A novel approach for local abdominal aortic aneurysm growth quantification

Area of Science:

• Biomedical engineering
• Medical imaging
• Computational modeling

Background:

• Abdominal aortic aneurysms (AAAs) pose rupture risks, even when smaller than 5 cm.
• Current rupture risk assessment relies heavily on maximum diameter, which may not fully capture localized wall stress.
• AAA expansion rate >10 mm/year is a surgical indication, but non-uniform growth complicates this metric.

Purpose of the Study:

• To introduce and validate a novel method for estimating AAA surface area growth.
• To provide a more accurate measure of local wall deformation compared to maximum diameter changes.
• To assess the correlation between maximum diameter growth and surface area growth in patient-specific AAA models.

Main Methods:

• Development of a method based on the non-rigid iterative closest point algorithm for surface area growth estimation.
• Optimization and validation using 12 patient-specific AAA geometries with known nodal displacements.
• Application to ten patient-specific AAA follow-ups to analyze growth patterns.

Main Results:

• The proposed method quantifies AAA surface area growth, reflecting local wall deformation.
• Maximum diameter growth showed a moderate correlation with maximum surface growth (R² = 0.614).
• Maximum surface growth was not consistently located with maximum diameter or uniformly distributed across the aneurysm.

Conclusions:

• Surface growth quantification offers a superior measure of AAA remodeling activity compared to maximum diameter changes.
• This approach can potentially enhance the accuracy and effectiveness of AAA surveillance programs.
• Further investigation into surface growth patterns may refine risk stratification for AAA rupture.