STATISTICAL ANALYSIS FOR RUPTURE RISK PREDICTION OF ABDOMINAL AORTIC ANEURYSMS (AAA) BASED ON ITS MORPHOMETRY

2017 ◽  
Vol 17 (04) ◽  
pp. 1750065 ◽  
Author(s):  
VILALTA-ALONSO GUILLERMO ◽  
VILALTA-ALONSO JOSÉ ALBERTO ◽  
SOUDAH EDUARDO ◽  
NIETO-PALOMO FÉLIX ◽  
LIPSA LAUTENTIU ◽  
...  

The morphometry of the abdominal aortic aneurysms (AAA) has been recognized as one of the main factors that may predispose its rupture. The variation of the AAA morphometry, over time, induces modifications in hemodynamic behavior which, in turn, alters the spatial and temporal distribution of hemodynamic stress on the aneurismatic wall, establishing a bidirectional process that can influence the rupture phenomenon. In order to evaluate potential correlations between the main geometric parameters characterizing the AAA and hemodynamic stresses, 13 unrupture AAA patient-specific models were created. To AAA geometric characterization, 12 indices based on lumen center line were defined and determined. The computing of temporal and spatial distributions of hemodynamic stresses was conducted through Computational Fluid Dynamics. Statistical techniques were used to assess the relationships between the hemodynamic parameters and the different geometrical indices of the AAA. Regression analyses were conducted to obtain linear predictor models for hemodynamic stresses using the different indices defined in this paper as predictor variables. The statistical analysis confirmed that the length L, the asymmetry and the saccular index significantly influenced the hemodynamic stresses. The results obtained show the potential of the use of statistical techniques in predicting the rupture risk of patient-specific AAA.

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110037
Author(s):  
Félix Nieto-Palomo ◽  
María-Ángeles Pérez-Rueda ◽  
Laurentiu-Mihai Lipsa ◽  
Carlos Vaquero-Puerta ◽  
José-Alberto Vilalta-Alonso ◽  
...  

The morphometry of abdominal aortic aneurysms (AAA) has been recognized as one of the main factors that may predispose them to rupture. The need to quantify the morphometry of AAA on a patient-specific basis constitutes a valuable tool for assisting in rupture risk prediction. Previous results of this research group have determined the correlations between hemodynamic stresses and aneurysm morphometry by means of the Pearson coefficient. The present work aims to find how the AAA morphology correlates with the hemodynamic stresses acting on the arterial wall. To do so, the potential of the bootstrap technique has been explored. Bootstrap works appropriately in applications where few data are available (13 patient-specific AAA models were simulated). The methodology developed can be considered a contribution to predicting the hemodynamic stresses from the size and shape indices. The present work explores the use of a specific statistical technique (the bootstrap technique) to predict, based on morphological correlations, the patient-specific aneurysm rupture risk, provide greater understanding of this complex phenomenon that can bring about improvements in the clinical management of aneurysmatic patients. The results obtained using the bootstrap technique have greater reliability and robustness than those obtained by regression analysis using the Pearson coefficient, thus allowing to obtain more reliable results from the characteristics of the samples used, such as their small size and high variability. Additionally, it could be an indicator that other indices, such as AAA length, deformation rate, saccular index, and asymmetry, are important.


Author(s):  
Evelyne van Dam ◽  
Marcel Rutten ◽  
Frans van de Vosse

Rupture risk of abdominal aortic aneurysms (AAA) based on wall stress analysis may be superior to the currently used diameter-based rupture risk prediction [4; 5; 6; 7]. In patient specific computational models for wall stress analysis, the geometry of the aneurysm is obtained from CT or MR images. The wall thickness and mechanical properties are mostly assumed to be homogeneous. The pathological AAA vessel wall may contain collageneous areas, but also calcifications, cholesterol crystals and large amounts of fat cells. No research has yet focused yet on the differences in mechanical properties of the components present within the degrading AAA vessel wall.


2019 ◽  
Vol 19 (03) ◽  
pp. 1950015 ◽  
Author(s):  
JOSEPH R. LEACH ◽  
CHENGCHENG ZHU ◽  
DAVID SALONER ◽  
MICHAEL D. HOPE

Biomechanical analyses can be used to better understand the rupture risk of abdominal aortic aneurysms (AAAs) on a patient-specific basis using vascular geometries obtained from medical imaging. Methodologies of varying complexity are used to estimate the unloaded state of the imaged vessel to provide a reference configuration for finite element simulations. In this work, we compare the implementation and results of two of these methods, one based on geometric scaling and the other using an iterative determination of unloaded vessel geometry. We find that the two methods result in significantly different stress predictions, and that the iterative method offers superior geometric accuracy. Our findings lend context to the variation in finite element results presented in the AAA stress analysis literature.


2018 ◽  
Vol 25 (6) ◽  
pp. 750-756 ◽  
Author(s):  
Antti Siika ◽  
Moritz Lindquist Liljeqvist ◽  
Rebecka Hultgren ◽  
T. Christian Gasser ◽  
Joy Roy

Purpose: To investigate how 2-dimensional geometric parameters differ between ruptured and asymptomatic abdominal aortic aneurysms (AAAs) and provide a biomechanical explanation for the findings. Methods: The computed tomography angiography (CTA) scans of 30 patients (mean age 77±10 years; 23 men) with ruptured AAAs and 60 patients (mean age 76±8 years; 46 men) with asymptomatic AAAs were used to measure maximum sac diameter along the center lumen line, the cross-sectional lumen area, the total vessel area, the intraluminal thrombus (ILT) area, and corresponding volumes. The CTA data were segmented to create 3-dimensional patient-specific models for finite element analysis to compute peak wall stress (PWS) and the peak wall rupture index (PWRI). To reduce confounding from the maximum diameter, 2 diameter-matched groups were selected from the initial patient cohorts: 28 ruptured AAAs and another with 15 intact AAAs (diameters 74±12 vs 73±11, p=0.67). A multivariate model including the maximum diameter, the lumen area, and the ILT area of the 60 intact aneurysms was employed to predict biomechanical rupture risk parameters. Results: In the diameter-matched subgroup comparison, ruptured AAAs had a significantly larger cross-sectional lumen area (1954±1254 vs 1120±623 mm2, p=0.023) and lower ILT area ratio (55±24 vs 68±24, p=0.037). The ILT area (2836±1462 vs 2385±1364 mm2, p=0.282) and the total vessel area (3956±1170 vs 4338±1388 mm2, p=0.384) did not differ statistically between ruptured and intact aneurysms. The PWRI was increased in ruptured AAAs (0.80 vs 0.48, p<0.001), but the PWS was similar (249 vs 284 kPa, p=0.194). In multivariate regression analysis, lumen area was significantly positively associated with both PWS (p<0.001) and PWRI (p<0.01). The ILT area was also significantly positively associated with PWS (p<0.001) but only weakly with PWRI (p<0.01). The lumen area conferred a higher risk increase in both PWS and PWRI when compared with the ILT area. Conclusion: The lumen area is increased in ruptured AAAs compared to diameter-matched asymptomatic AAAs. Furthermore, this finding may in part be explained by a relationship with biomechanical rupture risk parameters, in which lumen area, irrespective of maximum diameter, increases PWS and PWRI. These observations thus suggest a possible method to improve prediction of rupture risk in AAAs by measuring the lumen area without the use of computational modeling.


2004 ◽  
Vol 1268 ◽  
pp. 1090-1095 ◽  
Author(s):  
M Breeuwer ◽  
U Götte ◽  
R Hoogeveen ◽  
B.J.B.M Wolters ◽  
S de Putter ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Judith H. C. Fonken ◽  
Esther J. Maas ◽  
Arjet H. M. Nievergeld ◽  
Marc R. H. M. van Sambeek ◽  
Frans N. van de Vosse ◽  
...  

Currently, the prediction of rupture risk in abdominal aortic aneurysms (AAAs) solely relies on maximum diameter. However, wall mechanics and hemodynamics have shown to provide better risk indicators. Patient-specific fluid-structure interaction (FSI) simulations based on a non-invasive image modality are required to establish a patient-specific risk indicator. In this study, a robust framework to execute FSI simulations based on time-resolved three-dimensional ultrasound (3D+t US) data was obtained and employed on a data set of 30 AAA patients. Furthermore, the effect of including a pre-stress estimation (PSE) to obtain the stresses present in the measured geometry was evaluated. The established workflow uses the patient-specific 3D+t US-based segmentation and brachial blood pressure as input to generate meshes and boundary conditions for the FSI simulations. The 3D+t US-based FSI framework was successfully employed on an extensive set of AAA patient data. Omitting the pre-stress results in increased displacements, decreased wall stresses, and deviating time-averaged wall shear stress and oscillatory shear index patterns. These results underline the importance of incorporating pre-stress in FSI simulations. After validation, the presented framework provides an important tool for personalized modeling and longitudinal studies on AAA growth and rupture risk.


Author(s):  
Amirhossein Arzani ◽  
Shawn C. Shadden

Abdominal aortic aneurysms (AAA) are characterized by disturbed flow patterns, low and oscillatory wall shear stress with high gradients, increased particle residence time, and mild turbulence. Diameter is the most common metric for rupture prediction, although this metric can be unreliable. We hypothesize that understanding the flow topology and mixing inside AAA could provide useful insight into mechanisms of aneurysm growth. AAA morphology has high variability, as with AAA hemodynamics, and therefore we consider patient-specific analyses over several small to medium sized AAAs. Vortical patterns dominate AAA hemodynamics and traditional analyses based on the Eulerian fields (e.g. velocity) fail to convey the complex flow structures. The computation of finite-time Lyapunov exponent (FTLE) fields and underlying Lagrangian coherent structures (LCS) help reveal a Lagrangian template for quantifying the flow [1].


2017 ◽  
Vol 83 ◽  
pp. 151-156 ◽  
Author(s):  
Kamil Novak ◽  
Stanislav Polzer ◽  
Tomas Krivka ◽  
Robert Vlachovsky ◽  
Robert Staffa ◽  
...  

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