Peer-reviewed veterinary case report
3D synthetic models of healthy aortas for research
By Bosnjak D et al.·2026·View original on Europe PMC →
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Original publication title: SynthAorta: A 3D Mesh Dataset of Parametrized Physiological Healthy Aortas.
Plain-English summary
This research focuses on creating a new set of computer models of the aorta, which is the large artery that carries blood from the heart. The goal is to better understand how the shape of the aorta affects its function and potential health issues. The researchers developed a dataset called SynthAorta, which includes synthetic models that accurately represent the aorta's structure while being easy to use for simulations and studies. These models are based on statistical data and can help bridge the gap between medical practice and engineering. Overall, this work provides valuable tools for future research on aortic health and disease.
Abstract
The effects of the aortic geometry on its mechanics and blood flow, and subsequently on aortic pathologies, remain largely unexplored. The main obstacle lies in obtaining patient-specific aorta models, an extremely difficult procedure in terms of ethics and availability, segmentation, mesh generation, and all of the accompanying processes. Contrastingly, idealized models are easy to build but do not faithfully represent patient-specific variability. Additionally, a unified aortic parametrization in clinic and engineering has not yet been achieved. To bridge this gap, we introduce a new set of statistical parameters to generate synthetic models of the aorta. The parameters possess geometric significance and fall within physiological ranges, effectively bridging the disciplines of clinical medicine and engineering. Smoothly blended realistic representations are recovered with convolution surfaces. These enable high-quality visualization and biological appearance, whereas the structured mesh generation paves the way for numerical simulations. The only requirement of the approach is one patient-specific aorta model and the statistical data for parameter values obtained from the literature. The output of this work is SynthAorta, a dataset of ready-to-use synthetic, physiological aorta models, each containing a centerline, surface representation, and a structured hexahedral finite element mesh. The meshes are structured and fully consistent between different cases, making them imminently suitable for reduced order modeling and machine learning approaches.
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Search related cases →Original publication on Europe PMC: https://europepmc.org/article/MED/40824977