Dataset Information

Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.

ABSTRACT: Abdominal aortic aneurysm (AAA) is a vascular disease characterized by the enlargement of the infrarenal segment of the aorta. A ruptured AAA can cause internal bleeding and carries a high mortality rate, which is why the clinical management of the disease is focused on preventing aneurysm rupture. AAA rupture risk is estimated by the change in maximum diameter over time (i.e., growth rate) or if the diameter reaches a prescribed threshold. The latter is typically 5.5 cm in most clinical centers, at which time surgical intervention is recommended. While a size-based criterion is suitable for most patients who are diagnosed at an early stage of the disease, it is well known that some small AAA rupture or patients become symptomatic prior to a maximum diameter of 5.5 cm. Consequently, the mechanical stress in the aortic wall can also be used as an integral component of a biomechanics-based rupture risk assessment strategy. In this work, we seek to identify geometric characteristics that correlate strongly with wall stress using a sample space of 100 asymptomatic, unruptured, electively repaired AAA models. The segmentation of the clinical images, volume meshing, and quantification of up to 45 geometric measures of each AAA were done using in-house Matlab scripts. Finite element analysis was performed to compute the first principal stress distributions from which three global biomechanical parameters were calculated: peak wall stress, 99th percentile wall stress and spatially averaged wall stress. Following a feature reduction approach consisting of Pearson's correlation matrices with Bonferroni correction and linear regressions, a multivariate stepwise regression analysis was conducted to find the geometric measures most highly correlated with each of the biomechanical parameters. Our findings indicate that wall stress can be predicted by geometric indices with an accuracy of up to 94% when AAA models are generated with uniform wall thickness and up to 67% for patient specific, non-uniform wall thickness AAA. These geometric predictors of wall stress could be used in lieu of complex finite element models as part of a geometry-based protocol for rupture risk assessment.

SUBMITTER: Wu W

PROVIDER: S-EPMC6610879 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.

Wu Wei W Rengarajan Balaji B Thirugnanasambandam Mirunalini M Parikh Shalin S Gomez Raymond R De Oliveira Victor V Muluk Satish C SC Finol Ender A EA

Annals of biomedical engineering 20190408 7

Abdominal aortic aneurysm (AAA) is a vascular disease characterized by the enlargement of the infrarenal segment of the aorta. A ruptured AAA can cause internal bleeding and carries a high mortality rate, which is why the clinical management of the disease is focused on preventing aneurysm rupture. AAA rupture risk is estimated by the change in maximum diameter over time (i.e., growth rate) or if the diameter reaches a prescribed threshold. The latter is typically 5.5 cm in most clinical centers ...[more]

PMID: 30963384

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Project description:Abdominal aortic aneurysm (AAA) is a prevalent cardiovascular disease characterized by the focal dilation of the aorta, which supplies blood to all the organs and tissues in the systemic circulation. With the AAA increasing in diameter over time, the risk of aneurysm rupture is generally associated with the size of the aneurysm. If diagnosed on time, intervention is recommended to prevent AAA rupture. The criterion to decide on surgical intervention is determined by measuring the maximum diameter of the aneurysm relative to the critical value of 5.5 cm. However, a more reliable approach could be based on understanding the biomechanical behavior of the aneurysmal wall. In addition, geometric features that are proven to be significant predictors of the AAA wall mechanics could be used as surrogates of the AAA biomechanical behavior and, subsequently, of the aneurysm's risk of rupture. The aim of this work is to identify those geometric indices that have a high correlation with AAA wall stress in the population of patients who received an emergent repair of their aneurysm. In-house segmentation and meshing algorithms were used to model 75 AAAs followed by estimation of the spatially distributed wall stress by performing finite element analysis. Fifty-two shape and size geometric indices were calculated for the same models using MATLAB scripting. Hypotheses testing were carried out to identify the indices significantly correlated with wall stress by constructing a Pearson's correlation coefficient matrix. The analyses revealed that 12 indices displayed high correlation with the wall stress, amongst which wall thickness and curvature-based indices exhibited the highest correlations. Stepwise regression analysis of these correlated indices indicated that wall stress can be predicted by the following four indices with an accuracy of 76%: maximum aneurysm diameter, aneurysm sac length, average wall thickness at the maximum diameter cross-section, and the median of the wall thickness variance. The primary outcome of this work emphasizes the use of global measures of size and wall thickness as geometric surrogates of wall stress for emergently repaired AAAs.

Project description:Abdominal aortic aneurysm (AAA) is an asymptomatic aortic disease with a survival rate of 20% after rupture. It is a vascular degenerative condition different from occlusive arterial diseases. The size of the aneurysm is the most important determining factor in its clinical management. However, other measures of the AAA geometry that are currently not used clinically may also influence its rupture risk. With this in mind, the objectives of this work are to develop an algorithm to calculate the AAA wall thickness and abdominal aortic diameter at planes orthogonal to the vessel centerline, and to quantify the effect of geometric indices derived from this algorithm on the overall classification accuracy of AAA based on whether they were electively or emergently repaired. Such quantification was performed based on a retrospective review of existing medical records of 150 AAA patients (75 electively repaired and 75 emergently repaired). Using an algorithm implemented within the MATLAB computing environment, 10 diameter- and wall thickness-related indices had a significant difference in their means when calculated relative to the AAA centerline compared to calculating them relative to the medial axis. Of these 10 indices, nine were wall thickness-related while the remaining one was the maximum diameter (Dmax). Dmax calculated with respect to the medial axis is over-estimated for both electively and emergently repaired AAA compared to its counterpart with respect to the centerline. C5.0 decision trees, a machine learning classification algorithm implemented in the R environment, were used to construct a statistical classifier. The decision trees were built by splitting the data into 70% for training and 30% for testing, and the properties of the classifier were estimated based on 1000 random combinations of the 70/30 data split. The ensuing model had average and maximum classification accuracies of 81.0 and 95.6%, respectively, and revealed that the three most significant indices in classifying AAA are, in order of importance: AAA centerline length, L2-norm of the Gaussian curvature, and AAA wall surface area. Therefore, we infer that the aforementioned three geometric indices could be used in a clinical setting to assess the risk of AAA rupture by means of a decision tree classifier. This work provides support for calculating cross-sectional diameters and wall thicknesses relative to the AAA centerline and using size and surface curvature based indices in classification studies of AAA.

Project description:ObjectiveGuidelines for repair of bicuspid aortic valve-associated ascending thoracic aortic aneurysms have been changing, most recently to the same criteria as tricuspid aortic valve-ascending thoracic aortic aneurysms. Rupture/dissection occurs when wall stress exceeds wall strength. Recent studies suggest similar strength of bicuspid aortic valve versus tricuspid aortic valve-ascending thoracic aortic aneurysms; thus, comparative wall stress may better predict dissection in bicuspid aortic valve versus tricuspid aortic valve-ascending thoracic aortic aneurysms. Our aim was to determine whether bicuspid aortic valve-ascending thoracic aortic aneurysms had higher wall stresses than their tricuspid aortic valve counterparts.MethodsPatients with bicuspid aortic valve- and tricuspid aortic valve-ascending thoracic aortic aneurysms (bicuspid aortic valve = 17, tricuspid aortic valve = 19) greater than 4.5 cm underwent electrocardiogram-gated computed tomography angiography. Patient-specific 3-dimensional geometry was reconstructed and loaded to systemic pressure after accounting for prestress geometry. Finite element analyses were performed using the LS-DYNA solver (LSTC Inc, Livermore, Calif) with user-defined fiber-embedded material model to determine ascending thoracic aortic aneurysm wall stress.ResultsBicuspid aortic valve-ascending thoracic aortic aneurysms 99th-percentile longitudinal stresses were 280 kPa versus 242 kPa (P = .028) for tricuspid aortic valve-ascending thoracic aortic aneurysms in systole. These stresses did not correlate to diameter for bicuspid aortic valve-ascending thoracic aortic aneurysms (r = -0.004) but had better correlation to tricuspid aortic valve-ascending thoracic aortic aneurysms diameter (r = 0.677). Longitudinal stresses on sinotubular junction were significantly higher in bicuspid aortic valve-ascending thoracic aortic aneurysms than in tricuspid aortic valve-ascending thoracic aortic aneurysms (405 vs 329 kPa, P = .023). Bicuspid aortic valve-ascending thoracic aortic aneurysm 99th-percentile circumferential stresses were 548 kPa versus 462 kPa (P = .033) for tricuspid aortic valve-ascending thoracic aortic aneurysms, which also did not correlate to bicuspid aortic valve-ascending thoracic aortic aneurysm diameter (r = 0.007).ConclusionsCircumferential and longitudinal stresses were greater in bicuspid aortic valve- than tricuspid aortic valve-ascending thoracic aortic aneurysms and were more pronounced in the sinotubular junction. Peak wall stress did not correlate with bicuspid aortic valve-ascending thoracic aortic aneurysm diameter, suggesting diameter alone in this population may be a poor predictor of dissection risk. Our results highlight the need for patient-specific aneurysm wall stress analysis for accurate dissection risk prediction.

Dataset Information

Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.

Publications

Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms.

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