Heart failure is a complex clinical syndrome, the principal symptom of which is profound exercise intolerance (an inability to perform even day-to-day activities), the severity of which relates to disease severity. Exercise tolerance is determined partly by the dynamic balance between skeletal muscle oxygen delivery (blood flowing to working muscle) and oxygen utilisation (by mitochondria to provide energy for contractions). Although many patients have central (cardiac) issues that limit oxygen delivery to working skeletal muscle, a large proportion also have oxygen utilisation issues at the skeletal muscle (mitochondrial) level. For this latter group, improving cardiac function, e.g. using cardiac resynchronisation therapy, has little effect on their exercise tolerance, and treatments should be targeted at the skeletal muscle. However, identifying such patients is problematic, as direct measures of oxygen delivery and utilisation can only be made invasively. Near infrared spectroscopy (NIRS) can be used non-invasively to measure muscle oxygenation, but is limited by its inability to distinguish whether oxygenation issues are a consequence of oxygen delivery or utilisation problems.
In an attempt to overcome this limitation, we have developed a computational model describing skeletal muscle oxygenation during exercise, and recently integrated this with our novel mathematical descriptions of the resultant NIRS signals that would be measured experimentally during exercise testing protocols. This integrated model potentially provides us with a tool to “back calculate” the separate oxygen delivery and utilisation dynamics from measured NIRS data. However, the model needs to be optimised and validated, and its effectiveness in separating out oxygen delivery and utilisation information from non-invasive NIRS measures (i.e. oxygenation signals) assessed.
The objectives of this project are therefore: (i) Optimise and validate our novel model of muscle oxygenation and NIRS signals, using measurements made experimentally in young healthy subjects and in heart failure patients during exercise; (ii) Assess the effectiveness of the model at back-calculating separate oxygen delivery and utilisation information from non-invasive NIRS signals, therefore determining whether the model will provide a useful clinical tool.
When optimised and validated, our model of muscle oxygenation and NIRS signals, when deployed with non-invasive NIRS in a clinical setting, could guide clinicians on whether treatments should be targeted centrally or peripherally. This would result in better-targeted therapy and could avoid unnecessary procedures, therefore improving patient outcomes.
The successful applicant will have a background in either exercise physiology or computational modelling/mathematics; We can teach programming and mathematical skills to those who have an exercise physiology background, and vice versa for those with a modelling/mathematics background. For more details of our group’s research, please see: https://biologicalsciences.leeds.ac.uk/sport-exercise-sciences/doc/sport-research-themes/page/6 https://biologicalsciences.leeds.ac.uk/school-biomedical-sciences/staff/27/dr-al-benson
Benefits of being in the DiMeN DTP:
This project is part of the Discovery Medicine North Doctoral Training Partnership (DiMeN DTP), a diverse community of PhD students across the North of England researching the major health problems facing the world today. Our partner institutions (Universities of Leeds, Liverpool, Newcastle and Sheffield) are internationally recognised as centres of research excellence and can offer you access to state-of the-art facilities to deliver high impact research.
We are very proud of our student-centred ethos and committed to supporting you throughout your PhD. As part of the DTP, we offer bespoke training in key skills sought after in early career researchers, as well as opportunities to broaden your career horizons in a range of non-academic sectors.
Being funded by the MRC means you can access additional funding for research placements, international training opportunities or internships in science policy, science communication and beyond. See how our current DiMeN students have benefited from this funding here: http://www.dimen.org.uk/overview/student-profiles/flexible-supplement-awards
Further information on the programme can be found on our website: http://www.dimen.org.uk/
Davies MJ, Benson AP, Cannon DT, Marwood S, Kemp GJ, Rossiter HB & Ferguson C (2017) Dissociating external power from intramuscular exercise intensity during intermittent bilateral knee-extension in humans. Journal of Physiology 595, 6673-6686.
Benson AP, Grassi B & Rossiter HB (2013) A validated model of oxygen uptake and circulatory dynamic interactions at exercise onset in humans. Journal of Applied Physiology 115, 743-755.
Bowen TS, Rossiter HB, Benson AP, Amano T, Kondo N, Kowalchuk JM & Koga S (2013). Slowed oxygen uptake kinetics in hypoxia correlate with the transient peak and reduced spatial distribution of absolute skeletal muscle deoxygenation. Experimental Physiology 98, 1585-1596.