Local aortic aneurysm wall expansion measured with automated image analysis

Area of Science:

• Medical Imaging
• Biomechanical Engineering
• Cardiovascular Research

Background:

• Regional aortic wall deformation (RAWD) may offer superior prediction of abdominal aortic aneurysm (AAA) rupture compared to maximal diameter or growth rate.
• Current assessment methods for AAA rupture risk can be improved with more precise deformation analysis.

Purpose of the Study:

• To develop and validate a streamlined, semiautomated method for computing RAWD using deformable image registration (dirRAWD) from sequential CTAs.
• To assess the accuracy of the dirRAWD technique by comparing it to manual measurements and landmark displacements.

Main Methods:

• Sequential CTAs from 15 AAA patients were analyzed.
• A semiautomated method combining manual segmentation and deformable image registration was used to calculate RAWD.
• Accuracy was validated by comparing dirRAWD with displacements of fiducial markers and manual RAWD measurements.

Main Results:

• The dirRAWD technique was successful in all patients with a mean landmark displacement error of 0.59 ± 0.93 mm.
• The absolute difference between manual maximal RAWD and dirRAWD was 0.27 ± 0.23 mm (7.9% relative difference).
• Semiautomated segmentation yielded comparable maximal dirRAWD accuracy to manual segmentation.

Conclusions:

• Accurate and automated RAWD measurements are feasible with clinically insignificant errors.
• Semiautomated segmentation does not compromise dirRAWD accuracy compared to manual segmentation.
• Future research will explore dirRAWD's correlation with finite element analysis-derived wall stress and its potential as an independent rupture risk predictor.