@article{Oh2022b,

title = {Automated landmark identification on one cone beam computed tomography: Accuracy and reliability},

author = {A Ghowsi and D Hatcher and H Suh and D Wiled and W Castro and J Krueger and J Park and H Oh},

url = {https://pubmed.ncbi.nlm.nih.gov/35653226/},

doi = {10.2319/122121-928.1},

year  = {2022},

date = {2022-06-02},

urldate = {2022-06-02},

journal = {Angle Orthodontist},

volume = {92},

pages = {642-654},

abstract = {Objectives: To evaluate the accuracy and reliability of a fully automated landmark identification (ALI) system as a tool for automatic landmark location compared with human judges.



Materials and methods: A total of 100 cone-beam computed tomography (CBCT) images were collected. After the calibration procedure, two human judges identified 53 landmarks in the x, y, and z coordinate planes on CBCTs using Checkpoint Software (Stratovan Corporation, Davis, Calif). The ground truth was created by averaging landmark coordinates identified by two human judges for each landmark. To evaluate the accuracy of ALI, the mean absolute error (mm) at the x, y, and z coordinates and mean error distance (mm) between the human landmark identification and the ALI were determined, and a successful detection rate was calculated.



Results: Overall, the ALI system was as successful at landmarking as the human judges. The ALI's mean absolute error for all coordinates was 1.57 mm on average. Across all three coordinate planes, 94% of the landmarks had a mean absolute error of less than 3 mm. The mean error distance for all 53 landmarks was 3.19 ± 2.6 mm. When applied to 53 landmarks on 100 CBCTs, the ALI system showed a 75% success rate in detecting landmarks within a 4-mm error distance range.



Conclusions: Overall, ALI showed clinically acceptable mean error distances except for a few landmarks. The ALI was more precise than humans when identifying landmarks on the same image at different times. This study demonstrates the promise of ALI in aiding orthodontists with landmark identifications on CBCTs.},

keywords = {3D landmark identification, AAOF, accuracy, Automated, CBCT, Landmark error, Reliability},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021b,

title = {Radiographic interpretation using high-resolution Cbct to diagnose degenerative temporomandibular joint disease},

author = {J Bianchi and J Roberto Goncalves and A Carlos De Oliveira Ruellas and J Vierira Pastana Bianchi and LM Ashman and et al },

url = {https://pubmed.ncbi.nlm.nih.gov/34375354/},

doi = {10.1371/journal.pone.0255937},

year  = {2021},

date = {2021-08-10},

urldate = {2021-08-10},

journal = {PLOS ONE},

volume = {16},

number = {8},

pages = {e0255937},

abstract = {The objective of this study was to use high-resolution cone-beam computed images (hr- CBCT) to diagnose degenerative joint disease in asymptomatic and symptomatic subjects using the Diagnostic Criteria for Temporomandibular Disorders DC/TMD imaging criteria. This observational study comprised of 92 subjects age-sex matched and divided into two groups: clinical degenerative joint disease (c-DJD, n = 46) and asymptomatic control group (n = 46). Clinical assessment of the DJD and high-resolution CBCT images (isotropic voxel size of 0.08mm) of the temporomandibular joints were performed for each participant. An American Board of Oral and Maxillofacial Radiology certified radiologist and a maxillofacial radiologist used the DC/TMD imaging criteria to evaluate the radiographic findings, followed by a consensus of the radiographic evaluation. The two radiologists presented a high agreement (Cohen's Kappa ranging from 0.80 to 0.87) for all radiographic findings (osteophyte, erosion, cysts, flattening, and sclerosis). Five patients from the c- DJD group did not present radiographic findings, being then classified as arthralgia. In the asymptomatic control group, 82.6% of the patients presented radiographic findings determinant of DJD and were then classified as osteoarthrosis or overdiagnosis. In conclusion, our results showed a high number of radiographic findings in the asymptomatic control group, and for this reason, we suggest that there is a need for additional imaging criteria to classify DJD properly in hr-CBCT images.},

keywords = {AAOF, Adolescents, anterior openbite, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, fixed appliances, Growth, hyperdivergent, Mandibular fixed retainer},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021,

title = {Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications.},

author = {J Bianchi and A Ruellas and J C Prieto and T Li and R Soroushmehr and K Najarian and J Gryak and R Deleat-Besson and C Le and M Yatabe and M Gurgel and N A Turkestani and B Paniagua and L Cevidanes},

url = {https://pubmed.ncbi.nlm.nih.gov/34305383/},

doi = {10.1053/j.sodo.2021.05.004},

year  = {2021},

date = {2021-05-19},

urldate = {2021-05-19},

journal = {Seminars in Orthodontics},

volume = {27},

number = {2},

pages = {78-86},

abstract = {With the exponential growth of computational systems and increased patient data acquisition, dental research faces new challenges to manage a large quantity of information. For this reason, data science approaches are needed for the integrative diagnosis of multifactorial diseases, such as Temporomandibular joint (TMJ) Osteoarthritis (OA). The Data science spectrum includes data capture/acquisition, data processing with optimized web-based storage and management, data analytics involving in-depth statistical analysis, machine learning (ML) approaches, and data communication. Artificial intelligence (AI) plays a crucial role in this process. It consists of developing computational systems that can perform human intelligence tasks, such as disease diagnosis, using many features to help in the decision-making support. Patient's clinical parameters, imaging exams, and molecular data are used as the input in cross-validation tasks, and human annotation/diagnosis is also used as the gold standard to train computational learning models and automatic disease classifiers. This paper aims to review and describe AI and ML techniques to diagnose TMJ OA and data science approaches for imaging processing. We used a web-based system for multi-center data communication, algorithms integration, statistics deployment, and process the computational machine learning models. We successfully show AI and data-science applications using patients' data to improve the TMJ OA diagnosis decision-making towards personalized medicine.},

keywords = {AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Hardin2021,

title = {Estimating craniofacial growth cessation: Comparison of asymptote- and rate-based methods},

author = {A M Hardin and R P Knigge and H Oh and et al},

url = {https://journals.sagepub.com/doi/full/10.1177/10556656211002675},

doi = {10.1177/10556656211002675},

year  = {2021},

date = {2021-05-17},

urldate = {2021-05-17},

journal = {The Cleft Palate-Craniofacial Journal},

abstract = {To identify differences between asymptote- and rate-based methods for estimating age and size at growth cessation in linear craniofacial measurements.},

keywords = {AAOF, Cranial base, craniofacial, Discrepency Index, Mandibular fixed retainer, Mandibular remodeling, retrospective, teaching},

pubstate = {published},

tppubtype = {article}

}

@article{Turkestani2021,

title = {Clinical decision support systems in orthodontics: A narrative review of data science approaches.},

author = {N Al Turkestani and J Bianchi and R Deleat-Besson and et al},

url = {https://onlinelibrary.wiley.com/doi/10.1111/ocr.12492},

doi = {10.1111/ocr.12492 },

year  = {2021},

date = {2021-05-11},

urldate = {2021-05-11},

journal = {Orthod Craniofac Res},

abstract = {Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (C) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems. },

keywords = {AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique},

pubstate = {published},

tppubtype = {article}

}

@article{Cong2021,

title = {Dental long axes using digital dental models compared to cone-beam computed tomography.},

author = {A Cong and C Massaro and J Bianchi and ACDO Ruellas and et al},

url = {https://onlinelibrary.wiley.com/doi/10.1111/ocr.12489},

doi = {10.1111/ocr.12489},

year  = {2021},

date = {2021-05-09},

urldate = {2021-05-09},

journal = {Orthod Cranifac Res},

abstract = {Standard methods of evaluating tooth long axes are not comparable (digital dental models [DDMs], panoramic and cephalometric radiographs) or expose patients to more radiation (cone-beam computed tomography [CBCT]). This study aimed to compare angular changes in tooth long axes using DDMs vs using CBCTs. },

keywords = {AAOF, adult, clear aligners, Cranial base, hyperdivergent, Mandibular fixed retainer, Posttreatment, retrospective, teaching},

pubstate = {published},

tppubtype = {article}

}

@article{Parizotto2021,

title = {Craniofacial and airway morphology of individuals with oculoauriculovertebral spectrum.},

author = {JOL Parizotto and AP Peixoto and KT Borsato and J Bianchi and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/33713375/},

doi = {10.1111/ocr.12483},

year  = {2021},

date = {2021-03-13},

urldate = {2021-03-13},

journal = {Orthodontics & Craniofacial Research},

abstract = {The objectives of this study were to characterize the craniofacial and airway morphology of oculo-auriculo-vertebral spectrum (OAVS) individuals using computed tomography (CT) examination.},

keywords = {AAOF, anterior openbite, clear aligners, clinical orthodontist, Mandibular fixed retainer, Posttreatment, research, technique, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Boubolo2021,

title = {FlyBy CNN: a 3D surface segmentation framework},

author = {Louis Boubolo and Maxime Dumont and Serge Brosset and Jonas Bianchi and Antonio Ruellas and Marcela Gurgel and Camila Massaro and Aron Aliaga Del Castillo and Marcos Ioshida and Marilia Yatabe and Erika Benavides and Hector Rios and Fabiana Soki and Gisele Neiva and Beatriz Paniagua and Lucia Cevidanes and Martin Styner and Juan Carlos Prieto},

url = {https://pubmed.ncbi.nlm.nih.gov/33758460/},

doi = {10.1117/12.2582205},

year  = {2021},

date = {2021-02-15},

journal = {Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115962B },

abstract = {In this paper, we present FlyBy CNN, a novel deep learning based approach for 3D shape segmentation. FlyByCNN consists of sampling the surface of the 3D object from different view points and extracting surface features such as the normal vectors. The generated 2D images are then analyzed via 2D convolutional neural networks such as RUNETs. We test our framework in a dental application for segmentation of intra-oral surfaces. The RUNET is trained for the segmentation task using image pairs of surface features and image labels as ground truth. The resulting labels from each segmented image are put back into the surface thanks to our sampling approach that generates 1-1 correspondence of image pixels and triangles in the surface model. The segmentation task achieved an accuracy of 0.9.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, technique, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Brosset2021,

title = {"Web infrastructure for data management, storage and computation", Proc. SPIE 11600,},

author = {Serge Brosset and Maxime Dumont and Lucia Cevidanes and Reza Soroushmehr and Jonas Bianchi and Marcela L Gurgel and Romain Deleat-besson and Celia Le and Antonio Ruellas and Marilia Yatabe and Liliane Rosas and Joao Goncalves and Kayvan Najarian and Jonathan Gryak and Beatriz Paniagua and Martin Styner and Juan Carlos Prieto},

url = {https://www.researchgate.net/publication/349303820_Web_Infrastructure_for_Data_Management_Storage_and_Computation},

doi = {10.1117/12.2582283},

year  = {2021},

date = {2021-02-14},

journal = {Proc SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1166001N},

abstract = {The Data Storage for Computation and Integration (DSCI) proposes management innovations for web-based secure data storage, algorithms deployment, and task execution. Its architecture allows inclusion of plugins for upload, browsing, sharing, and task execution in remote computing grids. Here, we demonstrate the DSCI implementation and the deployment of Image processing tools (TMJSeg), machine learning algorithms (MandSeg, DentalModelSeg), and advanced statistical packages (Multivariate Functional Shape Data Analysis, MFSDA), with data transfer and task execution handled by the clusterpost plug-in. Due to its comprehensive web-based design, local software installation is no longer required. The DSCI aims to enable and maintain a distributed computing and collaboration environment across multi-site clinical centers for the data processing of multisource features such as clinical, biological markers, volumetric images, and 3D surface models, with particular emphasis on analytics for temporomandibular joint osteoarthritis (TMJ OA).},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, fixed appliances, hyperdivergent, Mandibular fixed retainer, Peer Assessment Rating Index},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021b,

title = {Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis.},

author = {J Bianchi and J R Goncalves and A C de Oliveira Ruellas and L M Ashman and J-B Vimort and M Yatabe and B Paniagua and P Hernandez and E Benavides and F N Soki and M Loshida and L H S Cevidanes},

url = {https://pubmed.ncbi.nlm.nih.gov/32605824/},

doi = {10.1016/j.ijom.2020.04.018},

year  = {2021},

date = {2021-02-00},

journal = {International Journal of Oral and Maxillofacial Surgery},

volume = {50},

number = {2},

pages = {227-235},

abstract = {Bone degradation of the condylar surface is seen in temporomandibular joint osteoarthritis (TMJ OA); however, the initial changes occur in the subchondral bone. This cross-sectional study was performed to evaluate 23 subchondral bone imaging biomarkers for TMJ OA. The sample consisted of high-resolution cone beam computed tomography scans of 84 subjects, divided into two groups: TMJ OA (45 patients with TMJ OA) and control (39 asymptomatic subjects). Six regions of each mandibular condyle scan were extracted for computation of five bone morphometric and 18 grey-level texture-based variables. The groups were compared using the Mann-Whitney U-test, and the receiver operating characteristics (ROC) curve was determined for each variable that showed a statically significance difference. The results showed statistically significant differences in the subchondral bone microstructure in the lateral and central condylar regions between the control and TMJ OA groups (P< 0.05). The area under the ROC curve (AUC) for these variables was between 0.620 and 0.710. In conclusion, 13 imaging bone biomarkers presented an acceptable diagnostic performance for the diagnosis of TMJ OA, indicating that the texture and geometry of the subchondral bone microarchitecture may be useful for quantitative grading of the disease.},

keywords = {AAOF, Adolescents, biomarkers, Cone-beam computed tomography, Cranial base, osteoarthritis, temporomandibular joint},

pubstate = {published},

tppubtype = {article}

}

@article{Sherwood2020,

title = {Bayesian Approach to Longitudinal Craniofacial Growth: The Craniofacial Growth Consortium Study.},

author = {R Sherwood and H Oh and M Valiathan and K McNulty and D Duren and R Knigge and A Hardin and C Holzhauser and K Middleton},

url = {https://anatomypubs.onlinelibrary.wiley.com/doi/10.1002/ar.24520},

doi = {10.1002/ar.24520},

year  = {2020},

date = {2020-10-04},

urldate = {2020-10-04},

journal = {American Association of Orthodontists Foundation},

abstract = {Early in the 20th century, a series of studies were initiated across North America to investigate and characterize childhood growth. The Craniofacial Growth Consortium Study (CGCS) combines craniofacial records from six of those growth studies (15,407 lateral cephalograms from 1,913 individuals; 956 females, 957 males, primarily European descent). Standard cephalometric points collected from the six studies in the CGCS allows direct comparison of craniofacial growth patterns across six North American locations. Three assessors collected all cephalometric points and the coordinates were averaged for each point. Twelve measures were calculated from the averaged coordinates. We implemented a multilevel double logistic equation to estimate growth trajectories fitting each trait separately by sex. Using Bayesian inference, we fit three models for each trait with different random effects structures to compare differences in growth patterns among studies. The models successfully identified important growth milestones (e.g., age at peak growth velocity, age at cessation of growth) for most traits. In a small number of cases, these milestones could not be determined due to truncated age ranges for some studies and slow, steady growth in some measurements. Results demonstrate great similarity among the six growth studies regarding craniofacial growth milestone estimates and the overall shape of the growth curve. These similarities suggest minor variation among studies resulting from differences in protocol, sample, or possible geographic variation. The analyses presented support combining the studies into the CGCS without substantial concerns of bias. The CGCS, therefore, provides an unparalleled opportunity to examine craniofacial growth from childhood into adulthood.},

keywords = {AAOF, Adolescents, anterior openbite, Cranial base, Growth, hyperdivergent, Mandibular fixed retainer},

pubstate = {published},

tppubtype = {article}

}

@article{Brosset2020,

title = {3D Auto-Segmentation of Mandibular Condyles},

author = {B Serge and D Maxime and J Bianchi and R Antonio and C Lucia and Y Marilia and G Joao and C Erika and S Fabiana and P Beatriz and P Juan and N Kayvan and G Jonathan and S Reza },

url = {https://pubmed.ncbi.nlm.nih.gov/33018219/},

doi = {10.1109/EMBC44109.2020.9175692},

year  = {2020},

date = {2020-07-00},

urldate = {2020-07-00},

journal = {2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)},

pages = {1270-1273},

abstract = {Temporomandibular joints (TMJ) like a hinge connect the jawbone to the skull. TMJ disorders could cause pain in the jaw joint and the muscles controlling jaw movement. However, the disease cannot be diagnosed until it becomes symptomatic. It has been shown that bone resorption at the condyle articular surface is already evident at initial diagnosis of TMJ Osteoarthritis (OA). Therefore, analyzing the bone structure will facilitate the disease diagnosis. The important step towards this analysis is the condyle segmentation. This article deals with a method to automatically segment the temporomandibular joint condyle out of cone beam CT (CBCT) scans. In the proposed method we denoise images and apply 3D active contour and morphological operations to segment the condyle. The experimental results show that the proposed method yields the Dice score of 0.9461 with the standards deviation of 0.0888 when it is applied on CBCT images of 95 patients. This segmentation will allow large datasets to be analyzed more efficiently towards data sciences and machine learning approaches for disease classification.},

keywords = {AAOF, Adolescents, anterior openbite, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, extraction, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, orthodontic, Peer Assessment Rating Index, Posttreatment, teaching},

pubstate = {published},

tppubtype = {article}

}

@article{Currie2020,

title = {CBCT assessment of posterior cranial base and surrounding structures in orthodontically treated adolescents. Int Orthod.},

author = {Currie K and Oh H and Flores-Mir C and Lagravere M},

url = {https://pubmed.ncbi.nlm.nih.gov/32044297/},

doi = {10.1016/j.ortho.2020.01.004},

year  = {2020},

date = {2020-06-18},

urldate = {2020-06-18},

journal = {Int Orthod},

volume = {2},

pages = {266-275},

abstract = { Understanding craniofacial growth and development is important for accurate diagnosis, treatment planning and post-treatment evaluation of orthodontic cases. Paramount to this is knowledge of the cranial base growth and development, since it is the foundation upon which the remaining facial structures develop. The purpose of this study was to analyse different anatomical structures in the posterior cranial base and determine its changes during the adolescent years (13-15 year of age) using CBCT.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, Mandibular fixed retainer, Mandibular remodeling, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Chen2020,

title = {The three-dimensional stable mandibular landmarks in patients between the ages of 12.5 and 17.1 years.},

author = {G Chen and M Al Awadi and D W Chambers and M O Lagravere-Vich and Y Xu and H Oh },

url = {https://pubmed.ncbi.nlm.nih.gov/32460733/},

doi = {10.1186/s12903-020-01142-2},

year  = {2020},

date = {2020-05-27},

urldate = {2020-05-27},

journal = {BMC Oral Health},

volume = {20},

number = {1},

pages = {153},

abstract = {With the aid of implants, Björk identified two-dimensional mandibular stable structures in cephalograms during facial growth. However, we do not know what the three-dimensional stable structures are with certainty. The purpose of this study was to identify the most stable mandibular landmarks in growing patients using three-dimensional images.},

keywords = {AAOF, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, technique},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2020b,

title = {Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning.},

author = {Bianchi J and A C De Oliveira Ruellas and J R Goncalves and B Paniagua and J C Prieto and S Martin and Li Tengfei and Zhu Hongtu and S James and G William and B Erika and Soki Fabiana and Yatabe Marilia and Ashman Lawrence and W David and Soroushmehr Reza and N Kayvan and L H S Cevidanes },

url = {https://pubmed.ncbi.nlm.nih.gov/32415284/},

doi = {10.1038/s41598-020-64942-0},

year  = {2020},

date = {2020-05-15},

urldate = {2020-05-15},

journal = {Scientific Reports},

volume = {10},

number = {1},

pages = {8012},

abstract = {After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthritis (OA) increases with aging, and the main goal is to diagnosis before morphological degeneration occurs. Here, we address this challenge using advanced data science to capture, process and analyze 52 clinical, biological and high-resolution CBCT (radiomics) markers from TMJ OA patients and controls. We tested the diagnostic performance of four machine learning models: Logistic Regression, Random Forest, LightGBM, XGBoost. Headaches, Range of mouth opening without pain, Energy, Haralick Correlation, Entropy and interactions of TGF-β1 in Saliva and Headaches, VE-cadherin in Serum and Angiogenin in Saliva, VE-cadherin in Saliva and Headaches, PA1 in Saliva and Headaches, PA1 in Saliva and Range of mouth opening without pain; Gender and Muscle Soreness; Short Run Low Grey Level Emphasis and Headaches, Inverse Difference Moment and Trabecular Separation accurately diagnose early stages of this clinical condition. Our results show the XGBoost + LightGBM model with these features and interactions achieves the accuracy of 0.823, AUC 0.870, and F1-score 0.823 to diagnose the TMJ OA status. Thus, we expect to boost future studies into osteoarthritis patient-specific therapeutic interventions, and thereby improve the health of articular joints.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, technique, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2020,

title = {Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis},

author = {J Bianchi and J R Goncalves and A C de Oliveira Ruellas and L M Ashman and J B Vimort and M Yatabe and B Paniagua and P Hernandez and E Benavides and F N Soki and M Loshida and L H S Cevidanes},

url = {https://www.sciencedirect.com/science/article/pii/S0901502720301636#:~:text=%20Quantitative%20bone%20imaging%20biomarkers%20to%20diagnose%20temporomandibular,This%20study%20followe...%204%20References.%20%20More%20},

doi = {0.1016/j.ijom.2020.04.018},

year  = {2020},

date = {2020-04-28},

urldate = {2020-04-28},

journal = {International Journal of Oral and Maxillofacial Surgery},

volume = {50},

number = {2},

pages = {227-235},

abstract = {Bone degradation of the condylar surface is seen in temporomandibular joint osteoarthritis (TMJ OA); however, the initial changes occur in the subchondral bone. This cross-sectional study was performed to evaluate 23 subchondral bone imaging biomarkers for TMJ OA. The sample consisted of high-resolution cone beam computed tomography scans of 84 subjects, divided into two groups: TMJ OA (45 patients with TMJ OA) and control (39 asymptomatic subjects). Six regions of each mandibular condyle scan were extracted for computation of five bone morphometric and 18 grey-level texture-based variables. The groups were compared using the Mann–Whitney U-test, and the receiver operating characteristics (ROC) curve was determined for each variable that showed a statically significance difference. The results showed statistically significant differences in the subchondral bone microstructure in the lateral and central condylar regions between the control and TMJ OA groups (P <  0.05). The area under the ROC curve (AUC) for these variables was between 0.620 and 0.710. In conclusion, 13 imaging bone biomarkers presented an acceptable diagnostic performance for the diagnosis of TMJ OA, indicating that the texture and geometry of the subchondral bone microarchitecture may be useful for quantitative grading of the disease.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, orthodontic, pressure tension, technique},

pubstate = {published},

tppubtype = {article}

}

@article{Joy2020,

title = {Airway and cephalometric changes in adult orthodontic patients after premolar extractions.},

author = {A Joy and J Park and D Chambers and H Oh},

url = {https://pubmed.ncbi.nlm.nih.gov/31403835/#:~:text=Airway%20and%20cephalometric%20changes%20in%20adult%20orthodontic%20patients,measures%20in%20the%20nasopharynx%2C%20retropalatal%2C%20or%20retroglossal%20regions.},

doi = {10.2319/021019-92.1},

year  = {2020},

date = {2020-01-00},

urldate = {2020-01-00},

journal = {Angle Orthod},

volume = {90},

number = {1},

pages = {39-46},

abstract = {To examine changes in the airway and cephalometric measurements associated with orthodontic treatment of adults with and without premolar extractions. The study investigated whether extractions had a direct or indirect effect on the airway and examined selected skeletal and dental features.},

keywords = {AAOF, Adolescents, ariway, Cranial base, hyperdivergent, Mandibular fixed retainer, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Park2019,

title = {Reliability of 3D dental and skeletal landmarks on CBCT images.},

author = {Park J and S Baumrind and Curry S and Carlson S and H Oh},

url = {https://pubmed.ncbi.nlm.nih.gov/30883187/},

doi = {10.2319/082018-612.1},

year  = {2019},

date = {2019-09-00},

journal = {Angle Orthod},

volume = {89},

number = {5},

pages = {758-767},

abstract = {To quantify reliability of three-dimensional skeletal landmarks and a comprehensive set of dental landmarks in cone-beam computed tomography (CBCT) and to determine the shapes of envelope of error.},

keywords = {AAOF, Cranial base, Discrepency Index, extraction, hyperdivergent, Mandibular fixed retainer, Mandibular remodeling, Peer Assessment Rating Index},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2019,

title = {Software comparison to analyze bone radiomics from high resolution CBCT scans of mandibular condyles.},

author = {Bianchi J and R C Joao and A C De Oliveira Ruellas and J B Vimort and Marilia Yatabe and P Beatriz and H Pablo and B Erika and N S Fabiana and S C Lucia Helena },

url = {https://pubmed.ncbi.nlm.nih.gov/31075043/},

doi = {10.1259/dmfr.20190049},

year  = {2019},

date = {2019-09-00},

urldate = {2019-09-00},

journal = {Dento Maxillo Facial Radiology},

volume = {48},

number = {6},

abstract = {Radiomics refers to the extraction and analysis of advanced quantitative imaging from medical images to diagnose and/or predict diseases. In the dentistry field, the bone data from mandibular condyles could be computationally analyzed using the voxel information provided by high-resolution CBCT scans to increase the diagnostic power of temporomandibular joint (TMJ) conditions. However, such quantitative information demands innovative computational software, algorithm implementation, and validation. Our study's aim was to compare a newly developed BoneTexture application to two-consolidated software with previous applications in the medical field, Ibex and BoneJ, to extract bone morphometric and textural features from mandibular condyles.},

keywords = {AAOF, Cone-beam computed tomography, software validation, temporomandibular joint disorders, tomography, X-ray computed},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2019,

title = {Predicting Adult Facial Type From Mandibular Landmark Data At Young Ages.},

author = {H Oh and R Knigge and A Hardin and R Sherwood and D Duren and M Valathan and E Leary and K McNulty},

url = {https://pubmed.ncbi.nlm.nih.gov/31074133/},

doi = {10.1111/ocr.12296.},

year  = {2019},

date = {2019-05-22},

urldate = {2019-05-22},

journal = {Orthod Craniofac Res},

volume = {1},

pages = {154-162},

abstract = {To assess the potential of predicting adult facial types at different stages of mandibular development.},

keywords = {AAOF, anterior openbite, Cone-beam computed tomography, Cranial base, Mandibular remodeling},

pubstate = {published},

tppubtype = {article}

}

@article{Sam2019,

title = {Reliability of different 3D cephalometric landmarks in CBCT: A systematic review.},

author = {A Sam and K Currie and H Oh and C Flores-Mir and M Lagravere-Vich},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120873/},

doi = {10.2319/042018-302.1},

year  = {2019},

date = {2019-03-00},

urldate = {2019-03-00},

journal = {Angle Orthod},

volume = {89},

number = {2},

pages = {317-332},

abstract = {Conventional two-dimensional (2D) cephalometric radiography is an integral part of orthodontic patient diagnosis and treatment planning. One must be mindful of its limitations as it indeed is a 2D representation of a vaster three-dimensional (3D) object. Issues with projection errors, landmark identification, and measurement inaccuracies impose significant limitations, which may now be overcome with the advent of cone-beam computed tomography (CBCT). A systematic review of the reliability of different 3D cephalometric landmarks in CBCT imaging was conducted.},

keywords = {AAOF, anterior openbite, Cone-beam computed tomography, Cranial base, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling},

pubstate = {published},

tppubtype = {article}

}

@article{Garnett2019,

title = {Cephalometric comparison of adult anterior open bite treatment using clear aligners and fixed appliances.},

author = {B Garnett and K Mahod and M Nguyen and A Al-Khateeb and S Liu and R Boyd and H Oh},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137127/},

doi = {10.2319/010418-4.1},

year  = {2019},

date = {2019-01-00},

journal = {Angle Orthodontist},

volume = {89},

number = {1},

pages = {3-9},

abstract = {To compare fixed appliances and clear aligner therapy in correcting anterior open bite and in controlling the vertical dimension in adult patients with hyperdivergent skeletal patterns.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, extraction, fixed appliances, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, mapping, open bite, Peer Assessment Rating Index, Posttreatment, research, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2017,

title = {Effect of temporomandibular joint articular disc repositioning on anterior open-bite malocclusion: An orthodontic-surgical approach},

author = {Bianchi J and S P Ary Dos and I Jaqueline and P O R Daniel and R G Joao },

url = {https://www.sciencedirect.com/science/article/pii/S0889540617306121},

doi = {10.1016/j.ajodo.2016.09.032},

year  = {2017},

date = {2017-12-00},

urldate = {2017-12-00},

journal = {Am J Orthod Dentofacial Orthop},

volume = {152},

number = {6},

pages = {848-858},

abstract = {An anterior open bite is a challenge to orthodontic treatment; it has a multifactorial etiology and a wide range ofintervention options. Temporomandibular joint (TMJ) disorders are a risk factor for the development of malocclu-sions such as the anterior open bite, especially in patients who have TMJ osteoarthritis with disc displacement.Articular disc repositioning surgery is an available option for treating this pathology, and it contributes to main-taining the condyles in a more stable position. The aim of this article was to report the case of a 20-year-oldwoman diagnosed with anterior open bite and TMJ osteoarthritis with bilateral disc displacement. The patientreceived both orthodontic treatment and TMJ disc repositioning surgery. Cone-beam computed tomographywas used to create 3-dimensional models of the condyles with regional superposition, and assessment ofbone remodeling was performed at different time intervals. Complete orthodontic and surgical treatment timewas approximately 12 months. The results provided a stable correction of the patient's anterior open bite witha 2-year follow-up and favorable bone remodeling of the condyles due to functional improvement of the TMJ.(Am J Orthod Dentofacial Orthop 2017;152:848-58)},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, hyperdivergent, Mandibular fixed retainer, Mandibular remodeling, orthodontic, retrospective, teaching, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Currie2017b,

title = {Posterior cranial base natural growth and development: A systematic review. },

author = {K Currie and D Sawchuk and H Saltaji and H Oh and C Flores-Mir and M Lagravere-Vich},

url = {https://pubmed.ncbi.nlm.nih.gov/28737426/},

doi = {10.2319/032717-218.1},

year  = {2017},

date = {2017-11-00},

journal = {Angle Orthodontist},

volume = {87},

number = {6},

pages = {897-910},

abstract = {To provide a synthesis of the published studies evaluating the natural growth and development of the human posterior cranial base (S-Ba).},

keywords = {AAOF, adult, Cranial base, extraction, fixed appliances, Growth, mandibular asymmetry, Mandibular fixed retainer, Posttreatment, pressure tension, research, retrospective, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Xu2017,

title = {Malocclusion Class II-Division 1 skeletal and dental relationships measured by Cone-Beam Computed Tomography. },

author = {Y Xu and H Oh and M Lagravere-Vich},

url = {https://www.sciencedirect.com/science/article/pii/S1761722717300621},

doi = {10.1016/j.ortho.2017.06.014},

year  = {2017},

date = {2017-09-00},

journal = {International Journal of Orthodontics},

volume = {15},

number = {3},

pages = {365-387},

abstract = {The purpose of this study was to locate traditionally-used landmarks in two-dimensional (2D) images and newly-suggested ones in three-dimensional (3D) images (cone-beam computer tomographies [CBCTs]) and determine possible relationships between them to categorize patients with Class II-1 malocclusion.},

keywords = {AAOF, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, pressure tension, retrospective},

pubstate = {published},

tppubtype = {article}

}

@article{Hwang2017,

title = {Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry},

author = {Hyeon-Shik Hwang and Min-Hee Oh and Hee-Kyun Oh and Heesoo Oh},

url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/11/Surgery-first-approach-in-correctingskeletal-CLass-III_AJODO-2017.pdf},

doi = {10.1016/j.ajodo.2014.10.040},

year  = {2017},

date = {2017-08-01},

urldate = {2017-08-01},

journal = {American Journal of Orthodontics and Dentofacial Orthopedics},

volume = {152},

number = {2},

pages = {255-267},

abstract = {This case report describes a surgical orthodontic case that used the recently introduced surgery-first approach to correct a severe skeletal Class III malocclusion. A 19-year-old woman presented with severe mandibular prognathism and facial asymmetry; she had been waiting for growth completion in order to pursue surgical correction. After prediction of the postsurgical tooth movement and surgical simulation, 2-jaw surgery that included maxillary advancement and differential mandibular setback was performed using a surgery-first approach. Immediate facial improvement was achieved and postsurgical orthodontic treatment was efficiently carried out. The total treatment time was 16 months. The patient's facial appearance improved significantly and a stable surgical orthodontic outcome was obtained. (Am J Orthod Dentofacial Orthop 2017;152:255-67) },

keywords = {AAOF, adult, Class III, Cranial base, Discrepency Index, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, mapping, open bite, orthodontic, surgery-first},

pubstate = {published},

tppubtype = {article}

}

@article{Liu2017b,

title = {Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists.},

author = {S Lui and H Oh and D Chambers and X Weng and Q Chen and S Baumrind and T Xu},

url = {https://pubmed.ncbi.nlm.nih.gov/28670875/},

doi = {10.1111/ocr.12195},

year  = {2017},

date = {2017-08-00},

journal = {Orthodontics and Craniofacial Research},

volume = {20},

number = {3},

pages = {140-145},

abstract = {To assess the validity of the American Board of Orthodontics Discrepancy Index (ABO-DI) and Peer Assessment Rating (PAR) Index in evaluating malocclusion severity in Chinese orthodontic patients.},

keywords = {AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Hwang2017b,

title = {Surgery-first approach in correcting skeletal Class III malocclusion with mandibular asymmetry. },

author = {HS Hwang and MH Oh and HK Oh},

url = {https://pubmed.ncbi.nlm.nih.gov/28760288/},

doi = {10.1016/j.ajodo.2014.10.040},

year  = {2017},

date = {2017-08-00},

journal = {Am J Orthod Dentofacial Orthop},

volume = {152},

number = {2},

pages = {255-267},

abstract = {This case report describes a surgical orthodontic case that used the recently introduced surgery-first approach to correct a severe skeletal Class III malocclusion. A 19-year-old woman presented with severe mandibular prognathism and facial asymmetry; she had been waiting for growth completion in order to pursue surgical correction. After prediction of the postsurgical tooth movement and surgical simulation, 2-jaw surgery that included maxillary advancement and differential mandibular setback was performed using a surgery-first approach. Immediate facial improvement was achieved and postsurgical orthodontic treatment was efficiently carried out. The total treatment time was 16 months. The patient's facial appearance improved significantly and a stable surgical orthodontic outcome was obtained.},

keywords = {AAOF, adult, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Cranial base, Discrepency Index, fixed appliances, malocclusion severity, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, retrospective},

pubstate = {published},

tppubtype = {article}

}

@article{Afrand2017b,

title = {Growth changes in the anterior and middle cranial bases as assessed through cone-beam computed tomography in adolescents.},

author = {M Afrand and H Oh and C Flores-Mir and M Lagravere-Vich},

url = {https://www.sciencedirect.com/science/article/pii/S0889540616307405},

doi = {10.1016/j.ajodo.2016.02.032},

year  = {2017},

date = {2017-02-00},

journal = {Am J Orthod Dentofacial Orthop},

volume = {151},

number = {2},

pages = {342-350},

abstract = {Initially, cone-beam computed tomography images from dry skulls were used to 3 dimensionallyevaluate intrarater and interrater reliabilities and accuracy of selected 3-dimensional landmarks located in theanterior and middle cranial bases. Thereafter, dimensional changes of the anterior and middle cranial baseswith growth were evaluated by using the previously selected landmarks.Methods:Cone-beam computed to-mography images of 10 dry skulls were used to identify useful landmarks from different areas of the anteriorand middle cranial bases based on their reliability and accuracy. These selected landmarks were identified inthe images of an already available sample of adolescents (n560) taken at 2 time points (19 months apart)to assess dimensional changes with growth.Results:The majority of the proposed 3-dimensional landmarkswith the exception of the lesser wing of the sphenoid showed acceptable intrarater and interrater reliabilities.The distances measured between foramina and canals in the transverse dimension showed evidence ofincreases in size. However, the mean amounts of increase in these transverse distances were equal to orless than 1.05 mm (from 1.1% to 4.1%). No change was observed between the right and left anterior andposterior clinoid processes. The vertical dimensions showed evidence of some changes, but these werewithin 2% of the original distances.Conclusions:In this adolescent sample, minor growth-related changeswere observed in the anterior and middle cranial bases. The midsagittal area of the anterior cranial base(foramen caecum to presphenoid) was stable. The right and left anterior and posterior clinoid processes canbe used for transverse superimposition. (Am J Orthod Dentofacial Orthop 2017;151:342-50)},

keywords = {AAOF, anterior openbite, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, hyperdivergent, Mandibular fixed retainer, orthodontic, Peer Assessment Rating Index, Posttreatment, retrospective, technique},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2017,

title = {A retrospective study of Class II mixed-dentition treatment. },

author = {H Oh and S Baumrind and S Dugoni and R Boero and M Aubert and R Boyd},

url = {https://pubmed.ncbi.nlm.nih.gov/27391205/},

doi = {10.2319/012616-72.1},

year  = {2017},

date = {2017-01-00},

journal = {Angle Orthodontist},

volume = {87},

number = {1},

pages = {56-67},

abstract = {To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions.},

keywords = {AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, mapping, technique, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2016b,

title = {Evaluation of Post-treatment stability following orthodontic treatment in the mixed and permanent dentitions.},

author = {H Oh and N Ma and P Feng and K Kieu and R Boero and S Dugoni and M Aubert and D Chambers},

url = {https://pubmed.ncbi.nlm.nih.gov/27214339/},

doi = {10.2319/122315-881.1},

year  = {2016},

date = {2016-11-00},

journal = {Angle Orthodontist},

volume = {86},

number = {6},

pages = {1010-1018},

abstract = {To investigate posttreatment changes in the maxillary and mandibular arches in patients who underwent orthodontic treatment during the mixed and permanent dentitions.},

keywords = {AAOF, Cone-beam computed tomography, Cranial base, hyperdivergent, Peer Assessment Rating Index, Posttreatment, pressure tension, research, retrospective, technique},

pubstate = {published},

tppubtype = {article}

}

@article{Baumrind2011,

title = {The AAOF craniofacial growth legacy collection:  A powerful new tool for orthodontic teaching and research},

author = { Sheldon Baumrind and Sean Curry},

url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/12/AAOF-Collection-Mich-Monographs-S.BaumrindS.Curry_.pdf},

year  = {2011},

date = {2011-01-01},

journal = {AAOF Craniofacial Growth Legacy Collection},

pages = {297-318},

abstract = {This chapter reports and illustrates a multi-institutional project that uses the capabilities of cloud computing and the Internet to collect and share craniofacial images and numerical data of  importance to orthodontic education and research. The project will provide interested investigators all over the world with near instantaneous access to longitudinal information on the spontaneous craniofacial growth of untreated children with various kinds of malocclusion. The collection will facilitate investigations on the spontaneous course of development in children with malocclusions of different types. In addition, the AAOF Legacy Collection constitutes a unique source of control samples for testing the validity of consensually accepted beliefs about the effects of orthodontic treatment.},

keywords = {AAOF, craniofacial, Legacy Collection, orthodontic, research, teaching},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2009,

title = {Correlation between cephalometric and photographic measurements of facial attractiveness in  Chinese and U.S. patients at the end of orthodontic treatment.},

author = {HS Oh and EL Korn and XY Zhang and Y Liu and T-M Xu and R Boyd and S Baumrind},

url = {https://pubmed.ncbi.nlm.nih.gov/19962590/},

doi = {10.1016/j.ajodo.2009.04.020},

year  = {2009},

date = {2009-12-00},

journal = {American Journal of Orthodontics & Dentofacial Orthopedics},

volume = {136},

number = {6},

pages = {e1-14; discussion 762-3},

abstract = {Orthodontists rely on esthetic judgments from facial photographs. Concordance between estimates of facial attractiveness made from lateral cephalograms and those made from clinical photographs has not been determined. We conducted a preliminary examination to correlate clinicians' rankings of facial attractiveness from standardized end-of-treatment facial photographs (Photo Attractiveness Rank) with cephalometric measurements of facial attractiveness made for the same subjects at the same time.},

keywords = {AAOF, Adolescents, anterior openbite, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, Discrepency Index, hyperdivergent, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment},

pubstate = {published},

tppubtype = {article}

}

@article{Liu2009,

title = {Comparison of Chinese and U.S. Orthodontists' Averaged Evaluations of "Facial Attractiveness" from End-of-Treatment Facial Photographs. },

author = {Y Lui and EL Korn and HS Oh and H Pearson and T-M Xu and S Baumrind},

url = {https://pubmed.ncbi.nlm.nih.gov/19409345/},

doi = {10.1016/j.ajodo.2007.04.039},

year  = {2009},

date = {2009-05-00},

journal = {American Journal of Orthodontics & Dentofacial Orthopedics},

volume = {135},

number = {5},

pages = {621-34},

abstract = {This study continues our assessment of agreement and disagreement among 25 Chinese and 20 US orthodontists in the ranking for facial attractiveness of end-of-treatment photographs of randomly sampled growing Chinese and white orthodontic patients. The main aims of this article were to (1) measure the overall pattern of agreement between the mean rankings of US and Chinese orthodontists, and (2) measure the strength of agreement between the rankings of the US and Chinese orthodontists for each patient.},

keywords = {AAOF, Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, Mandibular fixed retainer, Mandibular remodeling, technique, vertical control, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Xu2008,

title = {"Facial Attractiveness": Ranking of End-of-Treatment Facial Photographs by Chinese and U.S. Orthodontists.},

author = {T-M Xu and EL Korn and Y Liu and HS Oh and KH Lee and S Baumrind},

url = {https://pubmed.ncbi.nlm.nih.gov/18617106/},

doi = {10.1016/j.ajodo.2006.08.023},

year  = {2008},

date = {2008-07-00},

journal = {American Journal of Orthodontics & Dentofacial Orthopedics},

volume = {134},

number = {1},

pages = {74-84},

abstract = {In this study, we assessed agreement and disagreement among pairs of Chinese and US orthodontists in the ranking for "facial attractiveness" of end-of-treatment photographs of growing Chinese and white orthodontic patients.},

keywords = {AAOF, Adolescents, anterior openbite, clinical orthodontist, Cone-beam computed tomography, Cranial base, hyperdivergent, Mandibular fixed retainer, open bite, retrospective},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2019b,

title = {Comparison of traditional RPE with two types of micro-implant assisted RPE: CBCT study.},

author = {H Oh and Park J and M Lagravere-Vich },

url = {https://www.sciencedirect.com/science/article/pii/S1073874619300076},

doi = {10.1053/j.sodo.2019.02.007},

journal = {Semin Orthod},

volume = {25},

number = {1},

pages = {60-68},

abstract = {Recently, various types of the Micro-implant Assisted RPE (MARPE) were introduced to obtain greater skeletal expansion and to minimize dental effects. In the present study, we evaluated skeletal and dental effects immediately after the completion of expansion using three different types of expanders— a traditional tooth-anchored maxillary expander (TAME) and two different types of MARPE, bone-anchored maxillary expander (BAME) and tooth-bone-anchored expander (MSE) using CBCT in adolescents. Overall, the MSE group showed much greater skeletal changes than the TAME and BAME groups, especially, at the nasal floor, maxillary base, and palatal suture. About 72–78% of suture opening was at PNS, which indicates slightly more opening anteriorly than posteriorly; however, it was relatively parallel in nature than anticipated. In all three groups, the greatest transverse changes with expansion occurred at the molar crowns and the 2nd greatest changes at the palatal suture opening at ANS. It is suggested that MSE can be a great alternative method in correcting maxillary skeletal transverse deficiency.},

keywords = {AAOF, adult, anterior openbite, Cranial base, extraction, Growth, Posttreatment, pressure tension, retrospective, technique, x-ray},

pubstate = {published},

tppubtype = {article}

}

@article{Bussolaro2019,

title = {Pharyngeal dimensional changes in class II malocclusion treatment when using Forsus® or intermaxillary elastics - An exploratory study.},

author = {Thereza-Bussolaro C and Oh HS and Lagravere M and Flores-Mir C },

url = {https://pubmed.ncbi.nlm.nih.gov/31492602/},

doi = {10.1016/j.ortho.2019.08.023},

journal = {Int Orthod},

volume = {17},

number = {4},

pages = {667-677},

abstract = {Pharyngeal airway obstruction can facilitate some forms of sleep disorder breathing (SDB) in susceptible children, especially in those having class II malocclusion. Changes in the anatomic areas surrounding the pharyngeal region during orthodontic treatment could hypothetically impact the pharyngeal airway dimensions. Management of a class II malocclusion on a growing individual with either intermaxillary elastics or different removable or fixed class II appliance designs have been proposed over the last century. The objective of this retrospective exploratory cohort study is to investigate to what extent the class II malocclusion treatment with either intermaxillary elastics (IME) or Forsus® fatigue resistance device (FFRD) leads to changes in oropharyngeal airway dimensions.},

keywords = {AAOF, adult, clear aligners, Cone-beam computed tomography, Cranial base, craniofacial, Mandibular fixed retainer, Mandibular remodeling, Peer Assessment Rating Index, pressure tension, research, teaching, technique, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022c,

title = {Treatment of anterior open bites using non-extraction clear aligner therapy in adult patients},

author = {H Suh and B Shen Garnett and K Mahood and N Mahjoub and RL Boyd and H Oh},

doi = {10.4041/kjod21.180},

journal = {The Korean Journal of Orthodontics },

volume = {52},

issue = {3},

abstract = {Objective: The purpose of this study was to examine the effectiveness and mechanism of clear aligner therapy for the correction of anterior open bite in adult nonextraction cases. Methods: Sixty-nine adult patients with anterior open bite were enrolled and classified into Angle's Class I, II, and III groups. Fifty patients presented with skeletal open bite (mandibular plane angle [MPA] ≥ 38°), whereas 19 presented with dental open bite. Fifteen cephalometric landmarks were identified before (T1) and after (T2) treatment. The magnitudes of planned and actual movements of the incisors and molars were calculated. Results: Positive overbite was achieved in 94% patients, with a mean final overbite of 1.1 ± 0.8 mm. The mean change in overbite was 3.3 ± 1.4 mm. With clear aligners alone, 0.36 ± 0.58 mm of maxillary molar intrusion was achieved. Compared with the Class I group, the Class II group showed greater maxillary molar intrusion and MPA reduction. The Class III group showed greater mandibular incisor extrusion with no significant vertical skeletal changes. Conclusions: Clear aligners can be effective in controlling the vertical dimension and correcting mild to moderate anterior open bite in adult nonextraction cases. The treatment mechanism for Class III patients significantly differed from that for Class I and Class II patients. Maxillary incisor extrusion in patients with dental open bite and MPA reduction with mandibular incisor extrusion in patients with skeletal open bite are the most significant contributing factors for open bite closure.},

keywords = {AAOF, aligner, aligner therapy, anterior openbite, non-extraction},

pubstate = {published},

tppubtype = {article}

}