Spatial augmented reality and simulations to improve abdominal aortic aneurysm diagnosis and monitoring

In this work we propose an approach based on IT tools to improve all the clinical activities related to Abdominal Aortic Aneurism (AAA) detection and treatment. In particular, the approach is focused on a 3D CAD model of the AAA and CFD simulations to improve diagnosis by evaluation of rupture risk indicators and Spatial Augmented Reality (SAR) to simulate endovascular repair (EVAR) of the pathology. Geometric model of the vascular wall is build from Computer Tomography (CT) data by using and customizing algorithms and tools implemented in Vascular Modeling ToolKit (VMTK) software library. Four methodologies of geometry initialization are compared and we choose those able to describe the vascular disease excluding any foreign tissue (i.e., bones, internal organs, and muscles). An evaluation of the problems connected to the relative parameters of reconstruction, their influence for the correct geometry representation, focusing the attention on segmentation level and the smoothing of the surface, are presented. In particular, we point out the effect of the smoothing by the use of the Hausdorff distance. We propose a standardized process able to guide users in the modeling of this type of vessels; moreover, SAR can dramatically improve the efficacy of AAA visualization for some different clinical aspects. The 3D geometry of the AAA can be used to carry out CFD analysis, to calculate parameters of the blood flow and evaluate the rupture risk indicator, like Oscillatory Shear Index (OSI). The availability of risk indicators facilitates the physician in the diagnosis and prognosis. Finally, we present a methodology and tools to simulate EVAR on a specific patient based on geometry reconstruction and CFD simulations; this type of procedure can effectively improve training and facilitate endovascular surgery.