Dr Al Benson
- Position: Lecturer in Cardiovascular Science
- Areas of expertise: computational modelling; cardiac arrhythmias; exercise intolerance; magnetic resonance imaging; optical imaging; cardiopulmonary exercise testing.
- Email: A.P.Benson@leeds.ac.uk
- Location: 7.56a Garstang
- BSc (Hons) Sports Science (2000-2003)
- PhD Computational Biology (2003-2006)
- Research Fellow (2006-2008)
- MRC Special Training Fellowship in Biomedical Informatics (2008-2011)
- BBSRC Research Fellow (2011-2013)
- Lecturer in Cardiovascular Science (since 2013)
- Undergraduate Admissions Tutor - Biomedical Sciences programmes
- Special Circumstances Committee member - Biomedical Sciences programmes
Computational modelling of cardiovascular physiology
My research interests are in the use of computational models, combined with magnetic resonance and other experimental techniques, to study cardiovascular physiology in health and disease. A particular focus has been the study of cardiac arrhythmias and exercise intolerance in heart failure.
Cardiac arrhythmias are a major cause of mortality and morbidity. Ventricular fibrillation is an often fatal arrhythmia in which the heart’s normal rhythm is disturbed when multiple electrical wavefronts continually re-excite the same tissue (re-entry); synchronous contraction of the ventricles is lost, circulation of the blood ceases and death occurs. Individuals with heart failure have a significantly increased risk of developing such arrhythmias.
Computational cardiac models provide tools for examining the mechanisms underlying the onset of such arrhythmias, and interventions aimed at either preventing this onset or restoring normal sinus rhythm, as the data they provide can be dissected in time and space, and by parameters. Working closely with Dr Michael Colman, we develop biophysically-detailed computational models of the heart (at the sub-cellular, cellular, tissue and organ levels), and use these models to examine the roles that the structural (anatomical) and functional (electrophysiological and mechanical) changes seen in heart failure have on the initiation, maintenance and termination of cardiac arrhythmias such as ventricular fibrillation. To facilitate this, we have recently developed, in collaboration with Professor Ed White and others, an experimental “pipeline” where physiological measurements, optical mapping, novel diffusion tensor magnetic resonance imaging (DT-MRI) measurements and computational simulations can all be linked to study mechanisms leading to the initiation of cardiac arrhythmias.
The ability to sustain muscular exercise is a key determinant of health, quality of life, and mortality. Poor exercise tolerance contributes to a downward spiral of inactivity, which is an “actual cause” of chronic disease, and the cardinal symptom of heart failure is a significant exercise intolerance which limits heart failure patients to a relatively sedentary lifestyle. However, the mechanisms limiting exercise tolerance remain poorly understood. Individuals capable of high rates of oxidative phosphorylation are able to tolerate sustained exercise at high levels. Achieving these high rates depends upon the effective integration of the physiological systems involved in O2 delivery and utilisation, clearance of CO2, and buffering of acid-producing reactions. However, because most conditions of physical activity are nonsteady-state, it is the integrated dynamics of these physiological systems that are most strongly related to exercise tolerance and longevity. Computational models allow us to study the intricately integrated (and therefore non-intuitive) relationships that exist between the different components of such a complex physiological system.
Working closely with Dr Harry Rossiter, Dr Carrie Ferguson and Dr Bryan Taylor, we examine how the pulmonary, circulatory and muscular systems integrate during dynamic activity across the continuum of biological function, from elite athletes to heart failure patients. Experimental data – obtained using cardiopulmonary exercise testing (CPX), near-infrared spectroscopy (NIRS), magnetic resonance spectroscopy (MRS) and other techniques – are used to develop novel computational models integrating physiological systems dynamics. The data generated by these experiments and computational models help us understand how systems dynamics conflate to produce the rapid O2 uptake (VO2) kinetics that are a major determinant of exercise tolerance, and thereby contribute to improving exercise performance, health, quality of life, and longevity.<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://biologicalsciences.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>
- BSc (Hons) Sports Science
- PhD Computational Biology
Research groups and institutes
- Sport and Exercise Sciences