Characterizing changes in abdominal aortic aneurysms using principal wall strain ultrasound elastography.

Abstract

Introduction: Aortic principal wall strain is a biomechanical parameter correlated with aneurysm growth rate that affects abdominal aortic aneurysm (AAA) stability. Characterize changes in pressure-normalized maximum mean aortic principal wall strain $\left(\overline{{\epsilon }_{\rho +}}/\mathrm{PP}\right)$ using ultrasound elastography (USE).

Methods: Axial ultrasound images of patient AAAs were collected at two consecutive clinic visits. The $\overline{{\epsilon }_{\rho +}}/\mathrm{PP}$ for each image was calculated using a novel finite element mesh technique. The cohort was separated by index $\overline{{\epsilon }_{\rho +}}/\mathrm{PP}$ terciles, and the rate of strain change, growth, intervention, and rupture were compared.

Results: 31 patients with a median age of 72.0 [65.0, 77.5] at index visits were included, with follow-up imaging taken at an average interval of 6.2 [6.0, 8.3] months. For the whole cohort, maximum $\overline{{\epsilon }_{\rho +}}/\mathrm{PP}$ decreased from 2.1 [1.1, 2.7] %/mmHg to 1.9 [1.3, 2.6] %/mmHg (p = 0.08), and maximum AAA diameter increased from a median of 4.3 [4.0, 4.7] cm to 4.4 [4.1, 4.9] cm (p = 0.04). The "high-strain" tercile was associated with a strain reduction of -1.3 [-2.5, -1.1] %/mmHg between index and follow-up imaging, as compared to the "low-strain" (-0.1 [-0.6, 0.5] %/mmHg, p < 0.01) and "intermediate-strain" (-0.4 [-0.5, -0.3] %/mmHg, p = 0.04) terciles. There was no difference in the rate of AAA growth, intervention, or rupture between terciles.

Discussion: The present findings indicate that $\overline{{\epsilon }_{\rho +}}/\mathrm{PP}$ at baseline predicts the degree and direction of $\overline{{\epsilon }_{\rho +}}/\mathrm{PP}$ change in AAAs over time. These findings offer insight into the natural history of AAA tissue mechanics and demonstrate the potential for a novel ultrasound technique to quantify biomechanical changes in the aortic wall. These findings may aid in the development of patient-specific risk stratification tools informed by biomechanical data in addition to conventional size-based criteria.