Recent studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) and expansion rate are not entirely reliable indicators of rupture potential. We hypothesize that aneurysm morphology and wall thickness can be quantified in a systematic approach leading to accurate differentiation of the geometric characteristics of aneurysm population subsets. A non-invasive, image-based evaluation of AAA shape was implemented on a retrospective study of sixty-six subjects who underwent elective repair and twenty-eight subjects who suffered AAA rupture within 1 month of their last pre-operative follow-up. The contrast-enhanced computed tomography (CT) scans of these patients were used to generate three-dimensional models from the segmented images. Twenty-eight geometry-based indices were calculated to characterize the size and shape of the AAA sac, and regional variations in wall thickness were estimated based on a novel segmentation algorithm. A multivariate analysis of variance using a maximum AAA diameter of 5.5 cm as a factor was performed for all indices as dependent variables, for the electively repaired group. Box and Whisker plots and ROC curves were generated to determine the indices’ potential as predictors of rupture risk. Listed from highest to lowest area under the ROC curve (AUC), the following six indices were found statistically significant (p < 0.05): volume (V, p < 0.0001), surface area (S, p < 0.0001), intraluminal thrombus volume (VILT, p < 0.0001), diameter-to-diameter ratio (DDr, p < 0.0001), diameter-to-height ratio (DHr, p = 0.015), and centroid distance of the maximum diameter (dc, p = 0.008). Given that individual AAAs have complex, tortuous and asymmetric shapes with local changes in surface curvature and wall thickness, the assessment of AAA rupture risk should require the accurate characterization of aneurysmal sac shape.

This content is only available via PDF.
You do not currently have access to this content.