# 3D Soft-Tissue Prediction Methodologies for Orthognathic Surgery--A Literature Review
## 3 Results
### Prediction Methodologies
#### 3.2.2 Works Based on Maximim Software (3D)
The second error reported by authors was in the differences between actual and planned measurements for SNA (angle between Sella, Nasion and A point) and for SNB (angle between Sella, Nasion and B point), with \(p\) = 0.008 and \(p\) = 0.006 respectively. In the opinion of the authors, virtual planning inaccuracies were principally caused by the difficulty of simulate the soft tissue changes. Moreover, they concluded that virtual planning could not relieve surgeons of the necessity of monitoring jaws movements intraoperatively and of a real time supervision of planned and actual outcome, despite a high level of accuracy for most of the analyzed parameters [25]. The double blind prospective study performed by [PERSON] et al. had the aim of providing a comparison between a traditional planning method and a 3D planning performed with Maxilim, both for hard and soft tissue [26]. In their analysis, authors considered 66 patients affected by class II or class III angle malocclusion underwent bimaxillary osteotomy (46 patients), BSSO (17) patients and LeFort I osteotomy (3 patients). Genioplasty was performed on 28 patients. For the 2D planning, clinical facial examination, lateral and frontal cephalospor were taken; 17 and 16 cephalometric landmarks were considered for 3D and for 2D respectively, to perform the validation of both 2D and 3D planning. The traditional planning was performed with Onyx Ceph Version 3.1.111 and the analyses of accuracy was performed by measuring projections on x and y axis of distances between the 16 selected points on the planned and on the actual post-operative. In the case of the 3D planning, the landmarks were defined in three dimensions and the planned and post-operative data were aligned. Distances between the 17 cephalometric points defined on planned and actual models were evaluated in depth, height and distance in the sagittal plane. As a result of the analysis, authors reported that, for hard tissue planning, the mean differences occurring between actual and planned outcome evaluated at cephalometric points were 1.71 mm and 1.42 mm in the horizontal direction and 1.69 mm and 1.44 mm in the vertical direction, for 2D and 3D respectively. Concerning soft tissue displacements, the mean values computed in the horizontal direction were 2.29 mm for traditional planning and 1.48 for Maxilim prediction; in the vertical direction, authors noted mean values of 2.07 mm and 1.46 mm for 2D and 3D techniques respectively. These evaluations led authors to conclude that there was a statistically significant difference in the soft-tissue prediction between the two considered methods (chi-squared test and independent t-test were used to determine statistical significance, with \(p\) < 0.005); particularly, the 3D approach seemed to be more predictive than the traditional one. No statistically significant differences were reported for hard tissue planning. The conclusion reached by authors was that, concerning the soft tissue prediction, the 3D planning approach here performed with Maxilim software led to a more accurate planning than the traditional method, even with disadvantages such as the cost of the software and of the CBCT scans. Moreover, a higher learning time must be considered when planning with the 3D method. In the authors' opinion, 3D planning will not replace the traditional prediction if those negative aspects are not addressed. The study by [PERSON] et al. focused on the accuracy of soft-tissue profile changes simulated by Maxilim with respect to the accuracy obtained with Dolphin. Particularly, the goal of the comparison was to assess if the 3D prevision was more accurate than the 2D one. A \"natural head distance\" was defined as distance between suprasternal notch and soft tissue pogonion to replicate patients' head position. On lateral cephalogram, soft tissue and hard tissue landmarks (15 and 25 points respectively) were located; soft tissue predictions were generated with Dolphin and Maxilim.