Cardiovascular Imaging

Our research in cardiovascular imaging focuses on; coronary haemodynamics, pulmonary circulation, and cardiac form and function.

Stylised image of cardiac 4D flow segmentation


Our research in cardiovascular imaging focuses on the following main topics:

  1. Coronary haemodynamics: Image based computer modelling of coronary artery disease and blood flow, clinical decision making in coronary artery disease and imaging to guide complex percutaneous coronary interventions
  2. Pulmonary circulation: Novel image and data analysis approaches for better phenotyping and risk stratification for individuals with pulmonary vascular disease
  3. Cardiac form and function: Cardiac imaging to better stratify patients with common cardiac disorders, develop non-invasive haemodynamic models for clinical applications and predict outcomes

Coronary Haemodynamics

Our focus is on analysis of invasive coronary angiogram images to better understand the limitation of blood flow to the myocardium produced by coronary artery disease. This feeds into our computational modelling work. It allows cardiologists to target their interventional therapies to lesions that matter, and reduce hazardous and unnecessary procedures. Our group also aims to develop a better understanding of the interface between coronary flow and myocardial ischaemia using first pass myocardial perfusion on MRI.  

Pulmonary Circulation

Our research ambition is to improve the management and outcome of patients with pulmonary vascular disease. We have ongoing projects that aim to:

  1. Improve the diagnosis of pulmonary hypertension and determine disease severity
  2. Better stratify patients in diagnostic categories: pulmonary arterial hypertension, pulmonary hypertension associated with left heart disease or lung disease and patients with chronic thromboembolic disease
  3. Improve risk stratification to allow for better predictions of therapy response and 1 year mortality

Our research utilises data from the ASPIRE registry; a large DICOM imaging repository with computed tomography (CT) and cardiac magnetic resonance (CMR) imaging scans in individuals with suspected pulmonary hypertension cases (>5000 cases).  We are developing and utilising machine learning approaches within the group and in collaboration with the Department of Computer Science, and other universities e.g Leiden Medical Centre.

Stylised CT image showing the great vessels
Stylised CT image showing the great vessels

Cardiac form and function

Our vision is to develop an optimal imaging approach for patients with several cardiovascular disorders. We aim to do this by utilising state-of-the-art imaging techniques like four-dimensional flow (4D flow) CMR. Also, we develop novel image analysis approaches to better stratify patients and make better predictions of their clinical outcomes. 

Stylised image of short axis stack cardiac MRI
Stylised image of a short axis stack of cardiac MR iamges in a patient with pulmonary arterial hypertension

We have established a unique partnership with Sheffield Teaching Hospitals through a joint venture called 3D lab. The 3D lab provides a wealth of clinical imaging with encoded clinically relevant data for informing patient outcomes in the real world. The 3D lab imaging database has a large repository of CMR and cardiac CT scans. In the long run, our vision is that this resource will provide access to carry out large observational studies exploring the value of clinical imaging. The main strengths of this database are that it records all imaging based segmentation data, which can be then investigated for patient outcomes. This database is also well integrated with other clinical databases at Sheffield Teaching Hospitals. This pioneering collaboration between the University academics and the NHS is also supported by the technical expertise of the Medical Physics Department of Sheffield Teaching Hospitals.  

People, Projects & Publications

  • Pete Metherall (Clinical Scientist at STH NHS Foundation Trust)
  • Michael Sharkey (Clinical Scientist at STH NHS Foundation Trust)
Current Projects / Grants
  • 02/2021 – 02/2023. Interactively trained ‘human-in-the-loop’ deep learning approach to improve cardiac CT and MRI assessment for accurate therapy response and mortality prediction. NIHR AI in Health and Care Award. Swift, Wild, Kiely, Shahin, Alabed
  • 10/2019 – 10/2021. Wellcome Digital Innovator Award. Developing an intelligent tool to improve prognostic and treatment response assessment on cardiac MRI data with machine learning. Wellcome Digital Innovator Award. Swift, Garg, Kiely and Wild
  • 02/2018 – 02/2021. Whole heart, four dimensional flow magnetic resonance imaging for accurate assessment of right and left heart flow haemodynamics. Academy of Medical Sciences. Garg 
  • 08/2017 – 08/2022. Imaging Pulmonary Vascular Disease: Computational Modelling and large data analytics. Wellcome Trust - Clinical Research Training Fellowship. Swift
Past Projects / Grants
  • 07/2017 – 08/2018. Validation of a non-invasive magnetic resonance image based computational tool for the diagnosis of PH. MRC confidence in concept award. PI Swift. CoI’s Garg and Wild
  • 01/2016 – 01/2017. Computational imaging assessment of pulmonary haemodynamics for non-invasive diagnosis of patients with pulmonary hypertension. Sheffield Hospitals Charitable Trust.
  • 01/2015 – 08/2018. Repeatability of magnetic resonance imaging cardiopulmonary metrics in pulmonary arterial hypertension - Implications for trial design. GlaxoSmithKline. PI Swift. CoI Wild
  • 2016 Virtual coronary intervention: instant one-stop in silico treatment planning. BHF Clinical Research Training Fellowship (VIRTU-3). BHF FS/16/48/32306. £343,941. Gosling R, Gunn J
  • 2016 A prototype tool to calculate 'virtual' myocardial fractional flow reserve (vFFR) non-invasively (VIRTU-3). NIHR i4i. II-LB-0216-20006. £378,304. Gunn J, Morris P, Smith S, Wilkinson A, Lawford P, Hose R
Recent Publications

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