A biomechanics-based rupture potential index for abdominal aortic aneurysm risk assessment: demonstrative application

Abstract

Abdominal aortic aneurysms (AAAs) can typically remain stable until the strength of the aortic wall is unable to withstand the forces acting on it as a result of the luminal blood pressure, resulting in AAA rupture. The clinical treatment of AAA patients presents a dilemma for the surgeon: surgery should only be recommended when the risk of rupture of the AAA outweighs the risks associated with the interventional procedure. Since AAA rupture occurs when the stress acting on the wall exceeds its strength, the assessment of AAA rupture should include estimates of both wall stress and wall strength distributions. The present work details a method for noninvasively assessing the rupture potential of AAAs using patient-specific estimations the rupture potential index (RPI) of the AAA, calculated as the ratio of locally acting wall stress to strength. The RPI was calculated for thirteen AAAs, which were broken up into ruptured (n = 8 and nonruptured (n = 5) groups. Differences in peak wall stress, minimum strength and maximum RPI were compared across groups. There were no statistical differences in the maximum transverse diameters (6.8 +/- 0.3 cm vs. 6.1 +/- 0.5 cm, p = 0.26) or peak wall stress (46.0 +/- 4.3 vs. 49.9 +/- 4.0 N/cm(2), p = 0.62) between groups. There was a significant decrease in minimum wall strength for ruptured AAA (81.2 +/- 3.9 and 108.3 +/- 10.2 N/cm(2), p = 0.045). While the differences in RPI values (ruptured = 0.48 +/- 0.05 vs. nonruptured = 0.36 +/- 0.03, respectively; p = 0.10) did not reach statistical significance, the p-value for the peak RPI comparison was lower than that for both the maximum diameter (p = 0.26) and peak wall stress (p = 0.62) comparisons. This result suggests that the peak RPI may be better able to identify those AAAs at high risk of rupture than maximum diameter or peak wall stress alone. The clinical relevance of this method for rupture assessment has yet to be validated, however, its success could aid clinicians in decision making and AAA patient management.