Lateral cephalometric parameters among Arab skeletal classes II and III patients and applying machine learning models.

BACKGROUND: The World Health Organization considers malocclusion one of the most essential oral health problems. This disease influences various aspects of patients' health and well-being. Therefore, making it easier and more accurate to understand and diagnose patients with skeletal malocclusions is necessary. OBJECTIVES: The main aim of this research was the establishment of machine learning models to correctly classify individual Arab patients, being citizens of Israel, as skeletal class II or III. Secondary outcomes of the study included comparing cephalometric parameters between patients with skeletal class II and III and between age and gender-specific subgroups, an analysis of the correlation of various cephalometric variables, and principal component analysis in skeletal class diagnosis. METHODS: This quantitative, observational study is based on data from the Orthodontic Center, Jatt, Israel. The experimental data consisted of the coded records of 502 Arab patients diagnosed as Class II or III according to the Calculated_ANB. This parameter was defined as the difference between the measured ANB angle and the individualized ANB of Panagiotidis and Witt. In this observational study, we focused on the primary aim, i.e., the establishment of machine learning models for the correct classification of skeletal class II and III in a group of Arab orthodontic patients. For this purpose, various ML models and input data was tested after identifying the most relevant parameters by conducting a principal component analysis. As secondary outcomes this study compared the cephalometric parameters and analyzed their correlations between skeletal class II and III as well as between gender and age specific subgroups. RESULTS: Comparison of the two groups demonstrated significant differences between skeletal class II and class III patients. This was shown for the parameters NL-NSL angle, PFH/AFH ratio, SNA angle, SNB angle, SN-Ba angle. SN-Pg angle, and ML-NSL angle in skeletal class III patients, and for S-N (mm) in skeletal class II patients. In skeletal class II and skeletal class III patients, the results showed that the Calculated_ANB correlated well with many other cephalometric parameters. With the help of the Principal Component Analysis (PCA), it was possible to explain about 71% of the variation between the first two PCs. Finally, applying the stepwise forward Machine Learning models, it could be demonstrated that the model works only with the parameters Wits appraisal and SNB angle was able to predict the allocation of patients to either skeletal class II or III with an accuracy of 0.95, compared to a value of 0.99 when all parameters were used ("general model"). CONCLUSION: There is a significant relationship between many cephalometric parameters within the different groups of gender and age. This study highlights the high accuracy and power of Wits appraisal and the SNB angle in evaluating the classification of orthodontic malocclusion.

Craniofacial Cephalometric Morphology in Polish Adolescents with Cleft Palate Only.

Background: Cephalometric studies indicate that craniofacial morphology in patients with cleft palate only (CPO) differs from other forms of orofacial clefts and healthy patients. Planning orthodontic treatment for patients with different craniofacial deformities requires knowledge on the craniofacial complex. The aim of the present study was to describe the cephalometric craniofacial morphology in adolescents with cleft palate only compared to generally healthy orthodontic patients. Methods: The study comprised 100 lateral cephalograms (taken in the years 2003-2020) of Polish patients with cleft palate only aged from 11.1 to 14.2 (mean age 12.43 y) and a matched control group of 100 children without orofacial clefts aged 12-14 (mean age 12.25). All digital images were analyzed in specialized cephalometric software. Results: Statistically significantly lower values of both SNA (p < 0.001) and ANB (p < 0.001) were found in the study group versus the control group. Mandibular line to cranial base angle (ML-NSL) as well as maxillary base to cranial base (NL-NSL) were significantly higher in the CPO group. Both the maxilla and mandible were rotated distally in CPO. Moreover, the intermaxillary vertical angle (ML-NL) was reduced in CPO. Mandibular angle in CPO was significantly higher (p = 0.005), reflecting posterior mandibular rotation. Conclusions: In adolescents with CPO, maxillary deficiency is found, without a severe sagittal jaw discrepancy, with a slight compensatory lingual inclination of the lower incisors. Mandibular deficiency in CPO is concurrent with posterior rotation and an increased mandibular angle.

In utero nicotine exposure affects murine palate development.

OBJECTIVES: Despite data linking smoking to increased risk of fetal morbidity and mortality, 11% of pregnant women continue to smoke or use alternative nicotine products. Studies confirm that nicotine exposure during pregnancy increases the incidence of birth defects; however, little research has focused on specific anatomic areas based on timing of exposure. We aim to determine critical in utero and postnatal periods of nicotine exposure that affect craniofacial development, specifically palate growth. Malformation of the palatal structures can result in numerous complications including facial growth disturbance, or impeding airway function. We hypothesized that both in utero and postnatal nicotine exposure will alter palate development. MATERIALS AND METHODS: We administered pregnant C57BL6 mice water supplemented with 100 µg/mL nicotine during early pregnancy, throughout pregnancy, during pregnancy and lactation, or lactation only. Postnatal day 15 pups underwent micro-computed tomography (µCT) analyses specific to the palate. RESULTS: Resultant pups revealed significant differences in body weight from lactation-only nicotine exposure, and µCT investigation revealed several dimensions affected by lactation-only nicotine exposure, including palate width, palate and cranial base lengths, and mid-palatal suture width. CONCLUSIONS: These results demonstrate the direct effects of nicotine on the developing palate beyond simple tobacco use. Nicotine exposure through tobacco alternatives, cessation methods, and electronic nicotine delivery systems (ENDS) may disrupt normal growth and development of the palate during development and the postnatal periods of breastfeeding. Due to the recent dramatic increase in the use of ENDS, future research will focus specifically on this nicotine delivery method.

Comparative analysis of deep-learning-based bone age estimation between whole lateral cephalometric and the cervical vertebral region in children.

Bone age determination in individuals is important for the diagnosis and treatment of growing children. This study aimed to develop a deep-learning model for bone age estimation using lateral cephalometric radiographs (LCRs) and regions of interest (ROIs) in growing children and evaluate its performance. This retrospective study included 1050 patients aged 4-18 years who underwent LCR and hand-wrist radiography on the same day at Pusan National University Dental Hospital and Ulsan University Hospital between January 2014 and June 2023. Two pretrained convolutional neural networks, InceptionResNet-v2 and NasNet-Large, were employed to develop a deep-learning model for bone age estimation. The LCRs and ROIs, which were designated as the cervical vertebrae areas, were labeled according to the patient's bone age. Bone age was collected from the same patient's hand-wrist radiograph. Deep-learning models trained with five-fold cross-validation were tested using internal and external validations. The LCR-trained model outperformed the ROI-trained models. In addition, visualization of each deep learning model using the gradient-weighted regression activation mapping technique revealed a difference in focus in bone age estimation. The findings of this comparative study are significant because they demonstrate the feasibility of bone age estimation via deep learning with craniofacial bones and dentition, in addition to the cervical vertebrae on the LCR of growing children.

Effect of Fixed and Removable Functional Therapy on Mandibular Anterior Bone Structures: A Fractal Analysis Study.

(1) Background and aim: The effects of functional therapies on dentoalveolar and skeletal structures have been investigated in orthodontics for many years. The aim of this retrospective study was to evaluate the changes caused by fixed and removable functional therapy in the mandibular anterior trabecular structures using fractal dimension (FD) analysis. (2) Methods: A total of 60 patients with skeletal and dental class II malocclusion were included in the study and three groups were formed: the untreated control group (CG), the Forsus fatigue-resistant device group (FFRDG), and the Monoblock group (MBG). Bone areas of interest determined in the buccoapical of the mandibular incisors and the symphysis in the lateral cephalometric radiographs taken before (T0) and after (T1) functional therapy were evaluated using FD analysis. The relationship between the FD and IMPA (Incisor Mandibular Plane Angle) angles was evaluated. Parametric and nonparametric tests were used in statistical analysis according to normality distribution. The statistical significance level was determined as p < 0.05. (3) Results: There was no statistically significant difference between the FD values of all groups at T0 (p > 0.05). At T1, buccoapical FD values were significantly lower in FFRDG and MBG compared to the control group (p < 0.05), while symphyseal FD values were not found to be significant (p > 0.05). The IMPA angle was significantly lower in the FFRDG and MBG than in the control group at T0, while it was higher at T1 (p < 0.05). While a significant negative correlation was observed between the IMPA angle and buccoapical FD values in both FFRDG and MBG (p < 0.05), it was not observed with the symphysis FD values (p > 0.05). (4) Conclusions: Trabecular changes caused by functional therapy in the mandibular anterior bone can be evaluated on lateral cephalometric radiographs with FD analysis. It was concluded that orthodontists should ensure controlled changes in the IMPA angle during functional therapy, especially for the decreases in FDs seen in the buccoapical alveolar region due to the forward movement of the mandibular incisors.

DC-YOLOv5-based target detection algorithm for cervical vertebral maturation.

The cervical vertebral maturation (CVM) method is essential to determine the timing of orthodontic and orthopedic treatment. In this paper, a target detection model called DC-YOLOv5 is proposed to achieve fully automated detection and staging of CVM. A total of 1800 cephalometric radiographs were labeled and categorized based on the CVM stages. We introduced a model named DC-YOLOv5, optimized for the specific characteristics of CVM based on YOLOv5. This optimization includes replacing the original bounding box regression loss calculation method with Wise-IOU to address the issue of mutual interference between vertical and horizontal losses in Complete-IOU (CIOU), which made model convergence challenging. We incorporated the Res-dcn-head module structure to enhance the focus on small target features, improving the model's sensitivity to subtle sample differences. Additionally, we introduced the Convolutional Block Attention Module (CBAM) dual-channel attention mechanism to enhance focus and understanding of critical features, thereby enhancing the accuracy and efficiency of target detection. Loss functions, precision, recall, mean average precision (mAP), and F1 scores were used as the main algorithm evaluation metrics to assess the performance of these models. Furthermore, we attempted to analyze regions important for model predictions using gradient Class Activation Mapping (CAM) techniques. The final F1 scores of the DC-YOLOv5 model for CVM identification were 0.993, 0.994 for mAp0.5 and 0.943 for mAp0.5:0.95, with faster convergence, more accurate and more robust detection than the other four models. The DC-YOLOv5 algorithm shows high accuracy and robustness in CVM identification, which provides strong support for fast and accurate CVM identification and has a positive effect on the development of medical field and clinical diagnosis.

Craniomaxillofacial landmarks detection in CT scans with limited labeled data via semi-supervised learning.

Background: Three-dimensional cephalometric analysis is crucial in craniomaxillofacial assessment, with landmarks detection in craniomaxillofacial (CMF) CT scans being a key component. However, creating robust deep learning models for this task typically requires extensive CMF CT datasets annotated by experienced medical professionals, a process that is time-consuming and labor-intensive. Conversely, acquiring large volume of unlabeled CMF CT data is relatively straightforward. Thus, semi-supervised learning (SSL), leveraging limited labeled data supplemented by sufficient unlabeled dataset, could be a viable solution to this challenge. Method: We developed an SSL model, named CephaloMatch, based on a strong-weak perturbation consistency framework. The proposed SSL model incorporates a head position rectification technique through coarse detection to enhance consistency between labeled and unlabeled datasets and a multilayers perturbation method which is employed to expand the perturbation space. The proposed SSL model was assessed using 362 CMF CT scans, divided into a training set (60 scans), a validation set (14 scans), and an unlabeled set (288 scans). Result: The proposed SSL model attained a detection error of 1.60 ± 0.87 mm, significantly surpassing the performance of conventional fully supervised learning model (1.94 ± 1.12 mm). Notably, the proposed SSL model achieved equivalent detection accuracy (1.91 ± 1.00 mm) with only half the labeled dataset, compared to the fully supervised learning model. Conclusions: The proposed SSL model demonstrated exceptional performance in landmarks detection using a limited labeled CMF CT dataset, significantly reducing the workload of medical professionals and enhances the accuracy of 3D cephalometric analysis.

Evaluation of the facial profile of skeletal Class III patients undergoing camouflage orthodontic treatment: a retrospective study.

Objective: To identify objective metrics for evaluating the esthetics of facial profiles in skeletal Class III patients undergoing camouflage orthodontic treatment. Methods: Eighty Asian-Chinese patients classified as skeletal Class III were included. Thirty cephalometric measurements of pre- and posttreatment cephalograms were analyzed. Ten orthodontists assigned visual analog scale (VAS) scores to the pre- and posttreatment profiles based on standardized lateral photographs. Correlations between subjective VAS scores and objective measurements were assessed using Pearson correlation and stepwise multiple linear regression analysis. Results: Lower incisor (L1) protrusion, nasolabial angle, lower lip-E line distance, SNB angle, and L1 to AP plane were significantly correlated with VAS scores of pretreatment profiles of skeletal Class III patients. Factors such as retraction of the lower incisor, increased interincisal angle and overjet, reduction of lower lip-E line distance, as well as augmentation of the Z angle and nasolabial angle were significantly correlated with the changes in VAS scores post-camouflage orthodontic treatment. Stepwise multiple linear regression analysis revealed that pretreatment nasolabial angle, changes in the lower lip-E line distance, and pretreatment Pog-NB distance were the key factors influencing the posttreatment facial profile esthetics of skeletal Class III patients with camouflage orthodontic treatment. Conclusion: Several cephalometric measurements correlate with subjective facial esthetic evaluations of skeletal Class III patients. Changes in lower lip prominence, the pretreatment nasolabial angle, and Pog-NB distance are the main factors related to facial esthetics in skeletal Class III patients after camouflage orthodontic treatment.

Genetic Insights into Skeletal Malocclusion: The Role of the FBN3 rs7351083 SNP in the Romanian Population.

Background and Objectives: irregularities in the growth and development of the jawbones can lead to misalignments of maxillary and mandibular structures, a complex condition known as skeletal malocclusion, one of the most common oral health problems. Skeletal malocclusions, particularly Class II and Class III, can significantly affect facial appearance, chewing efficiency, speech, and overall oral health, often requiring orthodontic treatment or surgery to correct. These dentofacial anomalies are influenced by genetic and environmental factors and exhibit diverse phenotypic expressions. Materials and Methods: in this study, we investigated the correlation between the rs7351083 SNP of the FBN3 gene that encodes a member of the fibrillin protein family and malocclusion risk in a group of 57 patients from Romania. Results: the results shed light on the relationship between the selected genetic marker and the investigated dentofacial disorder, revealing a positive association between the reference allele (A) and Class II and that the alternate allele (G) is associated with Class III. Conclusions: cephalometric analysis revealed no significant differences among genotypes, suggesting that while genetic factors are implicated in malocclusion, they may not directly affect cephalometric parameters or that the sample size was too small to detect these differences. The discovery of an A > T transversion in one individual with a Class II deformity underscores the genetic diversity within the population and the necessity of comprehensive genotyping to uncover rare genetic variants that might influence craniofacial development and the risk of malocclusion. This study highlights the need for larger studies to confirm these preliminary associations.

Sagittal cranial projections dataset extracted from CBCT volumes corrected to natural head position in a mixed ethnicity population.

This dataset features 200 sagittal projection images derived from Cone Beam Computed Tomography (CBCT) scans, corrected according to the Natural Head Position (NHP) guidelines proposed by Fredrik Lundström and Anders Lundström. The images originate from orthodontic patients in Cali, Valle del Cauca, Colombia, encompassing both initial phases and ongoing treatments. The dataset is divided into two groups: 100 images from female subjects (CoF) and 100 from male subjects (CoM), facilitating gender-specific studies. The dataset is accompanied by an Excel file ``Data info.xlsx'' that details the rotation angles in the axial (Yaw), coronal (Roll), and sagittal (Pitch) planes, along with the pixel size and image dimensions. This detailed documentation supports the replication of studies and aids in the interpretation of cephalometric analyses. Corrections made to align the images with NHP standards involve adjustments in the three main anatomical planes using points from the frontozygomatic suture (Fz) in the axial and coronal planes, and sella (S) and nasion (N) for the sagittal plane.

Large Language Models Diagnose Facial Deformity.

Purpose: This study examines the application of Large Language Models (LLMs) in diagnosing jaw deformities, aiming to overcome the limitations of various diagnostic methods by harnessing the advanced capabilities of LLMs for enhanced data interpretation. The goal is to provide tools that simplify complex data analysis and make diagnostic processes more accessible and intuitive for clinical practitioners. Methods: An experiment involving patients with jaw deformities was conducted, where cephalometric measurements (SNB Angle, Facial Angle, Mandibular Unit Length) were converted into text for LLM analysis. Multiple LLMs, including LLAMA-2 variants, GPT models, and the Gemini-Pro model, were evaluated against various methods (Threshold-based, Machine Learning Models) using balanced accuracy and F1-score. Results: Our research demonstrates that larger LLMs efficiently adapt to diagnostic tasks, showing rapid performance saturation with minimal training examples and reducing ambiguous classification, which highlights their robust in-context learning abilities. The conversion of complex cephalometric measurements into intuitive text formats not only broadens the accessibility of the information but also enhances the interpretability, providing clinicians with clear and actionable insights. Conclusion: Integrating LLMs into the diagnosis of jaw deformities marks a significant advancement in making diagnostic processes more accessible and reducing reliance on specialized training. These models serve as valuable auxiliary tools, offering clear, understandable outputs that facilitate easier decision-making for clinicians, particularly those with less experience or in settings with limited access to specialized expertise. Future refinements and adaptations to include more comprehensive and medically specific datasets are expected to enhance the precision and utility of LLMs, potentially transforming the landscape of medical diagnostics.

Cephalometric Evaluation of Children with Short Stature of Genetic Etiology: A Review.

Introduction: A plethora of biological molecules regulate chondrogenesis in the epiphyseal growth plate. Disruptions of the quantity and function of these molecules can manifest clinically as stature abnormalities of various etiologies. Traditionally, the growth hormone/insulin-like growth factor 1 (IGF1) axis represents the etiological centre of final stature attainment. Of note, little is known about the molecular events that dominate the growth of the craniofacial complex and its correlation with somatic stature. Aim: Given the paucity of relevant data, this review discusses available information regarding potential applications of lateral cephalometric radiography as a potential clinical indicator of genetic short stature in children. Materials and Methods: A literature search was conducted in the PubMed electronic database using the keywords: cephalometric analysis and short stature; cephalometric analysis and achondroplasia; cephalometric analysis and hypochondroplasia; cephalometric analysis and skeletal abnormalities; cephalometr* and SHOX; cephalometr* and CNP; cephalometr* and ACAN; cephalometr* and CNVs; cephalometr* and IHH; cephalometr* and FGFR3; cephalometr* and Noonan syndrome; cephalometr* and "Turner syndrome"; cephalometr* and achondroplasia. Results: In individuals with genetic syndromes causing short stature, linear growth of the craniofacial complex is confined, following the pattern of somatic short stature regardless of its aetiology. The angular and linear cephalometric measurements differ from the measurements of the average normal individuals and are suggestive of a posterior placement of the jaws and a vertical growth pattern of the face. Conclusions: The greater part of the existing literature regarding cephalometric measurements in short-statured children with genetic syndromes provides qualitative data. Furthermore, cephalometric data for individuals affected with specific rare genetic conditions causing short stature should be the focus of future studies. These quantitative data are required to potentially establish cut-off values for reference for genetic testing based on craniofacial phenotypes.

Evaluation of Sella Turcica Variations in Lateral Cephalometric Radiographs and its Association with Malocclusion.

Objectives: Understanding the shape and size of the sella turcica may help predict future orthodontic treatment needs related to skeletal malocclusion. This study aims to assess different morphological types of the sella turcica in lateral cephalometric radiographs and its correlation with malocclusion, as well as the relationship between gender and linear measurements of sella turcica. Materials and Methods: The lateral cephalometric radiographs of 410 volunteers (111 men and 299 women) aged 8 to 30 years were evaluated. The patients were divided into three groups based on their skeletal growth patterns (cl I, II, and III). Then the anatomical shape and linear dimensions of sella turcica were assessed. Measurements were made using Adobe Photoshop Version: 20.0.0 software, and data analysis was performed by IBM SPSS Statistics version 25. Results: The following morphologies were observed: normal (37.8%), oblique anterior wall (9.3%), double contour of the floor (21.5%), sella turcica bridge (8.8%), irregularity (notching) in the posterior part of sella turcica (16.6%), and pyramidal shape of the dorsum sellae (6.1%). No statistically significant relationship was found between sella turcica variations and skeletal malocclusion. The correlation between female sex with the diameter (p=0.027) and depth values (p=0.035) of sella turcica was statistically significant. There was no statistically significant difference (p>0.05) in length based on gender. Conclusion: The most morphological type reported was normal sella turcica (37.8%). Anatomical variations of sella turcica had no association with malocclusion. The most considerable depth and diameter of sella turcica were found in women.

Obstacles behind the innovation- a peek into Artificial intelligence in the field of orthodontics - A Literature review.

This article explores the potential benefits of Artificial Intelligence (AI) and Machine Learning (ML) in Orthodontics, highlighting their efficiency and accuracy. While AI has influenced various fields, its application in orthodontics is just being explored. With the innovation comes challenges that are associated with AI. This article emphasizes the documented role of AI and its associated barriers in Orthodontics. Methods: Literature research is performed in data sources like online library journals PubMed and MEDLINE, NIH (National Institute of Health), Science Direct, WILEY online library, and ORAL HEALTH GROUP, among others. Our review was carried out on articles published to date. Conclusion: The findings in this review highlight the considerable promise of employing AI within orthodontics. However, the emergence of AI also brings forth fresh challenges that must be considered. Striking a balance between innovation and addressing these challenges is crucial for advancing orthodontics.

Assessing the Impact of AI-Enhanced Diagnostic Tools on the Treatment Planning of Orthodontic Cases: An RCT.

Background: Orthodontic treatment planning involves the precise assessment of dental and skeletal anomalies, which can be facilitated by AI-enhanced diagnostic tools. Materials and Methods: A total of 100 orthodontic cases were included in this RCT. Patients were randomly assigned to two groups: an AI-enhanced diagnostic group and a traditional diagnostic group. The AI-enhanced diagnostic group underwent orthodontic assessment with the aid of AI-powered software, which provided automated cephalometric analysis, 3D model evaluations, and treatment suggestions. The traditional diagnostic group received conventional diagnostic assessments by orthodontists. The primary outcome measures included treatment planning accuracy, treatment time, and patient satisfaction. Secondary outcomes included the number of appointments required and treatment cost. Results: The AI-enhanced diagnostic group demonstrated a significantly higher accuracy in treatment planning compared to the traditional diagnostic group (P < 0.05). The AI group also required fewer appointments (mean ± SD: 10.2 ± 2.1 vs. 12.8 ± 3.4) and had a shorter treatment time (mean ± SD: 14.6 ± 3.2 months vs. 18.9 ± 4.5 months) (P < 0.001 for both comparisons). Additionally, patient satisfaction scores were higher in the AI group (mean ± SD: 9.2 ± 0.6 vs. 8.1 ± 0.8) (P < 0.001). However, the AI-enhanced diagnostic group had a slightly higher treatment cost. Conclusion: AI-enhanced diagnostic tools significantly enhance the accuracy of treatment planning in orthodontic cases, leading to reduced treatment time, fewer appointments, and increased patient satisfaction.

Comparative Analysis of Pharyngeal Airway Changes Following All Four Versus All Five Premolar Extractions in Orthodontic Treatments: A Cephalometric Study.

BACKGROUND: Orthodontic treatment, particularly involving premolar extractions, has been a subject of ongoing debate within the orthodontic community. The impact of such interventions on the pharyngeal airway, a critical component of the respiratory system, remains a topic of exploration. OBJECTIVE: This retrospective cephalometric study aims to investigate changes in pharyngeal airway dimensions following orthodontic treatment involving either all four or all five premolar extractions. METHODS: A sample of 68 participants, extracted from orthodontic records, underwent cephalometric analysis to quantify changes in pharyngeal airway dimensions. The study compared two groups: those treated with all four premolar extractions (n=34) and those treated with all five premolar extractions (n=34). Cephalometric radiographs taken before and after treatment were analyzed, focusing on airway width, length, and volume. RESULTS: Preliminary findings indicate significant changes in airway dimensions within each group. In the all four premolar extraction group, there was a statistically significant decrease in airway width (p=0.02) and volume (p=0.04). Similarly, the all five premolar extraction group exhibited significant reductions in airway width (p=0.03) and volume (p=0.02). However, the between-group comparisons revealed no significant differences in changes between the two groups. CONCLUSION: This study sheds light on the intricate relationship between orthodontic interventions, specifically premolar extractions, and changes in pharyngeal airway dimensions. While significant changes were observed within each group, the lack of significant differences between the all four and all five premolar extraction groups raises intriguing questions about the specific impact of premolar extraction patterns on the upper airway.

Evaluation of the soft tissue facial profile in different skeletal malocclusions in relation to age.

BACKGROUND: The aim of the study was to assess the thickness of the soft tissue facial profile (STFP) in relation to the skeletal malocclusion, age and gender. METHODS: All patients, aged 7-35 years, who were seeking orthodontic treatment at the Department of Orthodontics, Medical University of Warsaw between 2019 and 22 were included in the study. All patients had lateral head radiographs taken before the treatment. The cephalometric analysis was performed including the STFP analysis. The patients were allocated to one of six groups based on age and skeletal relations (ANB angle). The minimum number of patients in each group was 60 with equal gender distribution. The STFP analysis included ten linear measurements. RESULTS: A total of 300 patients were included in the study and allocated to five groups. Group 6 (growing patients with skeletal Class III malocclusion) was not included in the study as it failed to achieve the assumed group size. There were significant differences in the thickness of the STFP in relation to the skeletal malocclusions. Adults with skeletal Class III malocclusion had significantly thicker subnasal soft tissues compared to patients with skeletal Class I and Class II malocclusions. The thickness of the lower lip in patients with Class II skeletal malocclusion was significantly bigger compared to the other groups. Children and adolescents with Class II malocclusions had thicker lower lip in comparison to the group with Class I malocclusion. The majority of the STFP measurements were significantly smaller in children and adolescents compared to adults. The thickness of the STFP in males was significantly bigger in all age groups compared to females. CONCLUSIONS: The thickness of facial soft tissues depends on the patient's age and gender. The degree of compensation of the skeletal malocclusion in the STFP may be a decisive factor during orthodontic treatment planning regarding a surgical approach or a camouflage treatment of skeletal defects.

Comparison of Soft Tissue Chin Thickness in Adult Patients With Various Mandibular Divergence Patterns.

Objective This study aimed to compare the soft tissue chin (STC) thickness at different levels in patients presenting for orthodontic treatment with different vertical facial types. Materials and methods This comparative cross-sectional study was conducted at Sharif Medical & Dental College, Lahore, Pakistan, on 195 subjects. Patients presenting for orthodontic treatment, both genders, aged from 18 to 32 years, and Pakistani nationals were included. Patients with any craniofacial deformity, syndrome, cleft lip and palate, previous orthodontic or orthognathic treatment, and multiple missing teeth and prostheses in edentulous areas were excluded. Vertical facial patterns and STC thickness were recorded from pre-treatment lateral cephalograms. One-way analysis of variance (ANOVA) was applied to compare STC among various vertical facial patterns. Post-hoc analysis was done using the Tukey test. Results There were 126 females (64.62%) and 69 males (35.38%). The mean age was 21.66 ± 3.44 years. All three soft tissue chin thickness distances significantly differed among vertical facial patterns (p<0.001). Multiple comparisons show that the distance between soft and hard tissue pogonion was insignificant between low and normal angle facial heights (p=0.5). Similarly, no significant difference was observed for the distance between soft and hard tissue menton in low and normal angle subjects (p=0.4). The rest of the multiple comparisons were statistically significant (p<0.05). Conclusion The STC thickness is significantly associated with vertical facial divergence. While planning orthognathic surgery or genioplasty of the mandible, due consideration should be given to vertical divergence of the face to avoid unwanted facial changes.

LOW CERTAINTY OF EVIDENCE SUPPORTS THE APPLICATION OF (AI) FOR THE AUTOMATIC DETECTION OF CEPHALOMETRIC LANDMARKS WITH PROSPECTS FOR IMPROVEMENTS.

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179. doi:10.1007/s10278-022-00766-w. SOURCE OF FUNDING: The study was financed in part by the Coordenacao de Aperfeicoamentode Pessoal de Nivel Superior-Brazil (CAPES)-Finance Code 001. TYPE OF STUDY/DESIGN: Systematic review and meta-analysis.

Incisor and Soft Tissue Characteristics of Adult Bimaxillary Protrusion Patients among Different Skeletal Anteroposterior Classifications.

The objective of this study was to investigate the upper incisors (U1), lower incisors (L1), and soft tissue profiles of bimaxillary protrusion (BM) adult patients among skeletal Class I (BM1), II (BM2) and III (BM3). Understanding these characteristics would be useful for incisor and lip diagnostics in different skeletal classifications. Fourteen linear and twelve angular variables of the incisors and lips were evaluated in 214 lateral cephalograms (BM1 = 91, BM2 = 84, BM3 = 39). ANOVA and Bonferroni tests compared the measurements. BM1 and BM3 exhibited a greater U1 position and U1 inclination than the norms, while BM2 presented only a greater U1 position than the norms but normal U1 inclination. BM1 and BM3 had a significantly greater U1 position than BM2. BM1 and BM2 demonstrated a greater L1 position and L1 inclination than the norms, whereas BM3 displayed only a greater L1 position than the norms but normal L1 inclination. BM2 had the most anterior L1 position, whereas BM3 had the least anterior position. Only BM2 had a longer anterior dental height (ADH) than the norms, while BM1 and BM3 had a normal ADH and the significantly shortest ADH, respectively. Only BM1 had a normal upper incisor display at rest (U1R), while BM2 and BM3 displayed an increased and decreased U1R, respectively, with significant differences among the three groups. The most significantly protruded upper and lower lips were presented in BM2, but these were exhibited the least in BM3. The most significant acute nasolabial angle (NLA) was found in BM3, whereas BM2 presented the least acute NLA. A normal lip-chin-throat angle (LCTA) was observed in BM1 and BM3, while only BM2 had a greater LCTA than the norms. The most significant obtuse LCTA was found in BM2, while BM3 had the least obtuse LCTA. Therefore, both U1 and L1 in all groups presented protrusion and proclination, except for U1 in BM2, while L1 in BM3 exhibited normal inclination. The ADH and U1R were increased in BM2 but decreased in BM3. The most acute NLA was found in BM3, whereas the least acute was found in BM2. The most obtuse LCTA was in BM2, while the least was in BM3.