Aneurysm rupture prediction based on strain energy-CFD modelling

• Main Authors: Al-Jumaily, Ahmed M., Embong, Abd Halim, AL-Rawi, Mohammad, Mahadevan, Giri, Shukei, Sugita
• Format: Article
• Language: English; English
• Published: Multidisciplinary Digital Publishing Institute 2023
• Subjects: TA164 Bioengineering
• Online Access: http://irep.iium.edu.my/107597/7/107597_Aneurysm%20rupture%20prediction%20based%20on%20strain%20energy.pdf; http://irep.iium.edu.my/107597/13/107597_Aneurysm%20rupture%20prediction%20based%20on%20strain%20energy_SCOPUS.pdf; http://irep.iium.edu.my/107597/; https://www.mdpi.com/2306-5354/10/10/1231/pdf?version=1697878895; https://doi.org/10.3390/bioengineering10101231
• Institution: Universiti Islam Antarabangsa Malaysia

This paper presents a Patient-Specific Aneurysm Model (PSAM) analyzed using Computational Fluid Dynamics (CFD). The PSAM combines the energy strain function and stress–strain relationship of the dilated vessel wall to predict the rupture of aneurysms. This predictive model is developed by analyzing ultrasound images acquired with a 6–9 MHz Doppler transducer, which provides real-time data on the arterial deformations. The patient-specific cyclic loading on the PSAM is extrapolated from the strain energy function developed using historical stress–strain relationships. Multivariant factors are proposed to locate points of arterial weakening that precede rupture. Biaxial tensile tests are used to calculate the material properties of the artery wall, enabling the observation of the time-dependent material response in wall rupture formation. In this way, correlations between the wall deformation and tissue failure mode can predict the aneurysm’s propensity to rupture. This method can be embedded within the ultrasound measures used to diagnose potential AAA ruptures.