The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

Abdominal aortic aneurysm (AAA) is an irreversible, localized growth, typically in the infrarenal region of the aorta. Nearly 8% of the population above 65 years old is diagnosed with this disease [1], which has been shown to be associated with smoking history, heredity, and male gender. As it is asymptomatic, vascular surgeons may opt for surgical intervention or follow a wait-and-watch strategy if their assessment of the risk of rupture is low. Different criteria, such as maximum diameter, growth rate, wall stiffness, thickness of intraluminal thrombus (ILT), wall tension, etc., have been proposed for predicting rupture risk [2], which should be weighed against the risk of surgery, given that most AAA patients are elderly. The maximum diameter criterion is widely used in clinical practice [3], with the threshold diameter for decision making (typically 5.5 cm) following an evidence-based approach. However, an autopsy study of 473 AAA cases found that 13% of aneurysms 5 cm in diameter or smaller ruptured, whereas 60% of aneurysms of diameter greater than 5 cm did not [4]. Diameter-based rules for rupture prediction fail for 10%–25% patients in small and large AAA [5]. Hence, there is a clear need to accurately assess rupture risk on a patient-specific basis by using more rigorous, scientific means. A biomechanics-based approach can be helpful toward achieving this goal by accurately modeling the individual AAA geometry. Wall thickness is an important geometry variable that can potentially increase the accuracy of AAA biomechanical analysis. Rupture is a local phenomenon that should be assessed by modeling spatially varying local geometry, thereby eliminating the role of globally defined criteria, such as diameter and sac volume for patient-specific rupture risk analysis. Vascular wall thickness is believed to be an influential geometric feature for biomechanical stress evaluation. From a mechanics perspective, the shape of an aneurysm and the thickness of the artery should govern dominantly the stress distribution compared to the overall size of the aneurysm [6]. Acknowledging that there are limitations inherent to image acquisition sequences and resolution, deriving accurate segmentation and geometric modeling algorithms are highlighted as open problems in computational vascular biomechanics [7]. Thickness, nonlinear material behavior, strength of the AAA wall, and the spatial distribution of these variables are said to be essential for achieving accurate finite element (FE) simulations and, therefore, also for a realistic prediction of AAA rupture risk [8,9]. Few studies report experimental measurements of aneurysmatic wall thickness [10–12,33] and with large differences in their findings, as described in Table ​Table1.1. The autopsy-based observation that AAA rupture location occurs mostly on the posterior wall [4] is in agreement with the finding by Raghavan et al. [11] that wall thickness is slightly less in the posterior region compared to the anterior region. It should be noted that the severity of a posterior wall rupture is relatively less than that of an anterior wall rupture. Hence, it is more likely that posterior wall rupture cases are documented in the medical literature, since a patient with anterior wall rupture may not reach a hospital alive, thereby compounding the aforementioned observations. In a healthy aorta, the anterior wall is thicker than the posterior [10] and with a mean wall thickness of 1.39 mm [13]. The challenge of estimating regional variations of wall thickness and the subsequent incorporation in FE analysis is a complex one. Hence, the assumption of a uniform wall thickness in numerical models reported in the literature is questionable, and there is need for addressing whether the regional variations are needed on a patient-specific basis. To that end, Martufi et al. [14] reported the validation of a set of matlab routines for estimating regional vessel wall thickness from CT images by comparing it with postmortem AAA tissue measurements [11], resulting in an average relative difference of 7.8%. A framework for semiautomatic vessel wall detection and quantification of thickness using contrast-enhanced CT images was described by Shum et al. [15], resulting in low repeatability and reproducibility errors when compared to the manual segmentations performed by trained vascular surgeons. Quantitative assessment of AAA geometry [16] has shown promising results, with wall thickness being one of the morphological indicators significant for rupture risk stratification. These developments are paving the way for noninvasive, automatic geometric assessment of AAAs yielding population stratification in clinical practice. Table 1 Brief summary of previously reported experimental measurements on wall thickness (eAAA—electively repaired AAA; rAAA—ruptured AAA)