil leads to low volumes and decreased lung compliance. The model could be used in the study of the interaction between respiratory and cardiovascular systems in pathophysiological conditions.

Intra-aortic balloon counterpulsation timing: A new numerical model for programming and training in the clinical environment

BACKGROUND AND OBJECTIVE

The intra-aortic balloon pump (IABP) is the most widely available device for short-term mechanical circulatory support, often used to wean off cardiopulmonary bypass or combined with extra-corporeal membrane oxygenation support or as a bridge to a left ventricular assist device. Although based on a relatively simple principle, its complex interaction with the cardiovascular system remains challenging and open to debate. The aim of this work was focused on the development of a new numerical model of IABP.

METHODS

The new model was implemented in CARDIOSIM©, which is a modular software simulator of the cardiovascular system used in research and e-learning environment. The IABP is inserted into the systemic bed divided in aortic, thoracic and two abdominal tracts modelled with resistances, inertances and compliances. The effect induced by the balloon is reproduced in each tract of the aorta by the presence of compliances connected to PIABP generator and resistances. PIABP generator reproduces the balloon pressure with the option to change IABP timing. We have used literature data to validate the potential of this new numerical model.

RESULTS

The results have shown that our simulations reproduced the typical effects induced during IABP assistance. We have also simulated the effects induced by the device on the hemodynamic variables when the IABP ratio was set to 1:1, 1:2, 1:4 and 1:8. The outcome of these simulations is in accordance with literature data measured in the clinical environment.

CONCLUSIONS

The new IABP module is easy to manage and can be used as a training tool in a clinical setting. Although based on literature data, the outcome of the simulations is encouraging. Additional work is ongoing with a view to further validate its features. The configuration of CARDIOSIM© presented in this work allows the simulation of the effects induced by mechanical ventilatory assistance. This facility may have significant importance in the management of patients affected by COVID-19 when they require mechanical circulatory support devices.

Reusable learning objects for nurse education: development, evaluation, challenges and recommendations

Online resources are expected within healthcare education, and a plethora of online or technology-based delivery methods are available. Reusable learning objects (RLOs) are a form of digitally supported education that can be used multiple times in various locations; they are especially favoured by nurses. Little is understood about the issues involved in their creation. This article examines the development of an RLO in respiratory physiology for first-year nurses and how those creating it worked together. Feedback during the development of the RLO was gathered over 1 year from academics, technologists and students. Issues that arose included variations and misunderstanding regarding terminology and academics' not appreciating the time it took to develop the resource and its potential. Practical matters included sourcing royalty-free or in-house images, record-keeping and version control, and addressing production logic in case developers moved to other projects. It is important to include students during the design process rather than in just evaluating the final product because user experience and navigation have to be considered together with pedagogical content. Addressing these issues when developing an RLO will help streamline the process and generate a student-focused output.

How can LVAD support influence ventricular energetics parameters in advanced heart failure patients? A retrospective study

BACKGROUND AND OBJECTIVE

Here we present a retrospective analysis of six heart failure patients previously discussed at a multidisciplinary team meeting. Only three out of six patients underwent LVAD insertion as the most appropriate management option.

METHODS

We sought to reproduce the baseline conditions of these patients on hospital admission using our cardiovascular software simulator (CARDIOSIM^©). Subsequently, we simulated the effects of LVAD support and drug administration on left and right ventricular energetics parameters. LVAD assistance was delivered by CARDIOSIM^© based on the module reproducing the behaviour of the Berlin Heart INCOR pump.

RESULTS

The results of our simulations were in agreement with the multidisciplinary team meeting outcome. The analysis of ventricular energetics parameters based on external work and pressure volume area confirmed LVAD support as a beneficial therapeutic option for the three patients considered eligible for this type of treatment. The effects induced by LVAD support and drugs administration showed specific patterns between the two groups of patients.

CONCLUSION

A quantitative approach with the ability to predict outcome during patient's assessment may well be an aid and not a substitute for clinical decision-making.

Simulation as a preoperative planning approach in advanced heart failure patients. A retrospective clinical analysis

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 and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates.

RESULTS

We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM^© was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process.

CONCLUSIONS

Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.

Using numeric simulation in an online e-learning environment to teach functional physiological contexts

BACKGROUND AND OBJECTIVES

Mathematical models are suitable to simulate complex biological processes by a set of non-linear differential equations. These simulation models can be used as an e-learning tool in medical education. However, in many cases these mathematical systems have to be treated numerically which is computationally intensive. The aim of the study was to develop a system for numerical simulation to be used in an online e-learning environment.

METHODS

In the software system the simulation is located on the server as a CGI application. The user (student) selects the boundary conditions for the simulation (e.g., properties of a simulated patient) on the browser. With these parameters the simulation on the server is started and the simulation result is re-transferred to the browser.

RESULTS

With this system two examples of e-learning units were realized. The first one uses a multi-compartment model of the glucose-insulin control loop for the simulation of the plasma glucose level after a simulated meal or during diabetes (including treatment by subcutaneous insulin application). The second one simulates the ion transport leading to the resting and action potential in nerves. The student can vary parameters systematically to explore the biological behavior of the system.

CONCLUSIONS

The described system is able to simulate complex biological processes and offers the possibility to use these models in an online e-learning environment. As far as the underlying principles can be described mathematically, this type of system can be applied to a broad spectrum of biomedical or natural scientific topics.