A scaling aneurysm model-based approach to assessing the role of flow pattern and energy loss in aneurysm rupture prediction

Yunling Long, Jingru Zhong, Hongyu Yu, Huagang Yan, Zhizheng Zhuo, Qianqian Meng, Xinjian Yang, Haiyun Li

Energy loss (EL) was regarded to be one of the key parameters in predicting the rupture risk of IA. In this paper, we took varied aspect ratio (AR) as a scaling law to create a series of longitudinal models to investigate the longitudinal changes of flow pattern and EL as the AR varies, in order to explore the relationship between the longitudinal characteristic EL parameters with aneurysm rupture risk. Seven original intracranial aneurysms (IA) models with similar locations were reconstructed from patient 3D rotational angiography (3DRA) images. Based on these models, a series of scaling aneurysm models with different ARs were created with our proposed scaling algorithms. Fluid-solid interaction (FSI) simulations were performed on every model to obtain hemodynamics flow pattern and EL. With AR increasing, flow pattern became more complex, with vortices appearing gradually in the aneurysms (AR > 1.5). Furthermore, the velocity significantly decreased in aneurysms with high ARs (>1.5). Meanwhile, the aneurysm EL increased with increasing AR. Once AR exceeded 1.5, EL changed drastically. EL was a potential parameter predicting future rupture of unruptured aneurysms. If the EL during the growth of the unruptured aneurysms increased sharply, we strongly recommend an intervention.