Utilizing Computational Modeling to Detect, Predict, and Prevent Aortic Ruptures
Up to 80% of patients with a ruptured abdominal aortic aneurysm (AAA) may not survive without early intervention, which can prevent rupture, improve outcomes, and ultimately save lives. Researchers from the Indian Institute of Technology (BHU) Varanasi and Indian Institute of Technology Kanpur have developed a computational model of the cardiovascular system to predict early AAA rupture and monitor patients’ blood vessel conditions.
By investigating the effect of realistic, patient-specific AAA shapes on the hemodynamics of pulsatile Newtonian fluids in an aortofemoral artery under normal and diseased conditions, the researchers were able to predict the risk of AAA rupture by combining imaging studies and clinical factors.
Treatment options such as surgical repair or endovascular stent grafting are available to prevent rupture if an AAA is detected early.
The researchers used image-based computational blood dynamics to mimic specific health conditions and investigate various hemodynamic parameters. Their findings suggest that aneurysm size alters the blood flow velocity distribution and that flow separation occurs during systolic deceleration, which may affect blood circulation of lower extremities.
In the future, such computational work may help in the development of digital twins of the cardiovascular system, which can receive real-time updates on a variety of data variables and help doctors forecast disease and choose the best course of therapy. Continue reading in Physics of Fluids (link).