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Developing computer models to help doctors manage aortic dissection

Professor Stavroula Balabani (lead researcher)

University College London

Start date: 01 April 2016 (Duration 3 years)

Investigation of the haemodynamics of dissected aortas: an in vitro, in-vivo and in silico study (Ms Gala Franzetti)

Supervised by mechanical engineer Dr Stavroula Balabani, the PhD student on this project is studying aortic dissection. Aortic dissection is a life threatening condition where the wall of the main blood vessel leaving the heart, the aorta, splits and forms an additional false vessel. It is associated with high blood pressure and with less common conditions such as Marfan syndrome. It is one of the complications of a thoracic aortic aneurysm. Aortic dissection affects the flow of blood through the aorta and the circulation system, causing various complications. How the disease progresses depends on the patient and how blood flow is affected. Surgeons routinely perform imaging scans of patients to help treatment decisions in people with aortic dissection, but these scans provide limited information about blood flow. A technique used in aerospace engineering called computational fluid dynamics, could provide more information, helping doctors tailor treatments to individual patients, decide when to intervene surgically and manage the disease better. But this technique needs to be thoroughly tested to ensure it provides an accurate picture of a person’s condition. In this project, the student will develop reliable computational tools to understand aortic dissection and its progression and help doctors manage the disease. The researchers will combine measurements in the body, lab experiments and computer fluid-structure interaction studies to understand how blood flow changes in aortic dissections. The tool they develop will be used in patients to reveal how aortic dissection affects blood flow and ultimately their outlook.

Project details

Grant amount £106,363
Grant type Fellowships
Application type PhD Studentship
Start Date 01 April 2016
Duration 3 years
Reference FS/15/22/31356
Status Complete
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