# 3D Soft-Tissue Prediction Methodologies for Orthognathic Surgery--A Literature Review
## 3 Results
### Prediction Methodologies
#### 3.2.2 Works Based on Maximim Software (3D)  
In this section a collection of studies is presented considering patients' soft tissue prediction obtained with Maximim software (Medicim--Medical Image Computing, Mechelen, Belgium). This software, based on the mass tensor model algorithm (MTM), allows surgeons to determine bony movements and to see the effect of the procedure [19]. MTM has been introduced by [PERSON] et al. ; the geometry of the anatomical structure is discretized into a tetrahedral mesh in which the displacement vector at a generic internal point is defined as a function of vertices displacement vectors. The elastic force is written as a function of these same four vectors. The displacement for a set of mass points is set fixed and other model points will move as consequence of elastic forces due to the displacements of fixed points; finally, the new rest position of the free points is computed by integrating the Newtonian motion equation [20]. [PERSON] et al. [21] investigated the accuracy of Maximim using cone-beam computed tomography (CBCT) scans in pre- and post-surgery phases (6-12 months after surgery) for 13 patients subjected to Le Fort I surgery. A 3D mesh was generated from skeletal movements (predicted model). Subsequently, the mesh generated from the post-operative of the patient and the predicted model were compared to evaluate the accuracy of the prediction. The soft tissue was divided in different areas: nose, right and left nares, right and left paranasal regions upper and lower lip and chin. The absolute distance was calculated between the meshes for each region. For each facial region, the absolute distance was calculated between the meshes. In almost all the facial regions, the accuracy was significantly less than 3.00 mm (3.00 mm is clinically acceptable). The upper lip area was the exception; in fact, for this region, the accuracy was greater than 3.00 mm. In all cases, Maximim produced an over prediction of the new position of the upper lip. A possible reason could be a non-linear response of the upper lip to some hard-tissue movements and, consequently, the modeling algorithm used (MTM) hardly previewed this response. The conclusion of the authors was that the 3D soft tissue prediction for Le Fort I advancements produced by Maximim was in general clinically satisfactory, but it was associated with marked errors around the region of the upper lip. [PERSON] et al. evaluated the accuracy of Maximim for 3D simulation of soft tissue changes after bimaxillary osteotomy. The 3D rendered pre- and post-operative scans were matched. Segmented maxilla and mandible were aligned to the post-operative position. In order to calculate the error between the simulation and the actual post-operative condition, authors used 3D distance maps and cephalometric analysis. Concerning the facial profile, the mean absolute error between the 3D simulation and the actual post-operative facial profile was 0.81 \(\pm\) 0.22 mm for the face as a whole. In this study, the accuracies of the simulation (average absolute error \(\leq\)2 mm) for the whole face and for the upper lip, lower lip and chin sub regions were 100%, 93%, 90% and 95%, respectively. Authors affirmed that the MTM based soft tissue simulation is an accurate model for the prediction of soft tissue changes following bimaxillary surgery. The magnitude of skeletal movements influences the accuracy of the prediction; moreover, the age of the patient and the use of V-Y closure affect the precision of the predicted model. Low predictability on the upper and lower lip regions is registered once again [22]. The same authors evaluated Maximim performances for soft-tissue simulation in 100 patients underwent BSSO for mandibular advancement [23]. As in the previous case, the accuracy of the simulation was assessed with two methods, a 3D cephalometric analysis and a 3D distance map for the entire face and for specific regions of interest.