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Published on: September 19, 2018
Use of Phantoms to Enhance Mechanical Knowledge About Aortic Aneurysms: A Systematic Review
Louise Koskas1,2, Steeve Doizi3, Emma Parmentier4,2
1Arts et Métiers Institute of Technology, Cnam, LIFSE, Paris F-75013, France;Ecole Nationale Supérieure d'Arts et Métiers, 151 Boulevard de l'Hôpital, Paris 75013, France.
Abstract:
Aortic aneurysms represent a major public health issue, whose growth and rupture are driven by complex interactions between hemodynamics, wall mechanics, and biochemical factors. While the biological understanding of the arterial network has advanced, its mechanical behavior remains less explored. Experimental simulations, particularly those using arterial phantoms, are essential for approximating physiological conditions and improving biomechanical understanding, which may ultimately support a shift from statistical to individualized risk assessment. This systematic review aims to identify key parameters and evaluate advances in the phantom-based experimental research on aortic aneurysms. A systematic review was conducted in July 2025 following preferred reporting items for systematic reviews and meta-analyses guidelines, using the Medline database, without time or language restrictions. Studies were included if they focused on experimental research with aortic aneurysm phantoms. Computational studies, aortic dissections, and nonresearch applications were excluded. A narrative synthesis was applied due to outcome heterogeneity. From 2332 records, 68 studies were included: 21 investigated isolated arterial phantoms, and 47 used phantoms within circulatory loops. Arterial modeling is challenging due to the difficulty of reproducing both the wall mechanics and blood flow. Current models often emphasize certain features at the expense of overall biosimilarity. Future efforts should focus on integrating patient-specific geometries, realistic materials, and advanced circulatory systems to deepen the biomechanical understanding of aneurysms. This foundational work may ultimately inform more personalized strategies for monitoring and treatment.
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