Backgrounds The present study was designed to define: (1) which are the less predictable OTM with Invisalign aligners when the treatment plan is designed by expert operators, (2) if the presence and shape of attachments influence the predictability of OTM and (3) if patients’ demographics influence OTM predictability. The sample comprises 79 prospectively recruited patients (mean age 30.8 years; SD 12.0; 23 M, 56 F), treated by expert operators with an average of 27 aligners (SD 15) in the maxillary arch and 25 aligners (SD 11) in the mandibular arch. Post-treatment digital models and final virtual treatment plan models were exported from ClinCheck® software as STL files and subsequently imported into Geomagic Qualify ®software, to compare final teeth positions. The differences were calculated and tested for statistical significance for each tooth in the mesial–distal, vestibular–lingual and occlusal–gingival directions, as well as for angulation, inclination and rotation. In addition, the statistical significance of categorical variables was tested. Results The lack of correction was significant for all movements and in all group of teeth (P < 0.01) except for the rotation of maxillary first molar. The prescribed OTM, the group of teeth and movement, the frequency of aligner change and the use of attachment influence the outcome. The greatest discrepancies in predicted and achieved tooth position were found for angular movements and rotation of teeth characterized by round-shaped crowns, for a ratio of approximately 0.4° per 1° prescribed. Optimized attachments for upper canines and lower premolar rotation seem not working properly. Second molar movements are mostly unexpressed. Furthermore, changing the aligner every 14 days will reduce the lack of correction of the 12% with respect to 7 days aligner change. Conclusions Predictability of orthodontic movement with aligners still has limitations related to the biomechanics of the system: the shape of some attachments and the characteristics of aligner material need to be redefined. However, the results of this study allow to properly design the virtual treatment plan, revealing how much overcorrection is needed and which attachments are most effective.

Due to technical aspects of Cone Beam Computed Tomography (CBCT), the automatic methods for bone segmentation are not widely used in the clinical practice of endodontics, orthodontics, oral and maxillofacial surgery. The aim of this study was to evaluate method’s accuracy for bone segmentation in CBCT data sets. The sliding three dimensional (3D) window, histogram filter and Otsu’s method were used to implement the automatic segmentation. The results of automatic segmentation were compared with the results of segmentation performed by an experienced oral and maxillofacial surgeon. Twenty patients and their forty CBCT data sets were used in this study (20 preoperative and 20 postoperative). Intraclass Correlation Coefficients (ICC) were calculated to prove the reliability of surgeon segmentations. ICC was 0.958 with 95% confidence interval [0.896 ... 0.983] in preoperative data sets and 0.931 with 95% confidence interval [0.836 ... 0.972] in postoperative data sets. Three basic metrics were used in order to evaluate the accuracy of the automatic method—Dice Similarity Coefficient (DSC), Root Mean Square (RMS), Average Distance Error (ADE) of surfaces mismatch and additional metric in order to evaluate computation time of segmentation was used. The mean value of preoperative DSC was 0.921, postoperative—0.911, the mean value of preoperative RMS was 0.559 mm, postoperative—0.647 mm, the ADE value of preoperative cases was 0.043 mm, postoperative—0.057 mm, the mean computational time to perform the segmentation was 46 s. The automatic method showed clinically acceptable accuracy results and thus can be used as a new tool for automatic bone segmentation in CBCT data. It can be applied in oral and maxillofacial surgery for performance of 3D Virtual Surgical Plan (VSP) or for postoperative follow-up.