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The advantages of advanced computer-assisted diagnostics and three-dimensional preoperative planning on implant position in orbital reconstruction
Advanced three-dimensional (3D) diagnostics and preoperative planning are the first steps in computer-assisted surgery (CAS). They are an integral part of the workflow, and allow the surgeon to adequately assess the fracture and to perform virtual surgery to find the optimal implant position. The go...
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Published in: | Journal of cranio-maxillo-facial surgery 2018-04, Vol.46 (4), p.715-721 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Advanced three-dimensional (3D) diagnostics and preoperative planning are the first steps in computer-assisted surgery (CAS). They are an integral part of the workflow, and allow the surgeon to adequately assess the fracture and to perform virtual surgery to find the optimal implant position. The goal of this study was to evaluate the accuracy and predictability of 3D diagnostics and preoperative virtual planning without intraoperative navigation in orbital reconstruction.
In 10 cadaveric heads, 19 complex orbital fractures were created. First, all fractures were reconstructed without preoperative planning (control group) and at a later stage the reconstructions were repeated with the help of preoperative planning. Preformed titanium mesh plates were used for the reconstructions by two experienced oral and maxillofacial surgeons. The preoperative virtual planning was easily accessible for the surgeon during the reconstruction. Computed tomographic scans were obtained before and after creation of the orbital fractures and postoperatively. Using a paired t-test, implant positioning accuracy (translation and rotations) of both groups were evaluated by comparing the planned implant position with the position of the implant on the postoperative scan.
Implant position improved significantly (PÂ |
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ISSN: | 1010-5182 1878-4119 |
DOI: | 10.1016/j.jcms.2018.02.010 |