A rapid and intelligent designing technique for patient-specific and 3D-printed orthopedic cast
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Two point four out of 100 people suffer from one or more fractures in the course of average lifetimes. Traditional casts are featured as cumbersome structures that result in high risk of cutaneous complications. Clinical demands for developing a hygienic cast have gotten more and more attention. 3D printing technique is rapidly growing in the fabrication of custom-made rehabilitation tools. The objective of this study is to develop a rapid and intelligent modeling technique for developing patient-specific and hygienic orthopedic casts produced by 3D printing technologies.
A cast model is firstly created from a patient’s image to develop patient-specific features. A unique technique to creating geometric reference has been developed to perform detail modeling cast. The cast is modeled as funnel-shaped geometry to create smooth edges to prevent bruises from mild movements of injured limbs. Surface pattern includes ventilation structure and opening gap for hygienic purpose and wearing comfort. The cast can be adjusted to accommodate swelling from injured limbs during treatment. Finite element analysis (FEA) is employed to validate the mechanical performance of the cast structure and identify potential risk of the structural collapse due to concentrated stresses. The cast is fabricated by 3D printing technology using approval material.
The 3D-printed prototype is featured as super lightweight with 1/10 of weight in compared with traditional alternatives. Medical technicians with few experiences can design cast within 20 min using the proposed technique. The image-based design minimizes the distortion during healing process because of the best fit geometry. The highly ventilated structure develops hygienic benefits on reducing the risk of cutaneous complications and potentially improve treatment efficacy and increase patients’ satisfactions.
KeywordsOrthopedic cast 3D-printed Rapid Intelligent Patient-specific Hygienic Ventilated
The authors wish to acknowledge Teng Zhang, Matthew-Lun Wong, Ka-Long Ko, Ka-Hei Ko, Lily Ma, Jin-Peng Lee for their import contributions to the software development, and Nicholas K.W. Kwok, Winnie Chiu-Wing Chu, Jack Chun-Yiu Cheng for their great advices and helpful discussions.
The work described in this paper was supported by a grant from the Innovation and Technology Commission of the Hong Kong Special Administrative Region, China (Project No: ITS/149/14FP), and a grant from The Science, Technology and Innovation Commission of Shenzhen Municipality (Project No.: CXZZ20140606164105361), and a grant from the National Natural Science Foundation of China (Project No. 81271653).
HL conceived the design, carried out the method development, drafted and edited manuscript. LS carried out data collection and analysis, edited the manuscript. DW carried out the method design and development, edited and critically revised the manuscript. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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