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  MRC DiMeN Doctoral Training Partnership: THROMB-AI: Computational risk stratification of thrombus formation and lysis in post-stroke patients


   MRC DiMeN Doctoral Training Partnership

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  Dr Wahbi El-Bouri, Prof GYH Lip, Dr Ying Gue, Prof Diana Gorog, Dr Andrew Narracott  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Cardiovascular disease is the leading cause of mortality and morbidity in developed countries. Often, the main pathological process responsible is the development of an arterial thrombus (or blood clot). The resultant blockage of arteries leads to drops in blood flow and eventual tissue death, such as in ischaemic stroke. There is a natural balance in the blood between agents that stimulate thrombus formation, and agents that break down clots (also known as thrombolysis). In disease, this balance can be disrupted leading to thrombus formation. As such, the usual treatment for such conditions is the use of anti-thrombotics to reduce the propensity for further thrombus formation. However, with an increasingly complex, multi-morbid and ageing population, balancing thrombotic and bleeding risks becomes more difficult. Therefore, being able to personalise risk and tailor treatment will aid clinicians in making right decisions and improving patient outcomes.

The Global Thrombosis Test (GTT) is a point-of-care test that measures a patient’s blood clotting capability and thrombolytic activity1,2. This project will use the GTT outputs of time-to-occlusion and time-to-lysis, along with patient data and mathematical models to predict patients at risk of arterial thrombotic events and their relative risk of anti-thrombotic use.

The objectives of the PhD will be split into 3 work packages:

WP1: Data collection - Sequential GTT in a post-stroke cohort

As part of an ongoing study at the University of Liverpool, the PhD candidate will analyse bloods taken from post-stroke patients using the GTT, obtaining personalised curves of time-to-occlusion and time-to-lysis for each patient. Patients will be followed up after 3 months for a second blood draw. Clinical outcomes assessing adverse cardiovascular events will be collected at 12 months.

WP2: Mathematical modelling - Personalised in silico model of thrombus formation and lysis

Using the data gathered, the candidate will build upon prior mathematical models of thrombus formation that are dependent on shear strain rate3. The parameters used to model thrombus formation and lysis will be fitted to patient data collected in WP1 – effectively developing personalised models of thrombus formation, lysis, and the impact of anti-thrombotics on an individual. These models will be used, in combination with blood flow models, to determine whether certain patients are at risk of heart attack and stroke in specific arterial regions (e.g. coronary arteries).

WP3: Machine learning - Clinical risk prediction

This WP will combine outcomes from WP1 and WP2 to predict clinical outcomes such as death and ischaemic events. The risk prediction model will be built using machine learning methods e.g. random forests and support vector machines. We will compare if the addition of GTT times and information from the personalised in silico models significantly improves risk prediction beyond that possible with standard clinical parameters4,5.

The work to be undertaken will be conducted at the Liverpool Centre for Cardiovascular Science as a collaboration between biomedical engineers (Dr El-Bouri, Dr Narracott) and clinical experts in cardiovascular disease and thrombosis (Prof Lip, Dr Gue, Prof Gorog). Training will be provided in using the GTT and in machine learning/mathematical modelling.

Please direct any enquiries about this project to Dr Wahbi El-Bouri: [Email Address Removed]

 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, York 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 and how to apply can be found on our website:

http://www.dimen.org.uk/how-to-apply/application-overview


Biological Sciences (4) Computer Science (8) Engineering (12) Mathematics (25) Medicine (26)

Funding Notes

Studentships are fully funded by the Medical Research Council (MRC) for 4yrs. Funding will cover UK tuition fees, stipend and project costs as standard. We also aim to support the most outstanding applicants from outside the UK and are able to offer a limited number of bursaries that will enable full studentships to be awarded to international applicants. These full studentships will be awarded to exceptional candidates only, due to the competitive nature of this scheme. Please read additional guidance here: http://www.dimen.org.uk/how-to-apply/eligibility-funding
Studentships commence: 1st October 2022
Good luck!

References

1. Yamamoto, J. et al. Görög Thrombosis Test: a global in-vitro test of platelet function and thrombolysis. Blood Coagul. fibrinolysis an Int. J. Haemost. Thromb. 14, 31–39 (2003).
2. Otsui, K. et al. Global Thrombosis Test – a possible monitoring system for the effects and safety of dabigatran. Thromb. J. 13, 39 (2015).
3. Mehrabadi, M., Casa, L. D. C., Aidun, C. K. & Ku, D. N. A Predictive Model of High Shear Thrombus Growth. Ann. Biomed. Eng. 44, 2339–2350 (2016).
4. Sharma, S. et al. Impaired thrombolysis: a novel cardiovascular risk factor in end-stage renal disease. Eur. Heart J. 34, 354–363 (2013).
5. Taomoto, K. et al. Platelet function and spontaneous thrombolytic activity of patients with cerebral infarction assessed by the global thrombosis test. Pathophysiol. Haemost. Thromb. 37, 43–48 (2010).

Where will I study?

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