In this webinar, we will discuss:
<h2>The risks of thoracic aortic aneurysms</h2><p>A thoracic aortic aneurysm (TAA) is a life-threatening health condition that can cause death if the aortic wall ruptures. TAA can be treated by the placement of a thoracic stent graft with the minimally invasive thoracic endovascular aortic repair (TEVAR) procedure. The primary function of the stent graft is to exclude the aneurysm so that the diseased aortic wall is protected from physiologic blood pressures thus preventing aneurysm growth and potential rupture. Aneurysm exclusion is achieved by having the stent graft form a “seal” above and below the aneurysm. Therefore, for successful TEVAR outcomes, preventing leakage (through lack of “seal”) around the stent graft is essential to stopping aneurysm growth and preventing rupture.</p><h2>CFD delivers essential insights on blood flow for stents</h2><p>Determining the leakage flow around the stent into the aneurysm is a direct and effective way to evaluate the hemodynamic performance of a deployed stent graft. Clinically, the measurement of these leakage flows is challenging, but computationally it is not. This highlights one of the most powerful aspects of simulation—the ability to quantify characteristics of interest in situations where it would be very difficult to do so in vivo, or even in bench tests. In the case of the stent flow, CFD (computational fluid dynamics) simulation can provide the essential insights.</p><h2>Know the result before placing a stent</h2><p>Thornton Tomasetti, a US-based scientific and engineering consulting firm, has created two CFD models to demonstrate how a stent graft can allow blood leakage to the aneurysm and how a well-deployed stent graft can seal the leakage. The fluid domains for these CFD models were extracted from previously completed finite element analyses (FEA) which virtually deployed stent grafts into virtual patient anatomies which are representatives of the diseased patient population.</p><h2>Developing physics-informed AI/ML models for rapid assessment of stent effectiveness</h2><p>Learning from these CFD and FEA simulations, Thornton Tomasetti have created a workflow to adopt artificial intelligence and machine learning (AI/ML) to assess the factors responsible for safe and effective TAA treatment using the TEVAR procedure. By using this computational-model-based workflow, it is possible to quantitatively determine if a particular stent graft deployment will provide a successful seal simply by assessing parameters based on the TAA anatomy, the stent graft geometry, and the deployment process for a large cohort of virtual patients. </p>
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