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.

BACKGROUND: Forensic dentistry integrates interdisciplinary scientific knowledge to produce accurate and reliable forensic statements. Anthropometry, essential since its introduction by Alphonse Bertillon in 1882, describes human body shapes and has significant forensic applications. This study focuses on sexual dimorphism, phenotypic differences between males and females, using lateral cephalometric measurements to determine sex in children aged 10-12 years from the Chengalpattu population.
METHODS: The cross-sectional study included 80 participants (40 boys and 40 girls). Lateral cephalograms were analyzed using Ceph Ninja Pro software to obtain 15 cephalometric measurements. Statistical analysis using SPSS Software (Version 22.0) involved t-tests to identify significant differences (P<0.05). Discriminant function analysis assessed the predictive power of these variables.
RESULTS: Seven variables showed significant differences between sexes. Discriminant models based on these variables determined sex with varying reliability. Ramus length was the most reliable predictor (81%), while maxillary length had the lowest reliability (62%).
CONCLUSIONS: The study\'s findings align with existing literature, indicating the robustness of ramus length for sex determination. However, the low reliability of maxillary length contrasts with studies that found it useful for sex differentiation, suggesting variability across populations and age groups. Combining multiple cephalometric variables improved accuracy, consistent with previous research.
CONCLUSIONS: Lateral cephalograms are effective for assessing sexual dimorphism in children. The study supports the forensic and clinical utility of cephalometric measurements and calls for further research with diverse populations and advanced imaging techniques to enhance method reliability and applicability.

Background/Objectives: To systematically review and summarize the existing scientific evidence on the diagnostic performance of artificial intelligence (AI) in assessing cervical vertebral maturation (CVM). This review aimed to evaluate the accuracy and reliability of AI algorithms in comparison to those of experienced clinicians. Methods: Comprehensive searches were conducted across multiple databases, including PubMed, Scopus, Web of Science, and Embase, using a combination of Boolean operators and MeSH terms. The inclusion criteria were cross-sectional studies with neural network research, reporting diagnostic accuracy, and involving human subjects. Data extraction and quality assessment were performed independently by two reviewers, with a third reviewer resolving any disagreements. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used for bias assessment. Results: Eighteen studies met the inclusion criteria, predominantly employing supervised learning techniques, especially convolutional neural networks (CNNs). The diagnostic accuracy of AI models for CVM assessment varied widely, ranging from 57% to 95%. The factors influencing accuracy included the type of AI model, training data, and study methods. Geographic concentration and variability in the experience of radiograph readers also impacted the results. Conclusions: AI has considerable potential for enhancing the accuracy and reliability of CVM assessments in orthodontics. However, the variability in AI performance and the limited number of high-quality studies suggest the need for further research.

OBJECTIVE: We conducted a three-dimensional (3D) analysis of orthodontic tooth movement (TM) using digital dental models (DMs), focusing on the palatal region of interest (PROI), aiming to evaluate the long-term stability of the PROI, validate the 3D TM analysis with PROI registration, and compare it with conventional lateral cephalometric analyses.
METHODS: Twenty adult patients treated with a multibracket appliance were evaluated at their first visit (T0) and at least 5 years later (T1) using DMs and lateral cephalograms (LCs). The long-term stability of PROI was assessed by calculating the point cloud distances between DM-T0 and DM-T1. TM analysis using DM with PROI registration for the maxillary central incisors was assessed through linear and angular measurements in the sagittal view and subsequently compared with the LCs.
RESULTS: The average point cloud distance of the PROI between DM-T0 and DM-T1 was 0.21 mm (standard deviation, 0.13 mm). TM analysis using DMs demonstrated excellent reproducibility for both linear and angular measurements (intra-rater correlation coefficient, > 0.99). The 95% limits of agreement between the DM and LC measurements were < 5.14° for angular change, 3.53 mm for vertical displacement, and 0.98 mm for horizontal displacement. No significant differences were observed in the angular and linear measurements when the TM was compared using the DMs and LCs.
CONCLUSIONS: The PROI remained stable for over 5 years, supporting the reproducibility and accuracy of TM assessment using PROI registration in orthodontic clinical practice.
CONCLUSIONS: DM analysis lacks the risks associated with X-ray exposure and can be easily performed in daily clinical practice, indicating its potential for future clinical applications. These findings further support the use of DM with PROI registration for TM analysis in orthodontic clinical practice, emphasizing its long-term stability and reproducibility.

This study investigated compensation in skeletal Class III subjects to compare various severities of abnormal jaws. A retrospective analysis of 137 skeletal Class III cephalograms (63 males and 74 females) was conducted, with cephalometric assessments determining skeletal and dental values. The results were compared with Class I cephalograms. Incisor compensation was examined by pairing normal jaws with varied abnormal jaws, classified by severity using one standard deviation (SD). Statistical analyses included Kruskal-Wallis tests, Bonferroni tests, Spearman\'s correlations, and multiple linear regression. Four skeletal Class III groups were identified: OMx+PMd, RMx+OMd, OMx+OMd, and PMx+PMd (P = prognathic; O = orthognathic; R = retrognathic; Mx = maxilla; Md = mandible.). The upper central incisor (U1) showed proclination, and the lower central incisor (L1) showed retroclination across all groups except for U1 in PMx+PMd and L1 in OMx+OMd, which exhibited normal inclination. U1 exhibited limited compensation even with progressive maxillary retrognathism, while L1 showed limited compensation after one SD of mandibular prognathism. Maxilla (SNA) and jaw discrepancy (ANB) were inversely related to the U1 degree, whereas only jaw discrepancy (ANB) was positively related to the L1 degree. U1 in PMx+PMd and L1 in OMx+OMd showed no incisor compensation. U1 had limited compensation even with progressive maxillary retrognathism while L1 showed limited compensation after one SD mandibular prognathism.

OBJECTIVE: The present study was designed to define a novel algorithm capable of predicting female adolescents\' cervical vertebrae maturation stage with high recall and accuracy.
METHODS: A total of 560 female cephalograms were collected, and cephalograms with unclear vertebral shapes and deformed scales were removed. 480 films from female adolescents (mean age: 11.5 years; age range: 6-19 years) were used for the model development phase, and 80 subjects were randomly and stratified allocated to the validation cohort to further assess the model\'s performance. Derived significant predictive parameters from 15 anatomic points and 25 quantitative parameters of the second to fourth cervical vertebrae (C2-C4) to establish the ordinary logistic regression model. Evaluation metrics including precision, recall, and F1 score are employed to assess the efficacy of the models in each identified cervical vertebrae maturation stage (iCS). In cases of confusion and mispredictions, the model underwent modification to improve consistency.
RESULTS: Four significant parameters, including chronological age, the ratio of D3 to AH3 (D3:AH3), anterosuperior angle of C4 (@4), and distance between C3lp and C4up (C3lp-C4up) were administered into the ordinary regression model. The primary predicting model that implements the novel algorithm was built and the performance evaluation with all stages of 93.96% for accuracy, 93.98% for precision, 93.98% for recall, and 93.95% for F1-score were obtained. Despite the hybrid logistic-based model achieving high accuracy, the unsatisfactory performance of stage estimation was noticed for iCS3 in the primary cohort (89.17%) and validation cohort (85.00%). Through bivariate logistic regression analysis, the posterior height of C4 (PH4) was further selected in the iCS3 to establish a corrected model, thus the evaluation metrics were upgraded to 95.83% and 90.00%, respectively.
CONCLUSIONS: An unbiased and objective assessment of the cervical vertebrae maturation (CVM) method can function as a decision-support tool, assisting in the evaluation of the optimal timing for treatment in growing adults. Our novel proposed logistic model yielded individual formulas for each specific CVM stage and attained exceptional performance, indicating the capability to function as a benchmark for maturity evaluation in clinical craniofacial orthopedics for Chinese female adolescents.

In the past few years, there has been an enormous increase in the application of artificial intelligence and its adoption in multiple fields, including healthcare. Forensic medicine and forensic odontology have tremendous scope for development using AI. In cases of severe burns, complete loss of tissue, complete or partial loss of bony structure, decayed bodies, mass disaster victim identification, etc., there is a need for prompt identification of the bony remains. The mandible, is the strongest bone of the facial region, is highly resistant to undue mechanical, chemical or physical impacts and has been widely used in many studies to determine age and sexual dimorphism. Radiographic estimation of the jaw bone for age and sex is more workable since it is simple and can be applied equally to both dead and living cases to aid in the identification process. Hence, this systematic review is focused on various AI tools for age and sex determination in maxillofacial radiographs. The data was obtained through searching for the articles across various search engines, published from January 2013 to March 2023. QUADAS 2 was used for qualitative synthesis, followed by a Cochrane diagnostic test accuracy review for the risk of bias analysis of the included studies. The results of the studies are highly optimistic. The accuracy and precision obtained are comparable to those of a human examiner. These models, when designed with the right kind of data, can be of tremendous use in medico legal scenarios and disaster victim identification.

BACKGROUND: When it comes to orthodontic diagnosis and treatment planning, the structures of the upper and lower airway space are crucial because of the role they play in craniofacial development.
OBJECTIVE: The major objective of this study was to evaluate the accuracy of lateral cephalogram in the evaluation of upper and lower pharyngeal space by comparing it to clinical usage of cone-beam computed tomography (CBCT) in quantifying the 3D morphology of the pharyngeal airway.
METHODS: In total, 70 patients were included in the study. They had both a CBCT scan and a lateral cephalogram performed within a week of each other. Different cephalometric landmarks have been utilized to estimate linear and area dimensions for use in lateral cephalogram airway investigations. By superimposing the lateral cephalogram measurement of the vertical height of the pharyngeal airway over axial CBCT slices of 0.8 to 1 mm in thickness, airway volumes were calculated. For this study, we measured the pharyngeal airway space in each patient in two dimensions (2D) using the airway area from the lateral cephalogram and in three dimensions (3D) using the airway volume from the CBCT scan over the same region of interest, using a uniform scale and magnification throughout all split 3D volumes.
RESULTS:  The mean value of the area of pharyngeal space calculated by lateral cephalograph analysis (LCA) was 336.35 ± 86.49 mm2. The maximum value was 551.234 mm2. The minimum value was 206.32 mm2. The mean value of the volume of the same area calculated using CBCT was 3409.11 ± 1237.96 mm3. The maximum value was 5887.23 mm3. When the area calculated using LCA was compared with the volume calculated using CBCT, the correlation between them was significant statistically (r=0.831, p-value =0.000). The mean values of volume evaluated in 3D CBCT in males were 4198±1008 mm3 while for females it was 2980±1134.5 mm3. During the statistical analysis, these observations were found to have a positive correlation with increased volume of pharyngeal space in males as compared to that of females (p=0.006). The values of the area of pharyngeal space calculated using LCA in males was 370.1±60.9 mm2. while it was 301.9±88 mm2  in females.
CONCLUSIONS: The area estimated for the pharyngeal airway on LCA correlates strongly with the volume determined by a CBCT scan. Since we have considered pharyngeal space analysis using CBCT to be a reliable and standard methodology, therefore a positive correlation of area calculated using LCA with volume calculated using CBCT shows that the analysis made by LCA can be reliable.

The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed. A saliency map was generated by gradient-weighted class activation mapping for each output. The two deep learning models achieved high values in each performance metric according to accuracy, sensitivity (recall), precision, F1 score, and areas under the receiver operating characteristic curve. Both models showed substantial differences in the positions indicated in saliency maps for male and female images. The positions in saliency maps also differed between VGG16 and DenseNet-121, regardless of sex. This analysis of our proposed system suggested that sex estimation from lateral cephalograms can be achieved with high accuracy using deep learning.

OBJECTIVE: To evaluate the size and shape of sella turcica and cranial base in patients with different degrees of congenital absence of teeth.
METHODS: The subjects comprised 322 patients from the Department of Orthodontics, West China Hospital of Stomatology, Sichuan University from 2020 to 2021. Based on the number of congenital absence of teeth, the patients were divided into three groups: control group (without loss of teeth, n=112), group Ⅰ (loss of 1-2 teeth, n=104), and group Ⅱ (loss of 3 or more teeth, n=106). Uceph cephalometric software was used to measure the linear and angular parameters of cranial base. The length, depth, and diameter of sella turcica were also calculated. The shape of sella turcica was described as normal or with aberrations. Analysis of variance, Kruskal-Wallis H test, chi-square test, and Fisher\'s exact test were conducted with SPSS 21.0.
RESULTS: No statistical differences were observed in the length, depth, and diameter of sella turcica and parameters related to the cranial base among the three groups (P>0.05). The incidence of sella turcica bridge among the three groups was statistically significant (P=0.013). The incidence was higher in the study group compared with the control group (P<0.05), and no significant difference was observed between groups Ⅰ and Ⅱ (P>0.05).
CONCLUSIONS: Although the linear size of sella turcica and parameters related to the cranial base was not statistically different between normal subjects and patients with congenital absence of teeth, the incidence of sella turcica bridge was higher in patients with congenital absence of teeth, suggesting the possibly abnormal anatomical morphology of sella turcica in this population.
目的: 探究不同程度恒牙先天缺失患者蝶鞍与颅底的大小及形态差异。方法: 选取2020—2021年就诊于四川大学华西口腔医院正畸科的322例患者为研究对象，依据先天缺牙数目将患者分为3组：对照组（无恒牙先天缺失，112例）；试验Ⅰ组（先天缺失1~2颗恒牙，104例）；试验Ⅱ组（先天缺失3颗及以上恒牙，106例）。使用Uceph头影测量软件对每位患者头颅侧位片的蝶鞍的长度、深度和直径以及颅底相关线性和角度参数进行测量。对每位患者的蝶鞍形态进行判定。采用SPSS 21.0软件对数据进行统计学分析。结果: 3组的蝶鞍长度、深度、直径以及颅底相关的线性和角度参数差异均无统计学意义（P>0.05）。3组的鞍桥发生率的差异有统计学意义（P=0.013），试验组高于对照组（P<0.05），试验Ⅰ组和试验Ⅱ组差异无统计学意义（P>0.05）。结论: 虽然蝶鞍的线性大小及颅底特征在正常人和先天缺牙患者中未见明显差异，但在先天缺牙患者中鞍桥发生率更高，提示该人群的蝶鞍解剖学形态可能异常。.