Understanding heart damage caused by turbulent blood

Until recently, blood flow in large arteries was thought to be laminar, meaning it flows steadily and smoothly in parallel with the blood vessel. Recent research shows that this is not necessarily the case, and that blood flow can become turbulent. Turbulent blood flow is characterised by chaotic and random fluctuations in flow, and this is worsened in certain cardiovascular diseases. It can cause damage within the cardiovascular system, but its role in damaging the heart and arteries is not fully understood.

Emily Manchester from the Department for Mechanical, Aerospace and Civil Engineering at Manchester is using Computational Fluid Dynamics (CFD) to better understand the damaging effects of turbulent blood flow, drawing on expertise from cardiovascular sciences experts in the Faculty of Biology, Medicine and Health, among others. Here, she talks about her research.

Developing new computational methods

My research is focused on producing accurate computational methods with the long-term goal of correlating turbulence with heart and artery disease progression. This will allow us to understand how turbulent blood flow affects disease in individual patients and ultimately seek improvements in treatments for these patients.

I have developed a CFD workflow which simulates blood flow in arteries. No two arteries are alike; therefore, this workflow is tailored to each patient, meaning we can model an individual's unique blood flow behaviours.

To do this, I use different types of magnetic resonance imaging (MRI) data to make a model of the shape of a patients' artery (called arterial geometries) and to gather important information about the blood flow velocity (how their blood flows through their blood vessels). This ensures that the model accurately represents each individual patient and their unique haemodynamics.

Using this method, I have studied patients with aortic valve disease and patients who have had surgery to fix their aortic valves, so that I can:

• better understand turbulence production;
• measure the effects of turbulence on artery walls (which is important for arterial wall diseases);
• measure the additional burden on the heart caused by turbulence.

I have been awarded a National Fellowship in Fluid Dynamics (NFFDy) for a project titled Informing 4D flow MRI haemodynamic outputs with data science, mathematical models and scale-resolving computational fluid dynamics.

 

Improving scanning accuracy

Over the next three years, I plan to use data science and the CFD methods described above to improve the accuracy of 4D flow MRI, directly. 4D flow MRI takes into account a 3D model, but looks at this over time (4D).

It can currently measure blood flow velocities, but turbulence predictions are of poor quality and unreliable. If we can improve turbulence predictions calculated directly from 4D flow MRI, then this would reduce the need for costly CFD simulations.

Multidisciplinary collaborations

My research will be developed via collaboration with experts and state-of-the-art facilities found within the Department for Mechanical, Aerospace and Civil Engineering and the Division of Cardiovascular Sciences at Manchester.

The multidisciplinary project will draw expertise from researchers, clinicians and life scientists in the UK, as well as make use of MRI facilities at the BHF Manchester Centre for Heart & Lung Magnetic Resonance Research, enabling new scan acquisitions.

 

Future aims

My aim is to:

• advance data-driven fluid dynamics techniques and MR imaging methods;
• improve model accuracy;
• enable larger-scale studies to be carried out.

In the longer-term, I hope my research will impact on clinical healthcare by enabling development of new diagnostic and treatment tools for aortic disease, and ultimately improve patient outcomes and quality of life.