# 3D Soft-Tissue Prediction Methodologies for Orthognathic Surgery--A Literature Review
## 3 Results
### Prediction Methodologies
#### 3.2.1 Works Based on Traditional (2D) Methodologies  
Since a certain number of 3D software currently available for clinical practice are based on algorithm developed to work on 2D and then adapted to 3D representation of data, a section dedicated to traditional soft-tissue prediction is introduced. Moreover, since many surgeons currently rely more on traditional techniques than on three-dimensional methods, it is reasonable to focus on the limitations of this technology; 2D analysis based on lateral cephalosporams is subject to errors caused by the impossibility to accurately locate points on both hard and soft tissue relying only on 2D anatomic structures [7]. Analysis performed on cephalosporams reported that reasonable prediction can be made on soft-tissue landmarks positions, but with low accuracy concerning the lips and particularly in the vertical prediction of displacements [8]. Moreover, the inaccuracy increases with a higher level of complexity of intervention, which leads to errors both in hard- and soft-tissue simulation [9]. In this section, we particularly focused on study assessing the accuracy of Dolphin Imaging, but we also reported studies that took into consideration other software. [PERSON] et al. worked on the quantification of the accuracy of Dolphin VTO (visual treatment objective) in predicting soft tissue changes in patients with a class III deformity and on the validation of its efficacy. In their study, authors considered fourteen patients receiving comprehensive orthodontic treatment and orthognathic surgery including both maxillary advancement and/or mandibular setback. Cephalometric tracing and analysis were performed with Dolphin Imaging software; pre- and post-operative and traced cephalometrics were superimposed using the cranial base as reference. The maxillary movements were recorded at the anterior nasal spine (ANS) and A point, while the mandibular changes were recorded at B point and pogonion (Pg) in both x and y axis. Subsequently, the pre-treatment profile pictures were superimposed to digitally-traced soft-tissue landmarks of pre-treatment cephalometric radiograph to initiate software VTO simulation (Figure 1). Finally, a prediction profile photograph generated by the software was compared to actual post-operative patient's profile photograph; coordinates of nine soft-tissue landmarks were used to quantify on each axis the differences between the predicted and the actual of patients. The results reported in this study are consistent with the prevision error calculated in previous works; Dolphin Imaging software was found to have a much larger standard deviation in the Y direction than in the X, with various degrees of accuracy in both directions for all soft tissue landmarks. The accuracy was 79% and 61% for X-axis and Y-axis respectively, with an acceptable error set at 2.00 mm. Furthermore, for these surgical cases, the least accurate prediction was the one concerning the lower lip region. In conclusion, authors affirmed that VTO program can be useful for rough movement previsions during surgical planning, but surgeons cannot rely on it for precise surgical movements (measurement range lower than 1.00 mm) [10]. Figure 1: Super-imposition of pre- and post- and traced cephalometric tracing showing advancement of the maxilla and setback of the mandible [10]. In the study of [PERSON] et al., the treatment planning for each patient was constituted on the base of clinical and cephalometric evaluations, and pre-operative study models. All patients were treated with pre- and post-surgical fixed orthodontic appliances. Scanned images of cephalometric radiographs were processed using Dolphin Imaging software; the Ricketts and Steiner analysis was selected to start the digitization. To compare actual outcome and software simulation, firstly the superimposition of pre- and post-operative cephalograms was performed on the sella-nasion plane registered at sella.