Background and Objectives: Orthodontics is a field that has seen significant advancements in recent years, with technology playing a crucial role in improving diagnosis and treatment planning. The study aimed to implement artificial intelligence to predict the arch width as a preventive measure to avoid future crowding in growing patients or even in adult patients seeking orthodontic treatment as a tool for orthodontic diagnosis. Materials and Methods: Four hundred and fifty intraoral scan (IOS) images were selected from orthodontic patients seeking treatment in private orthodontic centers. Real inter-canine, inter-premolar, and inter-molar widths were measured digitally. Two of the main machine learning models were used: the Python programming language and machine learning algorithms, implementing the data on k-nearest neighbor and linear regression. Results: After the dataset had been implemented on the two ML algorithms, linear regression and k-nearest neighbor, the evaluation metric shows that KNN gives better prediction accuracy than LR does. The resulting accuracy was around 99%. Conclusions: it is possible to leverage machine learning to enhance orthodontic diagnosis and treatment planning by predicting linear dental arch measurements and preventing anterior segment malocclusion.

Hard palate is regarded as an important part of the human skull, which contributes to the separation of the oral and nasal cavities. The aims of the study were to investigate the morphology of the hard palate in order to create a general guideline of three-dimensional values of the palate in a Kurdish sample in the city of Sulaimani as well as determining the possible correlations between different palatal parameters in class I malocclusion with the maxillary arch form and perimeter. A retrospective study design was adopted by collecting 100 study models of orthodontic patients aged 16–24 years old attending different private dental clinics in the city of Sulaimani seeking orthodontic management. In this study, three-dimensional palatal measurements including depth, length, and width were measured in an attempt to discover their correlation with each maxillary arch form and perimeter. Additionally, measurements of inter-molar width, inter-canine width, and arch perimeter were carried out. About two-thirds of those seeking orthodontic treatment were females. Nearly 80% of the study sample had narrow palate followed by 15 and 5% of intermediate palate and broad palate, respectively. In regard to arch form, almost 90% of subjects were with tapered maxillary arch form and 10% of them with oval arch form. Males had increased dimensions compared to females, with significant differences, except in palatal depth in the molar area, and palatine height index, in which females showed increased dimensions than males but the differences were statistically non-significant. A strong positive correlation was observed between arch form and canine depth. In regard to arch perimeter, a strong negative correlation was found with molar depth and a medium positive correlation with each of canine depth, palatal width, and palatal length.

(1) Background: Accurate diagnosis and treatment plans in orthodontics were facilitated by novel technologies. The prediction of occlusal problems is of utmost importance for clinicians. This present study aimed to find any possible correlation between unilateral and bilateral palatally impacted maxillary canine, palatal dimensions, and maxillary arch perimeter using digital measurements and determine the factors that could be used as predictors for maxillary palatal canine impaction. (2) Method: A cross-sectional study was conducted on cone-beam computed tomography images of orthodontic patients aged 15 to 25. Palatal dimensions and maxillary arch perimeter were digitally measured using Materialize Interactive Medical Image Control System. (3) Results: A significant difference was found between the case and the study groups regarding palatal depth, length, and arch perimeter, except for the palatal width. A weak correlation was reported in palatal depth and length with canine impaction, whereas the correlation was moderate concerning the arch perimeter. They can be used as predictors for palatal canine impaction. (4) Conclusion: Palatal dimensions and dental arch perimeter affect maxillary palatal canine impaction. Deficient arch perimeter, palatal depth, and length could be helpful in the prediction of maxillary palatal canine impaction.

The current study aimed to find a prediction equation to estimate the arch perimeter (AP) depending on various arch dimensions including intercanine width (ICW), intermolar width (IMW), interpremolar width (IPMW), and arch length (AL) in a sample of the Kurdish population in Sulaimani City. The study sample was 100 pairs of preorthodontic dental casts. Calculations of dental arch dimensions and perimeter were performed by a digital vernier. Statistical analysis was performed via using the SPSS version 25 software. The developed prediction equation for the upper arch was , whereas the equation for the lower arch was . Paired -test revealed no statistical difference between predicted and real arch perimeters. Two separate prediction equations for upper and lower arches were developed based on the arch length (AL) and intermolar width (IMW) for the maxillary arch, intermolar (IMW), and inter canine widths (ICW) for the lower arch. The developed equations could have further beneficial impacts on orthodontic diagnosis and treatment planning.

Background: Numerous studies have investigated the applicability of Pont’s index using a variety of selection criteria. The morphology of teeth and the shapes of the face are significantly influenced by racial, cultural, and environmental factors, so the current study focused on these demographics. Methods: This study is a retrospective study and included one hundred intraoral scanned images selected from patients seeking orthodontic treatment. Medit design software was used to obtain the real measurements and compare them to the predicted values from Pont’s index. Paired t tests were used to test the validity of Pont’s index, and regression equations were advocated to predict the inter-molar, inter-premolar, and anterior arch widths via SPSS version 25. Results: There were significant differences between the real anterior, inter-premolar, and inter-molar widths and the predicted values obtained from Pont’s index, and there were weak positive correlations between the real values and the predicted values from Pont’s index. Conclusions: Pont’s index is not reliable to predict the arch widths for the Kurdish population, and new formulas are advocated. Hence, space analysis, malocclusion treatment, and arch expansion therapy should all take into account these results. Therefore, the derived equations may have further positive effects on diagnoses and treatment preparation.

Background/Objectives: The precision and bonding reliability of space maintainers are critical to their clinical success longevity. This study aimed to evaluate and compare the fit accuracy and shear peel bond strength of digitally fabricated space maintainers—cobalt–chromium (Co-Cr) and polyetheretherketone (PEEK)—against conventional space maintainers. Methods: Seventy-eight space maintainer bands were fabricated—milled PEEK, selective laser-melted (SLM; an additive manufacturing technique) Co-Cr, and conventional stainless steel (SS)—and tested. Fit accuracy was evaluated on 39 bands by measuring the root mean square (RMS) deviation from a master model using digital 3D analysis. Shear peel bond strength (SPBS) was tested on another 39 samples using a universal testing machine, and the adhesive remnant index (ARI) was recorded after debonding. Statistical analyses included a Welch ANOVA for fit accuracy and the Kruskal–Wallis test for the SPBS test; the ARI was analyzed using Fisher’s exact test (significance level p < 0.05). Results: Digitally fabricated bands demonstrated significantly higher fit accuracy than the stainless steel bands (mean RMS deviation: Co-Cr = 0.151 mm, PEEK = 0.152 mm, SS = 0.344 mm; p < 0.001). Co-Cr and PEEK demonstrated comparable adaptation. In contrast, bond strength was significantly greater in Co-Cr (1.657 MPa) and SS (1.481 MPa) compared to PEEK (0.393 MPa). ARI distribution varied significantly across the three groups. Conclusions: Both milled PEEK and Co-Cr bands demonstrated excellent adaptation compared with conventional SS bands. However, Co-Cr exhibited reliable bonding performance, yet PEEK may require additional surface treatment or bonding optimization to enhance adhesion.