3D printed ascending aortic simulators with physiological fidelity for surgical simulation
| Autor: | Alexander Emmott, Ali Alakhtar, Rosaire Mongrain, Cornelius Hart, Kevin Lachapelle, Richard L. Leask |
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| Rok vydání: | 2021 |
| Předmět: |
Energy loss
3d printed Materials science Stiffness Health Informatics 030204 cardiovascular system & hematology Straight tube Surgical training Education 03 medical and health sciences 0302 clinical medicine Modeling and Simulation medicine 030212 general & internal medicine Surgical simulation medicine.symptom Material properties Original Research Biomedical engineering Tensile testing |
| Zdroj: | BMJ Simul Technol Enhanc Learn |
| ISSN: | 2056-6697 |
| DOI: | 10.1136/bmjstel-2021-000868 |
| Popis: | IntroductionThree-dimensional (3D) printed multimaterial ascending aortic simulators were created to evaluate the ability of polyjet technology to replicate the distensibility of human aortic tissue when perfused at physiological pressures.MethodsSimulators were developed by computer-aided design and 3D printed with a Connex3 Objet500 printer. Two geometries were compared (straight tube and idealised aortic aneurysm) with two different material variants (TangoPlus pure elastic and TangoPlus with VeroWhite embedded fibres). Under physiological pressure, β Stiffness Index was calculated comparing stiffness between our simulators and human ascending aortas. The simulators’ material properties were verified by tensile testing to measure the stiffness and energy loss of the printed geometries and composition.ResultsThe simulators’ geometry had no effect on measured β Stiffness Index (p>0.05); however, β Stiffness Index increased significantly in both geometries with the addition of embedded fibres (pConclusionWe developed dynamic ultrasound-compatible aortic simulators capable of reproducing distensibility of real aortas under physiological pressures. Using 3D printed composites, we are able to tune the stiffness of our simulators which allows us to better represent the stiffness variation seen in human tissue. These models are a step towards achieving better simulator fidelity and have the potential to be effective tools for surgical training. |
| Databáze: | OpenAIRE |
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