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Rapid customization system for 3D-printed splint using programmable modeling technique – a practical approach

BACKGROUND: Traditional splinting processes are skill dependent and irreversible, and patient satisfaction levels during rehabilitation are invariably lowered by the heavy structure and poor ventilation of splints. To overcome this drawback, use of the 3D-printing technology has been proposed in rec...

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Detalles Bibliográficos
Autores principales: Li, Jianyou, Tanaka, Hiroya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5970151/
https://www.ncbi.nlm.nih.gov/pubmed/29882529
http://dx.doi.org/10.1186/s41205-018-0027-6
Descripción
Sumario:BACKGROUND: Traditional splinting processes are skill dependent and irreversible, and patient satisfaction levels during rehabilitation are invariably lowered by the heavy structure and poor ventilation of splints. To overcome this drawback, use of the 3D-printing technology has been proposed in recent years, and there has been an increase in public awareness. However, application of 3D-printing technologies is limited by the low CAD proficiency of clinicians as well as unforeseen scan flaws within anatomic models. A programmable modeling tool has been employed to develop a semi-automatic design system for generating a printable splint model. The modeling process was divided into five stages, and detailed steps involved in construction of the proposed system as well as automatic thickness calculation, the lattice structure, and assembly method have been thoroughly described. The proposed approach allows clinicians to verify the state of the splint model at every stage, thereby facilitating adjustment of input content and/or other parameters to help solve possible modeling issues. A finite element analysis simulation was performed to evaluate the structural strength of generated models. A fit investigation was applied on fabricated splints and volunteers to assess the wearing experience. RESULTS: Manual modeling steps involved in complex splint designs have been programed into the proposed automatic system. Clinicians define the splinting region by drawing two curves, thereby obtaining the final model within minutes. The proposed system is capable of automatically patching up minor flaws within the limb model as well as calculating the thickness and lattice density of various splints. Large splints could be divided into three parts for simultaneous multiple printing. CONCLUSIONS: This study highlights the advantages, limitations, and possible strategies concerning application of programmable modeling tools in clinical processes, thereby aiding clinicians with lower CAD proficiencies to become adept with splint design process, thus improving the overall design efficiency of 3D-printed splints.