Patient-based abdominal aortic aneurysm rupture risk prediction with fluid structure interaction modeling

Area of Science:

• Biomedical Engineering
• Cardiovascular Research
• Medical Imaging Analysis

Background:

• Abdominal aortic aneurysm (AAA) rupture risk is typically estimated using aneurysm size, a limited predictor.
• Current diagnostic methods lack patient-specific rupture risk assessment.
• Elective repair is indicated when rupture risk outweighs surgical risk.

Purpose of the Study:

• To present a novel methodology for patient-specific prediction of AAA rupture risk.
• To utilize biomechanical principles and computational modeling for improved risk assessment.
• To enhance the diagnostic and treatment strategies for AAA patients.

Main Methods:

• Reconstruction of patient-specific AAA models from CT scans.
• Conducting fluid-structure interaction (FSI) simulations.
• Mapping stress distribution within the aneurysmal wall to predict rupture location.

Main Results:

• The FSI methodology successfully predicted rupture locations in contained ruptured AAA (rAAA) cases.
• Analysis indicated that smaller rAAA cases presented a higher risk of rupture.
• The study demonstrated the capability of biomechanical modeling for rupture risk assessment.

Conclusions:

• The presented biomechanical methodology offers a reliable, patient-specific approach to AAA rupture risk prediction.
• This method provides a more refined assessment than size alone, potentially impacting clinical decision-making.
• Improved risk stratification can lead to better diagnostics and personalized treatment for AAA.