3D Soft Tissue Changes After 2-jaw Orthognathic-surgery

Objectives: 3D simulated navigation in orthognathic surgery is a new technique which simulate the surgery, and provides a bony "guiding splint" to place the bony segments into the precise planned position. The objective of this study is to analyze changes in soft tissue in response to surgical repositioning after 2 jaw orthognathic surgery.
Methods: Adults (n=40,11M/29F, age 23.5±4.9yrs) patients undergoing 2-jaw orthognathic surgery were selected retrospectively while excluding craniofacial syndromes. Each patient had complete records, including pre-surgical and 6 months post-surgical. We used two open-source software, ITK-SNAP and 3D-Slicer to segment, superimpose and quantify hard and soft tissue changes with surgery (midsagittal changes, e.g. ANS/tip of Nose,A/Subnasle,Upper-central-incisor, B/Si, and lateral landmarks such as tip of maxillary canine root to corresponding soft tissue landmarks).
Results: We analyzed the correlation between the hard and soft tissue landmarks, the ratio of soft to hard tissue change and developed a predictive regression equation (3D SOFT TISSUE=a0+a1*BONEAP+a2*BONEVer.+a3*BONELat.) for each landmark in 3 planes of space. We further subdivided the cases as Symmetry/Asymmetry and Clockwise/Counter-Clockwise rotators.
In 3D, AP soft tissue movement follows hard tissue with a ratio nearly equal to unity (>0.9) and with high correlation(r>0.9) in the mandible (B/Si,Pog,Me). Maxillary vertical bony changes have higher correlation to soft tissues specifically in counter clockwise rotators and symmetry groups vs. the other groups. Mandibular lateral-direction bony movement are correlated (r>0.7) with corresponding soft tissue change. We also found that the AP component of the A/Subnasale ratio was 0.59 and different from the 0.33 reported in the 2D literature.


Conclusions: Our study provides 3D-quantitative data for the orthognathic surgery planning, which has not been available previously. There are differences in the maxillary and mandibular soft tissue responses to bony segment repositioning and the predictive regression equations generated can be utilized in computer based prediction programs.