A system for saccular intracranial aneurysm analysis and virtual stent planning

Recent studies have found correlation between the risk of rupture of saccular aneurysms and their morphological characteristics, such as volume, surface area, neck length, among others. For reliably exploiting these parameters in endovascular treatment planning, it is crucial that they are accurately quantified. In this paper, we present a novel framework to assist physicians in accurately assessing saccular aneurysms and efficiently planning for endovascular intervention. The approach consists of automatically segmenting the pathological vessel, followed by the construction of its surface representation. The aneurysm is then separated from the vessel surface through a graph-cut based algorithm that is driven by local geometry as well as strong prior information. The corresponding healthy vessel is subsequently reconstructed and measurements representing the patient-specific geometric parameters of pathological vessel are computed. To better support clinical decisions on stenting and device type selection, the placement of virtual stent is eventually carried out in conformity with the shape of the diseased vessel using the patient-specific measurements. We have implemented the proposed methodology as a fully functional system, and extensively tested it with phantom and real datasets.