Cephalometric Analysis Research Articles

Comparative Analysis of 3D Cephalometry Provided with Artificial Intelligence and Manual Tracing

Objectives: To compare 3D cephalometric analysis performed using AI with that conducted manually by a specialist orthodontist. Methods: The CBCT scans (a field of view of 15 × 15 cm) used in the study were obtained from 30 consecutive patients, aged 18 to 50. The 3D cephalometric analysis was conducted using two methods. The first method involved manual tracing performed with the Invivo 6 software (Anatomage Inc., Santa Clara, CA, USA). The second method involved using AI for cephalometric measurements as part of an orthodontic report generated by the Diagnocat system (Diagnocat Ltd., San Francisco, CA, USA). Results: A statistically significant difference within one standard deviation of the parameter was found in the following measurements: SNA, SNB, and the left interincisal angle. Statistically significant differences within two standard deviations were noted in the following measurements: the right and left gonial angles, the left upper incisor, and the right lower incisor. No statistically significant differences were observed beyond two standard deviations. Conclusions: AI in the form of Diagnocat proved to be effective in assessing the mandibular growth direction, defining the skeletal class, and estimating the overbite, overjet, and Wits parameter.

The Relationship Between Orthodontic Malocclusion and Morphological Features of Sella Turcica Bridging and Ponticulus Posticus

Background and Objectives: Recent years have been marked by a search for new relationships between malocclusions and the morphological features of the cranial base and upper cervical spine. The aim of this study was to evaluate the relationship between skeletal orthodontic malocclusions and the morphological features of sella turcica bridging (STB) and ponticulus posticus (PP). Materials and Methods: The study sample consisted of 300 randomly selected pre-orthodontic treatment patients aged 7–40 years. Cephalometric analysis was performed twice by two researchers. The patients were divided into three groups according to the type of skeletal malocclusion. Statistical analysis was performed using SPSS 29.0 software. Results: The prevalence of incomplete PP was 40%, and the prevalence of complete PP was 11.33% and was significantly more common in males (56.7%). STB had a prevalence of 52.67% (15.67% complete, 37.0% partial), with a significantly higher prevalence in females (60.1%, p < 0.001). PP and STB were more common in Class II patients, followed by Class I and Class III. However, only PP showed a statistically significant difference (p = 0.042). According to logistic regression, men were twice as likely to have an open groove of PP (p = 0.015), while females had higher odds of partial and complete STB (p < 0.05). Class II malocclusion increases the odds of type 2 and type 4 PP as well as partial STB. However, it was not statistically significant (p > 0.05). Conclusions: The morphological features of sella turcica bridging and ponticulus posticus were related to sex and the orthodontic skeletal pattern. Ponticulus posticus was more prevalent in males, while sella turcica bridging was more prevalent in females; both conditions were more common in patients with a Class II skeletal pattern. Males were more likely to have an open groove of ponticulus posticus, whereas females were twice as likely to have both forms of sella turcica bridging.

Digital Cephalometric Analysis: Unveiling the Role and Reliability of Semi-automated OneCeph, Artificial Intelligence-Powered WebCeph Mobile App, and Semi-automated Computer-Aided NemoCeph Software in Orthodontic Practice

Digital Cephalometric Analysis: Unveiling the Role and Reliability of Semi-automated OneCeph, Artificial Intelligence-Powered WebCeph Mobile App, and Semi-automated Computer-Aided NemoCeph Software in Orthodontic Practice

Validation of 2D lateral cephalometric analysis using artificial intelligence-processed low-dose cone beam computed tomography

ObjectivesTraditional cephalometric radiographs depict a three-dimensional structure in a two-dimensional plane; therefore, errors may occur during a quantitative assessment. Cone beam computed tomography, on the other hand, minimizes image distortion, allowing essential areas to be observed without overlap. Artificial intelligence can be used to enhance low-dose cone beam computed tomography images. This study aimed to clinically validate the use of artificial intelligence-processed low-dose cone beam computed tomography for generating two-dimensional lateral cephalometric radiographs by comparing these artificial intelligence-enhanced radiographs with traditional two-dimensional lateral cephalograms and those derived from standard cone beam computed tomography. MethodsSixteen participants who had previously undergone both cone beam computed tomography and plain radiography were selected. Group I included standard lateral cephalometric radiographs. Group II included cone beam computed tomography-produced lateral cephalometric radiographs, and Group III included artificial intelligence-processed low-dose cone beam computed tomography-produced lateral cephalometric radiographs. Lateral cephalometric radiographs of the three groups were analyzed using an artificial intelligence-based cephalometric analysis platform. ResultsA total of six angles and five lengths were measured for dentofacial diagnosis. There were no significant differences in measurements except for nasion-menton among the three groups. ConclusionsLow-dose cone beam computed tomography could be an efficient method for cephalometric analyses in dentofacial treatment. Artificial intelligence-processed low-dose cone beam computed tomography imaging procedures have the potential in a wide range of dental applications. Further research is required to develop artificial intelligence technologies capable of producing acceptable and effective outcomes in various clinical situations. Clinical significanceReplacing standard cephalograms with cone beam computed tomography (CBCT) to evaluate the craniofacial relationship has the potential to significantly enhance the diagnosis and treatment of selected patients. The effectiveness of low-dose (LD)-CBCT was assessed in this study. The results indicated that lateral cephalograms reconstructed using LD-CBCT were comparable to standard lateral cephalograms.

Accuracy of web-based automated versus digital manual cephalometric landmark identification.

The purpose of this study was to assess the accuracy of two web-based automated cephalometric landmark identification and analysis programs. Manual landmark identification using Dolphin Imaging software was used as reference. 105 cephalograms were selected and divided into three groups of 35 subjects each, Class I, II and III. Radiographs were traced using Dolphin imaging software. WebCeph™ (South Korea) and Cephio™ (Poland) were used for the automated cephalometric analysis. Bland-Altman limits of agreement and the concordance correlation coefficient (CCC) were calculated. Kruskal Wallis test was used to compare the accuracy of WebCeph™ and Cephio™ measurements between the three groups. Mann-Whitney U test was used to compare the absolute difference between cephalometric measurements obtained using WebCeph™ and Cephio™. The mean difference (MD) between AI and manually-derived measurements was less than 1mm/degree and ranged from 0.01 to 0.8 except for upper lip protrusion (MD 1.35°), nasolabial angle (MD 5.01°), SN-GoGn (MD 1.41°), Ramus height (MD 1.46°), and IMPA (MD 1.94°). The mean CCC was 0.91 (range 0.60 to 0.96). No statistically significant differences were found between the three malocclusion groups for most of the measurements (P > 0.05). For most of the measurements, automated cephalometric measurements were clinically acceptable. Few differences were found between Webceph™ and Cephio™ for most measurements. Measurements including SNA, SN-PP, IMPA as well as soft tissue measurements require extra consideration and manual adjustment of respective landmarks for higher precision and improved efficiency.

Reliability and accuracy of Artificial intelligence-based software for cephalometric diagnosis. A diagnostic study

BackgroundArtificial intelligence (AI) is revolutionizing cephalometric diagnosis in orthodontics, streamlining the patient assessments. This study aimed to assess the reliability, accuracy, and time consumption of artificial intelligence (AI)-based software compared to a conventional digital cephalometric analysis method on 2D lateral cephalogram.Methods408 lateral cephalometries were analysed using three methods: manual landmark localization, automatic localization, and semi-automatic localization with AI-based software. On each lateral cephalogram, 15 variables were selected, including skeletal, dental, and soft tissue measurements. The difference between the two AI-based software options (automatic and semi-automatic) was compared with the conventional digital technique. The time required to produce a complete cephalometric tracing was evaluated for each method using Student’s t-test.ResultsStatistically significant differences in the accuracy of landmark positioning were detected among the three different techniques (p < 0,01). However, it is noteworthy that almost all of these differences were not clinically significant. There was a small difference in accuracy between the semi-automatic AI-based option and conventional digital techniques. Regarding the time used for each technique, the automatic version was the fastest, followed by the semi-automatic option and the conventional digital technique. (p < 0,000).ConclusionsThe study showed a statistical difference in accuracy between the conventional digital technique and two AI-based software alternatives, but these differences were not clinically significant except for specific measurements. The semi-automatic option was more accurate than the automatic one and faster than conventional tracing. Further research is needed to confirm AI’s accuracy in cephalometric tracing.

From Nasion to Sellion: repositioning landmarks for radioprotection-tailored 3D cephalometric analysis

ABSTRACT Purpose The present study aimed to three-dimensionally evaluate the correlation between cephalometric measurements utilizing Sellion in place of Nasion. Material and methods A pilot study using 25 CBCTs was carried out to determine the required sample size, reaching a minimum of 136 patients was required to validate the correlation between Nasion(N)- and Sellion(Se)-related measurements. Eight landmarks were manually annotated on full cranium CBCTs, resulting in six skeletal and six cutaneous/skeletal measurements. Therefore, data were statistically analysed after outliers’ detection and intraclass correlation coefficient (ICC) calculation. Pearson correlation coefficient (r) was used to assess the correlation between Nasion and Sellion measurements. At the end, simple linear regression was performed. Values of p < 0.01 and r > 0.80 were considered statistically and clinically relevant, respectively. Results ICC revealed a substantial degree of consistency. A total of 214 CBCTs were included in the present study. Pearson test revealed highly significant correlations for all the tested variables; the highest coefficient was found between N^Me^Go vs Se^Me^Go (r = 0.989, p < 0.001) while the lowest among SNA vs SSeA (ρ = 0.814, p < 0.001). Finally, linear regression provided the new norm range values for the Sellion-based measurements. Conclusion Pearson’s coefficients between Sellion- and Nasion-related measurements exhibited significantly high levels of correlation, suggesting the potential use of Sellion-based measurements for innovative cephalometric analyses. This method might comply with radiation protection principles in CBCT-based orthodontic cephalometry.

Stability of unilateral posterior crossbite treatment with the Function Generating Bite appliance : Association with reduction of mandibular clockwise rotation and increased maxillary transversal width measurements.

This observational study aimed to evaluate the stability of unilateral posterior crossbite (UPXB) correction with the functional appliance function generating bite (FGB appliance) during follow-up and its effects on craniofacial growth. Atotal of 102 age- and gender-matched patients were included: 51with UPXB (male [M] = 19; female [F] = 32; mean age ± standard deviation [SD] = 7.6 ± 1.4[years.months]) and 51controls (C; M = 19; F = 32; mean age ± SD = 7.9 ± 1.3). UPXB was corrected with the FGB appliance. Study casts were collected before treatment (T0), after correction (T1), after afollow-up of 3.7 ± 1.6[years.months] (T2) and different transversal measurements were performed with calipers: intermolar (IMD), intermolar gingival (IMGD), intercanine (ICD), and intercanine gingival distances (ICGD). In treated patients, in addition, lateral cephalometric tracings were analyzed at T0 and T2. At T0, all maxillary measurements were significantly smaller in the UPXB group compared to the controls (p < 0.001). Between T0 and T1, all maxillary variables increased significantly in the UPXB group (p < 0.001; IMD +4.3 ± 2.1 mm; ICD +3.1 ± 2 mm). Between T1 and T2, maxillary IMD increased further (p < 0.05; +2.2 ± 2 mm). The mean T0-T2 increases were 6.6 ± 2.6 mm (IMD) and 4.3 ± 2.6 mm (ICD). At T0, the cephalometric analysis showed significantly stronger mandibular clockwise rotation (p < 0.01) in the UPXB group compared to the control group. Between T0 and T2, the UPXB group showed asignificant reduction of mandibular (p < 0.001; SpP-CoOr T0 = -3.47°± 4.38, T2 = -1.14°± 4.01) and occlusal plane (p < 0.01; SpP-Oc T0 = 11.37°± 3.91, T2 = 9.86°± 3.83) clockwise rotation, and of intermaxillary divergence (p < 0.01; SpP-GoGn T0 = 27.8°± 5.39, T2 = 26.65°± 5.49). Treatment of UPXB with the FGB appliance effectively increased maxillary transversal width measurements, especially in the posterior region, even after follow-up, indicating stable results. Concurrently, mandibular clockwise rotation was reduced, indicating control of the vertical dimension.

Prediction of a Cephalometric Parameter and Skeletal Patterns from Lateral Profile Photographs: A Retrospective Comparative Analysis of Regression Convolutional Neural Networks.

Background/Objectives: Cephalometric analysis has a pivotal role in the quantification of the craniofacial skeletal complex, facilitating the diagnosis and management of dental malocclusions and underlying skeletal discrepancies. This study aimed to develop a deep learning system that predicts a cephalometric skeletal parameter directly from lateral profile photographs, potentially serving as a preliminary resource to motivate patients towards orthodontic treatment. Methods: ANB angle values and corresponding lateral profile photographs were obtained from the medical records of 1600 subjects (1039 female and 561 male, age range 3 years 8 months to 69 years 1 month). The lateral profile photographs were randomly divided into a training dataset (1250 images) and a test dataset (350 images). Seven regression convolutional neural network (CNN) models were trained on the lateral profile photographs and measured ANB angles. The performance of the models was assessed using the coefficient of determination (R2) and mean absolute error (MAE). Results: The R2 values of the seven CNN models ranged from 0.69 to 0.73, and the MAE values ranged from 1.46 to 1.53. Among the seven models, InceptionResNetV2 showed the highest success rate for predictions of ANB angle within 1° of range and the highest performance in skeletal class prediction, with macro-averaged accuracy, precision, recall, and F1 scores of 73.1%, 78.5%, 71.1%, and 73.0%, respectively. Conclusions: The proposed deep CNN models demonstrated the ability to predict a cephalometric skeletal parameter directly from lateral profile photographs, with 71% of predictions being within 2° of accuracy. This level of accuracy suggests potential clinical utility, particularly as a non-invasive preliminary screening tool. The system's ability to provide reasonably accurate predictions without radiation exposure could be especially beneficial for initial patient assessments and may enhance efficiency in orthodontic workflows.

AI-based open-source software for cephalometric analysis from limited FOV radiographs

BackgroundArtificial Intelligence (AI) in dental diagnostics is evolving, offering innovative approaches for conducting cephalometric analysis with less manual input and overcoming the limitations of traditional imaging methods. To enhance the diagnostic processes in dentistry, an open-source software that utilises AI to improve the extraction of cephalometric values from limited field of view (FOV) images was created. Material and MethodsReduced FOV images lack several vital cephalometric landmarks, prompting the creation of predictive models to estimate missing values. The GridSearchCV algorithm and other algorithms were used to construct predictive models using software and to select the best models. The software was validated by comparing the predicted values with the actual measurements and calculating the mean squared error using Excel. Further validation involved a randomly selected cohort of 25 untreated orthodontic cases. ResultsEvaluation of the software showed that it was effective in accurately predicting key cephalometric measurements, suggesting that it could be a reliable tool for clinical use. However, some variations were noted in its predictive accuracy across different measurements, indicating areas that could benefit from further development. The software could align closely with the actual cephalometric measurements through detailed statistical analysis. ConclusionsThe integration of AI into cephalometric analysis with the software could represent progress, potentially leading to more efficient dental diagnostics and a reduction in the need for additional X-rays. This study aimed to advance the integration and refinement of AI in healthcare, focusing on minimising bias and understanding its impact on clinical decisions. In future studies, the application of AI in dental practice should be expanded to address these challenges. Clinical Significance StatementThis software integrates AI into clinical practice to enhance the diagnostic and therapeutic phases for patient benefit. It enables precise and comprehensive cephalometric analyses using data previously considered insufficient, thereby reducing the need for X-rays and improving patient care.

Dentofacial and skeletal effects of two orthodontic maxillary protraction protocols: bone anchors versus facemask

BackgroundMaxillary retrognathia and/or mandibular prognathia are resulting in class III malocclusion. Regarding orthodontic class III malocclusion treatment, the literature reports several treatment approaches. This comparative clinical study investigated two maxillary protraction protocols including bone anchors and Delaire type facemask.MethodsCephalometric radiographs of n = 31 patients were used for data acquisition. The patients were divided into two groups according to their treatment protocol: bone anchored protraction (n = 12, 8 female, 4 male; mean age 11.00 ± 1.76 years; average application: 13.50 ± 5.87 months) and facemask protraction (n = 19, 11 female, 8 male; mean age 6.74 ± 1.15 years; average application: 9.95 ± 4.17 months). The evaluation included established procedures for measurements of the maxilla, mandibula, incisor inclination and soft tissue. Statistics included Shapiro-Wilk- and T-Tests for the radiographs. The level of significance was set at p < 0.05.ResultsThe cephalometric analysis showed differences among the two groups. SNA angle showed significant improvements during protraction with bone anchors (2.30 ± 1.18°) with increase in the Wits appraisal of 2.01 ± 2.65 mm. SNA angle improved also during protraction with facemask (1.22 ± 2.28°) with increase in the Wits appraisal of 1.85 ± 4.09 mm. Proclination of maxillary incisors was larger in patients with facemask (3.35 ± 6.18°) and ML-SN angle increased more (1.05 ± 1.51°) than in patients with bone anchors. Loosening rate of bone anchors was 14.58%.ConclusionsBoth treatment protocols led to correction of a class III malocclusion. However, this study was obtained immediately after protraction treatment and longitudinal observations after growth spurt will be needed to verify the treatment effects over a longer period. The use of skeletal anchorage for maxillary protraction reduces unwanted side effects and increases skeletal effects needed for class III correction.

Evaluation Of Accuracy And Reliability Of Artificial Intelligence-Based Fully Automated And Semi-Automated Cephalometric Analysis Software In Comparison With Manual Cephalometric Analysis

Introduction: Lateral cephalometric analysis stands as a pivotal diagnostic tool within the realm of Orthodontics, often regarded as the gold standard. Over time, several computerised programs have surfaced, aiming to streamline the process of digital cephalometric analysis, thereby offering efficiency gains and time savings. The current study sought to assess the diagnostic accuracy and reliability of four computerised cephalometric analysis programs. These encompassed three digital software solutions alongside an online artificial intelligence platform. The objective was to compare the digital approaches against the traditional method of manual cephalometric tracing. Materials and methodology: This study analysed thirty pre-treatment lateral cephalometric radiographs of individuals undergoing orthodontic treatment. Four computer programs—Dolphin Imaging software, Nemoceph, and FACAD for semi-automated cephalometric analysis, and WebCeph for artificial intelligence-based cephalometric analysis—were evaluated and compared with manual cephalometric tracing. Measurements were taken for five skeletal, four dental, and one soft tissue parameters, including six angular and four linear measurements derived from Steiner, McNamara, and Tweed cephalometric analysis. Fifteen cephalometric radiographs were remeasured to assess the intra-examiner correlation coefficient. One-way ANOVA was used to compare different cephalometric points among the various tracing methods, and multiple comparisons were performed using the Post Hoc Tukey’s test. Results: No significant difference was noted in SNA, SNB, ANB, FMA, IMPA, 1 to Pt A, 1 to N-A and nasolabial angle between the software. While 1 to A Pog and 1 to N-B revealed significant differences between the software. FACAD vs. NemoCeph showed a significant difference with a mean difference of -0.30 and -0.30 and a p-value of 0.03 and 0.02 for 1 to A Pog and 1 to N-B values respectively and this variability was noted between FACAD and NemoCeph. Conclusion: Digital and AI-based software have shown accuracy comparable to manual tracing. Among the software, Dolphin Imaging proved to be the most reliable, followed by WebCeph and NemoCeph, with FACAD showing the most variability. The variability, which lacked clinical significance, was primarily due to challenges in identifying certain landmarks.

Morphometric Tomographic Analysis of the Head of the Tridactyl Humanoid Specimen from Nasca-Peru

Objective: To report the tomographic and morphometric analysis of the head of the tridactyl humanoid specimen from Nazca, Peru. Method: A qualitative case study approach. RadiAnt DICOM Viewer software version 4.2.1 was used to analyze lengths, diameters, and volume in tomographic images of the head. The morphological biometric analysis applied anthropometric methods using some craniometric points and cephalometric angles. Results and Discussion: As a result, it is reported that there are atypical, strange, and exceptional morphometric imaging features in the cephalic segment of specimen M01. The cephalometric analysis based on the ANB angle revealed a class II skeletal pattern, and according to the Bjorl-Jarabak analysis, it has a convex facial profile with hypodivergent growth (brachyfacial). The patient also has maxillary biprotrusion, severe protrusion of upper and lower incisors, loss of teeth, presence of root remnants, severe dental abrasion, non-assessable canine class, absence of three third molars and ocular protrusion. Based on craniometric points, the SNA angle (Sella, Nasion and Point A) and the SNB angle (Sella, Nasion and Point B) maxillary protrusion and mandibular protrusion were diagnosed. Implications of the research: It is concluded that the combination of uncommon morpho-anatomical features in the maxillofacial and cranial massif do not correspond to a human craniofacial biotype, but could be considered as suggestive findings of morpho-anatomical features typical of a hominid species similar to humans. Originality/Value: The expansion of biometric and morphoanatomical data of the head reinforces the hypothesis that morphologically it would be a non-human hybrid species.

Upper airways changes associated with orthodontic molar distalization by Pendulum appliance in adolescent patients: a multicenter retrospective cephalometric study

ObjectivesThe purpose of this multicenter retrospective study was to perform a two-dimensional analysis of upper airway changes in adolescent patients following molar distalization with the Pendulum appliance.Materials and methodsThe study involved the cephalometric analysis of 88 patients, retrospectively categorized into two groups: skeletal Class II with a dental Class II molar relationship (36 patients, mean age 12.6 ± 1.1 years) and skeletal Class I with a dental Class II molar relationship (54 patients, mean age 12.3 ± 1.2 years). Changes were observed using lateral radiographs before (T0) and after Pendulum appliance removal (T1); treatment time averaged 7 months. Upper airways were subsequently analyzed by tracing lateral radiographs. The Shapiro-Wilk test showed a normal distribution of the data, therefore parametric tests were used for statistical analysis. Intragroup changes between T0 and T1 were evaluated using paired t-tests, and intergroup differences were assessed using independent student t-tests; statistical significance was set at 0.05.ResultsStatistically significant differences were observed in the skeletal measurements that characterized both groups, particularly in ANB and Wits appraisal, at T0 (P < 0.001). After molar distalization, Class I and Class II groups reported no statistically significant differences with changes almost equal to zero between timepoints (P > 0.05). Additionally, intergroup comparisons of airway changes at T1 did not show statistically significant differences (P > 0.05).ConclusionsThe Pendulum appliance does not significantly change the upper airway dimensions in Class I and Class II malocclusion patients, thereby minimizing potential respiratory risks.

Artificial Intelligence in Oral and Maxillofacial Surgery: Bridging the Gap between Technology and Clinical Practice a Narrative Review

Objective: To provide a comprehensive overview of current applications and future prospects of artificial intelligence (AI) in oral and maxillofacial surgery (OMFS), while critically analyzing implementation challenges and exploring potential advancements.  Methods A systematic literature review was conducted using PubMed/MEDLINE and Embase databases, encompassing English-language articles up to December 30, 2023. Search terms combined OMFS and AI concepts, with database-specific syntax employed.  Results AI applications in OMFS span multiple domains, including image analysis, surgical planning, intraoperative guidance, and clinical decision support. Deep learning models have demonstrated high accuracy in detecting mandibular fractures, performing cephalometric analyses, and classifying maxillofacial pathologies. AI-enhanced surgical planning and robotic systems show promise in improving precision and outcomes across various OMFS procedures. However, challenges persist in data quality, clinical validation, and seamless workflow integration.  Conclusions AI technologies have the potential to significantly enhance diagnostic accuracy, surgical precision, and treatment outcomes in OMFS. Future research directions include developing multimodal AI systems, advancing AI-powered surgical navigation, and exploring federated learning approaches. Successful implementation of AI in OMFS practice will require collaborative efforts among clinicians, researchers, engineers, and policymakers to address technical, ethical, and regulatory challenges. As these hurdles are overcome, AI is poised to become an integral part of OMFS, augmenting surgical capabilities and elevating patient care standards.

A cephalometric analysis of the antegonial notch in relation to the direction of mandibular growth.

Masticatory muscle forces influence craniofacial morphology development. The antegonial notch (Notch) is a bony concavity on the inferior border of the mandible. Considering the Notch is located anteriorly to the insertion of the masseter muscle and varies among individuals, we hypothesised that these muscles influence the formation of the Notch. Therefore, this study aimed to investigate the correlation between mandible morphology and Notch formation. Sixty Japanese patients who visited the Department of Orthodontics at our university hospital were retrospectively evaluated. Morphological and morphometric analyses of the Notch and related craniofacial parameters were conducted using lateral cephalograms taken at the patients' initial visits. Standard values for the Notch area and depth were determined, and the morphology of the Notch and mandible was analysed using Spearman's rank correlation coefficient (p < 0.05). The mean Notch area and depth was 78.71 ± 36.54 mm2 and 3.11 ± 1.09mm, respectively. The Notch area was significantly correlated with ramus inclination (p = 0.044, r = 0.261) and with the Y-axis (p = 0.039, r = 0.267). This study indicated that both the masticatory muscles and mandibular growth could contribute to the Notch formation.

Effects of mini-implant anchorage on mandibular rotation and esthetic outcomes in hyperdivergent skeletal Class II malocclusion treatment

Objectives: This research aimed to investigate the effects of mini-implants (MIs) on mandibular position and changes in lower face height, as well as their relationship with the position of the maxillary molars and incisors in the camouflage treatment of patients with hyperdivergent skeletal Class II malocclusion. Material and Methods: This retrospective study included 27 patients aged 15–38 years. The hyperdivergent patients were diagnosed with skeletal Class II malocclusion and treated with tooth compensation, tooth extraction, posterior repositioning of the maxillary incisors, and anchoring with MIs. Cephalometric analyses of these patients were performed before (T1) and after (T2) treatment. Measurements were taken at each treatment stage and analyzed. Results: Significant correlations were observed in the mandibular position and lower face height (P &lt; 0.05). The GoGnSN angle decreased (−1.05 ± 1.61°), the ANS-Me distance reduced (−1.98 ± 4.76 mm), and the NBaPtGn angle increased (1.67 ± 4.08°). In addition, the vertical height position of the maxillary first molar significantly decreased (6M-FH, −1.61 ± 3.74 mm), while the vertical height position of the maxillary incisor increased (U1-FH, 1.48 ± 2.11 mm). Conclusion: During the camouflaging treatment of patients with hyperdivergent skeletal Class II malocclusion using MIs anchorage, MIs helped intrude the maxillary first molar and extrude the maxillary incisor, leading to a difference in a mandibular counterclockwise rotation. Controlling the rotation of the lower jawbone helps create an improved esthetic for the patient after treatment.

Evaluation of Upper Airway Growth Patterns With Cephalometric Analysis Based on Cervical Vertebral Maturation in the Japanese: A Cross-Sectional Study.

Objective This study aims to establish standard values for the upper airway cross-sectional area and evaluate growth patterns using the cervical vertebral maturation stage (CVMS) in a Japanese population. Methods A cross-sectional sample of 400 patients, aged 6-20 years, was selected randomly from the Orthodontic Clinic at Tokyo Medical and Dental University (TMDU) dental hospital. Cervical vertebral maturation stages (CVMS I-V) guided the classification of participants into five equal groups. Lateral cephalometric radiographs taken prior to orthodontic treatment were used to measure the upper airway's cross-sectional area. The growth spurt and sex differences in growth patterns were assessed through these measurements. Results Standard values for the upper airway dimensions at each CVMS stage were established. Significant growth spurts were noted between CVMS II-III and CVMS III-IV in males and at CVMS II-III in females. The weighted kappa coefficient (κ) demonstrated almost perfect intra- and inter-evaluator agreement, confirming the reliability of CVMS in growth assessment. Conclusion CVMS provides a reliable framework for assessing growth patterns of the upper airway, with distinct variations between sexes noted. These findings support the utility of CVMS in clinical growth evaluation and orthodontic treatment planning.

Cephalometric analysis of traditional and new Sella point

Cephalometric analysis of traditional and new Sella point

Skeletal and dental features of class II malocclusion among Palestinian population: a retrospective cephalometric study

Aim. This study aims to assess the dentofacial characteristics for a sample of palestinian population with skeletal Class II malocclusion. Methods. A total of 170 lateral cephalograms for non-growing patients (age ranged between 19 and 32 years) with skeletal Class II malocclusion were retrieved. The lateral cephalograms were analyzed using virtual cephalometric analysis software - WeDoCeph® (Audax®, Ljubljana, Slovenia) to assess sagittal and vertical Skeletal parameters including SNA, SNB, ANB, SN/Mandibular Plane angle SN/Go-Gn, FMA and the Y axis angle were measured. Moreover, the upper and lower dental angular parameters (Maxillary incisor long axis with Sella - Nasion line (U1-SN), Maxillary incisor long axis with Nasion - point A angular (U1-A Point), Mandibular incisor long axis with mandibular plane (L1-MP), Mandibular incisor with nasion-point B (L1- NB) angular were also measured. The mean and standard deviation for each measurement were calculated using the Statistical Package for Social Sciences (Minitab) for Windows. Gender differences were analyzed using the independent t-test. Results. One-hundred and seventy lateral cephalometric radiographs were retrieved and analyzed. The Class II skeletal value (ANB value of 6.7 degrees) was mainly due to retrognathic mandible (SNB 75.5 degrees) rather than prognathic maxilla (SNA 82.2 degrees). In the vertical dimension, the Y axis angle, SN/Go-Gn angle, and FMA were generally increased. Regarding the dental parameters, the upper incisors were mostly retroclined, while the lower incisors were mostly proclined. There was a significant gender difference in two parameters (SN/Go-Gn and the L1-MP), where females showed more vertical growth and more lower incisors proclination. Conclusions. Skeletal class II malocclusion in the studied sample was characterized by retrognathic mandible, increased vertical growth, and compensated upper and lower incisors. Compared with male subjects, females significantly had more vertical growth and more lower incisor proclination.