In silico study of the haemodynamic effects induced by mechanical ventilation and biventricular pacemaker

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.

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.

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

There is an established tradition of cardiovascular simulation tools, but the application of this kind of technology in the e-Learning arena is a novel approach. This paper presents an e-Learning environment aimed at teaching the interaction of cardiovascular and lung systems to health-care professionals. Heart-lung interaction must be analyzed while assisting patients with severe respiratory problems or with heart failure in intensive care unit. Such patients can be assisted by mechanical ventilatory assistance or by thoracic artificial lung.

“In silico” cardiovascular simulator was experimented during a training course given to graduate students of the School of Specialization in Cardiology at ‘Sapienza’ University in Rome.

The training course employed CARDIOSIM^©: a numerical simulator of the cardiovascular system. Such simulator is able to reproduce pathophysiological conditions of patients affected by cardiovascular and/or lung disease. In order to study the interactions among the cardiovascular system, the natural lung and the thoracic artificial lung (TAL), the numerical model of this device has been implemented. After having reproduced a patient’s pathological condition, TAL model was applied in parallel and hybrid model during the training course.

Results obtained during the training course show that TAL parallel assistance reduces right ventricular end systolic (diastolic) volume, but increases left ventricular end systolic (diastolic) volume. The percentage changes induced by hybrid TAL assistance on haemodynamic variables are lower than those produced by parallel assistance. Only in the case of the mean pulmonary arterial pressure, there is a percentage reduction which, in case of hybrid assistance, is greater (about 40%) than in case of parallel assistance (20-30%).

At the end of the course, a short questionnaire was submitted to students in order to assess the quality of the course. The feedback obtained was positive, showing good results with respect to the degree of students’ learning and the ease of use of the software simulator.

Mechanical ventilation and thoracic artificial lung assistance during mechanical circulatory support with PUCA pump: in silico study

Patients assisted with left ventricular assist device (LVAD) may require prolonged mechanical ventilatory assistance secondary to postoperative respiratory failure. The goal of this work is the study of the interdependent effects LVAD like pulsatile catheter (PUCA) pump and mechanical ventilatory support or thoracic artificial lung (TAL), by the hemodynamic point of view, using a numerical simulator of the human cardiovascular system. In the simulator, different circulatory sections are described using lumped parameter models. Lumped parameter models have been designed to describe the hydrodynamic behavior of both PUCA pump and thoracic artificial lung. Ventricular behavior atrial and septum functions were reproduced using variable elastance model. Starting from simulated pathological conditions we studied the effects produced on some hemodynamic variables by simultaneous PUCA pump, thoracic artificial lung or mechanical ventilation assistance. Thoracic artificial lung was applied in parallel or in hybrid mode. The effects of mechanical ventilation have been simulated by changing mean intrathoracic pressure value from -4 mmHg to +5 mmHg. The hemodynamic variables observed during the simulations, in different assisted conditions, were: left and right ventricular end systolic (diastolic) volume, systolic/diastolic aortic pressure, mean pulmonary arterial pressure, left and right mean atrial pressure, mean systemic venous pressure and the total blood flow. Results show that the application of PUCA (without mechanical ventilatory assistance) increases the total blood flow, reduces the left ventricular end systolic volume and increases the diastolic aortic pressure. Parallel TAL assistance increases the right ventricular end diastolic (systolic) volume reduction both when PUCA is switched "ON" and both when PUCA is switched "OFF". By switching "OFF" the PUCA pump, it seems that parallel thoracic artificial lung assistance produces a greater cardiac output (respect to hybrid TAL assistance). Results concerning PUCA and TAL interaction produced by simulations cannot be compared with "in vivo" results since they are not presented in literature. But results concerning the effects produced by LVAD and mechanical ventilation have a trend consistent with those presented in literature.