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Erschienen in: Medical & Biological Engineering & Computing 7/2016

01.07.2016 | Original Article

Designing patient-specific 3D printed craniofacial implants using a novel topology optimization method

verfasst von: Alok Sutradhar, Jaejong Park, Diana Carrau, Tam H. Nguyen, Michael J. Miller, Glaucio H. Paulino

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 7/2016

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Abstract

Large craniofacial defects require efficient bone replacements which should not only provide good aesthetics but also possess stable structural function. The proposed work uses a novel multiresolution topology optimization method to achieve the task. Using a compliance minimization objective, patient-specific bone replacement shapes can be designed for different clinical cases that ensure revival of efficient load transfer mechanisms in the mid-face. In this work, four clinical cases are introduced and their respective patient-specific designs are obtained using the proposed method. The optimized designs are then virtually inserted into the defect to visually inspect the viability of the design . Further, once the design is verified by the reconstructive surgeon, prototypes are fabricated using a 3D printer for validation. The robustness of the designs are mechanically tested by subjecting them to a physiological loading condition which mimics the masticatory activity. The full-field strain result through 3D image correlation and the finite element analysis implies that the solution can survive the maximum mastication of 120 lb. Also, the designs have the potential to restore the buttress system and provide the structural integrity. Using the topology optimization framework in designing the bone replacement shapes would deliver surgeons new alternatives for rather complicated mid-face reconstruction.

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Metadaten
Titel
Designing patient-specific 3D printed craniofacial implants using a novel topology optimization method
verfasst von
Alok Sutradhar
Jaejong Park
Diana Carrau
Tam H. Nguyen
Michael J. Miller
Glaucio H. Paulino
Publikationsdatum
01.07.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 7/2016
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-015-1418-0

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