Publications
2021
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L
Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications. Journal Article
In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray
@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}
}
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.
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,
Clinical decision support systems in orthodontics: A narrative review of data science approaches. Journal Article
In: Orthod Craniofac Res, 2021.
Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique
@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}
}
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.
Parizotto, JOL; Peixoto, AP; Borsato, KT; Bianchi, J; et al,
Craniofacial and airway morphology of individuals with oculoauriculovertebral spectrum. Journal Article
In: Orthodontics & Craniofacial Research, 2021.
Abstract | Links | BibTeX | Tags: AAOF, anterior openbite, clear aligners, clinical orthodontist, Mandibular fixed retainer, Posttreatment, research, technique, vertical control, x-ray
@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}
}
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.
Boubolo, Louis; Dumont, Maxime; Brosset, Serge; Bianchi, Jonas; Ruellas, Antonio; Gurgel, Marcela; Massaro, Camila; Castillo, Aron Aliaga Del; Ioshida, Marcos; Yatabe, Marilia; Benavides, Erika; Rios, Hector; Soki, Fabiana; Neiva, Gisele; Paniagua, Beatriz; Cevidanes, Lucia; Styner, Martin; Prieto, Juan Carlos
FlyBy CNN: a 3D surface segmentation framework Journal Article
In: Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115962B , 2021.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, technique, vertical control
@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}
}
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.
2020
Chen, G; Awadi, M Al; Chambers, D W; Lagravere-Vich, M O; Xu, Y; Oh, H
The three-dimensional stable mandibular landmarks in patients between the ages of 12.5 and 17.1 years. Journal Article
In: BMC Oral Health, vol. 20, no. 1, pp. 153, 2020.
Abstract | Links | BibTeX | Tags: AAOF, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, technique
@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}
}
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.
J, Bianchi; Ruellas, A C De Oliveira; Goncalves, J R; Paniagua, B; Prieto, J C; Martin, S; Tengfei, Li; Hongtu, Zhu; James, S; William, G; Erika, B; Fabiana, Soki; Marilia, Yatabe; Lawrence, Ashman; David, W; Reza, Soroushmehr; Kayvan, N; Cevidanes, L H S
Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning. Journal Article
In: Scientific Reports, vol. 10, no. 1, pp. 8012, 2020.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, technique, vertical control, x-ray
@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}
}
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.
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S
Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis Journal Article
In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2020.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, orthodontic, pressure tension, technique
@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}
}
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.
2017
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T
In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017.
Abstract | Links | BibTeX | Tags: AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray
@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}
}
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.
Afrand, M; Oh, H; Flores-Mir, C; Lagravere-Vich, M
Growth changes in the anterior and middle cranial bases as assessed through cone-beam computed tomography in adolescents. Journal Article
In: Am J Orthod Dentofacial Orthop, vol. 151, no. 2, pp. 342-350, 2017.
Abstract | Links | BibTeX | Tags: 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
@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}
}
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)
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R
A retrospective study of Class II mixed-dentition treatment. Journal Article
In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017.
Abstract | Links | BibTeX | Tags: 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
@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}
}
To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions.
2016
Oh, H; Ma, N; Feng, P; Kieu, K; Boero, R; Dugoni, S; Aubert, M; Chambers, D
Evaluation of Post-treatment stability following orthodontic treatment in the mixed and permanent dentitions. Journal Article
In: Angle Orthodontist, vol. 86, no. 6, pp. 1010-1018, 2016.
Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, hyperdivergent, Peer Assessment Rating Index, Posttreatment, pressure tension, research, retrospective, technique
@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}
}
To investigate posttreatment changes in the maxillary and mandibular arches in patients who underwent orthodontic treatment during the mixed and permanent dentitions.
2009
Lui, Y; Korn, EL; Oh, HS; Pearson, H; Xu, T-M; Baumrind, S
Comparison of Chinese and U.S. Orthodontists' Averaged Evaluations of "Facial Attractiveness" from End-of-Treatment Facial Photographs. Journal Article
In: American Journal of Orthodontics & Dentofacial Orthopedics, vol. 135, no. 5, pp. 621-34, 2009.
Abstract | Links | BibTeX | Tags: AAOF, Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, Mandibular fixed retainer, Mandibular remodeling, technique, vertical control, x-ray
@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}
}
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.
1987
Curry, Sean; Baumrind, Sheldon; Anderson, J. M.
A technique for anatomic feature extraction and tracking on sequential digital X-ray images Journal Article
In: Photogrammetria, vol. 42, pp. 126-135, 1987.
Abstract | Links | BibTeX | Tags: extraction, technique, tracking, x-ray
@article{Curry1987,
title = {A technique for anatomic feature extraction and tracking on sequential digital X-ray images},
author = {Sean Curry and Sheldon Baumrind and J.M. Anderson},
url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/12/A-Technique-for-Anatomic-Feature-Extraction-and-Tracking-on-Sequential-Digital-X-Ray-Images.pdf},
year = {1987},
date = {1987-08-03},
journal = {Photogrammetria},
volume = {42},
pages = {126-135},
abstract = {The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.},
keywords = {extraction, technique, tracking, x-ray},
pubstate = {published},
tppubtype = {article}
}
The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.
0000
Oh, H; J, Park; Lagravere-Vich, M
Comparison of traditional RPE with two types of micro-implant assisted RPE: CBCT study. Journal Article
In: Semin Orthod, vol. 25, no. 1, pp. 60-68, 0000.
Abstract | Links | BibTeX | Tags: AAOF, adult, anterior openbite, Cranial base, extraction, Growth, Posttreatment, pressure tension, retrospective, technique, x-ray
@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}
}
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.
C, Thereza-Bussolaro; HS, Oh; M, Lagravere; C, Flores-Mir
Pharyngeal dimensional changes in class II malocclusion treatment when using Forsus® or intermaxillary elastics - An exploratory study. Journal Article
In: Int Orthod, vol. 17, no. 4, pp. 667-677, 0000.
Abstract | Links | BibTeX | Tags: 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
@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}
}
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.
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L
Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications. Journal Article
In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,
Clinical decision support systems in orthodontics: A narrative review of data science approaches. Journal Article
In: Orthod Craniofac Res, 2021.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Parizotto, JOL; Peixoto, AP; Borsato, KT; Bianchi, J; et al,
Craniofacial and airway morphology of individuals with oculoauriculovertebral spectrum. Journal Article
In: Orthodontics & Craniofacial Research, 2021.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Boubolo, Louis; Dumont, Maxime; Brosset, Serge; Bianchi, Jonas; Ruellas, Antonio; Gurgel, Marcela; Massaro, Camila; Castillo, Aron Aliaga Del; Ioshida, Marcos; Yatabe, Marilia; Benavides, Erika; Rios, Hector; Soki, Fabiana; Neiva, Gisele; Paniagua, Beatriz; Cevidanes, Lucia; Styner, Martin; Prieto, Juan Carlos
FlyBy CNN: a 3D surface segmentation framework Journal Article
In: Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115962B , 2021.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Chen, G; Awadi, M Al; Chambers, D W; Lagravere-Vich, M O; Xu, Y; Oh, H
The three-dimensional stable mandibular landmarks in patients between the ages of 12.5 and 17.1 years. Journal Article
In: BMC Oral Health, vol. 20, no. 1, pp. 153, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
J, Bianchi; Ruellas, A C De Oliveira; Goncalves, J R; Paniagua, B; Prieto, J C; Martin, S; Tengfei, Li; Hongtu, Zhu; James, S; William, G; Erika, B; Fabiana, Soki; Marilia, Yatabe; Lawrence, Ashman; David, W; Reza, Soroushmehr; Kayvan, N; Cevidanes, L H S
Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning. Journal Article
In: Scientific Reports, vol. 10, no. 1, pp. 8012, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S
Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis Journal Article
In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2020.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T
Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists. Journal Article
In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Afrand, M; Oh, H; Flores-Mir, C; Lagravere-Vich, M
Growth changes in the anterior and middle cranial bases as assessed through cone-beam computed tomography in adolescents. Journal Article
In: Am J Orthod Dentofacial Orthop, vol. 151, no. 2, pp. 342-350, 2017.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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)
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R
A retrospective study of Class II mixed-dentition treatment. Journal Article
In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions.
Oh, H; Ma, N; Feng, P; Kieu, K; Boero, R; Dugoni, S; Aubert, M; Chambers, D
Evaluation of Post-treatment stability following orthodontic treatment in the mixed and permanent dentitions. Journal Article
In: Angle Orthodontist, vol. 86, no. 6, pp. 1010-1018, 2016.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
To investigate posttreatment changes in the maxillary and mandibular arches in patients who underwent orthodontic treatment during the mixed and permanent dentitions.
Lui, Y; Korn, EL; Oh, HS; Pearson, H; Xu, T-M; Baumrind, S
Comparison of Chinese and U.S. Orthodontists' Averaged Evaluations of "Facial Attractiveness" from End-of-Treatment Facial Photographs. Journal Article
In: American Journal of Orthodontics & Dentofacial Orthopedics, vol. 135, no. 5, pp. 621-34, 2009.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
Curry, Sean; Baumrind, Sheldon; Anderson, J. M.
A technique for anatomic feature extraction and tracking on sequential digital X-ray images Journal Article
In: Photogrammetria, vol. 42, pp. 126-135, 1987.
@article{Curry1987,
title = {A technique for anatomic feature extraction and tracking on sequential digital X-ray images},
author = {Sean Curry and Sheldon Baumrind and J.M. Anderson},
url = {http://162.214.24.32/~crilorg/wp-content/uploads/2018/12/A-Technique-for-Anatomic-Feature-Extraction-and-Tracking-on-Sequential-Digital-X-Ray-Images.pdf},
year = {1987},
date = {1987-08-03},
journal = {Photogrammetria},
volume = {42},
pages = {126-135},
abstract = {The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.
Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The
features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.
Oh, H; J, Park; Lagravere-Vich, M
Comparison of traditional RPE with two types of micro-implant assisted RPE: CBCT study. Journal Article
In: Semin Orthod, vol. 25, no. 1, pp. 60-68, 0000.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
C, Thereza-Bussolaro; HS, Oh; M, Lagravere; C, Flores-Mir
Pharyngeal dimensional changes in class II malocclusion treatment when using Forsus® or intermaxillary elastics - An exploratory study. Journal Article
In: Int Orthod, vol. 17, no. 4, pp. 667-677, 0000.
@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 = {},
pubstate = {published},
tppubtype = {article}
}
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.
2021 |
Bianchi, J; Ruellas, A; Prieto, J C; Li, T; Soroushmehr, R; Najarian, K; Gryak, J; Deleat-Besson, R; Le, C; Yatabe, M; Gurgel, M; Turkestani, N A; Paniagua, B; Cevidanes, L: Decision support systems in temporomandibular Joint osteoarthritis: A review of data science and artificial intelligence applications.. In: Seminars in Orthodontics, vol. 27, no. 2, pp. 78-86, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Discrepency Index, malocclusion severity, mandibular asymmetry, orthodontic, Peer Assessment Rating Index, technique, vertical control, x-ray)@article{Bianchi2021,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. |
Turkestani, N Al; Bianchi, J; Deleat-Besson, R; et al,: Clinical decision support systems in orthodontics: A narrative review of data science approaches.. In: Orthod Craniofac Res, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, clinical orthodontist, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, malocclusion severity, mandibular asymmetry, Posttreatment, technique)@article{Turkestani2021,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. |
Parizotto, JOL; Peixoto, AP; Borsato, KT; Bianchi, J; et al,: Craniofacial and airway morphology of individuals with oculoauriculovertebral spectrum.. In: Orthodontics & Craniofacial Research, 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, anterior openbite, clear aligners, clinical orthodontist, Mandibular fixed retainer, Posttreatment, research, technique, vertical control, x-ray)@article{Parizotto2021,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. |
Boubolo, Louis; Dumont, Maxime; Brosset, Serge; Bianchi, Jonas; Ruellas, Antonio; Gurgel, Marcela; Massaro, Camila; Castillo, Aron Aliaga Del; Ioshida, Marcos; Yatabe, Marilia; Benavides, Erika; Rios, Hector; Soki, Fabiana; Neiva, Gisele; Paniagua, Beatriz; Cevidanes, Lucia; Styner, Martin; Prieto, Juan Carlos: FlyBy CNN: a 3D surface segmentation framework. In: Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115962B , 2021. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, pressure tension, technique, vertical control)@article{Boubolo2021,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. |
2020 |
Chen, G; Awadi, M Al; Chambers, D W; Lagravere-Vich, M O; Xu, Y; Oh, H: The three-dimensional stable mandibular landmarks in patients between the ages of 12.5 and 17.1 years.. In: BMC Oral Health, vol. 20, no. 1, pp. 153, 2020. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, clear aligners, clinical orthodontist, Cone-beam computed tomography, Cranial base, technique)@article{Chen2020,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. |
J, Bianchi; Ruellas, A C De Oliveira; Goncalves, J R; Paniagua, B; Prieto, J C; Martin, S; Tengfei, Li; Hongtu, Zhu; James, S; William, G; Erika, B; Fabiana, Soki; Marilia, Yatabe; Lawrence, Ashman; David, W; Reza, Soroushmehr; Kayvan, N; Cevidanes, L H S: Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning.. In: Scientific Reports, vol. 10, no. 1, pp. 8012, 2020. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, craniofacial, hyperdivergent, Mandibular fixed retainer, Peer Assessment Rating Index, Posttreatment, technique, vertical control, x-ray)@article{Bianchi2020b,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. |
Bianchi, J; Goncalves, J R; de Oliveira Ruellas, A C; Ashman, L M; Vimort, J B; Yatabe, M; Paniagua, B; Hernandez, P; Benavides, E; Soki, F N; Loshida, M; Cevidanes, L H S: Quantitative bone imaging biomarkers to diagnose temporomandibular joint osteoarthritis. In: International Journal of Oral and Maxillofacial Surgery, vol. 50, no. 2, pp. 227-235, 2020. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, Growth, hyperdivergent, mandibular asymmetry, Mandibular fixed retainer, Mandibular remodeling, orthodontic, pressure tension, technique)@article{Bianchi2020,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. |
2017 |
Lui, S; Oh, H; Chambers, D; Weng, X; Chen, Q; Baumrind, S; Xu, T: Validity and reliability of the ABO Discrepancy Index and PAR Index (Peer Assessment Rating) for evaluating malocclusion severity among Chinese orthodontists.. In: Orthodontics and Craniofacial Research, vol. 20, no. 3, pp. 140-145, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, extraction, fixed appliances, hyperdivergent, malocclusion severity, Mandibular fixed retainer, Mandibular remodeling, Posttreatment, retrospective, technique, x-ray)@article{Liu2017b,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. |
Afrand, M; Oh, H; Flores-Mir, C; Lagravere-Vich, M: Growth changes in the anterior and middle cranial bases as assessed through cone-beam computed tomography in adolescents.. In: Am J Orthod Dentofacial Orthop, vol. 151, no. 2, pp. 342-350, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: 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)@article{Afrand2017b,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) |
Oh, H; Baumrind, S; Dugoni, S; Boero, R; Aubert, M; Boyd, R: A retrospective study of Class II mixed-dentition treatment. . In: Angle Orthodontist, vol. 87, no. 1, pp. 56-67, 2017. (Type: Journal Article | Abstract | Links | BibTeX | Tags: 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)@article{Oh2017,To consider the effectiveness of early treatment using one mixed-dentition approach to the correction of moderate and severe Class II malocclusions. |
2016 |
Oh, H; Ma, N; Feng, P; Kieu, K; Boero, R; Dugoni, S; Aubert, M; Chambers, D: Evaluation of Post-treatment stability following orthodontic treatment in the mixed and permanent dentitions.. In: Angle Orthodontist, vol. 86, no. 6, pp. 1010-1018, 2016. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Cone-beam computed tomography, Cranial base, hyperdivergent, Peer Assessment Rating Index, Posttreatment, pressure tension, research, retrospective, technique)@article{Oh2016b,To investigate posttreatment changes in the maxillary and mandibular arches in patients who underwent orthodontic treatment during the mixed and permanent dentitions. |
2009 |
Lui, Y; Korn, EL; Oh, HS; Pearson, H; Xu, T-M; Baumrind, S: Comparison of Chinese and U.S. Orthodontists' Averaged Evaluations of "Facial Attractiveness" from End-of-Treatment Facial Photographs. . In: American Journal of Orthodontics & Dentofacial Orthopedics, vol. 135, no. 5, pp. 621-34, 2009. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, Adolescents, Cone-beam computed tomography, Cranial base, craniofacial, Discrepency Index, Growth, hyperdivergent, Mandibular fixed retainer, Mandibular remodeling, technique, vertical control, x-ray)@article{Liu2009,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. |
1987 |
Curry, Sean; Baumrind, Sheldon; Anderson, J. M.: A technique for anatomic feature extraction and tracking on sequential digital X-ray images. In: Photogrammetria, vol. 42, pp. 126-135, 1987. (Type: Journal Article | Abstract | Links | BibTeX | Tags: extraction, technique, tracking, x-ray)@article{Curry1987,The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data. Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic sucgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays. Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or "frame grabber" installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years. A number of anatomic features were manually selected on the first image of each series. The features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images. |
0000 |
Oh, H; J, Park; Lagravere-Vich, M: Comparison of traditional RPE with two types of micro-implant assisted RPE: CBCT study.. In: Semin Orthod, vol. 25, no. 1, pp. 60-68, 0000. (Type: Journal Article | Abstract | Links | BibTeX | Tags: AAOF, adult, anterior openbite, Cranial base, extraction, Growth, Posttreatment, pressure tension, retrospective, technique, x-ray)@article{Oh2019b,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. |
C, Thereza-Bussolaro; HS, Oh; M, Lagravere; C, Flores-Mir: Pharyngeal dimensional changes in class II malocclusion treatment when using Forsus® or intermaxillary elastics - An exploratory study.. In: Int Orthod, vol. 17, no. 4, pp. 667-677, 0000. (Type: Journal Article | Abstract | Links | BibTeX | Tags: 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)@article{Bussolaro2019,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. |