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

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.

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Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10888305
Citations
1
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.67

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article

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

Xudong Ru, Xingce Wang, Zeyao Zhang, Yicheng Zhu et al.
1 citations
Medical Imaging and Analysis
0.67
article

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

Xudong Ru, Xingce Wang, Zeyao Zhang, Yicheng Zhu, Jing-Yi Liu, Zhongke Wu
article en
1 citations

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.

Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Beijing Normal University (CN), Peking Union Medical College Hospital (CN)
Beijing Municipal Science and Technology Commission, Nature
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Openalex Percentile: Top 34%
Medical Imaging and Analysis
0.67
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Automatic Geometric Quantification and Rupture Risk Evaluation of 3D Intracranial Aneurysms — Xudong Ru, Xingce Wang, et al. · (2025) | TGRS Research Map | TGRS