Fulltext

Accuracy of Computational Soft Tissue Predictions in Orthognathic Surgery From Three-Dimensional Photographs 6 Months After Completion of Surgery: A Preliminary Study of 13 Patients

Terzic, Andrej ; Combescure, Christophe ; Scolozzi, Paolo

In: Aesthetic Plastic Surgery, 2014, vol. 38, no. 1, p. 184-191

Add to personal list
    Title
    • Accuracy of Computational Soft Tissue Predictions in Orthognathic Surgery From Three-Dimensional Photographs 6 Months After Completion of Surgery: A Preliminary Study of 13 Patients
    Author
    • Terzic, Andrej. Service of Maxillo-Facial and Oral Surgery, Department of Surgery, Faculty of Medicine, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1205, Geneva, Switzerland
    • Combescure, Christophe. Department of Health and Community Medicine, Centre of Clinical Research and Division of Clinical Epidemiology, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
    • Scolozzi, Paolo. Service of Maxillo-Facial and Oral Surgery, Department of Surgery, Faculty of Medicine, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1205, Geneva, Switzerland
    Document Type
    • Postprint
    Language
    • English
    Published in
    • Aesthetic Plastic Surgery, 2014, vol. 38, no. 1, p. 184-191. Springer US; http://www.springer-ny.com
    Other Version
    OAI-PMH Identifier
    • oai:doc.rero.ch:324852
    Summary
    Background: This study aimed at a preliminary evaluation of the accuracy of computed three-dimensional (3D) predictions in orthognathic surgery by comparing predicted and real postoperative results. Methods: Pre- and postoperative 3D photographs and time-matching computed tomography (CT) and cone-beam CT scans of the face of 13 patients with dentofacial deformities were analyzed. Three-dimensional photographs were fused with preoperative CT data using dedicated software (3dMDvultus, version 2.2.0.8). Postoperative CT data were superposed on the preoperative skull. With an activated rendering function, the osteotomies were simulated in the preoperative CT data and the bony segments moved to their real postoperative position, resulting in a textured soft tissue prediction. This computed skin surface was compared with the real postoperative result by dividing the face into a surgically treated lower half and an untreated upper half. A statistical quantitative analysis of the surfaces was performed. Results: The mean differences between surfaces were +0.27mm for the untreated upper half and -0.64mm for the surgically treated lower half (p<0.001). Averaged distributions of absolute errors showed more discrepancies between predicted and real postoperative results in the lower half of the face. Errors exceeding 3mm were encountered in 4% of the upper halves versus 29.8% of the lower halves (p<0.001). Conclusions: The accuracy of a specific software platform for predicting 3D soft tissue changes after surgery was insufficient. Level of Evidence IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .