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Improving the diagnosis and treatment of peripheral artery disease using computational modelling

Project ID: 2019_S07

1st supervisor: Jordi Alastruey, King’s College London
2nd supervisor: Ronak Rajani, Guy’s and St Thomas’ NHS Foundation Trust

This project will develop a multi-scale cardiovascular modelling framework tailored to the specificities of PAD that will allow us to provide efficient and accurate diagnostic tools, as well as valuable patient-specific, help-to-decision data for the treatment of PAD. The framework will be based on an approach that has previously been used for CAD.1,2 The project objectives are:

  • Obj. 1: Development of a computational modelling framework for the study of PAD;
  • Obj. 2: In vitro validation of the computational framework;
  • Obj. 3: Clinical feasibility study.

The following tasks will be carried out to fulfil these objectives:

Task 1: Computational model development (18 months) – The framework will simulate detailed blood flow patterns in locally complex arterial geometries with stenosis, as well as global flow patterns in the systemic circulation. It will be based on our in-house tools created to assess blood flow in the aorta of hypertensive patients,3,4 and will include the following geometric scales: (i) detailed macro-vascular stenosis scale accounting for anatomically-correct arterial geometries reconstructed from computed tomography angiography (CTA) data; (ii) averaged macro-vascular scale describing pulse wave propagation in the larger systemic arteries; and (iii) micro-vascular scale in the capillary network which is responsible for the collateral perfusion observed in PAD patients and which could play an important role in guiding treatment. The model will be used to develop novel haemodynamic biomarkers for accurate PAD diagnosis and assess the optimal treatment procedure (e.g. pharmacotherapy, stenting, revascularisation).

Task 2: In vitro validation (9 months) – Our EPSRC-funded, state-of-the-art, 1:1 scale cardiovascular simulator rig (CVSR) of the heart and larger systemic arteries includes peripheral arteries of the lower limbs.5 Different types and degrees of lower-limb atherosclerotic lesions (e.g. single, sequential, diffuse) will be (i) designed based on real lesions’ geometry, (ii) manufactured using 3D printing, and (iii) inserted into the lower-limb arteries of the CVSR. This will be used to validate the simulated blood pressure and flow data, especially in scenarios with complex sequential and diffuse lesions.

Task 3: In vivo validation (9 months) – The novel biomarkers developed in Task 1 and the ability of the computational framework to predict optimal treatment procedures will be tested in existing patient cohorts (with a variety of PAD symptoms) from Dr Rajani’s clinic, for which haemodynamic measurements and CTA imaging data are available pre- and post-operatively.

The project will improve PAD diagnosis and treatment by providing clinicians with a novel tool that combines haemodynamic measurements and medical images using validated, state-of-the-art, patient-specific models of blood flow. The integration of such tools in clinical routine is anticipated to improve PAD patient morbidity and mortality.

1 Jawaid MM, et al. Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles. Comput Biol Med 1;89:84–95, 2017
2 Rajani R, et al. Non-invasive fractional flow reserve using computed tomographic angiography: where are we now and where are we going? Heart 103(15):1216–22, 2017
3 Alastruey J, et al. On the impact of modelling assumptions in multi-scale, subject-specific models of aortic haemodynamics. J Royal Soc Interface 13(119):1–17, 2016
4 Vennin S, et al. Identifying hemodynamic determinants of pulse pressure – A combined numerical and physiological approach. Hypertension 70(6):1176–82, 2017
5 Gaddum N, et al. Relative contributions from the ventricle and arterial tree to arterial pressure and its amplification: an experimental study. Am J Physiol – Heart Circul Physiol 313(3):H558–67, 2017

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