Evaluation of Incisor Position in a Sample of Orthodontic Patients.

BACKGROUND: To achieve a successful result, the orthodontist must use a systematic approach to plan the orthodontic treatment. Defining the correct position of the upper and lower incisors and evaluating their relationship with intermaxillary discrepancy and facial divergence have been recognized as the starting point for the diagnostic decision regarding extractions and anchorage requirements. The aim of our study was to analyze the relationship between intermaxillary discrepancy (ANPg^), mandibular inclination (SN^GoGn), lip incompetence, and the positioning of the upper and lower incisors (UIPs and LIPs) in a group of orthodontic patients. This retrospective study included 290 lateral cephalograms in 122 males (42.1%) and 168 females (57.9%) aged 8 to 53 years (median 14; interquartile range IQR 12-17). Data were analyzed by means of one-way Analysis of Variance (ANOVA) and linear regression analysis. RESULTS: This study showed a statistically significant increase in LIP values in patients with lip incompetence (p < 0.001). Moreover, the distribution of LIPs in groups with various SN^GoGn and ANPg^ angles was significantly different (p < 0.001). The regression analysis also showed a positive association between the LIP and SN^GoGn and between the LIP and ANPg^. CONCLUSION: The LIP presented a statistically significant difference in patients with and without lip incompetence, which varied significantly in subjects with different sagittal malocclusions and vertical face patterns.

Comparison between twin block appliance and mandibular advancement on clear aligners in the improvement of airway dimension: incremental versus maximum bite advancement.

Objective: The aim of the present retrospective study was to compare the changes resulting from treatment using the MA and the TB with special regard to the oro-and naso-pharyngeal sagittal airway dimensions in subjects with dentoskeletal Class II malocclusions and positive history of Sleep Disorder Breathing (SDB) diagnosed through the Pediatric Sleep Questionnaire (PSQ). Materials and methods: This retrospective study involved 2 groups of subjects: patients treated with Twin Block (TB group: n = 22, 10 males, 12 females; mean age 12.0 ± 1.3 years) and patients treated with Mandibular Advancement (MA group: n = 23, 11 males, 12 females; mean age 12.2 ± 1.1 years). Pretreatment (T1) and posttreatment (T2) lateral cephalograms were analyzed. All patients underwent the PSQ to diagnose SDB. Results: In both treated groups there was an increase in the airways dimensions and an improvement in symptoms related SDB. The statistical comparison of the changes between T1 and T2 in the TB group showed a significant increment in upper airway size (PNS-AD2, +1.50 mm + -3.30; McNamara's upper pharynx dimension, +2.21 + -4.21) after active treatment. The MA group showed similar results during active treatment with a significant increase in both upper (PNS-AD2, +2.72 + -2.65; McNamara's upper pharynx dimension, +2.97 + -3.07) and lower (PNS-AD1, +2.17 mm + -3.54) airway size. Conclusions: Despite the different structure of these two devices and the different advancement protocols, both appliances were valuable as a suitable treatment option for Class II patients with respiratory disorders, inducing an increase of upper and lower airway size and a significant reduction in diurnal symptoms.

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.

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 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.

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.

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.

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.

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.

Correlation Between Cephalometric Values and Soft Tissue Profile in Class I and Class II Adult Patients based on Vertical Patterns.

Objective: To compare soft tissue profile variations between Class I and Class II adult patients due to three vertical skeletal facial patterns (normodivergent, hypodivergent and hyperdivergent) and determine which skeletal variation has the most significant impact on soft tissue profile. Methods: Retrospective soft tissue profile analysis was performed on lateral cephalograms of 131 adult patients. The analysis was divided into two categories correlated with subnasal and general soft tissue profiles. The sample was divided based on two sagittal skeletal patterns (Class I and II) and three vertical groups. In addition, comparisons were made between males and females. Viewbox 4 was used for the analysis. Descriptive, comparative, and correlation statistics were performed using SPSS software. Results: Statistically significant inter-gender differences were found at the subnasal profile level, but not at the general profile level. No significant differences were observed when comparing subnasal profiles for the sagittal groups. However, significant differences were observed at the level of the general profile, especially at the level of Z-angle, lower lip, and chin prominence. In the vertical groups, hyperdivergent facial patterns had significant differences at the level of subnasal and general profiles compared with other vertical facial patterns. Conclusion: Females had more convex subnasal profiles than males. Hyperdivergent facial patterns had an impact on both general and subnasal soft tissue profiles. The sagittal dimension affected only the general soft tissue profile. Therefore, changes in the vertical dimension had the greatest impact on facial esthetics.

Evaluation of mandibular growth in a prepubertal Class I and Class II population: a longitudinal analysis.

OBJECTIVE: This study aims to identify the presence, timing, and magnitude of a prepubertal mandibular growth spurt in a Class I and Class II population. METHODS: From the Burlington and Iowa Growth study of the AAOF Craniofacial Growth Legacy Collection, 83 Class I subjects (37 females and 46 males) and 32 Class II subjects (18 males and 14 females) were identified, as having at least seven consecutive annual lateral cephalograms taken from 5 to 11 years of age. Only subjects with a normodivergent facial pattern were considered. A customized cephalometric analysis was performed, and total mandibular length, defined as the distance between Condylion (Co) and Gnathion (Gn), was calculated. RESULTS: Overall, a significant early peak of mandibular growth was present in all the subjects analysed both in Class I (4.69 mm for males and 4.18 mm for females; P < .05) and in Class II (5.85 mm for males and 4.05 mm for females; P < .05). No differences between males and females were found for the timing of this peak (7 years for Class I and Class II females and 7 years for Class I and 6.5 years for Class II males). In males, a significantly larger peak was observed in Class II than Class I subjects (P = .007). LIMITATIONS: The main limitations of this study were the impossibility of using a suitable growth indicator to identify the timing of the early mandibular growth peak and the limited Class II records retrievable. CONCLUSION: This investigation suggests that a prepubertal mandibular growth peak is consistently present in both Class I and Class II males and females of clinically significant magnitude. Despite that, chronological age confirms to be unsuitable to identify this peak.

A Comparative Analysis of Skeletal and Dental Parameters in Bilateral Cleft Lip and Palate vs. Non-bilateral Cleft Lip and Palate Patients in the Central Indian Population: A NemoCeph Study.

Introduction Orthodontic diagnosis and treatment planning encounter distinctive complexities when dealing with cleft lip and palate anomalies. This research endeavors to thoroughly examine skeletal and dental characteristics through cephalometric analyses among individuals with bilateral cleft lip and palate (BCLP) within the central Indian population. Due to anatomical variations and growth constraints, traditional cephalometric mean values derived from standard population studies are often inadequate for these cases. Advanced technology, such as NemoCeph (Nemotech, Madrid, Spain) software, enhances measurement accuracy. Methods Fifty patients, including 25 with BCLP and 25 without BCLP, aged 10 to 18, were selected for this cross-sectional study. Lateral cephalograms were traced and analyzed using NemoCeph software. Skeletal and dental parameters were measured, and a comparison was made between BCLP patients and the general population. Statistical analysis was conducted using the Student's unpaired t-test. Both SPSS Statistics Version 24.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism Version 7.0 (GraphPad Software, San Diego, CA, USA) were used for data analysis. Results The investigation revealed significant disparities across several parameters, including sella-nasion-A point angle (SNA), sella-nasion-B point angle (SNB), A point-nasion-B point angle (ANB), the inter-incisal angle (the angle between the long axes of the upper and lower incisors), and UP 1 to A-pog (a specific vertical measurement between anatomical markers labeled "upper 1" and "A point to pogonion"), with associated p-values for the skeletal and dental parameters of 0.310, 0.259, 0.195, 0.0001, and 0.0001, respectively. A comparison between manual tracing and digital methods indicated a reduction in errors and an improvement in measurement precision. Notably, patients diagnosed with BCLP exhibited distinctive skeletal and dental traits, highlighting the necessity for tailored treatment approaches. Conclusion This study emphasizes the importance of personalized cephalometric evaluations for patients with BCLP. Standard mean values may not be applicable due to unique anatomical considerations in these cases. Advanced technology and patient-specific assessments are crucial for accurate diagnosis, treatment planning, and orthognathic procedures in individuals with cleft lip and palate conditions. Embracing digital tools and tailored approaches can enhance patient care quality and lead to better clinical outcomes.

Cephalometric analysis of patients with beta thalassemia receiving fetal hemoglobin induction therapy.

Objective: We aimed to determine the effects of fetal hemoglobin induction therapy in restricting or even reversing the cephalometric changes associated with beta thalassemia. Materials and methods: In this comparative observational study, 90 participants were equally divided into three groups: a control group; patients with thalassemia major receiving blood transfusion (BT group); and patients receiving induction therapy (i.e., hydroxyl urea (5-10 mg/kg/day) or as much as 20 mg/kg/day) and thalidomide (2-10 mg/kg/day) along with blood transfusion (IT group). All patients underwent history taking and examination, photographic assessment, and radiographic evaluation with a lateral cephalogram. One-way ANOVA followed by post-hoc Tukey test was used to determine differences among groups. Results: The IT group differed significantly from the BT group in all photographic and skull table parameters, and most cephalometric parameters, such as facial angle (p ≤ 0.001), middle and lower facial heights (p ≤ 0.001), and inter-incisal angle (p = 0.036); the mean values in the IT group were similar to those in the control group. In-addition, dental and soft tissue measurements significantly differed among groups. For most parameters, the mean difference indicated higher values in the BT group. Conclusion: Induction therapy appeared to improve the facial angles, heights, and inter-incisal angles, whereas a class II skeletal pattern was observed in the transfusion only group. These findings suggest that fetal hemoglobin induction therapy might have restricted some of the cephalometric changes in patients with beta thalassemia.

Accuracy and tracing time of cephalometric analyses on a tablet or desktop computer : A prospective study.

BACKGROUND: This prospective study aimed to evaluate the influence of the computer type (tablet or desktop) on accuracy and tracing time of cephalometric analyses. METHODS: Dental students used a web-based application specifically developed for this purpose to perform cephalometric analyses on tablet and desktop computers. Landmark locations and timestamps were exported to measure the accuracy, successful detection rate and tracing time. Reference landmarks were established by six experienced orthodontists. Statistical analysis included reliability assessment, descriptive statistics, and linear mixed effect models. RESULTS: Over a period of 8 semesters a total of 277 cephalometric analyses by 161 students were included. The interrater reliability of the orthodontists establishing the reference coordinates was excellent (ICC > 0.9). For the students, the mean landmark deviation was 2.05 mm and the successful detection rate for the clinically acceptable threshold of 2 mm suggested in the literature was 68.6%, with large variations among landmarks. No effect of the computer type on accuracy and tracing time of the cephalometric analyses could be found. CONCLUSION: The use of tablet computers for cephalometric analyses can be recommended.

AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning-A Comprehensive Review.

The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.

Cephalometric analysis performance discrepancy between orthodontists and an artificial intelligence model using lateral cephalometric radiographs.

PURPOSE: The purpose of the present clinical study was to compare the Ricketts and Steiner cephalometric analysis obtained by two experienced orthodontists and artificial intelligence (AI)-based software program and measure the orthodontist variability. MATERIALS AND METHODS: A total of 50 lateral cephalometric radiographs from 50 patients were obtained. Two groups were created depending on the operator performing the cephalometric analysis: orthodontists (Orthod group) and an AI software program (AI group). In the Orthod group, two independent experienced orthodontists performed the measurements by performing a manual identification of the cephalometric landmarks and a software program (NemoCeph; Nemotec) to calculate the measurements. In the AI group, an AI software program (CephX; ORCA Dental AI) was selected for both the automatic landmark identification and cephalometric measurements. The Ricketts and Steiner cephalometric analyses were assessed in both groups including a total of 24 measurements. The Shapiro-Wilk test showed that the data was normally distributed. The t-test was used to analyze the data (α = 0.05). RESULTS: The t-test analysis showed significant measurement discrepancies between the Orthod and AI group in seven of the 24 cephalometric parameters tested, namely the corpus length (p = 0.003), mandibular arc (p < 0.001), lower face height (p = 0.005), overjet (p = 0.019), and overbite (p = 0.022) in the Ricketts cephalometric analysis and occlusal to SN (p = 0.002) and GoGn-SN (p < 0.001) in the Steiner cephalometric analysis. The intraclass correlation coefficient (ICC) between both orthodontists of the Orthod group for each cephalometric measurement was calculated. CONCLUSIONS: Significant discrepancies were found in seven of the 24 cephalometric measurements tested between the orthodontists and the AI-based program assessed. The intra-operator reliability analysis showed reproducible measurements between both orthodontists, except for the corpus length measurement. CLINICAL SIGNIFICANCE: The artificial intelligence software program tested has the potential to automatically obtain cephalometric analysis using lateral cephalometric radiographs; however, additional studies are needed to further evaluate the accuracy of this AI-based system.

Reproducibility of Computerized Cephalometric Analysis Software Compared with Conventional Manual Tracing for Analyzing Skeletal Stability After Orthognathic Surgery.

Objective: This study aimed to compare the difference between analyzing skeletal stability after orthognathic surgery by lateral cephalogram measurement created from Dolphin software (version 11.95) compared with the manual technique. Methods: Twenty-eight patients who underwent mandibular setback surgery (BSSRO) were randomly selected between 2015 and 2021. Serial lateral cephalograms were analyzed at four different time sets postoperatively, and a total of 112 cephalometric radiographs were obtained. Horizontal measurement (BX), vertical measurement (BY), and 3 angular measurements (SNB, ANB, and Gonial angle) were analyzed by manual tracing and Dolphin software by 2 examiners. The intraclass correlation coefficient determined the intra-rater reliability. Parameter differences between timelines were observed for skeletal stability, and mean values between methods were compared using the Student's t-test. Results: Both examiners were generally consistent in the repeated measurements (ICCs of the manual method ranged from 0.926 to 0.994, and the digital method ranged from 0.719 to 0.956). All variables represented skeletal stability at T0-T1, T0-T2, and T0-T3 showed no statistically significant differences between methods except ANB (T0-T1; p value = 0.009). Conclusions: Computerized cephalometric analysis software is relatively reproducible for assessing skeletal changes after orthognathic surgery and can be used routinely in follow-up.

Association Between Gender, Age, and Skeletal Class With Mandibular Condyle Morphology: A Retrospective Study.

OBJECTIVES: This study aimed to examine the impact of demographic variables on mandibular condyle morphology, a critical factor in orthodontic treatment and maxillofacial surgery. The investigation focuses on the relationship between gender, age, and skeletal class with the morphological dimensions of the condyle, utilizing panoramic radiography as a diagnostic tool. METHODOLOGY: A retrospective analysis was conducted on 150 panoramic radiographs from individuals stratified into six groups according to gender and skeletal class. Skeletal classes were determined using Steiner and McNamara cephalometry. The Kodak Carestream software (Rochester, NY: Carestream Health) was employed to measure condylar height, width, and morphology. Statistical evaluations included ANOVA, correlation assessments, and multivariate binary logistic regression to discern the differences and associations among the variables studied. RESULTS: The findings revealed notable differences in condylar dimensions between genders across different skeletal classes, with males typically presenting larger condylar dimensions than females. The data also showed a moderate positive correlation between condyle height and width. Round-shaped condyles were the most common form found, with significant gender differences observed in certain skeletal classes. Additionally, logistic regression analysis identified significant associations between gender, age, and condylar width and shape. CONCLUSIONS: The study concludes that demographic factors, such as gender and age, significantly affect mandibular condyle morphology. These factors should be carefully considered in clinical evaluations using panoramic radiography to enhance the precision of diagnoses and the effectiveness of subsequent orthodontic and maxillofacial treatments. The results provide valuable insights for healthcare professionals in regions where more advanced imaging techniques may not be readily available.

Dentofacial characteristics of children and adolescents with foetal alcohol spectrum disorders: a comparison with matched controls.

BACKGROUND: Foetal alcohol spectrum disorders (FASD) include somatic and neurological developmental disturbances after prenatal alcohol exposure, including facial anomalies. However, the knowledge of the orthodontic skeletal and dental cephalometric relations in this group is limited. The aim of the study was to assess the dentofacial characteristics of children and adolescents with FASD and to compare them with a matched control group. METHODS: The study group comprised all available children and adolescents diagnosed with FASD (> 7 years of age) in whom good quality cephalograms were available. The control group comprised non-syndromic, orthodontically untreated children with normal occlusion and skeletal relations matched with age and gender. Cephalometric analysis included eighteen linear and angular measurements. The general linear model for repeated measures regarding age, gender and the type of FASD was applied. RESULTS: The group with FASD included 35 individuals (21 girls and 14 boys) aged 7-18 years including 21 with foetal alcohol syndrome. The mean age in the study and the control group was 12.8 years (SD, range 3.2, 7.1-18.1) and 13.0 (SD, range 2.9, 9.1-18.1), respectively. Statistically significant differences between the groups were found in 15 out of 18 of the cephalometric measurements (83%). In children with FASD the mandible was more retrusive, the incisors were more proclined and the mandibular incisors and the lips were more protruded when compared with controls. There was no significant evidence of an influence of age, gender or FASD type. CONCLUSIONS: Dentofacial characteristics of children and adolescents with FASD significantly differ from controls. Early orthodontic diagnosis and prophylaxis should play a part of the interdisciplinary care of patients in this group.

An MRI-only Three-dimensional Cephalometry Protocol based on the Integrated and Modular Architecture of the Human Head.

BACKGROUND: Currently, three-dimensional cephalometry measurements are mainly based on cone beam computed tomography (CBCT), which has limitations of ionizing radiation, lack of soft tissue information, and lack of standardization of median sagittal plane establishment. OBJECTIVES: This study investigated magnetic resonance imaging (MRI)-only based 3D cephalometry measurement based on the integrated and modular characteristics of the human head. METHODS: Double U-Net CycleGAN was used for CT image synthesis from MRI. This method enabled the synthesis of a CT-like image from MRI and measurements were made using 3D slicer registration and fusion. RESULTS: A protocol for generating and optimizing MRI-based synthetic CT was described and found to meet the precision requirements of 3D head measurement using MRI midline positioning methods reported in neuroscience to establish the median sagittal plane. An MRI-only reference frame and coordinate system were established enabling an MRI-only cephalometric analysis protocol that combined the dual advantages of soft and hard tissue display. The protocol was devised using data from a single volunteer and validation data from a larger sample remains to be collected. CONCLUSION: The reported method provided a new protocol for MRI-only cephalometric analysis of craniofacial growth and development, malformation occurrence, treatment planning, and outcomes.