NONINVASIVE BIOMECHANICAL CHARACTERIZATION OF THE AORTA

The aorta has many complex features including valve and vessel wall geometry, blood flow, and wall composition. Diseases such as aortic aneurysms and aortic valve lesions affect vessel function and may even lead to rupture, which can be fatal. However, current clinical diagnoses of aortopathies mainly rely on simple parameters such as diameter and growth rate. To better understand aortopathies and ultimately improve patient diagnoses and treatments, it is important to investigate disease progression as well as the effect of vessel wall composition changes and hemodynamic forces on aortic biomechanics, such as strain and wall shear stress distribution. Preclinical research using small animals allows for disease progression to be studied while controlling outside factors. The next important step is to apply the methods used in the preclinical studies to human patient data. Both preclinical and clinical studies often focus on noninvasive, patient-specific methods for further characterizing the biomechanics of the aorta using advanced techniques such as 4D flow magnetic resonance imaging, 4D ultrasound, computational fluid dynamics (CFD), and fluid structure interaction (FSI) modeling. Yet the challenge of bridging these research techniques to a clinical setting remains. Factors such as financial costs, acquisition time, and ease of analysis must be considered. Therefore, the following document highlights two specific aims to extend our knowledge about the effects of aneurysms and aortic valve lesions. We will 1) characterize the regional effects of murine abdominal aortic aneurysms on strain over time, and 2) use CFD and FSI to simulate the hemodynamic effects on the thoracic aorta using both murine and human patient imaging data. Conducting research using clinically translatable methods of biomechanical characterization that consider the complexity of the aorta on a patient-specific basis will contribute to our understanding and lead to better patient outcomes.