Browsing by Author "Hackett, Matthew G"

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    Supporting data for "3D Printed Anisotropic Tissue Simulants with Embedded Fluid Capsules for Medical Simulation and Training"
    (2025-02-10) Somayaji, Adarsh; Lawler, Matthew S; Gong, Alex T; Fuenning , Zachary M; Roach, Victoria A; S., Athira B; Traina, David J; Speich, Jason R; Wang, Ruikang K; Hackett, Matthew G; Hananel, David M; Sweet , Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C.; McAlpine Research Group
    Human tissues are primarily composed of collagen and elastin fiber networks that exhibit directional mechanical properties which are not replicable by conventional tissue simulants manufactured via casting. Here, we 3D print tissue simulants which incorporate anisotropic mechanical properties through the manipulation of infill voxel shape and dimensions. A mathematical model for predicting the anisotropy of single and multi-material structures with orthogonal infill patterns is developed. We apply this methodology to generate conformal printing toolpaths for replicating the structure and directional mechanics observed in native tissue within 3D printed tissue simulants. Further, a method to embed fluid-filled capsules within the infill structure of these tissue simulants to mimic blood is also presented. The improvements in simulation quality when using 3D printed anisotropic tissue simulants over conventional tissue simulants is demonstrated via a comparative acceptability study. These advances open new avenues for the manufacture of next-generation tissue simulants with high mechanical fidelity for enhanced medical simulation and training.