Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/113413
Título: Production of synthetic models for neuro-oncology training by additive manufacturing
Autores/as: Saceleanu, Vicentiu
Paz Hernández, Rubén 
Garcia Montagut, Carlos Joshua 
Rivero, Yamilet
Cîndea, Cosmin Nicodim
Cacciotti, Ilaria
Monzón Verona, Mario Domingo 
Clasificación UNESCO: 321308 Neurocirugía
321306 Cirugía experimental
Palabras clave: Additive Manufacturing
Brains With Tumors
Neurosurgery
Segmentation
Skull, et al.
Fecha de publicación: 2021
Publicación seriada: Applied Sciences (Switzerland)
Resumen: Neurosurgery is one of the medical specialties in which the practical training of students is more limiting since it requires a high degree of preparation for the interventions to be satisfactory. That is why the manufacture of synthetic models through additive manufacturing (AM) arises to develop the skills that the neurosurgeon requires. The present work is aimed at validating the use of AM for the neurosurgery training. To this regard, a meningioma case study was considered, and suitable materials and more appropriate AM technology were identified for a low-cost production of synthetic models of both skulls and brains with tumors. The skull was manufactured by material extrusion AM with two materials, a commercial composite filament composed of polylactic acid (PLA) with calcium carbonate (used in the area to be treated during the cutting process, due to its mechanical properties more comparable to those of the native bone, with 30% infill density) and standard PLA without additives (used in the rest of the model, with 20% infill density). On the other hand, different casting silicones in different proportions were tested under compression molding to find the best combination to mimic the brain and tumor. Ten synthetic models of a real-case meningioma were manufactured and used as training material by students in the neurosurgery sector, who rated the proposed training approach very highly, considering the employment of printed models as a key resource for improving their surgical skills.
URI: http://hdl.handle.net/10553/113413
ISSN: 2076-3417
DOI: 10.3390/app112411823
Fuente: Applied Sciences (Switzerland)[EISSN 2076-3417],v. 11 (24), (Diciembre 2021)
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