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      Accuracy of virtually planned mandibular distraction in a pediatric case series

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          Lengthening the Human Mandible by Gradual Distraction

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            3D planning in orthognathic surgery: CAD/CAM surgical splints and prediction of the soft and hard tissues results - our experience in 16 cases.

            The aim of this article is to determine the advantages of 3D planning in predicting postoperative results and manufacturing surgical splints using CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) technology in orthognathic surgery when the software program Simplant OMS 10.1 (Materialise(®), Leuven, Belgium) was used for the purpose of this study which was carried out on 16 patients. A conventional preoperative treatment plan was devised for each patient following our Centre's standard protocol, and surgical splints were manufactured. These splints were used as study controls. The preoperative treatment plans devised were then transferred to a 3D-virtual environment on a personal computer (PC). Surgery was simulated, the prediction of results on soft and hard tissue produced, and surgical splints manufactured using CAD/CAM technology. In the operating room, both types of surgical splints were compared and the degree of similitude in results obtained in three planes was calculated. The maxillary osteotomy line was taken as the point of reference. The level of concordance was used to compare the surgical splints. Three months after surgery a second set of 3D images were obtained and used to obtain linear and angular measurements on screen. Using the Intraclass Correlation Coefficient these postoperative measurements were compared with the measurements obtained when predicting postoperative results. Results showed that a high degree of correlation in 15 of the 16 cases. A high coefficient of correlation was obtained in the majority of predictions of results in hard tissue, although less precise results were obtained in measurements in soft tissue in the labial area. The study shows that the software program used in the study is reliable for 3D planning and for the manufacture of surgical splints using CAD/CAM technology. Nevertheless, further progress in the development of technologies for the acquisition of 3D images, new versions of software programs, and further studies of objective data are necessary to increase precision in computerised 3D planning. Copyright © 2011 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
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              Manufacturing splints for orthognathic surgery using a three-dimensional printer.

              A new technique for producing splints for orthognathic surgery using a 3D printer is presented. After 3-dimensional (3D) data acquisition by computerized tomography (CT) or cone-beam computerized tomography (CBCT) from patients with orthognathic deformations, it is possible to perform virtual repositioning of the jaws. To reduce artifacts, plaster models were scanned either simultaneously with the patient during the 3D data acquisition or separately using a surface scanner. Importing and combining these data into the preoperative planning situation allows the transformation of the planned repositioning and the ideal occlusion. Setting a virtual splint between the tooth rows makes it possible to encode the repositioning. After performing a boolean operation, tooth impressions are subtracted from the virtual splint. The "definitive" splint is then printed out by a 3D printer. The presented technique combines the advantages of conventional plaster models, precise virtual 3D planning, and the possibility of transforming the acquired information into a dental splint.
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                Author and article information

                Contributors
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                Journal
                Journal of Cranio-Maxillofacial Surgery
                Journal of Cranio-Maxillofacial Surgery
                Elsevier BV
                10105182
                February 2021
                February 2021
                : 49
                : 2
                : 154-165
                Article
                10.1016/j.jcms.2020.12.012
                33423894
                1e13e538-7321-4aa8-bc83-1926dfeb6b6b
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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