Soft-tissue changes measured with 3D software provides new insights for surgical predictions

Publication date: Available online 24 May 2017
Source:Journal of Oral and Maxillofacial Surgery
Author(s): Yu-Jen Chang, Antônio CO. Ruellas, Marilia S. Yatabe, Philip M. Westgate, Lucia HS. Cevidanes, Sarandeep S. Huja
PurposeEven though computer-aided craniofacial reconstructions allows for simulation of hard tissue changes, prediction of the final soft tissue facial changes remains a challenge. The purpose of this study was to evaluate three dimensions (3D) soft tissue changes in patients undergoing two-jaw orthognathic surgery.MethodsFor this retrospective cohort study, forty consecutive patients (11 men, 29 women; mean age 23.5 ± 4.9 years) that had undergone two-jaw orthognathic surgery were selected. We obtained medical/dental records from 3 weeks pre-surgery and 6 months post-surgery. We used image processing software to segment, superimpose, and quantify hard and soft tissue displacements in 3D before and after surgery at 15 paired locations. Soft-tissue and hard-tissue changes were determined through quantification of homologous landmark displacements between pre-surgical and post-surgical CT data. We measured the 3D soft/hard tissue changes and the antero-posterior, infero-superior and transverse components of the change. We quantified the ratios between soft to hard tissue change, and tested Pearson correlation between these changes and developed a predictive regression equation for observing at each location.ResultsWe found that soft tissue movement followed hard tissue movement with a correlation nearly equal to 0.9 (range: 0.85–0.98), suggesting that soft tissues of maxillary and mandibular landmarks were affected similarly by skeletal movements. Antero-posterior component of soft tissue three-dimensional displacements follow hard tissue movement with a ratio > 0.9 and with high correlation (r > 0.9) in the mandible.ConclusionThis study provides surgeons with a ratio of hard to soft tissue change and the strength of correlations that will allow more accurate predictions in 3D for both midline and lateral structures in bimaxillary orthognathic surgical cases. In addition, predictive equations for various landmarks were developed and can be utilized in computer-based prediction programs to aid treatment planning of soft tissue changes.



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