Artificial intelligence in age and sex determination using maxillofacial radiographs: A systematic review.

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.

Assessing the Accuracy of Lateral Cephalogram in Quantifying Three-Dimensional Pharyngeal Airway Morphology Compared to Cone-Beam Computed Tomography.

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. AIM: 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 AND MATERIALS: 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. CONCLUSION: 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.

Is Incisor Compensation Related to Skeletal Discrepancies in Skeletal Class III? A Retrospective Cephalometric Study.

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.

Mapping an intelligent algorithm for predicting female adolescents' cervical vertebrae maturation stage with high recall and accuracy.

BACKGROUNDS AND OBJECTIVES: 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.

Sex estimation from maxillofacial radiographs using a deep learning approach.

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.

Morphometric Analysis of Sella Turcica and a Proposed Novel Sella Turcica Index - A Digital Lateral Cephalometric Study.

Background: The sella turcica is a structure readily seen on lateral cephalograms and sella point is routinely traced for various cephalometric analyses. The aim of the present study was to evaluate the morphometric variation in size and shape of sella turcica via lateral cephalogram. The objectives were to introduce a novel sella turcica index (STI) and assess its reliability that could be helpful in gender determination. Materials and Methods: A total of 80 lateral cephalograms of the patients of age group 10-30 years were included for the study. The morphological variations of the sella turcica was done based on the classification given by Axelsson et al. (2004). The length, depth and perimeter of the sella turcica was measured and STI derived and calculated. The data was further subjected to discriminant analysis to validate the gender outcome. Reliability of the novel index was determined by calculating the sensitivity and specificity. Results: The overall most common morphological type of sella turcica was Type A (56.25%) followed by Type B (18.75%) and Type E (13.75%). The mean perimeter and depth of sella turcica was higher in females whereas the mean length of sella turcica was higher in males. The mean STI was higher in males and statistically highly significant. The sensitivity and specificity of this index was 72.5% and 90% respectively. Conclusion: A significant relationship was observed between the morphometric measurements of sella turcica and gender. STI could be of great help as a reliable tool for personal identification in forensic sciences. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-023-04082-9.

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.

Reliability and safety of miniscrew insertion planning with the use of lateral cephalograms assessed on corresponding cone-beam computer tomography images.

BACKGROUND/OBJECTIVES: Recently, lateral cephalograms have been proposed for guided miniscrew insertion planning. Therefore, the aim was to assess the reliability and safety of such planning on corresponding cone-beam computer tomography (CBCT) images. MATERIALS/METHODS: Intraoral scans, lateral cephalograms, and CBCT images of 52 subjects (even sexes distribution), aged 15.1 ±â€…2.5 years, were included. Miniscrew (n = 104) insertion planning was performed using lateral cephalograms superimposed on the maxillary intraoral scans, while the assessment of their bicortical placement, length in bone, contact with adjacent teeth, incisive canal, and nasal floor perforation was done on corresponding superimposed CBCT images. Moreover, maxillary incisor inclination, crowding, and the maxillary intercanine width were measured. RESULTS: The overall miniscrew length in bone was 7.2 ±â€…1.3mm. Bicortical placement was seen in 58.7% of the sample (38.5% of subjects). Incisive canal and nasal floor perforation was seen in 25% and 21.2% of subjects, respectively. No contact of the miniscrew with adjacent teeth was recorded. A negative significant interaction was seen between the miniscrew length in bone, the percentage of total miniscrew length and maxillary anterior teeth crowding (ß, -0.10, P = .047 and ß, -0.90, P = .006, respectively). Moreover, a positive significant interaction was seen between the incisive canal perforation and maxillary anterior teeth crowding (OR = 1.32, P = .021). LIMITATIONS: Exclusion of subjects with impacted teeth. CONCLUSIONS: Miniscrew insertion planning using lateral cephalograms, despite being safe in preventing contact with adjacent teeth, is limited in achieving bicortical placement and insufficient in completely avoiding incisive canal and nasal floor perforation.

Comparative manual and digital analysis of gonial angle in lateral cephalograms for gender determination.

Human skull has always been used for victim identification in forensic odontology. The gender-dimorphic bone of the skull is the mandible. The gonial angle has frequently been investigated for gender estimation with variable results and requires further exploration. We aim to compare the efficacy of gonial angle estimation by ancient methods of lateral cephalometric tracing compared with more recent digital analysis methods for gender estimation in the Indian population. Lateral cephalograms of 191 (96 M and 95F) cases above the age of 17 years were retrieved. Cephalometric analysis of gonial angle on radiographs was done using both manual cephalometric tracing method and digitally using Adobe Photoshop software. The results were subjected to statistical analysis for evaluation. The mean gonial angle was higher in females (125.05; 123.77 and 125.28) than in males (122.583; 121.715 and 122.008) using both manual and digital methods. On applying the logistical regression analysis (LRA), the digital method showed the highest gender estimation accuracy of 60.7% followed by Burstone's analysis (57.1%) and manual conventional analysis (56.5%). Burstone's analysis (57.9%) correctly identified increased females, whereas digital analysis (62.5%) and manual conventional analysis (59.4%) accurately recognised increased males. The present study showed a higher gender estimation accuracy using digital methods as compared to manual methods, but it still lacks the credibility to be used as a sole factor for predicting the gender of an individual. Hence, a cumulative factor must be taken into consideration for gender identification which would provide more promising results.

Effects of Twin-Block with an expanding device on the upper airway in growing children with skeletal class II malocclusion-a retrospective study based on the consistency of three-dimensional and two-dimensional data.

OBJECTIVES: Skeletal class II malocclusion is one of the most common malocclusions. Among the functional appliances for skeletal class II malocclusion, the Twin-Block appliance with a maxillary expander is effective in repositioning the mandible forward. In this study, we focused our efforts on investigating the effects of Twin-Block appliances with maxillary expanders on the upper airway in growing children with skeletal class II malocclusion by tracing and measuring lateral cephalograms after evaluating the consistency of three-dimensional CBCT data and two-dimensional lateral cephalogram data. MATERIALS AND METHODS: A total of 102 patients ranging from 9 to 15 years old (11.37 ± 2.80, male/female ratio = 1:1) with skeletal class II malocclusion were selected to evaluate the consistency of CBCT data and lateral cephalogram data. The strongly and moderately correlated segments were then selected to study the effects of Twin-Block with a maxillary expander on the upper airway in 66 growing children with skeletal class II malocclusion (11.31 ± 1.23 years old, male/female ratio = 1:1) by lateral cephalograms. RESULTS: The results showed a strong significant correlation in the nasopharynx (r = 0.708) and moderate significant correlations in the overall upper airway (r = 0.641), palatopharynx (r = 0.553), and glossopharynx (r = 0.575) but a weak correlation in the hypopharynx (r = 0.323). The corresponding determination coefficient (R2) was also determined by scatter plot analysis. Moreover, compared with the pretreatment data (T1), the total area of the upper airway and the areas of the nasopharynx, palatopharynx, and glossopharynx after functional treatment (T2) increased statistically and significantly. CONCLUSIONS: Lateral cephalograms can reflect the volume of the nasopharynx and oropharynx in skeletal class II children to a certain extent, while Twin-Block appliances with maxillary expanders can widen the volume of the nasopharynx and oropharynx significantly. CLINICAL RELEVANCE: The lateral cephalogram is reliable for analyzing the nasopharynx, palatopharynx, and glossopharynx in orthodontic clinical practice. Twin-Block appliances with maxillary expanders have a positive effect on skeletal class II patients with airway stenosis.

Correlation of "K" plane to occlusal plane and three different ala-tragal lines in dentulous subjects with different skeletal forms: A cephalometric study.

Aim: Orientation of the occlusal plane is an important clinical procedure for complete denture fabrication. An attempt had been made to reconstruct the occlusal plane using a different reference plane. The aim of this study was to find the correlation of the "K" plane to the occlusal plane and to assess the angular deviation between the K-plane to the occlusal plane (KO) with different skeletal forms. Settings and Design: An in vivo observational study was conducted on dentulous subjects having Class I dental occlusion with different skeletal forms undergoing orthodontic treatment. Materials and Methods: The study was conducted on 54 subjects aged 18-30 years. Metallic balls (3 mm in diameter) were attached to the desired landmarks, and a lateral cephalogram was taken for each subject. Cephalometric analysis was done using the Dolphin Imaging software, and the values obtained were recorded and subjected to statistical analysis. Statistical Analysis Used: The values obtained were recorded and subjected to statistical analysis using simple descriptive analysis, Shapiro-Wilk test, Mann-Whitney U-test, and Pearson's correlation. Results: A positive correlation was found between KO with a mean angular deviation of 8.59° ± 3.05°. The angle was found to be steeper in skeletal Class II subjects. Conclusions: Clinical application of the K-plane to use as a reference plane to orient the posterior occlusal plane can enhance the treatment outcome for a removable prosthesis. The results of this study provide a theoretical foundation for the practical restoration of the occlusal plane in different skeletal forms.

Role of the tonsil-oropharynx ratio on lateral cephalograms in assessing tonsillar hypertrophy in children seeking orthodontic treatment.

OBJECTIVES: To analyze the diagnostic value of the tonsil-oropharynx (T/O) ratio on lateral cephalograms for evaluating tonsillar hypertrophy (TH). METHODS: A cross-sectional study was performed on 185 consecutive children (101 males, 84 females; mean age 7.3 ± 1.4 years) seeking orthodontic treatment. The T/O ratios on lateral cephalograms were calculated following Baroni et al.'s method. Tonsil sizes were clinically determined according to the Brodsky grading scale. Spearman correlation coefficients between the T/O ratio and clinical tonsil size were calculated with the total sample and subgroups and then compared between subgroups. Diagnostic value was analyzed using the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive and negative predictive values, and accuracy. RESULTS: There was a strong correlation between the T/O ratio and clinical tonsil size in children (ρ = 0.73; P < 0.001). A significantly higher correlation coefficient was found in the Class III children. The ROC curve revealed an area under the curve of 0.90 (95% CI, 0.86-0.94; P < 0.001). The optimal cutoff value of the T/O ratio for predicting TH was 0.58, with a sensitivity of 98.7% and specificity of 64.2%. Employing the cutoff value of 0.5, the sensitivity was 100% and the specificity was 45.9%. CONCLUSIONS: Measurement of the T/O ratio on lateral cephalograms may be helpful to initial screening in children for TH. Practitioners may combine the clinical examination of tonsil size with the cephalometric findings for a more comprehensive evaluation.

Ceph-Net: automatic detection of cephalometric landmarks on scanned lateral cephalograms from children and adolescents using an attention-based stacked regression network.

BACKGROUND: The success of cephalometric analysis depends on the accurate detection of cephalometric landmarks on scanned lateral cephalograms. However, manual cephalometric analysis is time-consuming and can cause inter- and intra-observer variability. The purpose of this study was to automatically detect cephalometric landmarks on scanned lateral cephalograms with low contrast and resolution using an attention-based stacked regression network (Ceph-Net). METHODS: The main body of Ceph-Net compromised stacked fully convolutional networks (FCN) which progressively refined the detection of cephalometric landmarks on each FCN. By embedding dual attention and multi-path convolution modules in Ceph-Net, the network learned local and global context and semantic relationships between cephalometric landmarks. Additionally, the intermediate deep supervision in each FCN further boosted the training stability and the detection performance of cephalometric landmarks. RESULTS: Ceph-Net showed a superior detection performance in mean radial error and successful detection rate, including accuracy improvements in cephalometric landmark detection located in low-contrast soft tissues compared with other detection networks. Moreover, Ceph-Net presented superior detection performance on the test dataset split by age from 8 to 16 years old. CONCLUSIONS: Ceph-Net demonstrated an automatic and superior detection of cephalometric landmarks by successfully learning local and global context and semantic relationships between cephalometric landmarks in scanned lateral cephalograms with low contrast and resolutions.

Dental Occlusion Characteristics for Treatment Decision-Making Regarding Surgery-First Approach in Orthodontics.

The surgery-first approach (SFA) is conducted to decrease the difficulty and duration of orthodontic treatment by correcting the skeletal discrepancy at the initial stage of treatment. However, the indication of the SFA has not been well defined yet. This study explored the dental occlusion characteristics for treatment decision-making regarding the SFA. A total of 200 skeletal Class III patients were consecutively collected and divided into two groups: the orthodontic-first approach (OFA) group and the SFA group. The pretreatment digital dental models and lateral cephalograms were measured. Logistic regression was completed and receiver operating characteristic (ROC) curves were obtained to predict the probability of the SFA. Results showed that the ROC model with L1-MP, upper and lower arch length discrepancy, overbite, and asymmetric tooth number as influencing factors revealed that the sensitivity and specificity for determining SFA were 83.0% and 65.0%, respectively; the accuracy of prediction was 75.0%. In conclusion, our findings indicate that the six measurements from digital dental models and lateral cephalograms can be effectively applied in treatment decision-making for the SFA with satisfactory accuracy.

Contribution of masticatory muscle pattern to craniofacial morphology in normal adults: A cross-sectional MRI study.

Purpose: The study aimed to determine the muscle pattern of medial pterygoid, lateral pterygoid, and masseter (length, cross-section, and angulation) in adult non-orthodontic patients and its effect on craniofacial structures. Methods: The study was conducted from January 14, 2019 to January 14, 2020. Ethical clearance of this study was obtained from the ethical committee Ethical Clearance was obtained from Faculty of Dental Sciences, IMS, BHU, Institutional Ethical Committee with Ref no. Dean/2019/EC/1824 dated 23.04.2019 of the university. The sample size was estimated using the G-power statistical program. Power analysis indicated a minimum sample size of 27. Inclusion and exclusion criteria were set. Consent was taken from participants. Seventy-seven subjects who were willing to participate and have given written consent were enrolled for the study. Participants were sent for lateral cephalometry (Dolphin Cephalometric software) Dolphin Imaging and management solution, for 6 angular and 11 linear measurements. Nineteen subjects did not turn up for the scan. Twenty-eight participants underwent MRI (magnetic resonance imaging) to evaluate muscle patterns (masseter, medial, and lateral pterygoid). The intra-class correlation coefficient (ICC), Kolmogorov-Smirnov (KS) test, descriptive statistics, and multiple regression analysis were computed. The P value was set as ≤0.001(highly statistically significant) and ≤0.05 (significant relation). Results: There was a highly statistically significant (p ≤ 0.001) association between masseter length to upper facial height (N-Ans) and ramal length (Cd-Go). Length of medial pterygoid was significantly related (p ≤ 0.05) with SNB and length of body of mandible (Pog-Go). The cross-section of this muscle showed significant relation with upper facial height (N-Ans) and ramal length (Cd-Go). The correlation of the length of lateral pterygoid with upper facial height (N-Ans) and maxillary length (A-Ptm) was highly significant. Conclusion: The muscle pattern has a significant correlation with maxillofacial morphology. The masseter muscle is the longest and thickest (cross-section) and is angulated vertically than the other two muscles (medial pterygoid and lateral pterygoid). Of the three muscles, the medial pterygoid influences more common craniofacial parameters suggestive of its symbiotic activity. Lateral pterygoid affects the maxillary length and facial height.

Cervical Vertebral Maturation Assessment using various Machine Learning techniques on Lateral cephalogram: A systematic literature review.

Importance: For the assessment of optimum treatment timing in dentofacial orthopedics, understanding the growth process is of paramount importance. The evaluation of skeletal maturity based on study of the morphology of the cervical vertebrae has been devised to minimize radiation exposure of a patient due to hand wrist radiography. Cervical vertebral maturation assessment (CVMA) predictions have been examined in the state-of-the-art machine learning techniques in the recent past which require more attention and validation by clinicians and practitioners. Objectives: This paper aimed to answer the question "How are machine learning techniques being employed in studies concerning cervical vertebral maturation assessment using lateral cephalograms?" Method: A systematic search through the available literature was performed for this work based upon the Population, Intervention, Comparison and Outcome (PICO) framework. Data sources study selection data extraction and synthesis: The searches were performed in Ovid Medline, Embase, PubMed and Cochrane Central Register of Controlled Trials (CENTRAL) and Cochrane Database of Systematic Reviews (CDSR). A search of the grey literature was also performed in Google Scholar and OpenGrey. We also did a hand-searching in the Angle Orthodontist, Journal of Orthodontics and Craniofacial Research, Progress in Orthodontics, and the American Journal of Orthodontics and Dentofacial Orthopedics. References from the included articles were also searched. Main outcomes and measures results: A total of 25 papers which were assessed for full text, and 13 papers were included for the systematic review. The machine learning methods used were scrutinized according to their performance and comparison to human observers/experts. The accuracy of the models ranged between 60 and 90% or above, and satisfactory agreement and correlation with the human observers. Conclusions and relevance: Machine learning models can be used for detection and classification of the cervical vertebrae maturation. In this systematic review (SR), the studies were summarized in terms of ML techniques applied, sample data, age range of sample and conventional method for CVMA, which showed that further studies with a uniform distribution of samples equally in stages of maturation and according to the gender is required for better training of the models in order to generalize the outputs for prolific use to target population.

The psc-CVM assessment system: A three-stage type system for CVM assessment based on deep learning.

BACKGROUND: Many scholars have proven cervical vertebral maturation (CVM) method can predict the growth and development and assist in choosing the best time for treatment. However, assessing CVM is a complex process. The experience and seniority of the clinicians have an enormous impact on judgment. This study aims to establish a fully automated, high-accuracy CVM assessment system called the psc-CVM assessment system, based on deep learning, to provide valuable reference information for the growth period determination. METHODS: This study used 10,200 lateral cephalograms as the data set (7111 in train set, 1544 in validation set and 1545 in test set) to train the system. The psc-CVM assessment system is designed as three parts with different roles, each operating in a specific order. 1) Position Network for locating the position of cervical vertebrae; 2) Shape Recognition Network for recognizing and extracting the shapes of cervical vertebrae; and 3) CVM Assessment Network for assessing CVM according to the shapes of cervical vertebrae. Statistical analysis was conducted to detect the performance of the system and the agreement of CVM assessment between the system and the expert panel. Heat maps were analyzed to understand better what the system had learned. The area of the third (C3), fourth (C4) cervical vertebrae and the lower edge of second (C2) cervical vertebrae were activated when the system was assessing the images. RESULTS: The system has achieved good performance for CVM assessment with an average AUC (the area under the curve) of 0.94 and total accuracy of 70.42%, as evaluated on the test set. The Cohen's Kappa between the system and the expert panel is 0.645. The weighted Kappa between the system and the expert panel is 0.844. The overall ICC between the psc-CVM assessment system and the expert panel was 0.946. The F1 score rank for the psc-CVM assessment system was: CVS (cervical vertebral maturation stage) 6 > CVS1 > CVS4 > CVS5 > CVS3 > CVS2. CONCLUSIONS: The results showed that the psc-CVM assessment system achieved high accuracy in CVM assessment. The system in this study was significantly consistent with expert panels in CVM assessment, indicating that the system can be used as an efficient, accurate, and stable diagnostic aid to provide a clinical aid for determining growth and developmental stages by CVM.

Predictive Equation for Construction of Anatomic Porion with Machine Porion as Reference Point.

AIM: The aim of the study was to find a relationship between anatomic porion (PoA) and machine porion (PoM) and to construct PoA with the help of machine porion. METHODOLOGY: About 200 pretreatment lateral roentgenic cephalograms were used for the study. Perpendicular distances of PoA and PoM were measured from Sella-Nasion (SN) plane and SN perpendicular plane. The results were tabulated. With the help of statistical analysis, predictive equation was derived to construct PoA and PoM. p-value was set at p < 0.05. RESULTS: Anatomic porion distance from SN was 24.35 ± 3.96 and from SN perpendicular was 12.89 ± 4.56. Distance of PoM from SN was 22.46 ± 4.20 and from SN perpendicular was 16.76 ± 4.89. Sexual dimorphism was also seen. CONCLUSION: There is a relationship between the PoM and PoA, thus, PoA, which is more reliable, can be constructed with the help of PoM, which is easy to reproduce. CLINICAL SIGNIFICANCE: To overcome the inherent limitations of PoA and PoM, the present study aimed to find a relationship between the two so as to easily construct PoA that is more reliable while taking advantage of the ease of reproducibility of PoM.

Multi-stage Unet segmentation and automatic measurement of pharyngeal airway based on lateral cephalograms.

OBJECTIVES: Orthodontic treatment profoundly impact the pharyngeal airway (PA) of patients. Airway examination is an integral part of daily orthodontic diagnosis, and lateral cephalograms (LC) are reliable to reveal PA structures. This study attempted to develop a simple method to help clinicians make a preliminary judgement of patients' PA conditions and assess the impact of orthodontic treatment on their airways. METHODS: LCs of 764 patients were used to train a multistage unit segmentation model. Another 130 images were used to validate the model and more 130 images were used to test the model. RESULTS: Unet was used as the backbone, with a mean dice value of 0.8180, precision of 0.8393, and recall of 0.8188. Furthermore, we identified seven key points and measured related indices. The length of the line separating the nasopharynx and oropharynx and the line separating the oropharynx and hypopharynx were manually measured thrice and the average values was compared. The intraclass correlation coefficient (ICC) for the two lines was 0.599 and 0.855. Then, we performed a single linear regression analysis, which indicated a strong correlation between the predictions and measurements for the two lines. CONCLUSIONS: This method is reliable for segmenting three regions (nasopharynx, oropharynx, and hypopharynx) of the PA and calculating related indices. However, the predictions obtained from this model still have errors, and it is necessary for clinical practitioners to assess and adjust the predictions. CLINICAL SIGNIFICANCE: Our model can help orthodontists formulate personalised treatment plans and evaluate the risk of airway stenosis during orthodontic treatment. This method may mark the beginning of a new and simpler approach for PA obstruction detection, specifically tailored to orthodontic patients.

Radiodiagnostics of standard orthodontic radiographs-dental and extradental incidental findings : Do we see everything we should see?

OBJECTIVES: The extent of undetected incidental findings in routine orthodontic radiographs is still unknown. However, incidental findings that are not in the primary focus of orthodontic diagnostics may be of high medical relevance. Therefore, this study aimed to analyse whether incidental findings are reliably detected and which parameters influence the orthodontist's assessment. METHODS: In a clinical cross-sectional study 134 orthodontists evaluated two orthopantomogram (OPT) and two lateral cephalogram (LC) radiographs each via a standardised online survey. The radiographs were previously examined by three dentists and one radiologist-in a pilot phase-regarding the number of incidental findings and subsequently defining as gold standard in a consensus procedure. The radiographs were presented consecutively, the number of incidental findings detected were noted and the individual findings could be described in free text form. RESULTS: Overall, 39.1% of the incidental findings were detected. The orthodontists' focus was primarily on the dental region. Here, 57.9% of incidental findings were detected, while 20.3% were detected in extradental regions (p < 0.001). A highly relevant finding of suspected arteriosclerotic plaque was detected in 7.5% of cases (OPT). Significantly more incidental findings were detected on OPTs than on LCs (OPT 42.1%, LC 36.0%, p < 0.001). As participants' length of professional experience increased, significantly more time was spent on the assessment (p < 0.001), correlating positively with the detection of incidental findings. CONCLUSIONS: Even in daily routine practice, attention must be paid to a thorough assessment of all radiographed regions. The factors time and professional experience can prevent practitioners from overlooking findings outside the orthodontic focus.