Correlation between Hemodynamic Stresses and Morphometric Indices as a Predictor Potential of Abdominal Aortic Aneurysm Rupture

Special Article - Abdominal Aortic Aneurysms

Austin J Vasc Med. 2016; 3(1): 1014.

Correlation between Hemodynamic Stresses and Morphometric Indices as a Predictor Potential of Abdominal Aortic Aneurysm Rupture

Vilalta-Alonso JA1, Soudah-Prieto E2, Nieto- Palomo F3,4,7, Lipsa L3,7, Perez-Rueda MA4,7, Lopez-Aguilar BM1, Vaquero-Puerta C5,7 and Vilalta-Alonso G6,7*

1Department of Industrial Engineering, Instituto Superior Politécnico José Antonio Echeverria (Cujae), Cuba

2International Center for Numerical Methods in Engineering (CIMNE), Technical University of Catalonia, Spain

3Department of Mechanical Engineering, CARTIF Technological Center, Spain

4Department of Mechanical Engineering, University of Valladolid, Spain

5Angiology and Vascular Surgery Service, Clinic Hospital and University of Valladolid, Spain

6Department of Thermal Sciences and Fluid, Federal University of Sao Joao del-Rei, Brazil

7Institute for Advanced Production Technologies (ITAP), University of Valladolid, Spain

*Corresponding author: Vilalta-Alonso G, Thermal Sciences and Fluids Department, Federal University of Sao Joao del-Rei, Praca Frei Orlando 170, Centro, Sao Joao del-Rei, Brazil

Received: December 12, 2015; Accepted: January 29,2016; Published: February 01, 2016


Nowadays, there is consensus that current criteria to assess the abdominal aortic aneurysm rupture risk (maximum transverse diameter and growth rate) cannot be considered as reliable indicators. Therefore, accurate prediction of the AAA rupture risk is one of the main challenges that vascular surgeon face up today. Taking into account the physical principle governing this complex phenomenon, i.e, the rupture it is associated with the balance between internal forces exerted by blood flow on artery wall aneurysm and their ability to withstand it, it is expected that relationship between hemodynamic stresses and aneurysm morphology can shed light on defining some rupture risk indices. To assess potential correlations between the main geometric parameters characterizing the AAA and hemodynamic stresses, in order to improve the insight about the rupture phenomenon, thirteen models of unruptured AAA have been reconstructed from patient-specific CT data. It has been made using a noninvasive user defined algorithm, which has been developed by using MeVisLab software. For the geometric characterization, twelve shape and size quantitative indices based on the lumen centreline were defined and computed by using VMTK software. The calculation of the temporal and spatial distributions of hemodynamic stress has been carried out by means of Tdyn, software based on Computational Fluid Dynamics. Pearson correlation coefficient has been used to evaluate the relationships between the hemodynamic stresses and the geometric indices here defined. Statistical analysis has confirmed that the length, asymmetry and the saccular index affect hemodynamic stresses. These results highlight the potential of statistical techniques to assess the significant geometric parameters for the hemodynamic stresses prediction and their relevance for obtaining a rupture risk predictor.

Keywords: AAA; Statistical techniques; Morphology; Rupture risk; Peak wall shear stress; Peak intraluminal pressure


AAA: Abdominal aortic Aneurysm; CFD: Computational Fluid Dynamics; PWS: Peak Wall Stress; RPI: Rupture Potential Index; ILT: Intraluminal Thrombus; DICOM: Digital Imaging and Communications in Medicine; CT: Computed Tomography; VMTK: Vascular Modelling Tool Kit; STL: Stereo Lithography; FEM: Finite Element Method; WSS: Wall Shear Stress; PWSS: Peak Wall Shear Stress; PIP: Peak Intraluminal Pressure; FSI: Fluid-Solid Interaction


Abdominal Aortic Aneurysm (AAA) is a localized and irreversible dilation of the abdominal aorta resulting from a multifactorial process that culminates in an irreversible pathological remodeling of the aortic wall. The overall result is a gradual imbalance between synthesis and degradation of tissue constituents leading to the loss of structural integrity of the aortic wall modifying the mechanical properties of arterial wall. Nowadays, the current clinical management of rupture risk is based on geometrical indices: transversal maximum diameter and diameter growth rate [1,2]. However, the use of these parameters as a guide to making decisions about the appropriate treatment in aneurismatic patients has faced strong challenge because of its inability to accurately predict rupture for all AAAs [3-5]. The AAA morphometry is recognized as a rupture predictor because determines the spatial-temporal distribution of hemodynamic stress and the aneurysm rupture is a manifestation of the balance between the forces exerted by the blood (the hemodynamic stresses) on the arterial wall and their ability to withstand these forces. Based on that, others mechanics-based indices have been proposed as improved predictors of AAA rupture: aneurysm asymmetry, effect of intraluminal thrombus, wall stiffness and thickness saccular index, mechanical stress [6-8]. Some of these indices have been more successful than others due to the difficulty for extracting in vivo and non-invasive information, difficulting its implementation in daily clinical management. Also, as these indices do not consider, for example, biological factors they have not been fully correlated with the pathogenesis of AAA.

In this sense and taking into consideration the physical principle governing the aneurysm rupture phenomenon, as mentioned above, a new approach is being proposed. This approach relies on determine the relations between the hemodynamic stresses (wall shear stress + intraluminal pressure) and the aneurysm morphology. Recent work [9] has reported the correlation between the AAA morphology defined by five geometrical parameters and the hemodynamic stresses. The authors highlight the strong relation between the intraluminal pressure and two shape indices: deformation rate and saccular index. The peak wall shear stress is better correlated with aneurysm length.

From these initial results, the present work follow the main idea of this approach trying to find how the AAA morphology correlate with the hemodynamic stresses acting on arterial wall. To do that, the aneurysm morphology was defined by mean of twelve shape and size indices and thirteen patient-specific AAA were utilized.

We hypothesize that the results obtained by using this new approach will allow, in future steps and with more theoretical basics, to face the accurate identification of rupture risk, which will improve the clinical management of aneurismatic patients.

Materials and Methods

AAA geometric

The procedure for AAA reconstruction consists in the following steps:

The images stored in the files with. DICOM extension (the standardized type of file for medical images) were processed by using the MeVisLab® and Vmtk software, which are a multi-platform set of applications, specific for the medical images processing and visualization.

Lumen segmentation of the AAA surface and geometric reconstruction: To obtain the segmentation of the lumen we use a semi-automatic method executed with VMTK software where it is necessary to use CT scanning procedure that involves use of contrast medium.

The semi-automatic method is quite easy for the user, who has to select just two internal points in the lumen. The abdominal images were segmented from CT DICOM images combining two different segmentation procedures; thresholding and level set method (based on snakes). Thresholding is a nonlinear operation that converts a gray-scale image into a binary image where the two levels are assigned to pixels that are below or above the specified threshold value. The image snake operation creates or modifies an active contour/snake in a grey scale image. The operation iterates to minimize the snake’s energy which consists of multiple components including the length of the snake, its curvature, and image gradient.

Once obtained the segmentation of the lumen and of the external surface of the AAA, a smoothing process is applied through specific algorithms of the VMTK and MeVisLab software and it is stored in STL format. (Figure 1) shows the workflow used in the present work to AAA segmentation.