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A novel pulmonary fluid dynamics tool for early diagnosis of tuberculosis

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  • Full or part time
    Dr K Vogiatzaki
    Dr S Waddell
    Prof M Cercignani
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Tuberculosis (TB) is the leading infectious cause of death worldwide, killing 1.6 million people in 2017 (WHO TB Report, 2018). Drug resistance is hampering efforts to eliminate TB in many parts of the world. TB accounts for a quarter of antimicrobial resistant (AMR) infections, a major risk to worldwide health that is projected to cost 10 million lives a year and 100 trillion USD of economic output in 30 years’ time if novel solutions are not found (O’Neill, 2016). Current TB diagnostic testing in low-middle income countries relies on sputum microscopy, which only identifies 50% of cases, or chest x-ray. These tests are often charged to the patient and require hospital facilities; therefore, individuals delay or refrain from testing. A new non-invasive diagnostic for tuberculosis that is applicable to point-of-care settings would be transformative.

Tuberculosis causes lesions (holes) to form in the upper lobes of the lungs. In this project we aim to develop a novel computer model with the capability to quantify the extent of damage caused by TB and how this relates to the exhaled air flow characteristics and the internal condition of the lung. By the term ’lung condition’ we refer to: (i) Extent of damage at airway patency (ii) Lung elasticity changes due to tissue disruption (iii) Global and localised airways resistance through caseous necrotic lung tissue. The tool envisioned will be the equivalent in terms of simplicity and cost to a spirometer. The key characteristic of our model is that we suggest that there is a correlation between TB lung damage (holes in the lung tissue) and airflow characteristics of turbulent breathing frequencies of exhaled air, in the same way that oscillations at the exit of any high flow energy system can reveal information about the unstable character of the flow in the system. The pilot interdisciplinary project proposed here builds on the applicants experience in flow modelling of porous media (Dr Vogiatzaki), lung imaging (Prof Cercignani) and M. tuberculosis pathogenesis (Dr Waddell) to predict stages of tuberculosis lung disease from exhaled airflow characteristics in a non-invasive manner.

In the first year the student will work with Dr Waddell (Brighton and Sussex Centre for Global Health Research) in order to familiarise themself with tuberculosis microbiology and pathology as well as with Professor Cercignani (Clinical Imaging Sciences Centre) to produce CAD geometries for lungs based on MRI. The second and third years will be dedicated to developing a holistic CFD model based on the experimental data of Phase 1 that will account for a realistic all scale lung representation.

The PhD studentship will provide outstanding training in numerical modelling and fluid dynamics, with potential applications for biomedical systems microbiology and image processing. The successful candidate will be based both within the CEMS and BSMS and will undertake leading-edge research using state-of-the-art facilities. They will also have the opportunity to liaise with leading companies in the field of bio-engineering in order to explore further the commercialisation of the tools developed If desired, there will be opportunities to travel to partners in sub-Saharan Africa through the Brighton and Sussex Centre for Global Health Research. The PhD student will present findings at project review meetings with the supervisors and external partners, as well as at national and international conferences and in high impact journal publications.

Funding Notes

UK/EU students only.

This is a three-year, full time position, funded by the University of Brighton starting in October 2019. The funding will cover the university fees, and a PhD stipend at the UKRI rate, £15,009 pa for 2019/20.

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