Using additive manufacturing for craniocervical reconstruction in traditionally challenging cases Article Swipe
YOU?
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· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4622183/v1
Study Design: Retrospective case series. Objectives The aim of this study was to evaluate the clinical outcomes and effectiveness of using 3D printed implants in upper cervical spine and occipitocervical junction surgery. Methods C2 primary tumor patients who required axial en bloc resection and other patients who required partial bone decompression using customized 3D printed implants or fixation devices for surgery were included. Evaluate the stability and surgical outcomes of 3D printed implants through perioperative and follow-up period. Results Five tumor patients underwent reconstruction using customized 3D printed artificial vertebral bodies, while another five patients with atlantoaxial joint dislocation underwent reduction and decompression using customized 3D printed internal fixation devices. The postoperative imaging results showed that the 3D printed structures had good immediate stability and had no signs of displacement or subsidence. Follow up showed that all five cases of vertebral body reconstruction had achieved fusion. Only one patient died one month after surgery due to infection and respiratory difficulties. Other patients showed excellent improvement in neurological function in follow up. Conclusions The use of 3D printed implants in surgery involving the occipitocervical area is a feasible and reliable alternative choice. 3D printed implants can improve the safety and accuracy of surgery, provide good immediate stability, have a low incidence of subsidence, fewer related complications during the follow-up period.
Related Topics
- Type
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- Language
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- OpenAlex ID
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Raw OpenAlex JSON
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https://doi.org/10.21203/rs.3.rs-4622183/v1Digital Object Identifier
- Title
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Using additive manufacturing for craniocervical reconstruction in traditionally challenging casesWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-07-22Full publication date if available
- Authors
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Shilin Xue, Nanfang Xu, Shanshan Liu, Ming Yan, Yinglun Tian, Kanlin Hung, Zhongjun Liu, Shenglin WangList of authors in order
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https://doi.org/10.21203/rs.3.rs-4622183/v1Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.21203/rs.3.rs-4622183/v1Direct OA link when available
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Computer science, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| institutions_distinct_count | 8 |
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