Hemodynamics of thrombus formation in intracranial aneurysms: an in-silico observational study

Abstract

How prevalent is spontaneous thrombosis (ST) in intracranial aneurysms (IAs) for an all-size pop- ulation? How can we calibrate computational models of thrombosis based on published data from size-specific aneurysms cohorts? How does ST differ in normo- and hypertensive subjects? We ad- dress the first question by a thorough analysis of published that provide ST rates across different patient demographics and aneurysm characteristics. This analysis provides data for a subgroup of the gen- eral population, viz. large and giant aneurysms (>10 mm). Based on these observed ST rates, our novel computational modelling platform enables the first in-silico observational study of ST prevalence across a broader set of IA phenotypes. We generate 109 virtual patients and use a novel approach to calibrate two trigger thresholds: residence time (RT) and shear rate (SR), thus addressing the second question. We then address the third question by utilising this calibrated thrombosis model to provide new insights on the effects of hypertension on ST. We demonstrate how a mechanistic ST model calibrated on a reduced IA cohort can help esti- mate ST prevalence in a broader IA population. This study was enabled through a comprehensive and fully automatic multi-scale modeling pipeline. We use an emerging property, viz. ST, as an indirect population-level validation of a complex computational modeling framework. Furthermore, our frame- work allows exploration of the influence of hypertension in ST. This lays the foundation for in-silico clinical trials of cerebrovascular devices in high-risk populations, e.g. assessing the performance of flow diverters in cerebral aneurysms for hypertensive patients.