Frontiers in surgery · 2026
In silico workflow for validation of patient-specific 3D-printed casts in forearm fracture immobilization.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Bartos Marton, Pokorni Agoston Jakab, Hajnal Benjamin, Turbucz Mate, Horvath-Szekely Laszlo, Molnár Karsa Ferenc, Orosz Nándor, Bigdon Sebastian Frederick, Eltes Peter Endre
Аннотация
BACKGROUND: This paper aims to establish an in silico workflow for biomechanical assessment of patient-specific 3D-printed forearm casts using finite element analysis, and to apply this workflow to compare a novel computationally designed point-of-care cast with a commercially available state-of-the-art cast.
METHODS: A finite element model of a human forearm was generated from CT data, incorporating bones, soft tissues, and a simulated distal radius and ulna fracture. Two cast designs were virtually applied: a commercial cast (AA_CAST) and a point-of-care cast (POC_CAST) featuring a hexagonal lattice. The POC_CAST was simulated with three 3D-printing materials: Acrylonitrile Butadiene Styrene, Resin, and Polyamide. Six physiological loading conditions were assessed with the proximal end constrained: flexion, extension, radial and ulnar deviation (400 N load), and pronation and supination (1 Nm moment). Maximum von Mises stress in the casts and at the fracture surfaces, as well as maximum fracture displacement, were evaluated.
RESULTS: The AA_CAST model demonstrated superior fracture stabilization, showing consistently lower maximum von Mises stresses and displacements across all loading conditions. The POC_CAST exhibited its highest internal stresses during extension (36-37 MPa) and the largest fracture displacements during radial deviation (0.28-0.36 mm). In the POC_CAST simulations, printing material influenced fracture displacement but had negligible effect on maximum cast stress. All simulated configurations maintained fracture displacement below 0.4 mm, indicating adequate immobilization performance.
CONCLUSION: The in silico workflow proved effective for biomechanical evaluation of patient-specific 3D-printed casts and enabled direct comparison between a novel POC design and a commercial standard. While the commercial cast provided superior stabilization in simulation, the POC_CAST also demonstrated mechanically sound performance. These findings support the workflow as a robust tool for preclinical assessment, iterative design, and material selection for orthopedic devices.
METHODS: A finite element model of a human forearm was generated from CT data, incorporating bones, soft tissues, and a simulated distal radius and ulna fracture. Two cast designs were virtually applied: a commercial cast (AA_CAST) and a point-of-care cast (POC_CAST) featuring a hexagonal lattice. The POC_CAST was simulated with three 3D-printing materials: Acrylonitrile Butadiene Styrene, Resin, and Polyamide. Six physiological loading conditions were assessed with the proximal end constrained: flexion, extension, radial and ulnar deviation (400 N load), and pronation and supination (1 Nm moment). Maximum von Mises stress in the casts and at the fracture surfaces, as well as maximum fracture displacement, were evaluated.
RESULTS: The AA_CAST model demonstrated superior fracture stabilization, showing consistently lower maximum von Mises stresses and displacements across all loading conditions. The POC_CAST exhibited its highest internal stresses during extension (36-37 MPa) and the largest fracture displacements during radial deviation (0.28-0.36 mm). In the POC_CAST simulations, printing material influenced fracture displacement but had negligible effect on maximum cast stress. All simulated configurations maintained fracture displacement below 0.4 mm, indicating adequate immobilization performance.
CONCLUSION: The in silico workflow proved effective for biomechanical evaluation of patient-specific 3D-printed casts and enabled direct comparison between a novel POC design and a commercial standard. While the commercial cast provided superior stabilization in simulation, the POC_CAST also demonstrated mechanically sound performance. These findings support the workflow as a robust tool for preclinical assessment, iterative design, and material selection for orthopedic devices.