Biomechanics and Hemodynamics of Human Aorta with Remodeling after Endovascular Repair
- Institution
- CALIFORNIA STATE UNIVERSITY LONG BEACH, CA
- Principal investigator
- Ga-Young Kelly Suh
- Funding
- $188K
- Duration
- 2024–2028
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Abstract
PROJECT SUMMARY Type-B aortic dissection is a disease with a tear of the intimal layers of the aorta distal to the aortic arch and separation of the wall layers in the thoracic aorta, which may extend further. It is rare but life-threatening when left untreated since the weakened aortic wall could rupture resulting in internal bleeding, and the false lumen may disrupt the normal blood supply to the kidneys, intestines, and spinal cords. As a less-invasive surgical treatment, thoracic endovascular aortic repair (TEVAR) covers the dissected aorta with an endograft by inserting it through a distal vessel and deploying at the dissected region to seal the tear. Major concerns persist with the long-term TEVAR outcomes when multiple endografts and stents are implanted to treat extensive dissection. Two or more endografts are needed to cover extensive dissection since there is no standalone endograft which can cover the entire region. Extensive use of endografts can impact the biomechanics and hemodynamics of the aorta which requires careful pre- and post-TEVAR planning. After TEVAR, the aorta undergoes remodeling over time. Regular monitoring with computed tomography (CT) is necessary to keep track of aortic remodeling. The common radiographic features including aortic diameter and luminal volume are insufficient to predict long-term aortic remodeling. This investigation addresses the unmet need to assess the long-term impact of multiple endografts on the aorta. To this end, we will identify the key features to quantify aortic remodeling during the 1-year follow-up period. This investigation aims to characterize the long-term impact of extensive TEVAR on the aorta by identifying underlying biomechanical and hemodynamic features due to this condition. This will be achieved by identifying biomechanical features to characterize aortic remodeling triggered by extensive TEVAR (Specific Aim 1) and evaluating the impact of blood flow on aortic remodeling during the long-term follow-up (Specific Aim 2). To achieve these aims, we will utilize patient-specific CT at pre-, post-TEVAR, and 1-year follow-up, computational modeling, computational fluid dynamics, and feature correlation. Outcomes of this investigation will provide powerful features representing the adaptation of the aorta to extensive TEVAR and help guide optimal surgery to promote favorable aortic remodeling. Our techniques of feature identification using patient-specific CTs and computational analysis will be valuable in refining patient selection criteria for extensive TEVAR, helping strategic decisions for surgery, and planning for post-surgical surveillance.
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