AAA-100: A Curated Dataset of 3D Watertight Abdominal Aortic Aneurysm Models



An abdominal aortic aneurysm (AAA) is a local dilatation of the abdominal aorta exceeding 30 mm that might rupture, with fatal outcomes in 70-80% of cases. Personalized 3D models of AAAs, including surrounding vasculature such as iliac and renal arteries play an important role in tailored clinical decision-making for AAA patients. Models could be used for, e.g., AAA growth modeling, stentgraft sizing and positioning for endovascular aorta repair (EVAR) procedures, or 3D printing for surgical practice. Extracting high-quality 3D arterial models from imaging modalities such as computed tomography angiography (CTA) is a time-consuming and challenging problem. For downstream applications such as computational fluid dynamics (CFD) or shape analysis, models should have sub-voxel accuracy, be watertight, and adhere to topological constraints. We present the AAA-100 dataset, containing 100 detailed 3D AAA models with consistent anatomical boundaries acquired semi-automatically from pre-operative CTA scans. These models span a wide range of possible AAA pathology. Moreover, all models are carefully curated to be anatomically and topologically correct. A detailed description of the data set and file structure is provided in description.pdf. We kindly ask you to cite the following works when using the AAA-100 dataset in your research Alblas, D., Suk, J., Brune, C., Yeung, K. K., & Wolterink, J. M. (2023). SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks. arXiv preprint arXiv:2311.05400. Rygiel, P., Alblas, D., Brune, C., Yeung, K. K., & Wolterink, J. M. (2024). Global Control for Local SO (3)-Equivariant Scale-Invariant Vessel Segmentation. arXiv preprint arXiv:2403.15314.
Date made available5 Apr 2024

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