@article{Suh2023b,

title = {Anterior open bite correction via molar intrusion: Diagnosis, advantages, and complications},

author = {Choi YJ and Suh H and Park JJ and Park JH},

url = {https://pubmed.ncbi.nlm.nih.gov/38185583/},

doi = {10.1016/j.ejwf.2023.12.006},

year  = {2024},

date = {2024-01-06},

journal = {J World Fed Orthod},

volume = {S2212-4438},

issue = {23},

abstract = {Anterior open bite can be effectively treated nonsurgically via molar intrusion. This technique, involving the intrusion of posterior teeth using temporary skeletal anchorage devices, prompts counterclockwise rotation of the mandible. This rotation not only corrects anterior open bite but also contributes to a decrease in anterior facial height, improvements in lip incompetency, and forward movement of the chin. For successful outcomes, temporary skeletal anchorage devices, installed on both the buccal and palatal sides, must deliver equivalent intrusion force to the maxillary teeth. Treatment planning should consider factors such as skeletal discrepancies, vertical excess, incisor exposure, and configuration of the occlusal plane. Clinicians are advised to closely monitor periodontal changes and consider overcorrection to ensure lasting stability and maintenance of incisal overlap post-treatment.},

keywords = {anterior openbite, Molar intrusion, Temporary skeletal anchorage devices, Treatment planning, Vertical malocclusions},

pubstate = {published},

tppubtype = {article}

}

@article{Suh2023,

title = {Reliability statistics every orthodontist should know},

author = {Moon JH and Lee JM and Park JA and Suh H and Lee SJ},

url = {https://doi.org/10.1053/j.sodo.2023.12.004},

doi = {10.1053/j.sodo.2023.12.004},

issn = {1073-8746},

year  = {2023},

date = {2023-12-29},

journal = {Seminars in Orthodontics},

abstract = {It is essential to conduct a reliability examination even if the method was considered reliable in the past, as it may not be reliable in a new study conducted by different researchers using different materials. The current article highlights the importance of reliability examination in orthodontic studies and explains which assessment methods are more appropriate than others. Several fallacies in reporting and interpreting reliability are also discussed. In addition, the article presents examples of reliability examination for one-, two-, and three-dimensional data using graphic visualization in a tutorial format.},

keywords = {Bland-Altman plot, Confidence ellipse, Confidence interval, Reliability},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023n,

title = {Stability of skeletal class III surgical treatment. Affect of high condylectomy.},

author = {Kato RM and Bianchi J and Parizotto J and Wolford LM and Peixoto AP and Goncalves JR},

url = {https://www.researchgate.net/publication/376665721_Stability_of_skeletal_class_III_surgical_treatment_Affect_of_high_condylectomy},

doi = {10.55905/cuadv15n12-083},

year  = {2023},

date = {2023-12-21},

journal = {Cuadernos de Educación y Desarrollo},

pages = {16666-16681},

abstract = {Purpose: To evaluate the role of high condylectomy on surgical treatment stability of Class III patients with condylar hyperplasia. Materials and Methods: Twenty-four patients (9 females and 15 males) were paired according to gender, age, skeletal and dental characteristics in three groups. Group 1 (no condylar hyperplasia) underwent orthognathic surgery only, Group 2 (with unilateral or bilateral condylar hyperplasia) underwent high condylectomy, articular disc repositioning and orthognathic surgery in the same procedure and Group 3 (with unilateral or bilateral condylar hyperplasia) underwent orthognathic surgery only. Lateral cephalometric radiographs were selected at the immediately before surgery (T1), immediate after surgery (T2) and longest follow-up (T3). Results: Cephalometric comparison between the 3 groups showed no significant differences among the variables at the initial observation period (T1). During the observational period (T3-T2), patients in Group 3 showed significant relapse at SNB (mean = 2.18, sd = 1.39 degrees), ANB (mean = -2.68, sd = 2.24 degrees), SN.Pog (mean = -1.48, sd = 1.66 degrees), OJ (mean = -2.99, sd = 1.64 mm), OB (mean = 1.45, sd = 1.16 mm), Ar-Go (mean = 2.23, sd = 2.66 mm), Ar-Gn (mean = 3.76, sd = 1.48 mm), S-Gn (mean = 2.3, sd = 2.34 mm) and ANS-Me (mean = 2.06, sd = 2.2 mm) demonstrating that treatment adopted was insufficient for stable results within this Group. Groups 1 and 2 remained stable one year after surgery. Conclusions: Orthognathic surgery for correction of skeletal class III malocclusion is a stable procedure for patients without condylar growth abnormalities and for patients undergoing simultaneous high condylectomies and articular disc repositioning. Those patients with preoperative condylar hyperplasia who underwent double-jaw surgery and no TMJ intervention experienced significant relapse.},

keywords = {high condylectomy, skeletal class III, surgical treatment},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023l,

title = {Automated artificial intelligence‐based three‐dimensional comparison of orthodontic treatment outcomes with and without piezocision surgery.},

author = {Gurgel M and Alvarez M.A and Aristizabal J.F and Baquero B and Gillot M and Al Turkestani N and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/38009409/},

doi = {10.1111/ocr.12737},

year  = {2023},

date = {2023-11-27},

journal = {Orthod Craniofac Res},

abstract = {Objective(s): This study aims to evaluate the influence of the piezocision surgery in the orthodontic biomechanics, as well as in the magnitude and direction of tooth movement in the mandibular arch using novel artificial intelligence (AI)-automated tools.



Materials and methods: Nineteen patients, who had piezocision performed in the lower arch at the beginning of treatment with the goal of accelerating tooth movement, were compared to 19 patients who did not receive piezocision. Cone beam computed tomography (CBCT) and intraoral scans (IOS) were acquired before and after orthodontic treatment. AI-automated dental tools were used to segment and locate landmarks in dental crowns from IOS and root canals from CBCT scans to quantify 3D tooth movement. Differences in mesial-distal, buccolingual, intrusion and extrusion linear movements, as well as tooth long axis angulation and rotation were compared.



Results: The treatment time for the control and experimental groups were 13.2 ± 5.06 and 13 ± 5.52 months respectively (P = .176). Overall, anterior and posterior tooth movement presented similar 3D linear and angular changes in the groups. The piezocision group demonstrated greater (P = .01) mesial long axis angulation of lower right first premolar (4.4 ± 6°) compared with control group (0.02 ± 4.9°), while the mesial rotation was significantly smaller (P = .008) in the experimental group (0.5 ± 7.8°) than in the control (8.5 ± 9.8°) considering the same tooth.



Conclusion: The open source-automated dental tools facilitated the clinicians' assessment of piezocision treatment outcomes. The piezocision surgery prior to the orthodontic treatment did not decrease the treatment time and did not influence in the orthodontic biomechanics, leading to similar tooth movements compared to conventional treatment.},

keywords = {computer-assisted, Cone-beam computed tomography (CBCT), Damon system, Dental long axis, Image processing, imaging, self-ligating braces, three-dimensional},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023m,

title = {Enhancing skeletal stability and Class III correction through active orthodontist engagement in virtual surgical planning: A voxel-based 3-dimensional analysis. },

author = {Barone S and Cevidanes L and Miranda F and Gurgel ML and Anchling L and Hutin N and et al},

url = {https://www.sciencedirect.com/science/article/pii/S0889540623005966?via%3Dihub},

doi = {10.1016/j.ajodo.2023.09.016 },

year  = {2023},

date = {2023-11-27},

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

volume = {5406},

issue = {23},

abstract = {Introduction

Skeletal stability after bimaxillary surgical correction of Class III malocclusion was investigated through a qualitative and quantitative analysis of the maxilla and the distal and proximal mandibular segments using a 3-dimensional voxel-based superimposition among virtual surgical predictions performed by the orthodontist in close communication with the maxillofacial surgeon and 12-18 months postoperative outcomes.

Methods

A comprehensive secondary data analysis was conducted on deidentified preoperative (1 month before surgery [T1]) and 12-18 months postoperative (midterm [T2]) cone-beam computed tomography scans, along with virtual surgical planning (VSP) data obtained by Dolphin Imaging software. The sample for the study consisted of 17 patients (mean age, 24.8 ± 3.5 years). Using 3D Slicer software, automated tools based on deep-learning approaches were used for cone-beam computed tomography orientation, registration, bone segmentation, and landmark identification. Colormaps were generated for qualitative analysis, whereas linear and angular differences between the planned (T1-VSP) and observed (T1-T2) outcomes were calculated for quantitative assessments. Statistical analysis was conducted with a significance level of α = 0.05.

Results

The midterm surgical outcomes revealed a slight but significantly less maxillary advancement compared with the planned position (mean difference, 1.84 ± 1.50 mm; P = 0.004). The repositioning of the mandibular distal segment was stable, with insignificant differences in linear (T1-VSP, 1.01 ± 3.66 mm; T1-T2, 0.32 ± 4.17 mm) and angular (T1-VSP, 1.53° ± 1.60°; T1-T2, 1.54° ± 1.50°) displacements (P >0.05). The proximal segments exhibited lateral displacement within 1.5° for both the mandibular right and left ramus at T1-VSP and T1-T2 (P >0.05).

Conclusions

The analysis of fully digital planned and surgically repositioned maxilla and mandible revealed excellent precision. In the midterm surgical outcomes of maxillary advancement, a minor deviation from the planned anterior movement was observed.},

keywords = {3D analysis, Class III correction, maxillofacial surgeon, skeletal stability},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023c,

title = {Automatic landmark identification in cone‐beam computed tomography. },

author = {Gillot M and Miranda F and Baquero B and Ruellas A and Gurgel M and Al Turkestani N and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/36811276/},

doi = {10.1111/ocr.12642},

year  = {2023},

date = {2023-11-26},

journal = {Orthod Craniofac Res},

volume = {26},

issue = {4},

pages = {560-567},

abstract = {Objective: To present and validate an open-source fully automated landmark placement (ALICBCT) tool for cone-beam computed tomography scans.



Materials and methods: One hundred and forty-three large and medium field of view cone-beam computed tomography (CBCT) were used to train and test a novel approach, called ALICBCT that reformulates landmark detection as a classification problem through a virtual agent placed inside volumetric images. The landmark agents were trained to navigate in a multi-scale volumetric space to reach the estimated landmark position. The agent movements decision relies on a combination of DenseNet feature network and fully connected layers. For each CBCT, 32 ground truth landmark positions were identified by 2 clinician experts. After validation of the 32 landmarks, new models were trained to identify a total of 119 landmarks that are commonly used in clinical studies for the quantification of changes in bone morphology and tooth position.



Results: Our method achieved a high accuracy with an average of 1.54 ± 0.87 mm error for the 32 landmark positions with rare failures, taking an average of 4.2 second computation time to identify each landmark in one large 3D-CBCT scan using a conventional GPU.



Conclusion: The ALICBCT algorithm is a robust automatic identification tool that has been deployed for clinical and research use as an extension in the 3D Slicer platform allowing continuous updates for increased precision.},

keywords = {anatomic landmarks, fiducial markers, machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2023,

title = {Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton},

author = {Middleton K.M and Duren D.L and McNult K.P and Oh H and Valiathan M and Sherwood R

},

url = {https://doi.org/10.1038/s41598-023-46018-x},

doi = {10.1038/s41598-023-46018-x},

year  = {2023},

date = {2023-11-07},

urldate = {2023-11-07},

journal = {Sci Rep},

volume = {13},

issue = {19294},

abstract = {Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to limits of time, prohibitive cost, or health concerns of repeat radiologic imaging. In contrast, cross-sectional samples have few such drawbacks, but it is not known how well estimates of growth milestones can be obtained from cross-sectional samples. The Craniofacial Growth Consortium Study (CGCS) contains longitudinal growth data for approximately 2000 individuals. Single samples from the CGCS for individuals representing cross-sectional data were used to test the ability to predict growth parameters in linear trait measurements separately by sex. Testing across a range of cross-sectional sample sizes from 5 to the full sample, we found that means from repeated samples were able to approximate growth rates determined from the full longitudinal CGCS sample, with mean absolute differences below 1 mm at cross-sectional sample sizes greater than ~ 200 individuals. Our results show that growth parameters and milestones can be accurately estimated from cross-sectional data compared to population-level estimates from complete longitudinal data, underscoring the utility of such datasets in growth modeling. This method can be applied to other forms of growth (e.g., stature) and to cases in which repeated radiographs are not feasible (e.g., cone-beam CT).},

keywords = {Cone-beam computed tomography (CBCT), craniofacial skeleton, cross-sectional data, longitudinal growth},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023,

title = {Automated Orientation and Registration of Cone-Beam Computed Tomography Scans.},

author = {Anchling L and Hutin N and Huang Y and Barone S and Roberts S and Miranda F and et al},

url = {https://doi.org/10.1007/978-3-031-45249-9_5},

doi = {10.1007/978-3-031-45249-9_5},

isbn = {978-3-031-45249-9},

year  = {2023},

date = {2023-10-09},

urldate = {2023-10-09},

journal = {Lecture Notes in Computer Science},

volume = {14242},

abstract = {Automated clinical decision support systems rely on accurate analysis of three-dimensional (3D) medical and dental images to assist clinicians in diagnosis, treatment planning, intervention, and assessment of growth and treatment effects. However, analyzing longitudinal 3D images requires standardized orientation and registration, which can be laborious and error-prone tasks dependent on structures of reference for registration. This paper proposes two novel tools to automatically perform the orientation and registration of 3D Cone-Beam Computed Tomography (CBCT) scans with high accuracy (<3 and <2 mm of angular and linear errors when compared to expert clinicians). These tools have undergone rigorous testing and are currently being evaluated by clinicians who utilize the 3D Slicer open-source platform. Our work aims to reduce the sources of error in the 3D medical image analysis workflow by automating these operations. These methods combine conventional image processing approaches and Artificial Intelligence (AI) based models trained and tested on de-identified CBCT volumetric images. Our results showed robust performance for standardized and reproducible image orientation and registration that provide a more complete understanding of individual patient facial growth and response to orthopedic treatment in less than 5 min.},

keywords = {3D CBCT scans, Deep Learning, Image processing, medical image registration, standardized orientation},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023d,

title = {Three-dimensional decision support system for treatment of canine impaction.},

author = {Keener DJ and de Oliveria Ruellas A.C and Aron Aliaga Del Castillo and Arriola-Guillen LE and Bianchi J and Oh H and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/37037759/},

doi = {10.1016/j.ajodo.2023.02.016},

year  = {2023},

date = {2023-10-01},

journal = {Am J Orthod Dentofacial Orthop},

volume = {164},

issue = {4},

pages = {491-504},

abstract = {Introduction: This study aimed to develop a 3-dimensional (3D) characterization of the severity of maxillary impacted canines and to test the clinical performance of this characterization as a treatment decision support tool.



Methods: Cone-beam computed tomography images obtained from 83 patients with 120 impacted maxillary canines were included. Quantitative information on the canine 3D position and qualitative assessment of root damage of adjacent teeth were evaluated. A severity index was constructed on the basis of the quantitative findings. Clinical applicability was tested by comparing clinical diagnosis and treatment planning for conventional records vs the 3D characterization via a 2-part survey.



Results: The average quantitative assessments of impacted maxillary canine position were 6.4 ± 3.6 mm from the midsagittal plane, 11.6 ± 3.1 mm in height relative to the occlusal plane, 31.5° ± 18° of roll, and 48.8° ± 14.3° of pitch. The severity index ranged from 0-13 with a mean score of 4.5 ± 2.2. Overlap with adjacent teeth was the greatest contributor (33%) to the index. Bicortically impacted canines caused the most severe root damage. Cone-beam computed tomography was preferred for assessing root damage and overall severity, whereas conventional imaging was sufficient for height and angulation assessment. The 3D report was very important or important for evaluating root damage, canine position, overall severity, and overlap. The 3D report changed most of the decisions relating to biomechanics, patient education, and treatment time estimate. The decision of exposure and traction vs extraction was changed 22% of the time after the presentation of the 3D report.



Conclusions: The overlap with adjacent teeth frequently contributes the most to the severity index. The 3D report provided relevant clinical information regarding the canine position, damage to adjacent teeth, and the severity index, with a profound impact on the decisions of the clinicians regarding biomechanics, patient education, and treatment time estimate.},

keywords = {canine impaction, Cone-beam computed tomography (CBCT), three-dimensional},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023j,

title = {Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. },

author = {Miranda F and Choudhari V and Barone S and Anchling L and Hutin N and Gurgel M and et al},

url = {https://doi.org/10.1038/s41598-023-43125-7},

doi = {10.1038/s41598-023-43125-7},

year  = {2023},

date = {2023-09-22},

journal = {Scientific Reports},

volume = {15861},

abstract = {Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision.},

keywords = {3D landmark identification, alveolar bone defect, artificial intelligence, cleft lip, cleft lip and palate},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2023b,

title = {Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology. },

author = {K Cuenin and J Chen and S Tai and D Lee and G Gerges and H Oh},

url = {https://pubmed.ncbi.nlm.nih.gov/37702639/},

doi = {10.1016/j.ajodo.2023.06.026},

year  = {2023},

date = {2023-09-13},

journal = {Am J Orthod Dentofacial Orthop},

volume = {165},

pages = {54-63},

abstract = {Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians' abilities to detect and characterize caries in pediatric patients using this instrument.



Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading.



Results: The reliability of lesion characterization (ie, grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial.



Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.},

keywords = {5D, Bitewing (BW), infrared technology, Near-infrared imaging (NIRI), Pediatric patients},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2023d,

title = {Short-term stability of anterior open bite treatment with clear aligners in adults},

author = {H Suh and B Garnett and K Mahood and R Boyd and H Oh },

url = {https://pubmed.ncbi.nlm.nih.gov/37552148/},

doi = {10.1016/j.ajodo.2023.05.026},

year  = {2023},

date = {2023-08-07},

journal = {Am J Orthod Dentofacial Orthop},

volume = {164},

issue = {6},

pages = {774-782},

abstract = {Introduction: This study aimed to examine the stability of anterior open bite (AOB) treatment with clear aligners.



Methods: This retrospective cohort study included 52 adult AOB patients (aged >18 years; 15 males, 37 females) who underwent nonextraction clear aligner treatment and were at least 1 year posttreatment. Eleven cephalometric measurements were evaluated at pretreatment, end of active treatment, and at least 1-year posttreatment. Overbite change, the primary outcome variable, and other cephalometric changes during treatment and retention were calculated, and repeated measures analysis of variance were performed. Stepwise multiple regression was used to make a prediction equation for open bite relapse.



Results: The mean retention period was 2.1 ± 1.1 years. The mean change in overbite during treatment was 3.3 ± 1.5 mm; 6% of patients presented relapse at least 1 year after treatment completion. The mean change of overbite (0.2 ± 0.5 mm) during the retention period was not statistically significant (P = 0.59). None of the 11 cephalometric measurements showed significant change during the retention period. The prediction model showed that only the coefficient for a tongue posture issue at the initial examination was statistically significant.



Conclusions: AOB was successfully corrected in all 52 patients using only clear aligners with no additional adjunctive aids such as microimplants. When retained with maxillary and mandibular fixed retainers and maxillary and mandibular vacuum-formed retainers, there was no significant change in cephalometric measurements during the short-term retention period.},

keywords = {anterior openbite, clear aligners, short-term stability},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023h,

title = {Three-dimensional comparison between the effects of mandibular advancement device and maxillomandibular advancement surgery on upper airway.},

author = {Gurgel M and Cevidanes L and Costa F and Pereira R and Cunali P and Bittencourt L and et al},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314553/},

doi = {10.1186/s12903-023-03125-5},

year  = {2023},

date = {2023-06-30},

journal = {BMC Oral Health},

volume = {23},

issue = {436},

abstract = {Background

The efficacy of mandibular advancement devices (MAD) and maxillomandibular advancement (MMA) in improving upper airway (UA) patency has been described as being comparable to continuous positive airway pressure (CPAP) outcomes. However, no previous study has compared MAD and MMA treatment outcomes for the upper airway enlargement. This study aimed to evaluate three-dimensionally the UA changes and mandibular rotation in patients after MAD compared to MMA.



Methods

The sample consisted of 17 patients with treated with MAD and 17 patients treated with MMA matched by weight, height, body mass index. Cone-beam computed tomography from before and after both treatments were used to measure total UA, superior/inferior oropharynx volume and surface area; and mandibular rotation.



Results

Both groups showed a significant increase in the superior oropharynx volume after the treatments (p = 0.003) and the MMA group showed greater increase (p = 0.010). No statistical difference was identified in the MAD group considering the inferior volume, while the MMA group showed a significantly gain (p = 0.010) and greater volume (p = 0.024). Both groups showed anterior mandibular displacement. However, the mandibular rotation were statistically different between the groups (p < 0.001). While the MAD group showed a clockwise rotation pattern (-3.97 ± 1.07 and − 4.08 ± 1.30), the MMA group demonstrated a counterclockwise (2.40 ± 3.43 and 3.41 ± 2.79). In the MAD group, the mandibular linear anterior displacement was correlated with superior [p = 0.002 (r=-0.697)] and inferior [p = 0.004 (r = 0.658)] oropharynx volume, suggesting that greater amounts of mandibular advancement are correlated to a decrease in the superior oropharynx and an increase in the inferior oropharynx. In the MMA group, the superior oropharynx volume was correlated to mandibular anteroposterior [p = 0.029 (r=-0.530)] and vertical displacement [p = 0.047 (r = 0.488)], indicating greater amounts of mandibular advancement may lead to a lowest gain in the superior oropharynx volume, while a great mandibular superior displacement is correlated with improvements in this region.



Conclusions

The MAD therapy led to a clockwise mandibular rotation, increasing the dimensions of the superior oropharynx; while a counterclockwise rotation with greater increases in all UA regions were showed in the MMA treatment.},

keywords = {Cone-beam computed tomography (CBCT), mandibular advancement device, Maxillomandibular advancement, Obstructive sleep apnea, Three-dimensional assessment, Upper airway},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023g,

title = {Artificial Intelligence Applications in Dentistry},

author = {Bianchi J},

url = {https://doi.org/10.1080/19424396.2023.2204566},

year  = {2023},

date = {2023-05-31},

journal = {Journal of the California Dental Association },

volume = {51},

issue = {1},

keywords = {artificial intelligence, CHAT-GPT, DALL-E AI system, dentistry, OpenAI},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023f,

title = {Artificial intelligence applications in orthodontics. },

author = {Miranda F and Barone S and Gillot M and Baquero B and Anchling L and Hutlin B and et al},

url = {https://doi.org/10.1080/19424396.2023.2195585},

year  = {2023},

date = {2023-04-13},

urldate = {2023-04-13},

journal = {Journal of the California Dental Association },

volume = {51},

issue = {1},

abstract = {Objective

This manuscript describes strategies for assessment of precision of several diagnostic artificial intelligence (AI) tools in orthodontics, available open-source image analysis platforms, as well as the use of three-dimensional (3D) surface models and superimpositions.



Results

The advances described in this manuscript present perspectives on the controversies of whether AI is smarter than clinicians and may replace human clinical decisions. A thorough orthodontic diagnosis requires comprehensive 3D analysis of the interrelationships among the dentition, craniofacial skeleton and soft tissues. Forecasts have indicated that 3D printing technology will provide more than 60% of all dental treatment needs by 2025, and orthodontic companies as well as remote monitoring companies are already using AI technology, being it essential that the clinicians are prepared and knowledgeable with the technology advances now available.



Conclusions

The AI applications in orthodontics rely on the implementation into diagnostic image records, data analysis for clinical practice and research applications. Continuous training and validation of the AI orthodontic image tools are essential for improving the performance and generalizability of these methods.},

keywords = {artificial intelligence, imaging, orthodontics, three-dimensional},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023b,

title = {Clear aligner mandibular advancement in growing patients with Class II malocclusion.},

author = {Gurgel ML and de Oliveria Ruellas A.C and Bianchi J and McNamara JA and Tai S and Franchi L and et al.},

url = {https://pubmed.ncbi.nlm.nih.gov/37636594/},

doi = {10.1016/j.xaor.2023.01.003},

year  = {2023},

date = {2023-04-03},

journal = {AJO DO Clin Companion},

volume = {3},

issue = {2},

pages = {93-109},

abstract = {Treatment effects occurring during Class II malocclusion treatment with the clear aligner mandibular advancement protocol were evaluated in two growing patients: one male (12 years, 3 months) and one female (11 years, 9 months). Both patients presented with full cusp Class II molar and canine relationships. Intraoral scans and cone-beam computed tomography were acquired before treatment and after mandibular advancement. Three-dimensional skeletal and dental long-axis changes were quantified, in which the dental long axis was determined by registering the dental crowns obtained from intraoral scans to the root canals in cone-beam computed tomography scans obtained at the same time points. Class II correction was achieved by a combination of mandibular skeletal and dental changes. A similar direction of skeletal and dental changes was observed in both patients, with downward and forward displacement of the mandible resulting from the growth of the mandibular condyle and ramus. Dental changes in both patients included mesialization of the mandibular posterior teeth with flaring of mandibular anterior teeth. In these two patients, clear aligner mandibular advancement was an effective treatment modality for Class II malocclusion correction with skeletal and dental effects and facial profile improvement.},

keywords = {Class II malocclusion, clear aligners, growing patients, three-dimensional},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023e,

title = {Integrative Risk Predictors of Temporomandibular Joint Osteoarthritis Progression.},

author = {Cai L and Al Turkestani N and Cevidanes L and Bianchi J and Gurgel M and Najarian K and et al},

url = {https://doi.org/10.1117/12.2651940},

doi = {10.1117/12.2651940},

year  = {2023},

date = {2023-04-03},

journal = {Semantic Scholar},

abstract = {In this paper we propose feature selection and machine learning approaches to identify a combination of features for risk prediction of Temporomandibular Joint (TMJ) disease progression. In a sample of 32 TMJ osteoarthritis and 38 controls, feature selection of 5 clinical comorbidities, 43 quantitative imaging, 28 biological features and was performed using Maximum Relevance Minimum Redundancy, Chi-Square and Least Absolute Shrinkage and Selection Operator (LASSO) and Recursive Feature Elimination. We compared the performance of learning using concave and convex kernels (LUCCK), Support Vector Machine (SVM) and Random Forest (RF) approaches to predict disease cure/improvement or persistence/worsening. We show that the SVM model using LASSO achieves area under the curve (AUC), sensitivity and precision of 0.92±0.08, 0.85±0.19 and 0.76 ±0.18, respectively. Baseline levels of headaches, lower back pain, restless sleep, muscle soreness, articular fossa bone surface/bone volume and trabecular separation, condylar High Gray Level Run Emphasis and Short Run High Gray Level Emphasis, saliva levels of 6Ckine, Osteoprotegerin (OPG) and Angiogenin, and serum levels of 6ckine and Brain Derived Neurotrophic Factor (BDNF) were the most frequently occurring features to predict more severe TMJ osteoarthritis prognosis.

},

keywords = {machine learning, temporomandibular joint},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2023c,

title = {Survival rates of mandibular fixed retainers: comparison of a tube-type retainer and conventional multistrand retainers : A prospective randomized clinical trial },

author = {Lee KC and Lim SW and Cho Jh and Oh H and Hwang HS},

url = {https://pubmed.ncbi.nlm.nih.gov/36847790/},

doi = {10.1007/s00056-023-00447-5},

year  = {2023},

date = {2023-02-27},

journal = {Journal of Orofacial Orthopedics},

abstract = {Objective: The purposes of this study were to evaluate the survival rate of a tube-type mandibular fixed retainer and compare it to conventional multistrand retainers.



Materials and methods: In all, 66 patients who had completed their orthodontic treatment were enrolled in this study. They were allocated randomly to a tube-type retainer group or a 0.020 multistrand fixed retainer group. In case of the tube-type retainer, a thermoactive 0.012 NiTi was placed into 6 mini-tubes passively bonded to the anterior teeth. The patients were recalled at 1, 3, 6, 12, and 24 months after retainer placement. During the 2‑year follow-up period, any first-time failure of retainers was recorded. Kaplan-Meier survival analysis and log-rank tests were used to compare the failure rates between the two types of retainers.



Results: Of the 34 patients, 14 (41.2%) showed failure in the multistrand retainer group, whereas only 2 of 32 (6.3%) reported failure in the tube-type retainer group. There was a statistically significant difference in failure between the multistrand retainer and the tube-type retainer (log-rank test, P = 0.001). The hazard ratio was 11.937 (95% confidence interval 2.708-52.620; P = 0.005).



Conclusion: The tube-type retainer can be used with fewer concerns about recurrent retainer detachments during orthodontic retention.},

keywords = {dental adhesives, device failure, lingual bonded retainer, Mandibular fixed retainer, Orthodontic appliances fixed, Randomized clinical trials},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023,

title = {Complications of total temporomandibular joint replacement: a systematic review and meta-analysis.},

author = {Lima FGGP and Rios LGC and Bianchi J and Goncalves JR and Paranhos LR and Vieira WA and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/36494246/},

doi = {10.1016/j.ijom.2022.10.009},

year  = {2022},

date = {2022-12-07},

journal = {Int J Oral Maxillofac Surg},

volume = {52},

issue = {5},

pages = {584-594},

abstract = {The aim of this systematic review was to determine the most prevalent complications resulting from total temporomandibular joint (TMJ) replacement. An electronic search was performed using the Embase, LILACS, MEDLINE (via PubMed), SciELO, Scopus, and Web of Science databases up to June 2022. Prospective and retrospective clinical studies on patients who underwent TMJ replacement were included. Two reviewers performed the study selection, data extraction, and individual risk of bias assessment using the Joanna Briggs Institute Critical Appraisal Tools. The pooled prevalence of each complication was calculated through a proportion meta-analysis using the random-effects model. Twenty-eight studies met the eligibility criteria and were included in the review. All of the eligible studies had a low risk of bias. The results of the meta-analysis revealed that the most prevalent complication was paresis or paralysis of the facial nerve branches (7.8%; 95% confidence interval (CI) 2.6-15.1%, I2 = 94.5%), followed by sensory alterations (1.8%; 95% CI 0.6-4.9%, I2 = 88.8%), heterotopic bone formation (1.0%; 95% CI 0.1-2.5%, I2 = 75.8%), and infection (0.7%; 95% CI 0.1-1.6%, I2 = 22.7%). In conclusion, TMJ replacement has a low prevalence of complications, and most of them can be managed successfully.},

keywords = {Intraoperative complications, Joint prosthesis, Mandibular prosthesis, Postoperative complications, temporomandibular joint disorders},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022b,

title = {Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans during 3D UNETR},

author = {Gillot M and Baquero B and Le C and R Deleat-Besson and Bianchi J and Gurgel M and Yatabe M and Al Turkestani N and Najarian K},

url = {https://pubmed.ncbi.nlm.nih.gov/36223330/},

doi = {10.1371/journal.pone.0275033},

year  = {2022},

date = {2022-10-12},

journal = {PLoS One},

volume = {17},

issue = {10},

abstract = {The segmentation of medical and dental images is a fundamental step in automated clinical decision support systems. It supports the entire clinical workflow from diagnosis, therapy planning, intervention, and follow-up. In this paper, we propose a novel tool to accurately process a full-face segmentation in about 5 minutes that would otherwise require an average of 7h of manual work by experienced clinicians. This work focuses on the integration of the state-of-the-art UNEt TRansformers (UNETR) of the Medical Open Network for Artificial Intelligence (MONAI) framework. We trained and tested our models using 618 de-identified Cone-Beam Computed Tomography (CBCT) volumetric images of the head acquired with several parameters from different centers for a generalized clinical application. Our results on a 5-fold cross-validation showed high accuracy and robustness with a Dice score up to 0.962±0.02. Our code is available on our public GitHub repository.},

keywords = {3d, CBCT, Cone-beam computed tomography (CBCT), multi-anatomical skull structure, structure segmentation},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022c,

title = {Presurgical orthodontic decompensation with clear aligners},

author = {Cong A and de Oliveria Ruellas A.C and Tai S.K and Loh C.T and Barkley M and Yatabe M and Caminiti M and Massaro C and Bianchi J and Deleat-Besson R},

url = {https://pubmed.ncbi.nlm.nih.gov/36182208/},

doi = {10.1016/j.ajodo.2021.12.019},

year  = {2022},

date = {2022-10-01},

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

volume = {162},

issue = {4},

pages = {538-553},

abstract = {Introduction: Orthodontists, surgeons, and patients have taken an interest in using clear aligners in combination with orthognathic surgery. This study aimed to evaluate the accuracy of tooth movements with clear aligners during presurgical orthodontics using novel 3-dimensional superimposition techniques.



Methods: The study sample consisted of 20 patients who have completed presurgical orthodontics using Invisalign clear aligners. Initial (pretreatment) digital dental models, presurgical digital dental models, and ClinCheck prediction models were obtained. Presurgical models were superimposed onto initial ones using stable anatomic landmarks; ClinCheck models were superimposed onto presurgical models using surface best-fit superimposition. Five hundred forty-five teeth were measured for 3 angular movements (buccolingual torque, mesiodistal tip, and rotation) and 4 linear movements (buccolingual, mesiodistal, vertical, and total scalar displacement). The predicted tooth movement was compared with the achieved amount for each movement and tooth, using both percentage accuracy and numerical difference.



Results: Average percentage accuracy (63.4% ± 11.5%) was higher than in previously reported literature. The most accurate tooth movements were buccal torque and mesial displacement compared with lingual torque and distal displacement, particularly for mandibular posterior teeth. Clinically significant inaccuracies were found for the buccal displacement of maxillary second molars, lingual displacement of all molars, intrusion of mandibular second molars, the distal tip of molars, second premolars, and mandibular first premolars, buccal torque of maxillary central and lateral incisors, and lingual torque of premolars and molars.



Conclusions: Superimposition techniques used in this study lay the groundwork for future studies to analyze advanced clear aligner patients. Invisalign is a treatment modality that can be considered for presurgical orthodontics-tooth movements involved in arch leveling and decompensation are highly accurate when comparing the simulated and the clinically achieved movements.},

keywords = {clear aligners, decomposition, ortho, orthodontic},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022e,

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

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

url = {https://pubmed.ncbi.nlm.nih.gov/36148645/},

doi = {10.4041/kjod21.180.r},

year  = {2022},

date = {2022-09-25},

urldate = {2022-09-25},

journal = {Korean J Orthod},

volume = {52},

issue = {5},

pages = {383-384},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022d,

title = {Quantitative bone imaging biomarkers and joint space analysis of the articular Fossa in temporomandibular joint osteoarthritis using artificial intelligence models},

author = {Mackie T and Al Turkestani N and Bianchi J and Li T and Ruellas A and Gurgel M and Benavides E and Soki F and Cevidanes L},

url = {https://www.frontiersin.org/articles/10.3389/fdmed.2022.1007011/full},

doi = {https://doi.org/10.3389/fdmed.2022.1007011},

year  = {2022},

date = {2022-09-19},

journal = {Frontiers in Dental Medicine},

abstract = {Temporomandibular joint osteoarthritis (TMJ OA) is a disease with a multifactorial etiology, involving many pathophysiological processes, and requiring comprehensive assessments to characterize progressive cartilage degradation, subchondral bone remodeling, and chronic pain. This study aimed to integrate quantitative biomarkers of bone texture and morphometry of the articular fossa and joint space to advance the role of imaging phenotypes for diagnosis of Temporomandibular Joint Osteoarthritis (TMJ OA) in early to moderate stages by improving the performance of machine-learning algorithms to detect TMJ OA status. Ninety-two patients were prospectively enrolled (184 h-CBCT scans of the right and left mandibular condyles), divided into two groups: 46 control and 46 TMJ OA subjects. No significant difference in the articular fossa radiomic biomarkers was found between TMJ OA and control patients. The superior condyle-to-fossa distance (p < 0.05) was significantly smaller in diseased patients. The interaction effects of the articular fossa radiomic biomarkers enhanced the performance of machine-learning algorithms to detect TMJ OA status. The LightGBM model achieved an AUC 0.842 to diagnose the TMJ OA status with Headaches and Range of Mouth Opening Without Pain ranked as top features, and top interactions of VE-cadherin in Serum and Angiogenin in Saliva, TGF-β1 in Saliva and Headaches, Gender and Muscle Soreness, PA1 in Saliva and Range of Mouth Opening Without Pain, Lateral Condyle Grey Level Non-Uniformity and Lateral Fossa Short Run Emphasis, TGF-β1 in Serum and Lateral Fossa Trabeculae number, MMP3 in Serum and VEGF in Serum, Headaches and Lateral Fossa Trabecular spacing, Headaches and PA1 in Saliva, and Headaches and BDNF in Saliva. Our preliminary results indicate that condyle imaging features may be more important in regards to main effects, but the fossa imaging features may have a larger contribution in terms of interaction effects. More studies are needed to optimize and further enhance machine-learning algorithms to detect early markers of disease, improve prediction of disease progression and severity to ultimately better serve clinical decision support systems in the treatment of patients with TMJ OA.},

keywords = {articular fossa, artificial intelligence, hr-CBCT, imaging biomarkers, joint space, temporomandibular osteoarthritis},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022,

title = {Comparison between human judge and automatic landmark identification on digital models},

author = {N Dolatabadi and R Boyd and H Oh and et al},

url = {https://pubmed.ncbi.nlm.nih.gov/35933158/},

doi = {10.1016/j.ajodo.2021.08.020},

year  = {2022},

date = {2022-08-00},

journal = {Am J Orthod Dentofacial Orthop},

pages = {257-263},

abstract = {Introduction: Accurate landmark identification is a prerequisite for accurate and reliable biomedical image analysis. Orthodontic study models are valuable tools for diagnosis, treatment planning, and maintaining complete records. The purpose of this study was to evaluate the reliability and validity of a software program (Align Technology, Inc) as a tool for automatic landmark location.



Methods: Using digital intraoral scans of 10 dental arches, 4 calibrated human judges independently located cusp tips and interproximal contacts. The same landmarks were automatically identified by the software. Intraclass correlation coefficient (Cronbach α), absolute mean errors, and regression analysis were calculated. In addition, Bland-Altman 95% confidence limits were also applied to the data to graphically display agreement on landmark identification between the human judges and the software.



Results: The intraclass correlation coefficient between the software and the human judges' average for the x-, y-, and z-coordinates for all landmarks was excellent, at 1.0, 1.0, and 0.98, respectively. The regression analysis and Bland-Altman plots show no systematic errors for agreement on landmark identification between the human judges and the software.



Conclusions: Landmark location was nearly identical between the software and the human judges, making the methods interchangeable.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022e,

title = {Osteoarthritis Diagnosis Integrating Whole Joint Radiomics and Clinical Features for Robust Learning Models using Biological Privileged Information},

author = {Al Turkestani N and Cai L and Cevidanes L and Bianchi J and Zhang W and Gurgel M and Gillot M and Baguero B and Najarian K and Soroushmehr R },

url = {https://www.researchsquare.com/article/rs-1840348/v1},

doi = {https://doi.org/10.21203/rs.3.rs-1840348/v1},

year  = {2022},

date = {2022-07-14},

journal = {Research Square},

abstract = {This paper proposes a machine learning model using privileged information (LUPI) and normalized mutual information feature selection method (NMIFS) to build a robust and accurate framework to diagnose patients with Temporomandibular Joint Osteoarthritis (TMJ OA). To build such a model, we employ clinical, quantitative imaging and additional biological markers as privileged information. We show that clinical features play a leading role in the TMJ OA diagnosis and quantitative imaging features, extracted from cone-beam computerized tomography (CBCT) scans, improve the model performance. As the proposed LUPI model employs biological data in the training phase (which boosted the model performance), this data is unnecessary for the testing stage, indicating the model can be widely used even when only clinical and imaging data are collected. The model was validated using 5-fold stratified cross-validation with hyperparameter tuning to avoid the bias of data splitting. Our method achieved an AUC, specificity and precision of 0.81, 0.79 and 0.77, respectively.},

keywords = {feature selection, machine learning, osteoarthritis, temporomandibular joint},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022b,

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

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

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

doi = {10.2319/122121-928.1},

year  = {2022},

date = {2022-06-02},

urldate = {2022-06-02},

journal = {Angle Orthodontist},

volume = {92},

pages = {642-654},

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



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



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



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

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

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022f,

title = {Effects of Long-term use of the Lower Lingual Arch from 8.5 years to 13.2 years},

author = {M Josse and R Boero and D Chambers and H Oh },

url = {https://pubmed.ncbi.nlm.nih.gov/34813658/},

doi = {10.2319/052221-408.1},

year  = {2022},

date = {2022-03-01},

journal = {Angle Orthodontist},

volume = {92},

issue = {2},

pages = {189-196},

abstract = {Objectives: To investigate the effects of long-term use of the lower lingual arch (LLA) on the sagittal and vertical positions of the permanent lower incisors and first molars.



Materials and methods: The sample consisted of 98 patients who were treated with an LLA (LLA group) and 39 patients who were treated without an LLA (no-LLA group). The positional changes of the lower incisors and first molars were analyzed after performing mandibular structural superimpositions on lateral cephalometric radiographs taken before treatment (T1) and at the end of LLA therapy (T2). The mean ages at T1 and T2 were 8.5 years and 13.2 years, respectively. Study casts were analyzed to quantify arch dimensional changes.



Results: Mesial movement of the lower molar cusp was similar between the LLA and no-LLA groups, but the vertical position was slightly greater at T2 in the LLA group. In the LLA group, there was a molar tip-back effect, and the lower incisors were proclined 4.2° more than in the no-LLA group. Arch perimeter decreased 3.6 ± 2.6 mm without an LLA and 0.97 ± 3.7 mm with an LLA. Intercanine and intermolar widths both increased about 1 mm more with an LLA (P < .0001).



Conclusions: The LLA does not seem to restrict mesial movement and vertical eruption of the lower incisors and molars in the long term. The LLA effectively preserves the arch perimeter at the expense of a slight lower incisor proclination.},

keywords = {arch perimeter, incisor proclination, Leeway space, Long-term, Lower lingual arch, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022d,

title = {Craniofacial growth and morphology among intersecting clinical categories},

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

url = {https://pubmed.ncbi.nlm.nih.gov/35076186/},

doi = {10.1002/ar.24870},

year  = {2022},

date = {2022-02-11},

journal = {Anatomical Record (Hoboken)},

abstract = {Differential patterns of craniofacial growth are important sources of variation that can result in skeletal malocclusion. Understanding the timing of growth milestones and morphological change associated with adult skeletal malocclusions is critical for developing individualized orthodontic growth modification strategies. To identify patterns in the timing and geometry of growth, we used Bayesian modeling of cephalometrics and geometric morphometric analyses with a dense, longitudinal sample consisting of 15,407 cephalograms from 1,913 individuals between 2 and 31 years of age. Individuals were classified into vertical facial types (hyper-, normo-, hypo-divergent) and anteroposterior (A-P) skeletal classes (Class I, Class II, Class III) based on adult mandibular plane angle and ANB angle, respectively. These classifications yielded eight facial type-skeletal class categories with sufficient sample sizes to be included in the study. Four linear cephalometrics representing facial heights and maxillary and mandibular lengths were fit to standard double logistic models generating type-class category-specific estimates for age, size, and rate of growth at growth milestones. Mean landmark configurations were compared among type-class categories at four time points between 6 and 20 years of age. Overall, morphology and growth patterns were more similar within vertical facial types than within A-P classes and variation among A-P classes typically nested within variation among vertical types. Further, type-class-associated variation in the rate and magnitude of growth in specific regions identified here may serve as targets for clinical treatment of complex vertical and A-P skeletal malocclusion and provide a clearer picture of the development of variation in craniofacial form.},

keywords = {cephalometrics, craniofacial growth, geometric morphometrics, growth modeling, malocclusion},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022g,

title = {Condylar degeneration in anterior open bite patients: A cone-beam computed tomography (CBCT) study.},

author = {L Phi and B Albertson and D Hatcher and S Rathi and J Park and H Oh },

url = {https://pubmed.ncbi.nlm.nih.gov/34503937/},

doi = {10.1016/j.oooo.2021.07.019},

year  = {2022},

date = {2022-02-01},

journal = {Oral Surgery Oral Med Oral Path Oral Radiology },

volume = {133},

issue = {2},

pages = {221-228},

abstract = {Objectives: The purpose of this study was to investigate the prevalence of condylar degeneration in patients with anterior open bites (AOB).



Study design: Cone beam computed tomography (CBCT) scans of 194 patients with AOB (108 with skeletal open bites and 86 with dental open bites) and 100 patients serving as controls were included in this retrospective study. Two oral and maxillofacial radiologists categorized each of the 588 condyles as normal, degenerative-active, or degenerative-repair. The χ2 analysis with Bonferroni adjustment was used to evaluate the relationship of condylar status (normal vs degenerative) to anterior open bites.



Results: Of the 103 degenerative condyles, there were 59 in the group with skeletal open bites, 14 in the group with dental open bites, and 30 in the control group. Condylar degeneration occurred twice as frequently in patients with skeletal open bites as it did in the control group (P < .0001). Conversely, a greater frequency of normal condyles was found in the group of patients with dental open bites (P = .0002). The group with skeletal open bites also showed a significantly higher frequency of bilateral degenerative condyles (P = .0001). The frequency of condylar degeneration did not differ significantly between female and male individuals.



Conclusions: Degenerative condylar change was significantly more likely in patients with skeletal open bites and less likely in patients with dental open bites.},

keywords = {anterior openbite, CBCT, condylar degeneration, Cone-beam computed tomography},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022f,

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

author = {Cong A and Massaro C and Ruellas A.C and de O and Barkley M and Yatabe M and Bianchi J and Ioshida M and Alvarez M.A and Aristizabal J.F and Rey D},

url = {https://pubmed.ncbi.nlm.nih.gov/33966340/},

doi = {10.1111/ocr.12489},

year  = {2022},

date = {2022-02-01},

journal = {Orthod Craniofac Res},

volume = {25},

issue = {1},

pages = {64-72},

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



Settings and sample population: Secondary data analysis of DDMs and CBCTs, taken before and after orthodontic treatment with piezocision of 24 patients.



Methods: Angular changes in tooth long axes were evaluated using landmarks on first molars (centre of the occlusal surface and centre of the furcation), canines and incisors (cusp tip and centre of the root at the cementoenamel junction). Wilcoxon test, intraclass correlation coefficient (ICC) and Bland-Altman plots were used to test intra- and inter-rater agreement and compare DDM and CBCT measurements.



Results: The mesiodistal angulation and buccolingual inclination DDM measurements were reproducible. Overall mean differences between DDM and CBCT measurements of mesiodistal angulation, 1.9°±1.5°, and buccolingual inclination, 2.2 ± 2.2°, were not significant for all teeth. ICC between DDM and CBCT measurements ranged from good (0.85 molars) to excellent (0.94 canines; 0.96 incisors). The percentages of measurements outside the range of ±5 were 17.4% for molars, 13.8% for canines and 4.5% for incisors.



Conclusions: DDM assessment of changes in tooth long axes has good reproducibility and yields comparable measurements to those obtained from CBCT within a 5° range. These findings lay the groundwork for machine learning approaches that synthesize crown and root canal information towards planning tooth movement without the need for ionizing radiation scans.},

keywords = {CBCT, Dental long axis, digital dental models},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022k,

title = {Prevalence of mandibular asymmetry in different skeletal sagittal patterns: A systematic review},

author = {Evangelista K and Teodoro A.B and Bianchi J and Cevidanes L.H.S and de Oliveria Ruellas A.C and Silva M.A.G and Valladares-Neto J},

url = {https://pubmed.ncbi.nlm.nih.gov/34546287/},

doi = {10.2319/040921-292.1},

year  = {2022},

date = {2022-01-01},

journal = {Angle Orthodontist},

volume = {92},

issue = {1},

pages = {118-126},

abstract = {Objectives: To analyze the prevalence of mandibular asymmetry in skeletal sagittal malocclusions.



Materials and methods: PubMed/MEDLINE, EMBASE, LILACS, Web of Science, Scopus, LIVIVO and gray literature (OpenGrey, ProQuest, and Google Scholar) were electronically searched. Two independent investigators selected the eligible studies, and assessed risk of bias and certainty of evidence (GRADE). One reviewer independently extracted the data and the second reviewer checked this information. Any disagreement between the reviewers in each phase was resolved by discussion between them and/or involved a third reviewer for final decision.



Results: Electronic search identified 5,132 studies, and 5 observational studies were included. Risk of bias was low in two studies, moderate in one, and high in two. The studies showed high heterogeneity. Mandibular asymmetry ranged from 17.43% to 72.95% in overall samples. Horizontal chin deviation showed a prevalence of 17.66% to 55.6% asymmetry in Class I malocclusions, and 68.98% in vertical asymmetry index. In Class II patients, prevalence of mandibular asymmetry varied from 10% to 25.5% in horizontal chin deviation, and 71.7% in vertical asymmetry index. The Class III sample showed a prevalence of mandibular asymmetry ranging from 22.93% to 78% in horizontal chin deviation and 80.4% in vertical asymmetry index. Patients seeking orthodontic or orthognathic surgery treatment showed greater prevalence of mandibular asymmetry.



Conclusions: Skeletal Class III malocclusion showed the greatest prevalence of mandibular asymmetry. Mandibular vertical asymmetry showed a marked prevalence in all malocclusions. However, conclusions should be interpreted with caution due to use of convenience samples and low-quality study outcomes.},

keywords = {Angle's malocclusion classification, asymmetry, mandible, prevalence, systematic review},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2022,

title = {Three-dimensional craniofacial characteristics associated with obstructive sleep apnea severity and treatment outcomes},

author = {Gurgel M and Cevidanes L and Pereira R and Costa F and Ruellas A and Bianchi J adn Cunali P and Bittencourt L and Junior C.C},

url = {https://pubmed.ncbi.nlm.nih.gov/34273012/},

doi = {10.1007/s00784-021-04066-5},

year  = {2022},

date = {2022-01-01},

journal = {Clinical Oral Investigations},

volume = {26},

issue = {1},

pages = {875-887},

abstract = {Objectives: This study aims to assess craniofacial dimensions in obstructive sleep apnea (OSA) patients treated with a mandibular advancement device (MAD) and to identify anatomic influences on OSA severity and MAD therapy outcomes.



Materials and methods: Twenty patients with OSA were prospectively treated with MAD. Clinical, cone-beam computed tomography, and polysomnography exams were performed before treatment and 4-6 months after achieving the MAD therapeutic position. Polysomnographic exams and three-dimensional maxillary, mandibular, and upper airway (UA) measurements were evaluated. Pearson's correlation and t-tests were applied.



Results: Before MAD treatment, the transverse width measured at the frontomaxillary suture and the angle between the mandibular ramus and Frankfurt horizontal were statistically correlated with apnea and the hypopnea index (AHI), while the gonial angle was correlated with therapeutic protrusion. After MAD treatment, all patients showed a significant AHI reduction and an improvement in minimum oxyhemoglobin saturation. The UA total volume, superior and inferior oropharynx volume, and area were statistically correlated with MAD therapeutic protrusion. The UA total area showed a statistical correlation with the improvement in AHI, and the superior oropharynx volume and area increased significantly.



Conclusions: The transversal frontomaxillary suture width and the mandibular ramus facial angle may influence OSA severity. The gonial angle, volume, and area of all UA regions may indicate the amount of protrusion needed for successful MAD treatment.



Clinical relevance: The craniofacial characteristics reported as important factors for OSA severity and MAD treatment outcomes impact therapy planning for OSA patients, considering individual anatomic characteristics, prognosis, and cost benefits.},

keywords = {Airway management, anatomy, Cone-beam computed tomography (CBCT), mandibular advancement device, obstructive, occlusal splints, sleep apnea},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2023i,

title = {Dentalmodelseg: Fully Automated Segmentation of Upper and Lower 3D Intra-Oral Surfaces.},

author = {Leclercq M and Ruellas A and Gurgel M and Yatabe M and Bianchi J and Cevidanes L and et al},

url = {https://www.semanticscholar.org/paper/FiboSeg%3A-Fully-automated-segmentation-of-upper-and-Leclercq-Ruellas/7269780afbd9c060e4509465f2b24d7fdbc35924},

year  = {2022},

date = {2022-01-01},

journal = {Semantic Scholar},

abstract = {In this paper, we present a deep learning based method for surface segmentation. This technique consists of acquiring 2D views and extracting features from the surface such as the normal vectors. The rendered images are analyzed with a 2D convolutional neural network, such as UNETs. We test our method in a dental application for segmentation of dental crowns. The neural network is trained for the multi-class segmentation, using image labels as ground truth. The segmentation task achieved an average Dice of 0.97, sensitivity of 0.97 and precision of 0.97.},

keywords = {bone segmentation, Deep Learning, dental crown, intra-oral surface, Universal label id},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022i,

title = {Geometric morphometric analysis of growth patterns among facial types},

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

url = {https://pubmed.ncbi.nlm.nih.gov/34175161/},

doi = {10.1016/j.ajodo.2020.04.038},

year  = {2021},

date = {2021-09-02},

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

volume = {160},

issue = {3},

pages = {430-441},

abstract = {Introduction: Extreme patterns of vertical facial divergence are of great importance to clinicians because of their association with dental malocclusion and functional problems of the orofacial complex. Understanding the growth patterns associated with vertical facial divergence is critical for clinicians to provide optimal treatment. This study evaluates and compares growth patterns from childhood to adulthood among 3 classifications of vertical facial divergence using longitudinal, lateral cephalograms from the Craniofacial Growth Consortium Study.



Methods: Participants (183 females, 188 males) were classified into 1 of 3 facial types on the basis of their adult mandibular plane angle (MPA): hyperdivergent (MPA >39°; n = 40), normodivergent (28° ≤ MPA ≤ 39°; n = 216), and hypodivergent (MPA <28°; n = 115). Each individual had 5 cephalograms between ages 6 and 20 years. A set of 36 cephalometric landmarks were digitized on each cephalogram. Landmark configurations were superimposed to align 5 homologous landmarks of the anterior cranial base and scaled to unit centroid size. Growth trajectories were calculated using multivariate regression for each facial type and sex combination.



Results: Divergent growth trajectories were identified among facial types, finding more similarities in normodivergent and hypodivergent growth patterns than either share with the hyperdivergent group. Through the use of geometric morphometric methods, new patterns of facial growth related to vertical facial divergence were identified. Hyperdivergent growth exhibits a downward rotation of the maxillomandibular complex relative to the anterior cranial base, in addition to the increased relative growth of the lower anterior face. Conversely, normodivergent and hypodivergent groups exhibit stable positioning of the maxilla relative to the anterior cranial base, with the forward rotation of the mandible. Furthermore, the hyperdivergent maxilla and mandible become relatively shorter and posteriorly positioned with age compared with the other groups.



Conclusions: This study demonstrates how hyperdivergent growth, particularly restricted growth and positioning of the maxilla, results in a higher potential risk for Class II malocclusion. Future work will investigate growth patterns within each classification of facial divergence.},

keywords = {craniofacial consortium study, craniofacial growth, facial types, geometric morphometrics, growth patterns},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022h,

title = {The Significance of Utilizing a Corticotomy on Periodontal and Orthodontic Outcomes: A Systematic Review and Meta-Analysis},

author = {Gao J and Nguyen T and Oberoi S and Oh H and Kapila S Kao RT and Lin GH},

url = {https://pubmed.ncbi.nlm.nih.gov/34440034/},

doi = {10.3390/biology10080803},

year  = {2021},

date = {2021-08-19},

urldate = {2022-08-19},

journal = {Biology (Basel)},

volume = {10},

issue = {8},

pages = {803},

abstract = {Purpose: This systematic review compares the clinical and radiographic outcomes for patients who received only a corticotomy or periodontal accelerated osteogenic orthodontics (PAOO) with those who received a conventional orthodontic treatment.



Methods: An electronic search of four databases and a hand search of peer-reviewed journals for relevant articles published in English between January 1980 and June 2021 were performed. Human clinical trials of ≥10 patients treated with a corticotomy or PAOO with radiographic and/or clinical outcomes were included. Meta-analyses were performed to analyze the weighted mean difference (WMD) and confidence interval (CI) for the recorded variables.



Results: Twelve articles were included in the quantitative analysis. The meta-analysis revealed a localized corticotomy distal to the canine can significantly increase canine distalization (WMD = 1.15 mm, 95% CI = 0.18-2.12 mm, p = 0.02) compared to a conventional orthodontic treatment. In addition, PAOO also showed a significant gain of buccal bone thickness (WMD = 0.43 mm, 95% CI = 0.09-0.78 mm, p = 0.01) and an improvement of bone density (WMD = 32.86, 95% CI = 11.83-53.89, p = 0.002) compared to the corticotomy group.



Conclusion: Based on the findings of the meta-analyses, the localized use of a corticotomy can significantly increase the amount of canine distalization during orthodontic treatment. Additionally, the use of a corticotomy as a part of a PAOO procedure significantly increases the rate of orthodontic tooth movement and it is accompanied by an increased buccal bone thickness and bone density compared to patients undergoing a conventional orthodontic treatment.},

keywords = {acceleration, bone remodeling, orthodontics, peridontics, tooth movement technique},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021b,

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

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

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

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

year  = {2021},

date = {2021-08-10},

urldate = {2021-08-10},

journal = {PLOS ONE},

volume = {16},

number = {8},

pages = {e0255937},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Condylar Degeneration in Anterior Open Bite Patients Acone Beam Computed Tomography Study},

url = {https://www.sciencedirect.com/science/article/pii/S2212440321005496},

doi = {https://doi.org/10.1016/j.oooo.2021.07.019},

year  = {2021},

date = {2021-07-31},

urldate = {2021-07-31},

journal = {Science Direct},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Knigge2020,

title = {Geometric morphometric analysis of growth patterns among facial types. },

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

url = {https://www.sciencedirect.com/science/article/pii/S0889540621003486?via%3Dihub},

doi = {10.1016/j.ajodo.2020.04.038},

year  = {2021},

date = {2021-06-23},

urldate = {2021-06-23},

journal = {Am J Orthod Dentofacial Orthop},

volume = {160},

number = {3},

pages = {430-441},

abstract = {Extreme patterns of vertical facial divergence are of great importance to clinicians because of their association with dental malocclusion and functional problems of the orofacial complex. Understanding the growth patterns associated with vertical facial divergence is critical for clinicians to provide optimal treatment. This study evaluates and compares growth patterns from childhood to adulthood among 3 classifications of vertical facial divergence using longitudinal, lateral cephalograms from the Craniofacial Growth Consortium Study.},

keywords = {Adolescents, anterior openbite, Cranial base, craniofacial, extraction, Mandibular fixed retainer, retrospective, vertical control},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021,

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

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

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

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

year  = {2021},

date = {2021-05-19},

urldate = {2021-05-19},

journal = {Seminars in Orthodontics},

volume = {27},

number = {2},

pages = {78-86},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Hardin2021,

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

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

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

doi = {10.1177/10556656211002675},

year  = {2021},

date = {2021-05-17},

urldate = {2021-05-17},

journal = {The Cleft Palate-Craniofacial Journal},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Turkestani2021,

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

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

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

doi = {10.1111/ocr.12492 },

year  = {2021},

date = {2021-05-11},

urldate = {2021-05-11},

journal = {Orthod Craniofac Res},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Cong2021,

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

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

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

doi = {10.1111/ocr.12489},

year  = {2021},

date = {2021-05-09},

urldate = {2021-05-09},

journal = {Orthod Cranifac Res},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Parizotto2021,

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

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

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

doi = {10.1111/ocr.12483},

year  = {2021},

date = {2021-03-13},

urldate = {2021-03-13},

journal = {Orthodontics & Craniofacial Research},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Boubolo2021,

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

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

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

doi = {10.1117/12.2582205},

year  = {2021},

date = {2021-02-15},

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

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Brosset2021,

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

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

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

doi = {10.1117/12.2582283},

year  = {2021},

date = {2021-02-14},

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

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022j,

title = {Estimating Craniofacial Growth Cessation: Comparison of Asymptote- and Rate-Based Methods. },

author = {Hardin AM and Knigge RP and Oh H},

url = {https://pubmed.ncbi.nlm.nih.gov/33998905/},

doi = {10.1177/10556656211002675},

year  = {2021},

date = {2021-02-01},

urldate = {2021-02-01},

journal = {Cleft Palate Craniofacial Journal },

volume = {59},

issue = {2},

pages = {230-238},

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



Design: This is a retrospective, longitudinal study. Five linear measurements were collected from lateral cephalograms as part of the Craniofacial Growth Consortium Study (CGCS). Four estimates of growth cessation, including 2 asymptote- (GCasym, GCerr) and 2 rate-based (GCabs, GC10%) methods, from double logistic models of craniofacial growth were compared.



Participants: Cephalometric data from participants in 6 historic longitudinal growth studies were included in the CGCS. At least 1749 individuals (870 females, 879 males), unaffected by craniofacial anomalies, were included in all analyses. Individuals were represented by a median of 11 images between 2.5 and 31.3 years of age.



Results: GCasym consistently occurred before GCerr and GCabs consistently occurred before GC10% within the rate-based approaches. The ordering of the asymptote-based methods compared to the rate-based methods was not consistent across measurements or between males and females. Across the 5 measurements, age at growth cessation ranged from 13.56 (females, nasion-basion, GCasym) to 24.39 (males, sella-gonion, GCerr).



Conclusions: Adolescent growth cessation is an important milestone for treatment planning. Based on our findings, we recommend careful consideration of specific definitions of growth cessation in both clinical and research settings since the most appropriate estimation method may differ according to patients' needs. The different methods presented here provide useful estimates of growth cessation that can be applied to raw data and to a variety of statistical models of craniofacial growth.},

keywords = {cephalometry, craniofacial growth, craniofacial morphology, facial growth},

pubstate = {published},

tppubtype = {article}

}

@article{Bianchi2021b,

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

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

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

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

year  = {2021},

date = {2021-02-00},

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

volume = {50},

number = {2},

pages = {227-235},

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

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

pubstate = {published},

tppubtype = {article}

}

@article{Parizotto2020,

title = {"Can palatal splint improve stability of segmental Le Fort I osteotomies?."},

author = {O L P Juliana and T B Karina and P P Adriano and J Bianchi and S C Daniel and R G Joao },

url = {https://pubmed.ncbi.nlm.nih.gov/32533749/},

doi = {10.1111/ocr.12399},

year  = {2020},

date = {2020-11-00},

urldate = {2020-11-00},

journal = {Orthodontics & Craniofacial Research},

volume = {23},

number = {4},

pages = {486-492},

abstract = {The purpose of this study was to evaluate the influence of a palatal splint on stability in multi-segment maxillary osteotomies.},

keywords = {le fort, Orthognathic Surgery, osteotomy, segmental Le Fort I Osteotomy, stability},

pubstate = {published},

tppubtype = {article}

}

@article{Sherwood2020,

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

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

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

doi = {10.1002/ar.24520},

year  = {2020},

date = {2020-10-04},

urldate = {2020-10-04},

journal = {American Association of Orthodontists Foundation},

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

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

pubstate = {published},

tppubtype = {article}

}