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Proceedings Paper

Feasibility of fabricating personalized 3D-printed bone grafts guided by high-resolution imaging
Author(s): Abigail L. Hong; Benjamin T. Newman; Arbab Khalid; Olivia M. Teter; Elizabeth A. Kobe; Malika Shukurova; Rohit Shinde; Daniel Sipzner; Robert J. Pignolo; Jayaram K. Udupa; Chamith S. Rajapakse
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Paper Abstract

Current methods of bone graft treatment for critical size bone defects can give way to several clinical complications such as limited available bone for autografts, non-matching bone structure, lack of strength which can compromise a patient’s skeletal system, and sterilization processes that can prevent osteogenesis in the case of allografts. We intend to overcome these disadvantages by generating a patient-specific 3D printed bone graft guided by high-resolution medical imaging. Our synthetic model allows us to customize the graft for the patients’ macro- and microstructure and correct any structural deficiencies in the re-meshing process. These 3D-printed models can presumptively serve as the scaffolding for human mesenchymal stem cell (hMSC) engraftment in order to facilitate bone growth. We performed highresolution CT imaging of a cadaveric human proximal femur at 0.030-mm isotropic voxels. We used these images to generate a 3D computer model that mimics bone geometry from micro to macro scale represented by STereoLithography (STL) format. These models were then reformatted to a format that can be interpreted by the 3D printer. To assess how much of the microstructure was replicated, 3D-printed models were re-imaged using micro-CT at 0.025-mm isotropic voxels and compared to original high-resolution CT images used to generate the 3D model in 32 sub-regions. We found a strong correlation between 3D-printed bone volume and volume of bone in the original images used for 3D printing (R2 = 0.97). We expect to further refine our approach with additional testing to create a viable synthetic bone graft with clinical functionality.

Paper Details

Date Published: 13 March 2017
PDF: 6 pages
Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 101380O (13 March 2017); doi: 10.1117/12.2254475
Show Author Affiliations
Abigail L. Hong, Univ. of Pennsylvania (United States)
Benjamin T. Newman, Univ. of Pennsylvania (United States)
Arbab Khalid, Univ. of Pennsylvania (United States)
Olivia M. Teter, Univ. of Pennsylvania (United States)
Elizabeth A. Kobe, Univ. of Pennsylvania (United States)
Malika Shukurova, Univ. of Pennsylvania (United States)
Rohit Shinde, Univ. of Pennsylvania (United States)
Daniel Sipzner, Univ. of Pennsylvania (United States)
Robert J. Pignolo, Perelman School of Medicine, Univ. of Pennsylvania (United States)
Jayaram K. Udupa, Univ. of Pennsylvania (United States)
Chamith S. Rajapakse, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 10138:
Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications
Tessa S. Cook; Jianguo Zhang, Editor(s)

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