Characterizing the Biomechanics of an Endovascular Intervention in Cerebral Aneurysms Using Kirchhoff-Love Shells of Nonuniform Thickness

Abstract

Rupture of intracranial aneurysms is the most common cause of spontaneous subarachnoid bleeding, related to high morbidity and mortality rates. However, intracranial aneurysms have a higher prevalence than that due to their spontaneous rupture rate, exacerbated by the risks associated with occlusion intervention, which motivates the development of technological tools to support clinical diagnosis and endovascular occlusion intervention planning. In particular, the aneurysm dome is sensitive to applied loads in the contiguous surroundings to the aneurysm neck. Indeed, this region shows high complexity due to the arterial wall nature of the pathology. This work presents preliminary statistical analysis results of a thin shell model, with varying material and geometrical parameters, under a localized load emulating the effect of a microcatheter pressing the neck area. In a selection of 34 cases, we show that dimensionality reduction techniques such as Isomap can help determine non-trivial regions of interest under concentrated loads, leading to more general machine learning classification models for sensitive area identification.