American Journal of Orthodontics and Dentofacial Orthopedics最新文献

{"title":"Time proven","authors":"Peter M. Greco","doi":"10.1016/j.ajodo.2025.10.003","DOIUrl":"10.1016/j.ajodo.2025.10.003","url":null,"abstract":"","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 6-7"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An objective method for assessing the maturation of bone sutures involved in the rapid maxillary expansion","authors":"Fernanda Filgueiras ,&nbsp;Giovanni Cerrone Júnior ,&nbsp;Jocimara Domiciano Fartes de Almeida Campos ,&nbsp;Rogério Lacerda-Santos ,&nbsp;Fabício Tinoco Alvin de Souza ,&nbsp;Robert Willer Farinazzo Vitral ,&nbsp;Marcio José da Silva Campos","doi":"10.1016/j.ajodo.2025.08.013","DOIUrl":"10.1016/j.ajodo.2025.08.013","url":null,"abstract":"<div><h3>Introduction</h3><div>This study aimed to evaluate the maturation of the midpalatal suture (MPS), zygomaticomaxillary suture, and zygomaticotemporal suture (ZTS) (right and left) through density by multislice computed tomography in patients categorized by age groups.</div></div><div><h3>Methods</h3><div>We evaluated tomographic images of 192 participants (aged 7-30 years), divided into 3 groups by age. To analyze the maturation of the sutures, the density scores of MPS, zygomaticomaxillary, and ZTS were determined in Hounsfield units, within an area corresponding to 1 mm in width and length, referring to the longest length of each suture, in 3 regions: central, right adjacent, and left adjacent sites. A density cutoff point in MPS for performing rapid maxillary expansion was established using the receiver operating characteristic curve.</div></div><div><h3>Results</h3><div>The length of the sutures has a positive correlation with age and density. Density in all measurements showed a positive and significant correlation with age. All sutures had lower density in central sites than in adjacent sites (except in group 3: left adjacent sites of MPS and zygomatic site of ZTS sutures). There was no significant difference between the sexes. The density cutoff point in MPS was 294.4 Hounsfield units.</div></div><div><h3>Conclusions</h3><div>Density increases with age, showing a significant correlation. Central sites have lower density than adjacent sites, especially in younger patients. Sex does not have any relevant effects on the final measurement values , and density appears to be correlated with the degree of sutures maturation.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 12-21"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145226266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planned and achieved orthodontic tooth movement and labiolingual inclination changes of mandibular incisors during nonextraction space closure with clear aligners: A retrospective cohort study","authors":"Darshan N. Desai,&nbsp;Tony Weir,&nbsp;Maurice J. Meade","doi":"10.1016/j.ajodo.2025.09.012","DOIUrl":"10.1016/j.ajodo.2025.09.012","url":null,"abstract":"<div><h3>Introduction</h3><div>The study aimed to determine the center of rotation and the type of orthodontic tooth movement (OTM) of the mandibular central incisors (Cis) and lateral incisors (Lis), and the efficacy of achieving planned labiolingual incisor inclination changes after nonextraction space closure (NESC) with the Invisalign (Align Technology, Santa Clara, Calif) appliance.</div></div><div><h3>Methods</h3><div>Digital study models of initial, planned, and achieved treatment outcomes were obtained from the Invisalign treatment planning facility, ClinCheck. Vectors analogous to the long axes of the incisors were generated using Geomagic Control X (version 2022.0: 3D Systems, Cary, NC) metrology software. Intersecting vectors represented the incisors’ center of rotation, whereas measurement of the vectors to a reference y-plane enabled determination of incisor labiolingual inclination.</div></div><div><h3>Results</h3><div>A total of 166 mandibular incisors from 42 patients satisfied the inclusion criteria. The achieved mean (standard deviation) OTMs were 41.4% (23.6) of those planned. Translation was the least successful OTM, with 7.6% of Cis and 8.3% of Lis translating as planned. Planned retroclination resulted in overexpression of 151% for CIs and 165% for Lis. The accuracy of planned proclination was low, with only 16.7% of CIs and 25.8% of Lis proclining as planned, whereas the remainder retroclined instead.</div></div><div><h3>Conclusions</h3><div>Less than half of the planned OTM for the mandibular incisors during NESC was achieved. Planned retroclination was overexpressed, and most of planned proclination resulted in retroclination. Clinicians should consider these findings when planning NESC treatment with the Invisalign appliance.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 99-109"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145309947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of artificial intelligence in providing accurate and reliable information on surgically-assisted rapid palatal expansion: A cross-sectional study","authors":"Şirin Hatipoğlu ,&nbsp;Esra Çifçi Özkan ,&nbsp;Fatma Aslı Konca Taşova ,&nbsp;Özge Özdal Zincir","doi":"10.1016/j.ajodo.2025.08.015","DOIUrl":"10.1016/j.ajodo.2025.08.015","url":null,"abstract":"<div><h3>Introduction</h3><div>This study aimed to evaluate the accuracy, reliability, and comprehensibility of information about surgically-assisted rapid palatal expansion provided by language models based on artificial intelligence (AI).</div></div><div><h3>Methods</h3><div>A cross-sectional content analysis was conducted on the responses to surgically-assisted rapid palatal expansion-related questions by ChatGPT-4 (OpenAI LLC, San Francisco, Calif), Gemini (Alphabet Inc, Mountain View, Calif), and Copilot (Microsoft, Redmond, Wash). In total, 115 questions (categorized into 11 domains) were created by 3 orthodontists and 1 oral and maxillofacial surgeon. The accuracy of the answers generated by the AI language models was independently evaluated by the same experts via a 5-point Likert scale. To test the relationships among categorical variables, when the sample size assumption was met, the Pearson chi-square test was used. However, when the sample size assumption was not met, Fisher’s exact test was applied. Analyses were performed in SPSS (version 27; IBM, Armonk, NY).</div></div><div><h3>Results</h3><div>The responses of the AI types presented a general homogeneous distribution, with no statistically significant difference between the types of AI and the types of responses (<em>P</em> &gt;0.05). Although there were no significant differences, ChatGPT-4 had the highest objectively true rate. In contrast, Gemini produced answers with more balanced accuracy, whereas Copilot had the highest number of false answers.</div></div><div><h3>Conclusions</h3><div>These findings reveal that the accuracy of AI-supported language models in providing medical information may vary according to subject matter.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 31-41.e3"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145240301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authors’ response","authors":"Maurice J. Meade,&nbsp;Tony Weir,&nbsp;Haylea L. Blundell","doi":"10.1016/j.ajodo.2025.10.004","DOIUrl":"10.1016/j.ajodo.2025.10.004","url":null,"abstract":"","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 4-5"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of a new, slim, and rigid CAD-CAM transfer tray: An in vivo study","authors":"Mario Palone ,&nbsp;Petra J. Koch ,&nbsp;Julia De Geer ,&nbsp;Gianmarco Guidetti ,&nbsp;Francesca Cremonini ,&nbsp;Giorgio A. Spedicato ,&nbsp;Luca Brucculeri ,&nbsp;Alessandro Verducci ,&nbsp;Luca Lombardo","doi":"10.1016/j.ajodo.2025.08.016","DOIUrl":"10.1016/j.ajodo.2025.08.016","url":null,"abstract":"<div><h3>Introduction</h3><div>The objective of this study was to evaluate the in vivo transfer accuracy of a new slim and rigid computer-aided design and manufacturing (CAD-CAM) transfer tray.</div></div><div><h3>Methods</h3><div>Seventeen patients (9 males and 8 females; average age, 14.3 years) with permanent dentition undergoing orthodontic treatment were enrolled. Digital models were obtained, and brackets and molar tubes were virtually positioned. The CAD-CAM transfer tray was designed and 3-dimensionally printed, and the bonding procedure was performed. Transfer accuracy was assessed by measuring linear and angular deviations between planned and in vivo bonded bracket positions by superimposition using a local best-fit alignment performed by a semiautomatic algorithm in the analysis software Geomagic Control (3D System Inc, Rock Hill, NC).</div></div><div><h3>Results</h3><div>A total of 408 teeth (208 maxillary and 200 mandibular) were superimposed. All mean linear deviations were &lt;0.5 mm, although some exceeded the 0.25-mm cutoff (4.4% of mesiodistal measurements, 4.2% of vertical, and 0.2% of buccolingual). Angular discrepancies were greater, especially when using a 1° cutoff (25.7% for torque, 33.8% for rotation, and 18.6% for tip). However, these discrepancies decreased significantly when the cutoff was raised to 2° (in 5.6%, 9.3% and 3.4% respectively). Considering all brackets, no directional bias was detected, except in buccolingual measurements (35% vestibular and 65% lingual). Transfer accuracy was influenced by the variables tooth type, tooth position, and arch, which had various impacts across specific measurements.</div></div><div><h3>Conclusions</h3><div>The new CAD-CAM transfer tray demonstrated good overall transfer accuracy and some clinical advantages, although refinement of the design is required to enhance its performance.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 42-55.e1"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145369190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical advances in curve of Spee assessment: Deep learning for automatic tooth landmark detection in Invisalign","authors":"Songyang Ma ,&nbsp;Yang Liu ,&nbsp;Yue Zhao ,&nbsp;Qilin Wu ,&nbsp;Yao Hu ,&nbsp;Jianping Zhou ,&nbsp;Jingjie Yang ,&nbsp;Xuesha Tong ,&nbsp;Yunji Wang","doi":"10.1016/j.ajodo.2025.09.009","DOIUrl":"10.1016/j.ajodo.2025.09.009","url":null,"abstract":"<div><h3>Introduction</h3><div>The curve of Spee (COS) is a key indicator of occlusal function and orthodontic outcomes. Its measurement traditionally relies on manual landmark identification from intraoral scans, which is time-consuming and operator-dependent. This study introduces a deep learning–based method for fully automated COS assessment based on intraoral scan data, aiming to improve measurement efficiency and support the evaluation of the predictability of COS leveling in patients with varying vertical skeletal patterns undergoing Invisalign treatment (Align Technology, Santa Clara, Calif).</div></div><div><h3>Methods</h3><div>In this retrospective study, a total of 194 mandibular arch models were used to train and validate an automated network for measuring COS. This network adopted a Structure-Aware Long Short-Term Memory framework, which employed a 2-stage method for detecting coarse and fine tooth landmarks to assess COS depth. The accuracy of the landmarks was evaluated using the mean radial error and success detection rate, whereas COS depth was assessed using the paired Wilcoxon test. Finally, 55 patients with different vertical skeletal patterns were selected to analyze differences in COS leveling effects. In addition, the extrusion of teeth relative to the occlusal plane was compared.</div></div><div><h3>Results</h3><div>The proposed network closely approximated the manual method, with the mean radial error for landmark detection being 0.32 ± 0.09 mm. The median measurement error for COS was 0.05 mm (<em>P</em> &lt;0.001). ClinCheck predicted an average of 0.24 mm higher COS leveling than the actual outcome (<em>P</em> &lt;0.01). The hyperdivergent group exhibited the highest predictability at 69%, whereas the hypodivergent group showed the lowest predictability at 58%. The accuracy of extrusion relative to the occlusal plane at the first molar was the lowest (65%).</div></div><div><h3>Conclusions</h3><div>Deep learning can aid in measuring COS. In ClinCheck, considering various vertical skeletal patterns is necessary when designing the leveling objectives for COS, with the first molar requiring particular attention.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 110-125.e4"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated assessment of nasal septum deviation using cone-beam computed tomography images based on artificial intelligence: Development and multicenter validation","authors":"Qianglan Zhai ,&nbsp;Mengjuan Cui ,&nbsp;Yijiao Fu ,&nbsp;Xingtai Huang ,&nbsp;Zhengliang Wang ,&nbsp;Qingwen Wu ,&nbsp;Ning Cong ,&nbsp;Chao Liu","doi":"10.1016/j.ajodo.2025.09.006","DOIUrl":"10.1016/j.ajodo.2025.09.006","url":null,"abstract":"<div><h3>Introduction</h3><div>Nasal septum deviation (NSD) is one of the contributing factors to impaired nasal function and dentofacial developmental abnormalities. Although cone-beam computed tomography (CBCT) is clinically valuable for NSD diagnosis, manual interpretation remains labor-intensive and expertise-dependent.</div></div><div><h3>Methods</h3><div>Our study included 330 CBCT scans diagnosed with either NSD or non-NSD to develop an automated 2-stage artificial intelligence (AI) framework integrating real-time detection and classification for NSD screening. In the first stage, the YOLOv11 (You Only Look Once) object detection algorithm was employed to detect the region of interest containing the nasal septum. In the second stage, 3 convolutional neural network architectures, ResNet, EfficientNet, and MobileNet, were evaluated for classifying CBCT images into NSD and normal categories.</div></div><div><h3>Results</h3><div>Among the YOLOv11 variants, YOLOv11n demonstrated superior performance with a precision of 0.996, a recall of 1.000, an mAP50 of 0.995, and an mAP50-95 of 0.873. For the classification task, Mobile_small emerged as the top-performing model, achieving an area under the curve of 0.817, an area under the precision-recall curve of 0.845, and an accuracy of 0.749. An AI-assisted diagnostic tool was developed based on YOLOv11n and MobileNet models and validated on 50 internal and 50 external CBCT scans. With AI assistance, orthodontists’ diagnostic accuracy increased by 20.12% and 21.49%, respectively, whereas average diagnosis time decreased by 23.75 seconds, improving efficiency by 53.92%.</div></div><div><h3>Conclusions</h3><div>The proposed system enables rapid NSD screening with diagnostic-level accuracy, demonstrating the viability of lightweight AI models for clinical CBCT analysis. AI-assisted diagnosis improves orthodontists’ accuracy and time efficiency in identifying NSD.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Pages 56-66.e2"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145276541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Directory: AAO Officers and Organizations","authors":"","doi":"10.1016/S0889-5406(25)00518-9","DOIUrl":"10.1016/S0889-5406(25)00518-9","url":null,"abstract":"","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"169 1","pages":"Page 130"},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145792108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Micro-computed tomography assessment of regional and overall accuracy of thermoformed retainers and intraoral scanners","authors":"Maria Luna Montes ,&nbsp;Mina Atef Zakhary ,&nbsp;Santiago F. Cobos ,&nbsp;Chia-Ling Kuo ,&nbsp;Kelin Zhong ,&nbsp;Sarah Abu Arqub ,&nbsp;Flavio Uribe","doi":"10.1016/j.ajodo.2025.07.014","DOIUrl":"10.1016/j.ajodo.2025.07.014","url":null,"abstract":"<div><h3>Introduction</h3><div>This retrospective in vitro study aimed to assess the accuracy of retainers fabricated using Essix (Dentsply Sirona, Charlotte, NC) and Zendura (Zendura Dental, Fremont, Calif), and to compare the accuracy of intraoral scanners iTero (Align Technology, San Jose, Calif) and TRIOS (3Shape, Copenhagen, Denmark). In addition, regional accuracy across different areas of the mandibular arch was analyzed.</div></div><div><h3>Methods</h3><div>A total of 20 standard tessellation language files from postorthodontic treatment mandibular arches (from January 2019 to August 2024) were selected based on specific inclusion criteria. The standard tessellation language files were 3-dimensional printed and scanned using iTero Element 2 and TRIOS 4, then used to fabricate 20 sets of each thermoformed retainer (Zendura and Essix). All models were scanned using micro-computed tomography (Scanco Medical AG, Brüttisellen, Switzerland), serving as the gold standard for accuracy comparisons. Root mean square (RMS) error analysis was used to assess overall and regional accuracy.</div></div><div><h3>Results</h3><div>The RMS error between gold standard and retainers differed significantly overall (<em>P</em> = 0.044), particularly in the anterior (<em>P</em> = 0.030) and premolar (<em>P</em> = 0.017) regions, with greater discrepancies in Zendura retainers. RMS error differences were not significant between intraoral scanners across most regions, except for borderline significance in the anterior region (<em>P</em> = 0.058), in which TRIOS showed larger deviations.</div></div><div><h3>Conclusions</h3><div>Both intraoral scanners demonstrated comparable accuracy. However, Zendura retainers exhibited greater inaccuracies than Essix. Regional analysis showed higher deviations in the molar and lingual regions for scanners and the molar regions for retainers. Importantly, these discrepancies were low and clinically insignificant.</div></div>","PeriodicalId":50806,"journal":{"name":"American Journal of Orthodontics and Dentofacial Orthopedics","volume":"168 6","pages":"Pages 705-717"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145071075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}