研究目的
To establish foundations to understand the physics behind morphological changes prior to intracranial aneurysm rupture and provide first-principles equations for rupture risk assessment based on tissue thermodynamics.
研究成果
The study presents first-principles equations based on tissue mechanics and thermodynamics for intracranial aneurysm rupture risk assessment, which explain existing experimental and simulation results and provide insights into the physics of rupture. It advances research beyond statistical and numerical approaches by integrating angiography images with thermodynamic principles.
研究不足
The models are derived using approximations: (1) cylindrical shaped cross-sectional area for both ICA and IA, (2) uniform diameter d0 for ICA, and (3) uniform diameter d1 for IA. These approximations may introduce uncertainties in rupture risk predictions. Effects of deformed cross-sectional areas are not considered due to simplification.
1：Experimental Design and Method Selection:
The study uses thermodynamic principles and thin-walled cylinder models to derive equations for assessing intracranial aneurysm rupture risk. Theoretical models from established literature on circular cylinders and pressure vessels are applied.
2：Sample Selection and Data Sources:
Validation is performed using available experimental and numerical simulation data from literature, including studies by Zheng et al. (2016), Hussein et al. (2017), Dhar et al. (2008), Berg and Beuing (2018), and Skodvin et al. (2017), which involve patient data and computational fluid dynamics simulations.
3：List of Experimental Equipment and Materials:
No specific equipment or materials are mentioned in the paper; the focus is on theoretical modeling and data analysis from existing sources.
4：Experimental Procedures and Operational Workflow:
The methodology involves deriving equations (Eqs. 1-6) based on thin-walled cylinder models and thermodynamics, then comparing these with morphological parameters from angiography images and existing data to validate the models.
5：Data Analysis Methods:
Statistical comparisons and correlations with experimental and simulation results are used to validate the derived equations, focusing on morphological parameters such as size ratios and inclination angles.
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