SUBJECT: M.S. Thesis Presentation
BY: Marc-Philipp Schmid
TIME: Wednesday, April 10, 2024, 10:00 a.m.
PLACE: TEP, 387 Technology Circle NW, Atlanta, GA 30313, 216
TITLE: Growth Prediction of Type B Aortic Dissections using Wall-Stress-Driven Finite Element Simulation based on the Unified Fiber Distribution Model
COMMITTEE: Dr. Rudolph Gleason, Chair (ME)
Dr. Hai Dong (Emory University)
Prof. Dr.-Ing. Oliver Sawodny (University of Stuttgart)
Prof. Dr.-Ing. Cristina TarĂ­n (University of Stuttgart)


All arteries that supply the organs with oxygen-rich blood and transport blood to the periphery originate from the aorta, the largest blood vessel in the human body. Due to its elastic properties, the aorta acts like a buffer storing blood between the heartbeats and thus contributes to a continuous blood flow and blood pressure that does not drop to zero. It is, therefore, clear that a disease affecting the aorta can be life-threatening. Type B aortic dissections, as one of such diseases, occur if the inner wall layer of the aorta, the intima, tears in the descending aorta. This allows blood to penetrate the aortic wall and detach the intima from the remaining layers. Type B aortic dissections are associated with dangerous complications like malperfusion and enlargement of the aortic diameter, which can vary in severity depending on the patient's state of health (high blood pressure, previous cardiac diseases, smoking, etc.). In a worst-case scenario, the enlargement of the aorta can lead to its rupture. A meaningful growth prediction is, therefore, of great interest in order to help decide on appropriate treatment. In this work, the approach of wall-stress-driven aortic growth is investigated. For this purpose, the Unified Fiber Distribution model combined with a linear growth evolution law, which connects wall stresses and growth rates via patient-specific growth parameters, is used in finite element simulations. The growth parameters are determined via an optimization procedure for one patient, and a growth prediction is performed and analysed.