An abdominal aortic aneurysm (AAA) is a balloon-like dilation of the aorta, which is potentially fatal in case of rupture. Computational finite element (FE) analysis is a promising approach to a more accurate and patient-specific rupture risk prediction. AAA wall strength and rupture potential index (RPI) calculation are implemented in our FE software. Static structural FE simulations are performed on n = 30 non-ruptured asymptomatic, n = 9 non-ruptured symptomatic, and n = 14 ruptured AAAs. We calculate maximum values for diameter, wall displacement, strain, stress, and RPI as well as minimum wall strength for every AAA. All investigated quantities, except minimum strength, show statistically significant differences between non-ruptured asymptomatic and symptomatic/ruptured AAAs. Maximum wall stress and especially the RPI are notably increased for symptomatic and ruptured AAAs. The biggest difference is found to be the RPI (Δ = 44.9%, p = 8.0e-5). Lowest RPI obtained for symptomatic or ruptured AAAs is 0.3. The RPI of more than 55% of the investigated asymptomatic AAAs falls below this value. Maximum wall stress and maximum RPI criteria enable a reliable rupture risk evaluation for AAAs. Especially in the diameter range where surgical indication is not obvious, the RPI holds great potential for improvement of clinical decisions.
Maximum aortic FDG uptake correlated significantly with inflammation, followed by increased MMP expression and histopathologic characteristics of aneurysm wall instability and clinical symptoms. Therefore, FDG-PET/CT might be a new diagnostic technique to study AAA disease in vivo and may contribute to improve prediction of individual AAA rupture risk.
Both the clinically established diameter criterion and novel approaches of computational finite element (FE) analyses for rupture risk stratification of abdominal aortic aneurysms (AAA) are based on assumptions of population-averaged, uniform material properties for the AAA wall. The presence of inter-patient and intra-patient variations in material properties is known, but has so far not been addressed sufficiently. In order to enable the preoperative estimation of patient-specific AAA wall properties in the future, we investigated the relationship between non-invasively assessable clinical parameters and experimentally measured AAA wall properties. We harvested n = 163 AAA wall specimens (n = 50 patients) during open surgery and recorded the exact excision sites. Specimens were tested for their thickness, elastic properties, and failure loads using uniaxial tensile tests. In addition, 43 non-invasively assessable patient-specific or specimen-specific parameters were obtained from recordings made during surgery and patient charts. Experimental results were correlated with the non-invasively assessable parameters and simple regression models were created to mathematically describe the relationships. Wall thickness was most significantly correlated with the metabolic activity at the excision site assessed by PET/CT (ρ = 0.499, P = 4 × 10(-7)) and to thrombocyte counts from laboratory blood analyses (ρ = 0.445, P = 3 × 10(-9)). Wall thickness was increased in patients suffering from diabetes mellitus, while it was significantly thinner in patients suffering from chronic kidney disease (CKD). Elastic AAA wall properties had significant correlations with the metabolic activity at the excision site (PET/CT), with existent calcifications, and with the diameter of the non-dilated aorta proximal to the AAA. Failure properties (wall strength and failure tension) had correlations with the patient's medical history and with results from laboratory blood analyses. Interestingly, AAA wall failure tension was significantly reduced for patients with CKD and elevated blood levels of potassium and urea, respectively, both of which are associated with kidney disease. This study is a first step to a future preoperative estimation of AAA wall properties. Results can be conveyed to both the diameter criterion and FE analyses to refine rupture risk prediction. The fact that AAA wall from patients suffering from CKD featured reduced failure tension implies an increased AAA rupture risk for this patient group at comparably smaller AAA diameters.
Background Among asymptomatic patients with severe carotid artery stenosis but no recent stroke or transient cerebral ischaemia, either carotid artery stenting (CAS) or carotid endarterectomy (CEA) can restore patency and reduce long-term stroke risks. However, from recent national registry data, each option causes about 1% procedural risk of disabling stroke or death. Comparison of their long-term protective effects requires large-scale randomised evidence.Methods ACST-2 is an international multicentre randomised trial of CAS versus CEA among asymptomatic patients with severe stenosis thought to require intervention, interpreted with all other relevant trials. Patients were eligible if they had severe unilateral or bilateral carotid artery stenosis and both doctor and patient agreed that a carotid procedure should be undertaken, but they were substantially uncertain which one to choose. Patients were randomly allocated to CAS or CEA and followed up at 1 month and then annually, for a mean 5 years. Procedural events were those within 30 days of the intervention. Intention-to-treat analyses are provided. Analyses including procedural hazards use tabular methods. Analyses and meta-analyses of non-procedural strokes use Kaplan-Meier and log-rank methods. The trial is registered with the ISRCTN registry, ISRCTN21144362.
[(18)F]Galacto-RGD PET/CT shows specific tracer accumulation in human atherosclerotic carotid plaques, which correlates with αvβ3 expression. Based on these initial data, larger prospective studies are now warranted to evaluate the potential of molecular imaging of αvβ3 expression for assessment of plaque inflammation in patients.
Objectives: Abdominal aortic aneurysm (AAA) wall is characterized by degradation of extracellular matrix through matrix metalloproteinases (MMPs), chronic inflammatory cell infiltration and extensive neovascularization. So far, MMP expression within AAA wall in association with infiltrates and neovascularization has not yet been studied. Methods: Vessel walls of 15 AAA patients and 8 organ donors were analyzed by immunohistochemistry for expression of various MMPs (MMP-1, -2, -3, -7, -8, -9, -12 and -13) in all cells located within the AAAs and correlated with infiltrates and neovascularization. Results: Luminal endothelial cells (ECs) were positive for MMP-1, -3 and -9, ECs of mature neovessels were furthermore positive for MMP-2. Immature neovessels expressed all MMPs tested except for MMP-13. Aortic medial smooth muscle cells (SMCs) expressed MMP-1, -2, -3 and -9, SMCs of mature neovessels, only MMP-1, -3 and -9. Inflammatory infiltrates expressed all MMPs tested except for MMP-2, macrophages expressed all MMPs. Infiltrates were composed mainly of B cells (58.5 ± 10.9%) and T lymphocytes (26.3 ± 9.5%). Furthermore, significant inverse correlations were found between the amounts of inflammatory cells, neovessels and collagen/elastin content of the aortic vessel wall (r = +0.806/p < 0.001, r = –0.650/p = 0.012, r = –0.63/p < 0.015; respectively). Conclusion: Inflammatory infiltrates and invading neovessels are relevant sources of MMPs in the AAA wall and may substantially contribute to aneurysm wall instability.
Endovascular aneurysm repair (EVAR) can involve some unfavorable complications such as endoleaks or stent-graft (SG) migration. Such complications, resulting from the complex mechanical interaction of vascular tissue, SG and blood flow or incompatibility of SG design and vessel geometry, are difficult to predict. Computational vascular mechanics models can be a predictive tool for the selection, sizing and placement process of SGs depending on the patient-specific vessel geometry and hence reduce the risk of potential complications after EVAR. In this contribution, we present a new in silico EVAR methodology to predict the final state of the deployed SG after intervention and evaluate the mechanical state of vessel and SG, such as contact forces and wall stresses. A novel method to account for residual strains and stresses in SGs, resulting from the precompression of stents during the assembly process of SGs, is presented. We suggest a parameter continuation approach to model various different sizes of SGs within one in silico EVAR simulation which can be a valuable tool when investigating the issue of SG oversizing. The applicability and robustness of the proposed methods are demonstrated on the example of a synthetic abdominal aortic aneurysm geometry.
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