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Background Endovascular aortic repair is the common approach for abdominal aortic aneurysms, but endoleaks remain a significant problem with long-term success. Endoanchors have been found to reduce the incidence of type 1A endoleaks and can treat intraoperative type 1a endoleaks. However, little is known about the optimal number and position of endoanchors to achieve the best outcome. Methods Using image segmentation and a computational model derived from a reconstructed native patient abdominal aortic aneurysm geometry, the stability of the proximal seal zone was examined through finite element analysis in Abaqus (Dassault Systèmes, Providence, RI). The biomechanical parameter of contact area was compared for varying numbers (0, 2, 4, 8) and positions (proximal, medial, distal) of endoanchors under different adhesion strengths and physiologic pressure conditions. Results In every simulation, an increase in adhesion strength is associated with maintenance of proximal seal. For biologically plausible adhesion strengths, under conditions of normal blood pressure (120 mm Hg), the addition of any number of endoanchors increases the stability of the endograft-wall interface at the proximal seal zone by approximately 10% compared with no endoanchors. At hypertensive pressures (200 mm Hg), endoanchors increase the stability of the interface by 20% to 60% compared with no endoanchors. The positioning of endoanchors within the proximal seal zone has a greater effect at hypertensive pressures, with proximal positioning increasing stability by 15% compared with medial and distal positioning and 30% compared with no endoanchors. Conclusions Endoanchors improve fixation within the proximal seal zone particularly under conditions of high peak systolic pressure. Seal zone stabilization provides a mechanism through which endoanchor addition may translate into lower rates of type 1a endoleaks for patients.

Objectives: The prophylactic treatment of uncomplicated TBAD with TEVAR is controversial. This warrants the identification of a high-risk category of dissections that may particularly benefit from surgical intervention. The analysis of radiographic features presents a promising modality of assessing this high-risk cohort. We test the ability of aortic size and shape metrics from the literature to predict patient suitability for TEVAR from pre-operative imaging. Methods: We collected a single institutional retrospective cohort of 36 patients with TBAD who received TEVAR and had pre-operative and follow-up CTA imaging. We tested 8 aortic size and shape metrics. We segmented each patient’s aorta and true lumen from the pre-operative scan. Tortuosity, mean diameter, centerline curvature, and eccentricity were measured from the centerline. True and false lumen volumes and max diameter were calculated. The question mark angle, as previously defined by Li et al., was also measured. Univariate and multivariate logistic regression analyses were performed. Results: In the univariate analysis, pre-operative false lumen volume (OR 26.2 95% CI 2.72 to 252, p = .005), mean diameter (OR 9.6 95% CI 2.19 to 42.3, p = .003), and maximum diameter (OR 9.0 95% CI 2.12 to 38.3, p = .003) were all significantly associated with post-TEVAR outcomes. Tortuosity index (OR 2.7, 95% CI 1.14 to 6.37, p = .024) was the only significant shape parameter. In multivariate analysis, we found that pre-operative maximum diameter (OR 10.0, 95% CI 1.50 to 67.0, p < .018) is a significant predictor of TEVAR outcomes independent of shape parameters, all of which were not significant. Conclusions: False lumen volume and maximum diameter can predict the occurrence of reintervention and type I endoleak following TEVAR for uncomplicated TBAD. While size measures are effective in explaining aortic dissection behavior, current shape measures are not as effective and better methodologies must be developed.

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Cross-sectional imaging, such as computed tomography (CTA) scans, provide unparalleled visualization of aortic anatomy. However, despite the immense geometric and anatomic detail provided by CTA imaging, surgeons continue to interact with this data in a linear and dimensionally reduced feature space. Aortic pathologies such as aneurysms and dissections are clinically quantified using a single scalar: maximum aortic diameter. To date, not feature of aortic shape has reproducibly captured what surgeons often describe qualitatively when looking at CT scans or when in the operating room observing the physical anatomy. Shape along with size plays a central role in differentiating normal from diseased aortas. We defined a geometric feature space using tools of modern differential geometry that incorporate shape and size. We show that size can be parameterized by l, the radial aortic extent commonly taken as aortic diameter. Size invariant shape is quantified by performing a Gauss map of local regions on the aortic surface and calculating the variance of the total integrated curvature (δK) across each aorta. While we do not inherently study aortic stability as it relates to clinical rupture in this paper, aortas appearing at high δK are clinically classified by size and qualitative appearance as high risk. It is therefor interesting to conjecture that divergence in the (δK,l)-space is a sign of aortic topologic instability. Projection into (δK, l)-space provides two independent variables that show a natural division of the data as it transitions from size to shape dominated behavior, an indictor of aortic fragility.