Body landmark detection for a fully automatic AAA stent graft planning software system

In this paper, we present an approach to automate the planning of an endovascular stent graft for abdominal aortic aneurysms (AAAs), which are treated with bifurcated prosthesis (Y-stents) when located close to the iliac bifurcation. During the intervention, the folded Y-stent graft - consisting of several parts - is inserted via the iliac region and expanded inside the patient's body. The first step of the proposed approach is to detect different body landmarks with a statistical method. In the next step, these landmarks are used to calculate two vascular centerlines, which provide multiplanar reformatting (MPR) slices that are used for an automatic segmentation of the artery walls. The segmented artery walls provide the manufacturer specific measures to choose an adequate bifurcated prosthesis. In a final step, the expansion of the stent is simulated in the patient's data. Results for 50 abdominal aortic aneurysm cases provided by computed tomography angiography (CTA) acquisitions are successfully verified by a virtual stenting expert.