Biomedical subjects

Roger I Nokes

Publications and source records attributed to Roger I Nokes.

3 recordsLinked to original sources

PubMed2006

Simulating transient ventricular interaction using a minimal cardiovascular system model.

A minimal closed-loop cardiovascular system (CVS) model has been developed that can simulate ventricular interaction due to both direct interaction through the septum and series interaction through the circulation system. The model is used to simulate canine experiments carried out to study the transient response of the left ventricle due to changes in right ventricle pressures and volumes. The model-simulated trends in left and right ventricle pressures and volumes, septum deflection and arterial flow rates are compared with the experimental results. In spite of the limited physiological data available describing the animals, the model is shown to capture all the transient trends in the experimental data. This is the first known example of a physiological model that can capture all these trends. The model is then used to illustrate the separate effects of direct and series interactions independently. This study proves the value of this modelling method to be used in conjunction with experimental data for delineating and understanding the factors that contribute to ventricular dynamics.

Animals↗

PubMed2004

Minimal haemodynamic system model including ventricular interaction and valve dynamics.

Characterising circulatory dysfunction and choosing a suitable treatment is often difficult and time consuming, and can result in a deterioration in patient condition, or unsuitable therapy choices. A stable minimal model of the human cardiovascular system (CVS) is developed with the ultimate specific aim of assisting medical staff for rapid, on site modelling to assist in diagnosis and treatment. Models found in the literature simulate specific areas of the CVS with limited direct usefulness to medical staff. Others model the full CVS as a closed loop system, but they were found to be very complex, difficult to solve, or unstable. This paper develops a model that uses a minimal number of governing equations with the primary goal of accurately capturing trends in the CVS dynamics in a simple, easily solved, robust model. The model is shown to have long term stability and consistency with non-specific initial conditions as a result. An "open on pressure close on flow" valve law is created to capture the effects of inertia and the resulting dynamics of blood flow through the cardiac valves. An accurate, stable solution is performed using a method that varies the number of states in the model depending on the specific phase of the cardiac cycle, better matching the real physiological conditions. Examples of results include a 9% drop in cardiac output when increasing the thoracic pressure from -4 to 0 mmHg, and an increase in blood pressure from 120/80 to 165/130 mmHg when the systemic resistance is doubled. These results show that the model adequately provides appropriate magnitudes and trends that are in agreement with existing data for a variety of physiologically verified test cases simulating human CVS function.

Blood Flow Velocity↗

PubMed2003

Velocity profile method for time varying resistance in minimal cardiovascular system models.

This paper investigates the fluid dynamics governing arterial flow used in lumped parameter cardiovascular system (CVS) models, particularly near the heart where arteries are large. Assumptions made in applying equations conventionally used in lumped parameter models are investigated, specifically that of constant resistance to flow. The Womersley number is used to show that the effects of time varying resistance must be modelled in the pulsatile flow through the large arteries near the heart. It is shown that the equation commonly used to include inertial effects in fluid flow calculations is inappropriate for including time varying resistance. A method of incorporating time varying resistance into a lumped parameter model is developed that uses the Navier-Stokes equations to track the velocity profile. Tests on a single-chamber model show a 17.5% difference in cardiac output for a single-chamber ventricle model when comparing constant resistance models with the velocity profile tracking method modelling time varying resistance. This increase in precision can be achieved using 20 nodes with only twice the computational time required. The method offers a fluid dynamically and physiologically accurate method of calculating large Womersley number pulsatile fluid flows in large arteries around the heart and valves. The proposed velocity profile tracking method can be easily incorporated into existing lumped parameter CVS models, improving their clinical application by increasing their accuracy.

Animals↗