Automatic Geometric Quantification and Rupture Risk Evaluation of 3D Intracranial Aneurysms

Xudong Ru, Zeyao Zhang, Xingce Wang, Jing-Yi Liu, Yi-Cheng Zhu, Zhongke Wu

Abstract: Intracranial aneurysms (IAs) pose a significant risk due to their potential to rupture, leading to severe clinical outcomes. Accurate quantification of aneurysm morphology and assessment of rupture risk are crucial for timely intervention and treatment. In this study, we present an approach for the geometric quantification of IAs and clinical rupture risk evaluation based on the relationship between these measurements. Our approach includes a comprehensive set of geometric characteristics, such as height, width, neck width, arterial diameter, area, and volume. We applied these measurements to the public IntrA dataset, and to our knowledge, this is the first geometric analysis conducted on this dataset. By integrating these morphological characteristics with expert assessments, we developed a predictive model for IA rupture risk. Our findings reveal a strong correlation between aneurysm depth and rupture risk, with even stronger associations observed for higher-order dimension metrics like surface area and volume. This highlights the critical role of 3D automatic quantification in evaluating rupture risk. This research provides a foundation for further geometric analysis of IAs and offers potential advancements in automated diagnostics and precision medicine.