Quantitative Assessment of Abdominal Aortic Aneurysm Geometry

Abstract

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 are more predictive of rupture risk and can be the deciding factors in the clinical management of the disease. A non-invasive, imagebased evaluation of AAA shape was implemented on a retrospective study of 10 ruptured and 66 unruptured aneurysms. Three-dimensional models were generated from segmented, contrastenhanced computed tomography images. Geometric indices and regional variations in wall thickness were estimated based on novel segmentation algorithms. A model was created using a J48 decision tree algorithm and its performance was assessed using ten-fold cross validation. Feature selection was performed using the χ 2 -test. The model correctly classified 65 datasets and had an average prediction accuracy of 86.6% (κ = 0.37). The highest ranked features were sac length, sac height, volume, surface area, maximum diameter, bulge height, and intra-luminal thrombus volume. Given that individual AAAs have complex shapes with local changes in surface curvature and wall thickness, the assessment of AAA rupture risk should be based on the accurate quantification of aneurysmal sac shape and size.

Computational Growth and Remodeling of Abdominal Aortic Aneurysms Constrained by the Spine

“…Consistently, in hypothetical aneurysm models [56] found that the inflection regions are subject to the highest stress. Thus, the AAA shape, size, and wall thickness distribution altogether contribute to the complex wall stress distribution which is markedly evolving as the AAA enlarges [4]. We submit that morphological features alone may not be sufficient to determine the rupture potential.…”

“…7). Those geometrical features are suggested as diagnostic tools in the assessment of AAAs rupture potential [4,36]. Furthermore, Figs.…”

“…For decades, physicians have conducted a great deal of biomedical engineering research striving to understand why some small AAAs rupture, yet some large AAAs do not [1,2]. Growing evidence provides provisions that have a powerful systematic integration of data-driven specific markers [3,4] and biomechanics [5][6][7] for a more reliable criterion to determine the rupture risk.…”

A Methodology for the Derivation of Unloaded Abdominal Aortic Aneurysm Geometry With Experimental Validation

“…A semi-automatic methodology was followed to segment and create the masks for the three domains (i.e., lumen, intra luminal thrombus (ILT), and AAA wall). The lumen was automatically segmented using an intensitybased threshold technique that differentiates blood from the surrounding tissues in the CT image [31][32][33]. The ILT was manually segmented, while a uniform AAA wall was developed by dilation of the lumen-ILT boundary by two pixels after performing a combination of Boolean operations on the masks.…”

Biomechanical Approach to Improve the Abdominal Aortic Aneurysm (AAA) Rupture Risk Prediction

“…Initial studies have used uniform wall thickness in their attempt to characterize aneurysm shape. Although wall thickness was not one of the highest ranked features chosen with the feature selection algorithm based on the   test, its effect on aneurysm rupture cannot be ignore [45]. Typical values of wall thickness (t) in aneurysmatic arteries are ranged from 0.5 to 1.5 mm [46].…”