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Aortic disease

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Aortic disease is one of the most common forms of cardiovascular disease. Since the aorta is the main artery that supplies oxygenated blood from the heart, disorders of the aorta can be life-threatening. Pathologies of the aorta can vary from aneurysms and dissections to valvular disease. Due to the unique and complex fluid environment that these pathologies can result in, there exists a need to better understand the hemodynamics in the aorta. We use computational tools to quantify these hemodynamic changes to aid in the diagnosis and treatment of various aortic diseases. We create patient-specific models from non-invasive imaging and use these models to simulate the fluid dynamics in the aorta thereby creating a framework by which to aid clinical decision-making.

Aortic Coarctation

Aortic coarctation (CoA) is a congenital heart defect that is characterized by a constriction in the aorta, typically occurring just past the origin of the left subclavian artery. The narrowing of the aorta results in a sudden drop in blood pressure across the CoA. By the current clinical standard, a pressure drop ≥ 20 mmHg at rest across the CoA warrants corrective intervention such as reconstructive surgery or catheter-based stenting. 

The goal of this project is to develop a combination of computational and experimental tools to assist in treatment planning for CoA patients. We use 0D and 3D simulations to non-invasively identify candidates for interventional procedures by estimating pressure drops in patient-specific models. These simulations are validated against gold-standard invasive catheter measurements. 

We are simultaneously also working on an experimental approach. We are developing 3D-printed models that will be used in a flow loop setup on the bench. These models can be used to quantify patient-specific CoA hemodynamics using tools such as cardiac MRI.

Lab members involved in the project: Priya Nair

Aortic Dissection

Acute aortic dissection is a life-threatening cardiovascular disease in which the inner layers of the aortic wall abruptly delaminate and blood flows within this newly created false lumen. Acute aortic dissection is associated with a high mortality rate, and treatment strategies range from surgical and thoracic endovascular repair (TEVAR) to optimal medical therapy with blood pressure and pain control.

After patients progress to the chronic disease phase, life-long surveillance with imaging aims to detect the development of a false lumen aneurysm and other late adverse events. Biomechanical, mechanobiological, genetic, morphological, and hemodynamic factors all influence disease progression, making risk stratification of patients a challenging task.

Our research focuses on fluid-structure interaction simulations of patient-specific aortic dissections to investigate the interplay of morphology and hemodynamic features and understand the role of hemodynamics in disease progression. To benchmark and validate FSI simulations, we compared computational results with in vivo 4D-flow MRI scans and, in collaboration with the Cardiac Magnetic Resonance Group (Prof. Ennis, Stanford), in vitro phantom studies.

We also leverage our in silico approach to include morphologic and functional changes to patient specific aortic dissection models. This allows us to investigate the effects of various influencing factors, such as flap and wall mobility, entry and exit tear size, presence of fenestrations and many more on hemodynamics.

Lab members involved in the project: Kathrin Baeumler