Mimics Based Image Reconstruction Augments Diagnosis and Management of Vascular Pathologies : A Study of Ruptured Abdominal Aortic Aneurisms

Societal Relevance: Cardiovascular pathology is the leading cause of death and disability in the Western World. Rupture of abdominal aortic aneurysm (AAA), having a mortality rate of 50-75%, ranks as the 13th leading cause of death in the US. The ability to reliably predict the risk of rupture of AAA on a patient-specific basis could vastly improve the clinical management of these patients. The anatomic conditions that predispose to aneurismal dilation of the aorta are present to varying degrees in the majority of the Western population over age 50. Current diagnostic tests (CT / MR angiography and duplex ultrasound) can identify the existence of aneurysm pathology with a high degree of sensitivity, but are not specific enough to identify patients at high risk for disease progression and rupture. With the advances in computer graphics techniques for surface rendering, the potential for extracting valuable information from these modalities has emerged. Combining these modalities with advanced numerical simulations additionally facilitates the quantification of significant clinical parameters that offer enhanced diagnosis of the patient’s condition, and can be used to arrive to a better informed decision regarding the need for a surgical intervention. Innovation: High risk aneurysms that are candidates for surgical intervention are those with aneurismal diameter larger than 5.5cm. This size-based-criterion fails to differentiate between small diameter aneurysms with high risk of rupture and large diameter aneurysms that may be stable. To provide a way of quantifying the risk of rupture of AAAs, we introduced a methodological approach for developing a patient specific diagnostic tool of abdominal aortic aneurismal disease integrating elaborate medical imaging with advanced numerical modeling. The proposed methodology incorporates advanced constitutive material models of the various components of AAA in fluid structure interaction (FSI) simulations, including effects of anisotropy (structural strength based on collagen fibers orientation within the arterial wall), AAA intraluminal thrombus (ILT), and embedded calcifications. We incorporate in the methodology relevant clinical parameters obtained during prospective studies into patient-specific reconstructed models, including flow velocities measured by Doppler ultrasound and non-uniform wall thickness detection. In a ground breaking study of ruptured abdominal aortic aneurysms (AAAs), with the use of Mimics, a state-of-the-art image reconstruction tool, we simulate the interaction of blood with the anisotropic vessel wall, including important structures of the AAA pathology such as the intraluminal thrombus (ILT) and calcified spots. Economical potential: The developed methodology will lead to characterization of AAA geometric features, including: shape, length to traverse dimensions ratios, neck and iliac arteries angulation, tortuosity, wall thickness and strength, calcifications. The developed models are capable of predicting the rupture potential of AAAs based on wall stress mapping, incorporating wall strength estimations based on biomechanical and clinical parameters. The potential of such a non-invasive diagnostic tool, starting with Mimics in image reconstruction, certainly will be indispensable for physicians and scientists in quantifying the risk of rupture in AAAs. Such diagnostic capabilities are essential for improved clinical outcomes of procedures in which intervention is directed at those lesions most likely to become symptomatic. This methodology will be readily applicable for analyzing and diagnosing other cardiovascular pathologies, such as vulnerable plaques in carotid and coronary arteries. By refining the indications for elective surgery and eliminating unnecessary or low benefit surgery, the clinical endpoint will improve surgical outcomes, reduced mortality rates, and considerable savings in healthcare costs.