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Image, geometry and finite element mesh datasets for analysis of relationship between abdominal aortic aneurysm symptoms and stress in walls of abdominal aortic aneurysm.

ABSTRACT: These datasets contain Computed Tomography (CT) images of 19 patients with Abdominal Aortic Aneurysm (AAA) together with 19 patient-specific geometry data and computational grids (finite element meshes) created from these images applied in the research reported in Journal of Surgical Research article "Is There A Relationship Between Stress in Walls of Abdominal Aortic Aneurysm and Symptoms?"[1]. The images were randomly selected from the retrospective database of University Hospitals Leuven (Leuven, Belgium) and provided to The University of Western Australia's Intelligent Systems for Medicine Laboratory. The analysis was conducted using our freely-available open-source software BioPARR (Joldes et al., 2017) created at The University of Western Australia. The analysis steps include image segmentation to obtain the patient-specific AAA geometry, construction of computational grids (finite element meshes), and AAA stress computation. We use well-established and widely used data file formats (Nearly Raw Raster Data or NRRD for the images, Stereolitography or STL format for geometry, and Abaqus finite element code keyword format for the finite element meshes). This facilitates re-use of our datasets in practically unlimited range of studies that rely on medical image analysis and computational biomechanics to investigate and formulate indicators and predictors of AAA symptoms.

SUBMITTER: Wittek A

PROVIDER: S-EPMC7171530 | biostudies-literature |

REPOSITORIES: biostudies-literature

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An in-silico benchmark for the tricuspid heart valve - Geometry, finite element mesh, Abaqus simulation, and result data set.

Project description:This article provides Abaqus input files and user subroutines for performing finite element simulations of the tricuspid heart valve with an idealized geometry. Additional post-processing steps to obtain a ParaView visualization file (*.vtk) of the deformed geometry are also provided to allow the readers to use the included ParaView state file (*.pvsm) for customizable visualization and evaluation of the simulation results. We expect this first-of-its-kind in-silico benchmark dataset will facilitate user-friendly simulations considering material nonlinearity, leaflet-to-leaflet contact, and large deformations. Additionally, the information included herein can be used to rapidly evaluate other novel in-silico approaches developed for simulating cardiac valve function. The benchmark can be expanded to consider more complex features of the tricuspid valve function, such as the dynamic annulus motion or the time-varying transvalvular pressure. Interested readers are referred to the companion article (Johnson et al., 2021) for an example application of this in-silico tool for isogeometric analysis of tricuspid valves.

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Genes and abdominal aortic aneurysm.

Project description:Abdominal aortic aneurysm (AAA) is a multifactorial disease with a strong genetic component. Since the first candidate gene studies were published 20 years ago, approximately 100 genetic association studies using single nucleotide polymorphisms (SNPs) in biologically relevant genes have been reported on AAA. These studies investigated SNPs in genes of the extracellular matrix, the cardiovascular system, the immune system, and signaling pathways. Very few studies were large enough to draw firm conclusions and very few results could be replicated in another sample set. The more recent unbiased approaches are family-based DNA linkage studies and genome-wide genetic association studies, which have the potential of identifying the genetic basis for AAA, only when appropriately powered and well-characterized large AAA cohorts are used. SNPs associated with AAA have already been identified in these large multicenter studies. One significant association was of a variant in a gene called contactin-3, which is located on chromosome 3p12.3. However, two follow-up studies could not replicate this association. Two other SNPs, which are located on chromosome 9p21 and 9q33, were replicated in other samples. The two genes with the strongest supporting evidence of contribution to the genetic risk for AAA are the CDKN2BAS gene, also known as ANRIL, which encodes an antisense ribonucleic acid that regulates expression of the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B, and DAB2IP, which encodes an inhibitor of cell growth and survival. Functional studies are now needed to establish the mechanisms by which these genes contribute toward AAA pathogenesis.

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Project description:This SuperSeries is composed of the SubSeries listed below.

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2022-05-20 | PXD030441 | Pride

Metabolomic Profile of Abdominal Aortic Aneurysm.

Project description:Abdominal aortic aneurysm (AAA) is characterized by structural deterioration of the aortic wall, leading to aortic dilation and rupture. The aim was to compare 183 low molecular weight metabolites in AAA patients and aorta-healthy controls and to explore if low molecular weight metabolites are linked to AAA growth. Blood samples were collected from male AAA patients with fast (mean 3.3 mm/year; range 1.3-9.4 mm/year; n = 39) and slow growth (0.2 mm/year; range -2.6-1.1 mm/year; n = 40), and from controls with non-aneurysmal aortas (n = 79). Targeted analysis of 183 metabolites in plasma was performed with AbsoluteIDQ p180 kit. The samples were measured on a QTRAP 4500 coupled to an Agilent 1260 series HPLC. The levels of only four amino acids (histidine, asparagine, leucine, isoleucine) and four phosphatidylcholines (PC.ae.C34.3, PC.aa.C34.2, PC.ae.C38.0, lysoPC.a.C18.2) were found to be significantly lower (p < 0.05) after adjustment for confounders among the AAA patients compared with the controls. There were no differences in the metabolites distinguishing the AAA patients with slow or fast growth from the controls, or distinguishing the patients with slow growth from those with fast growth. The current study describes novel significant alterations in amino acids and phosphatidylcholines metabolism associated with AAA occurrence, but no associations were found with AAA growth rate.

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Project description: Not available

| S-EPMC10749584 | biostudies-literature

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Project description:IntroductionExtracellular matrix degradation is a hallmark of abdominal aortic aneurysm (AAA). Among proteases that are capable of degrading extracellular matrix are a disintegrin and metalloproteases with thrombospondin motifs (ADAMTS). Pathogenesis of these proteases in AAA has not been investigated until date.Methods and resultsHuman aneurysmal and control aortas were collected and analyzed with RT-PCR measuring the ADAMTS-1, 4,5,6,8,9,10,13,17 and ADAMTSL-1. Expression of a majority of the investigated ADAMTS members on mRNA level was decreased in aneurysm compared to control aorta. ADAMTS-1 was one of the members that was reduced most. Protein analysis using immunohistochemistry and western blot for localization and expression of ADAMTS-1 revealed that ADAMTS-1 was present predominantly in areas of SMCs and macrophages in aneurysmal aorta and higher expressed in AAA compared to control aortas. The role of ADAMTS-1 in AAA disease was further examined using ADAMTS-1 transgenic/apoE-/- mice with the experimental angiotensin II induced aneurysmal model. Transgenic mice overexpressing ADAMTS-1 showed to be similar to ADAMTS-1 wild type mice pertaining collagen, elastin content and aortic diameter.ConclusionSeveral of the ADAMTS members, and especially ADAMTS-1, are down regulated at mRNA level in AAA, due to unknown mechanisms, at the same time ADAMTS-1 protein is induced. The cleavage of its substrates, don't seem to be crucial for the pathogenesis of AAA but rather more important in the development of thoracic aortic aneurysm and atherosclerosis as shown in previous studies.

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