Turkish Journal of Orthodontics最新文献

{"title":"Evaluation of Orthodontic Patients' Anxiety Levels During the COVID-19 Pandemic: A 1-Year Follow-Up.","authors":"Mehmet Ali Yavan,&nbsp;Merve Nur Eğlenen","doi":"10.5152/TurkJOrthod.2022.22009","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.22009","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to evaluate the anxiety levels of orthodontic patients during the 1-year period in the ongoing pandemic.</p><p><strong>Methods: </strong>The study included patients between the ages of 12 and 30 years and who were continuing their fixed orthodontic treatment at Adıyaman University, Faculty of Dentistry, Department of Orthodontics and filled out the State-Trait Anxiety Inventory. A total of 266 patients filled out the questionnaire at their first clinical visit between June 8 and July 8, 2020 (T0) and 176 of 190 patients (response rate: 92.63%) that were still under treatment filled out the questionnaire for a second time between June 15 and July 16, 2021 (T1).</p><p><strong>Results: </strong>In the total population, there was a significant decrease in the State-Trait Anxiety Inventory-S score (P < .05), while there was no significant change in the State-Trait Anxiety Inventory-T score (P > .05). Anxiety scores were significantly higher in women and individuals aged over 18 years at T0 (P < .05), whereas only the anxiety scores of individuals aged over 18 years were significantly higher in T1 than in individuals aged below 18 years (P < .05). The State-Trait Anxiety Inventory-S score showed a significant decrease at T1 compared to T0 for female patients (36.02 ± 11.32 vs. 38.82 ± 9.84) and patients aged under 18 years (34.26 ± 9.54 vs. 36.85 ± 9.26) (P < .05).</p><p><strong>Conclusion: </strong>The state anxiety levels of orthodontic patients decreased during the 1-year period of the pandemic, while there was no significant change in their trait anxiety levels.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 3","pages":"180-185"},"PeriodicalIF":1.1,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9623189/pdf/tjo-35-3-180.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33481407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An assessment of the Quality of Information for Patients on YouTube™ Regarding Orthodontic Elastics.","authors":"Tuğba Haliloğlu Özkan,&nbsp;Derya Dursun","doi":"10.5152/TurkJOrthod.2022.21132","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.21132","url":null,"abstract":"<p><strong>Objective: </strong>The study aimed to investigate the quality of the information available to patients on YouTube™ concerning orthodontic elastics.</p><p><strong>Methods: </strong>A systematic search was carried out on YouTube™ using the keyword \"elastics.\" The first 120 videos were viewed by 2 independent reviewers, and after the inclusion criteria were applied, 39 videos were excluded from the study. Demographic data of the videos were collected for the remaining 81 videos. For each video, its purpose, target audience, and source were also recorded. A 10-point content scale was used to evaluate the video content. The Global Quality Scale was also used to determine the quality of the videos. Statistical analyses were performed using the Kruskal-Wallis and Mann-Whitney U tests, and correlation coefficient analyses were performed using Spearman's rho.</p><p><strong>Results: </strong>In total, 36% of the included videos were uploaded by dentists and 22% by laypersons. In 77% of the videos, the purpose was to inform laypersons, and in 4%, the purpose was to inform professionals only. The content discussed the most (85.2%) was the instruction of orthodontic elastics use. The mean 10-point Content Scale score and Global Quality Scale score of the videos were 2.25 ± 1.99 (poor) and 2.60 ± 0.73 (moderate), respectively. There was a positive correlation between 10-point Content Scale and Global Quality Scale score (r = 0.258).</p><p><strong>Conclusion: </strong>The information available on YouTube™ regarding orthodontic elastics is quite poor and can be misleading for patients. Therefore, health professionals with evidence-based knowledge and clinical experience should improve the way they use YouTube™ to inform patients about the correct use of orthodontic elastics and to improve compliance with wearing orthodontic elastics.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 3","pages":"192-197"},"PeriodicalIF":1.1,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9623206/pdf/tjo-35-3-192.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33481408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of a Convolutional Neural Network- Based Artificial Intelligence Algorithm for Automatic Cephalometric Landmark Detection.","authors":"Mehmet Uğurlu","doi":"10.5152/TurkJOrthod.2022.22026","DOIUrl":"10.5152/TurkJOrthod.2022.22026","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study is to develop an artificial intelligence model to detect cephalometric landmark automatically en- abling the automatic analysis of cephalometric radiographs which have a very important place in dental practice and is used routinely in the diagnosis and treatment of dental and skeletal disorders.</p><p><strong>Methods: </strong>In this study, 1620 lateral cephalograms were obtained and 21 landmarks were included. The coordinates of all landmarks in the 1620 films were obtained to establish a labeled data set: 1360 were used as a training set, 140 as a validation set, and 180 as a testing set. A convolutional neural network-based artificial intelligence algorithm for automatic cephalometric landmark detection was developed. Mean radial error and success detection rate within the range of 2 mm, 2.5 mm, 3 mm, and 4 mm were used to eval- uate the performance of the model.</p><p><strong>Results: </strong>Presented artificial intelligence system (CranioCatch, Eskişehir, Turkey) could detect 21 anatomic landmarks in a lateral ceph- alometric radiograph. The highest success detection rate scores of 2 mm, 2.5 mm, 3 mm, and 4 mm were obtained from the sella point as 98.3, 99.4, 99.4, and 99.4, respectively. The mean radial error ± standard deviation value of the sella point was found as 0.616 ± 0.43. The lowest success detection rate scores of 2 mm, 2.5 mm, 3 mm, and 4 mm were obtained from the Gonion point as 48.3, 62.8, 73.9, and 87.2, respectively. The mean radial error ± standard deviation value of Gonion point was found as 8.304 ± 2.98.</p><p><strong>Conclusion: </strong>Although the success of the automatic landmark detection using the developed artificial intelligence model was not in- sufficient for clinical use, artificial intelligence-based cephalometric analysis systems seem promising to cephalometric analysis which provides a basis for diagnosis, treatment planning, and following-up in clinical orthodontics practice.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"94-100"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450082/pdf/tjo-35-2-94.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Vivo Comparison of the Efficiency of En-Masse Retraction Using Temporary Anchorage Devices With and Without Orthodontic Appliances on the Posterior Teeth.","authors":"Sanjam Oswal,&nbsp;Sonali V Deshmukh,&nbsp;Sanket S Agarkar,&nbsp;Sachin Durkar,&nbsp;Chaitra Mastud,&nbsp;Jayesh S Rahalkar","doi":"10.5152/TurkJOrthod.2022.20149","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.20149","url":null,"abstract":"<p><strong>Objective: </strong>To compare the effectiveness of en-masse retraction of maxillary anterior teeth using temporary anchorage devices with and without orthodontic appliances on the posterior teeth.</p><p><strong>Methods: </strong>In the study, 20 participants (18.25 ± 4.07 years) meeting the inclusion criteria were randomly divided into 2 groups using the sequentially numbered opaque sealed envelopes method. In group I (control group, n = 10), en-masse retraction was carried out with conventional high hooks soldered to the retraction wire and posterior teeth were included. In group II (experimental group, n = 10), the en-masse retraction was carried out without an orthodontic appliance on posterior teeth and a modified retraction wire was incorporated. In both groups, mini-implants were placed bilaterally between the maxillary second premolar and maxillary first molar, and a retraction force of 6 ounces (180 g) was applied using power chains. Lateral cephalograms and study models were taken before retraction and 4 months after retraction. All statistical analyses were performed with Statistical Package for the Social Sciences soft- ware with a statistically significant level of 5%. We used unpaired t-tests for the comparison, and the error of the method was assessed using intraclass correlation coefficients and the Bland-Altman method.</p><p><strong>Results: </strong>The maxillary incisor apex retraction, change in maxillary incisor in the vertical plane, and its inclination showed statistically significant differences (P < .05). The rate of retraction was significantly greater in the experimental group when evaluated clinically and in the study models (P < .05).</p><p><strong>Conclusion: </strong>The rate/amount of retraction evaluated clinically and in the study models was significantly faster/greater when the pos- terior teeth were not included during anterior retraction. Also, a greater amount of bodily retraction of anterior teeth was achieved.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"112-119"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320341/pdf/tjo-35-2-112.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association of ACTN3 Rs1815739 Polymorphism with Various Malocclusion Phenotype.","authors":"Hussain Nihad Izaddin Alalim,&nbsp;Başak Funda Eken,&nbsp;Korkut Ulucan,&nbsp;Fulya Özdemir","doi":"10.5152/TurkJOrthod.2022.21171","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.21171","url":null,"abstract":"<p><strong>Objective: </strong>A functional polymorphism on the 16th exon of the alpha-actinin-3 gene has an effect on the protein structure and cellular signaling and therefore on muscle contraction. In this study, we aimed to analyze the alpha-actinin-3 rs1815739 polymorphism in 3-dimensional malocclusions and different craniofacial skeletal patterns.</p><p><strong>Methods: </strong>Forty-nine volunteering subjects enrolled for the study. Genotyping of alpha-actinin-3 rs1815739 polymorphism was per- formed using real-time polymerase chain reaction. Pre-orthodontic cephalometric radiographs were traced using NemoTech ceph- alometric tracing software. IBM SPSS Statistics for Windows was utilized to carry out statistical analysis. P < .05 was considered to be statistically significant.</p><p><strong>Results: </strong>The respective numbers and the percentages of alpha-actinin-3 rs1815739 polymorphisms for RR, RX, and XX genotypes were 39 (79.6%), 4 (8.2%), and 6 (12.2%), respectively. Twenty-one patients had low angle vertical patterns and 17 patients had Class I and the same number of the patients had Class III facial patterns. But none of these had statistically significant difference in terms of alpha-actinin-3 rs1815739 polymorphism and in vertical or sagittal facial patterns, and mandibular incisor inclination. When we examined the maxillary anteroposterior position, we found a significant difference between rs1815739 polymorphisms (P < .05). Also, we detected a significant difference between rs1815739 polymorphism and maxillary incisor inclination (P < .05).</p><p><strong>Conclusion: </strong>Maxillary incisor inclination and maxillary anteroposterior position are associated with alpha-actinin-3 rs1815739 poly- morphism in a Turkish cohort.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"127-132"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321258/pdf/tjo-35-2-127.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Risk Factors for Severe Apical Root Resorption in the Maxillary Incisors Following Fixed Orthodontic Treatment.","authors":"Bashar Shahrure,&nbsp;Ahu Acar","doi":"10.5152/TurkJOrthod.2022.20139","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.20139","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to retrospectively determine the prevalence of severe external root resorption in maxillary inci- sors during fixed orthodontic treatment and to evaluate the possible predisposing factors.</p><p><strong>Methods: </strong>The treatment records of 7000 patients who had been treated between 1990 and 2019 at the Department of Orthodontics Faculty of Dentistry Marmara University were examined, and a total of 120 patients with severe root resorption in at least one of their upper incisors were identified. The following data were retrieved from the patients' records and radiographs: gender, root morpholo- gy, overjet, overbite, treatment modality (extraction, non-extraction), treatment duration, buccal and palatal alveolar bone thickness for the maxillary incisors, and amount of movement of the incisal root apices and incisal edges. These data from a group of 90 patients with severe root resorption were compared with the data from a control group of 90 patients with minimal root resorption. The Chi- square test, the Mann-Whitney U-test, and the independent t-test were used for statistical analysis.</p><p><strong>Results: </strong>The prevalence of severe external root resorption was 3.23%, and the results demonstrated significant difference between the groups for the variables of treatment modality (extractions), treatment duration, thickness of the alveolar bone, and amount of incisor movement at the end of the treatment.</p><p><strong>Conclusion: </strong>It can be concluded that extractions, increased treatment duration, thin alveolar bone, and excessive incisor movement represent risk factors for severe root resorption in maxillary incisors following orthodontic treatment.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"75-83"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321704/pdf/tjo-35-2-75.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40561090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Management of Anterior Open Bite and Skeletal Class II Hyperdivergent Patient with Clear Aligner Therapy.","authors":"Sudha Gudhimella,&nbsp;Vaibhav Gandhi,&nbsp;Nichole Leigh Schiro,&nbsp;Nandakumar Janakiraman","doi":"10.5152/TurkJOrthod.2022.21053","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.21053","url":null,"abstract":"<p><p>In orthodontics, patients with hyperdivergent facial types or problems in the vertical dimension are often challenging to treat with predictable treatment results. Conventionally along with fixed appliances, a headgear, posterior bite block, extraction, temporary anchorage devices, or orthognathic surgery are preferable approaches to treat such patients. This case report illustrates a non-extraction, non-surgical orthodontic treatment of 5 mm anterior open bite in a non-growing adult patient, utilizing clear aligner therapy.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"139-149"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317343/pdf/tjo-35-2-139.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maxillary Incisor Intrusion Using Mini-Implants and Conventional Intrusion Arch: A Systematic Review and Meta-Analysis.","authors":"Prateek Shakti,&nbsp;Abhinav Singh,&nbsp;Abhishek Purohit,&nbsp;Nidhi Shah","doi":"10.5152/TurkJOrthod.2022.21080","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.21080","url":null,"abstract":"<p><p>The aim of this analysis was to evaluate the maxillary incisor intrusion and change in overbite achieved by micro-implants compared to Connecticut intrusion arches among post-pubertal patients with deep bite. Medline, PubMed, Cochrane, and Google scholar were searched for studies falling under the inclusion criteria. Randomized controlled trials (RCTs) and controlled clinical trials (CCTs) com- paring maxillary incisor intrusion among post-pubertal deep bite cases treated by mini-implants and Connecticut intrusion arches were to be included. Outcome data were extracted using guidelines published by the Cochrane Collaboration. A systematic review was conducted using Cochrane Program Review Manager, version 5. A random effects model was used to assess the mean difference in the amount of incisor intrusion and overbite correction achieved between the 2 methods. Statistical significance was set at P < .05. Assessment of certainty of evidence was conducted using GRADE analysis. Six trials met the inclusion criteria. Mean differences for incisor intrusion -0.67 [95% CI, 0.97, 0.38] I2 = 31%; P < .00001) and overbite correction -0.51 [95% CI, 0.85, 0.16] I2 = 50%; P = .004) achieved with mini-implants were found to be significantly effective when compared to the Connecticut intrusion arch. Low to mod- erate heterogeneity was noted for incisor intrusion and change in overbite analysis respectively. High certainty of evidence was noted for higher association of mini-implants with incisor intrusion and overbite correction. Our meta-analysis suggests that mini-implants are superior to the Connecticut intrusion arch with respect to the amount of incisor intrusion and overbite correction. Further studies are still needed to confirm the superiority.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"150-156"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316784/pdf/tjo-35-2-150.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Palatal Bone Thickness and Its Relationship with Palatal Vault Depth for Mini-Implant Insertion Using Cone Beam Computed Tomography Images.","authors":"Gholinia Faegheh,&nbsp;Negar Khosravifard,&nbsp;Dina Maleki,&nbsp;Sahar Khaje Hosseini","doi":"10.5152/TurkJOrthod.2022.20145","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.20145","url":null,"abstract":"<p><strong>Objective: </strong>The purpose of this study was to measure the thickness of the palatal bone using cone beam computed tomography images for placement of mini-screws and their relationship with palatal vault depth.</p><p><strong>Methods: </strong>This study was performed on 150 maxillary cone beam computed tomography images, 50% (n = 75) had deep palate and 50% (n = 75) had normal palate and 27.3% (n = 41) were male and 72.7% (n =109) were female. Coronal sections with a thickness of 1 mm were prepared at distances of 4 mm, 8 mm, 12 mm, 16 mm, 20 mm, and 24 mm from the posterior wall of the incisive foramen. Then, in each section, in the midsagittal line and at distances of 2 mm, 4 mm, 6 mm, 8 mm, and 10 mm from that to the lateral sides, the bone thickness was measured. The Korkhaus index was used to identify the patients with a high palatal vault.</p><p><strong>Results: </strong>The results showed that at the posterior sections in the midsagittal and parasagittal area, a significant difference (P < .05) was observed between deep and normal palate, and in these points, the bone thickness in the normal palate was greater. Also, in the section of 4 mm and 8 mm, a significant difference was observed between males and females in most of these points, and those were greater in males than females.</p><p><strong>Conclusion: </strong>The maximum thickness of the palatal bone was observed first along the midsagittal line and then the paramedian and in the anterior section. Patients with deep palate had less palatal bone thickness in the posterior sections.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"120-126"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316261/pdf/tjo-35-2-120.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cephalometric Variables Prediction from Lateral Photographs Between Different Skeletal Patterns Using Regression Artificial Neural Networks.","authors":"Saif Mauwafak Ali,&nbsp;Hayder Fadhil Saloom,&nbsp;Mohammed Ali Tawfeeq","doi":"10.5152/TurkJOrthod.2022.21087","DOIUrl":"https://doi.org/10.5152/TurkJOrthod.2022.21087","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to design an artificial neural network for the prediction of cephalometric variables via a lateral photo- graph in skeletal Class I, II, and III patterns.</p><p><strong>Methods: </strong>A total of 94 patients were recruited for this prospective study, with an age range of 15-20 years (41 boys and 53 girls) seek- ing orthodontic treatment. According to cephalometric analysis, using AutoCAD 21.0, they were allocated into three groups. Thirty with skeletal Class I (14 boys and 16 girls), 34 with skeletal Class II (14 boys and 20 girls), and 30 with skeletal Class III malocclusion (13 boys and 17 girls) according to SNA, SNB, and ANB angles measured from cephalometric radiographs. The study includes (1) finding the correlation of the skeletal measurements between lateral profile photographs and cephalometric radiographs for the recruited patients and (2) designing a specific artificial neural networks for the assessment of skeletal factors via lateral photographs, these artificial neural networks are trained and tested with the total of 94 standard lateral cephalograms.</p><p><strong>Results: </strong>This novel Network provided models of regression that can forecast the cephalometric variables through analogous photo- graphic measurements with excellent predictive power R = 0.99 and limited estimation error for each malocclusion (Class I, II, and III).</p><p><strong>Conclusion: </strong>This study suggests that artificial intelligence would be useful as an accurate method in orthodontics for the prediction of cephalometric variables and its performance was achieved by several factors such as proper selection of the input data, preferable generalization, and organization.</p>","PeriodicalId":37013,"journal":{"name":"Turkish Journal of Orthodontics","volume":"35 2","pages":"101-111"},"PeriodicalIF":1.1,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317940/pdf/tjo-35-2-101.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40563563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}