4D CT angiography and computational biomechanics dataset for structural integrity assessment of abdominal aortic aneurysms.
Authors
Affiliations (13)
Affiliations (13)
- Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Western Australia, Australia.
- Department of Mechanical Engineering, The University of Western Australia, Perth, Western Australia, Australia.
- Department of Vascular Surgery, Fiona Stanley Hospital, Perth, Australia.
- Curtin University, School of Medicine, Perth, Australia.
- Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, Western Australia, Australia.
- Medical School, The University of Western Australia, Perth, Western Australia, Australia.
- Department of Vascular Surgery, University Hospitals Leuven, Leuven, Belgium.
- Department of Cardiovascular Sciences, Research Unit of Vascular Surgery, KU Leuven, Leuven, Belgium.
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium.
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria.
- Department of Vascular Surgery, Medical University of Innsbruck, Innsbruck, Austria.
- Nurea, Bordeaux, France.
- Department of Radiology, Fiona Stanley Hospital, Perth, Australia.
Abstract
This data article describes a publicly available dataset supporting the study "Towards Personalised Assessment of Abdominal Aortic Aneurysm Structural Integrity" [1], published in the International Journal for Numerical Methods in Biomedical Engineering. The dataset is hosted on the Zenodo data repository and provides patient-specific imaging, geometric, and biomechanical data for abdominal aortic aneurysm (AAA) analysis. The dataset consists of electrocardiogram (ECG)-gated, time-resolved three-dimensional computed tomography angiography (4D CTA) data acquired over a full cardiac cycle from 20 patients diagnosed with AAA. For each patient, the dataset includes up to ten 3D CTA image frames representing different phases of the cardiac cycle, including systolic and diastolic phases. Patient-specific AAA wall geometries and finite element (FE) meshes derived from the image data and used for biomechanical computations are provided. In addition, computational outputs are included for each patient, comprising wall strain and tension maps, as well as structural integrity index (SII) and relative structural integrity index (RSII) maps of the AAA wall, enabling further investigation of AAA wall structural integrity. The imaging data were acquired at three clinical centres: Fiona Stanley Hospital (Australia), Medical University of Innsbruck (Austria), and University Hospitals Leuven (Belgium). All data were processed at the Intelligent Systems for Medicine Laboratory, The University of Western Australia (ISML-UWA). AAA geometries were extracted through a workflow integrating AI-assisted segmentation and automated surface model generation from the resulting segmentations. Segmentation was performed using PRAEVAorta software (NUREA) for patients 1-10 and the nnInteractive extension within the 3D Slicer platform for patients 11-20, followed by surface and mesh generation using the BioPARR (Biomechanics-based Prediction of Aneurysm Rupture Risk) software package. All files are provided in widely used formats, including NRRD for image data, VTP for geometries and computational results, and Abaqus input files for finite element models and meshes. This dataset can be reused for benchmarking AAA biomechanical analysis pipelines, including image-based strain computation, stress analysis, and structural integrity assessment. More broadly, by providing the biomechanical computation results, it supports further investigation of AAA wall structural integrity in relation to the severity and progression of AAA disease.