Accuracy of posteroanterior cephalogram landmarks and measurements identification using a cascaded convolutional neural network algorithm: A multicenter study.

Objective: : To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN).

Methods: : A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me).

Orthognathic surgical planning using graph CNN with dual embedding module: External validations with multi-hospital datasets.

Background And Objective: Despite recent development of AI, prediction of the surgical movement in the maxilla and mandible by OGS might be more difficult than that of tooth movement by orthodontic treatment. To evaluate the prediction accuracy of the surgical movement using pairs of pre-(T0) and post-surgical (T1) lateral cephalograms (lat-ceph) of orthognathic surgery (OGS) patients and dual embedding module-graph convolution neural network (DEM-GCNN) model.

Methods: 599 pairs from 3 institutions were used as training, internal validation, and internal test sets and 201 pairs from other 6 institutions were used as external test set.

The prediction of sagittal chin point relapse following two-jaw surgery using machine learning.

The study aimed to identify critical factors associated with the surgical stability of pogonion (Pog) by applying machine learning (ML) to predict relapse following two-jaw orthognathic surgery (2 J-OGJ). The sample set comprised 227 patients (110 males and 117 females, 207 training and 20 test sets). Using lateral cephalograms taken at the initial evaluation (T0), pretreatment (T1), after (T2) 2 J-OGS, and post treatment (T3), 55 linear and angular skeletal and dental surgical movements (T2-T1) were measured.

Accuracy and clinical validity of automated cephalometric analysis using convolutional neural networks.

Background: This study aimed to assess the error range of cephalometric measurements based on the landmarks detected using cascaded CNNs and determine how horizontal and vertical positional errors of individual landmarks affect lateral cephalometric measurements.

Methods: In total, 120 lateral cephalograms were obtained consecutively from patients (mean age, 32.5 ± 11.

Fully automated condyle segmentation using 3D convolutional neural networks.

The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy. 234 cone-beam computed tomography images of mandibular condyles were acquired from 117 subjects from two institutions, which were manually segmented to generate the ground truth. Semantic segmentation was performed using basic 3D U-Net and a cascaded 3D U-Net.

Accuracy of artificial intelligence-assisted landmark identification in serial lateral cephalograms of Class III patients who underwent orthodontic treatment and two-jaw orthognathic surgery.

Objective: To investigate the pattern of accuracy change in artificial intelligence-assisted landmark identification (LI) using a convolutional neural network (CNN) algorithm in serial lateral cephalograms (Lat-cephs) of Class III (C-III) patients who underwent two-jaw orthognathic surgery.

Methods: A total of 3,188 Lat-cephs of C-III patients were allocated into the training and validation sets (3,004 Lat-cephs of 751 patients) and test set (184 Lat-cephs of 46 patients; subdivided into the genioplasty and non-genioplasty groups, n = 23 per group) for LI. Each C-III patient in the test set had four Lat-cephs: initial (T0), pre-surgery (T1, presence of orthodontic brackets [OBs]), post-surgery (T2, presence of OBs and surgical plates and screws [S-PS]), and debonding (T3, presence of S-PS and fixed retainers [FR]).

Vertical bony step between proximal and distal segments after mandibular setback is related with relapse: A cone-beam computed tomographic study.

Introduction: Vertical bony step (VBS) occurs between proximal and distal segments of the mandible during mandibular setback surgery with bilateral sagittal split ramus osteotomy. The purpose of this study was to investigate whether VBS is correlated with the relapse of mandibular setback using 3-dimensional models constructed from cone-beam computed tomography.

Methods: The subjects consisted of 30 patients who underwent bilateral sagittal split ramus osteotomy for a mandibular setback.

Accuracy of auto-identification of the posteroanterior cephalometric landmarks using cascade convolution neural network algorithm and cephalometric images of different quality from nationwide multiple centers.

Introduction: The purpose of this study was to evaluate the accuracy of auto-identification of the posteroanterior (PA) cephalometric landmarks using the cascade convolution neural network (CNN) algorithm and PA cephalogram images of a different quality from nationwide multiple centers nationwide.

Methods: Of the 2798 PA cephalograms from 9 university hospitals, 2418 images (2075 training set and 343 validation set) were used to train the CNN algorithm for auto-identification of 16 PA cephalometric landmarks. Subsequently, 99 pretreatment images from the remaining 380 test set images were used to evaluate the accuracy of auto-identification of the CNN algorithm by comparing with the identification by a human examiner (gold standard) using V-Ceph 8.

Comparison of one-jaw and two-jaw orthognathic surgery in patients with skeletal Class III malocclusion using data from 10 multi-centers in Korea: Part I. Demographic and skeletodental characteristics.

Objective: To investigate demographic and skeletodental characteristics of one-jaw (1J-OGS) and two-jaw orthognathic surgery (2J-OGS) in patients with skeletal Class III malocclusion.

Methods: 750 skeletal Class III patients who underwent OGS at 10 university hospitals in Korea between 2015 and 2019 were investigated; after dividing them into the 1J-OGS (n = 186) and 2J-OGS groups (n = 564), demographic and skeletodental characteristics were statistically analyzed.

Results: 2J-OGS was more frequently performed than 1J-OGS (75.

Accuracy of one-step automated orthodontic diagnosis model using a convolutional neural network and lateral cephalogram images with different qualities obtained from nationwide multi-hospitals.

Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals.

Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard.

Projected lifetime cancer risk from cone-beam computed tomography for orthodontic treatment.

Objective: To estimate the projected cancer risk attributable to diagnostic cone-beam computed tomography (CBCT) performed under different exposure settings for orthodontic purposes in children and adults.

Methods: We collected a list of CBCT machines and their specifications from 38 orthodontists. Organ doses were estimated using median and maximum exposure settings of 105 kVp/156.

Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi-centres.

Objective: To investigate the accuracy of automated identification of cephalometric landmarks using the cascade convolutional neural networks (CNN) on lateral cephalograms acquired from nationwide multi-centres.

Settings And Sample Population: A total of 3150 lateral cephalograms were acquired from 10 university hospitals in South Korea for training.

Materials And Methods: We evaluated the accuracy of the developed model with independent 100 lateral cephalograms as an external validation.

Nonsurgical correction of a Class III skeletal anterior open-bite malocclusion using multiple microscrew implants and digital profile prediction.

A 20-year-old woman had a severe anterior skeletal open bite and a moderate skeletal Class III relationship with a prognathic mandible and a straight profile. She declined surgery. However, molar intrusion in a Class III patient with a straight profile can cause forward mandibular rotation and deterioration of the profile to a concave pattern.

Finite-element analysis of the center of resistance of the mandibular dentition.

Objective: The aim of this study was to investigate the three-dimensional (3D) position of the center of resistance of 4 mandibular anterior teeth, 6 mandibular anterior teeth, and the complete mandibular dentition by using 3D finite-element analysis.

Methods: Finite-element models included the complete mandibular dentition, periodontal ligament, and alveolar bone. The crowns of teeth in each group were fixed with buccal and lingual arch wires and lingual splint wires to minimize individual tooth movement and to evenly disperse the forces onto the teeth.

The effects of alveolar bone loss and miniscrew position on initial tooth displacement during intrusion of the maxillary anterior teeth: Finite element analysis.

Objective: The aim of this study was to determine the optimal loading conditions for pure intrusion of the six maxillary anterior teeth with miniscrews according to alveolar bone loss.

Methods: A three-dimensional finite element model was created for a segment of the six anterior teeth, and the positions of the miniscrews and hooks were varied after setting the alveolar bone loss to 0, 2, or 4 mm. Under 100 g of intrusive force, initial displacement of the individual teeth in three directions and the degree of labial tilting were measured.

Finite element analysis of maxillary incisor displacement during en-masse retraction according to orthodontic mini-implant position.

Objective: Orthodontic mini-implants (OMI) generate various horizontal and vertical force vectors and moments according to their insertion positions. This study aimed to help select ideal biomechanics during maxillary incisor retraction by varying the length in the anterior retraction hook (ARH) and OMI position.

Methods: Two extraction models were constructed to analyze the three-dimentional finite element: a first premolar extraction model (Model 1, M1) and a residual 1-mm space post-extraction model (Model 2, M2).

Stress distributions in peri-miniscrew areas from cylindrical and tapered miniscrews inserted at different angles.

Objective: The purpose of this study was to analyze stress distributions in the roots, periodontal ligaments (PDLs), and bones around cylindrical and tapered miniscrews inserted at different angles using a finite element analysis.

Methods: We created a three-dimensional (3D) maxilla model of a dentition with extracted first premolars and used 2 types of miniscrews (tapered and cylindrical) with 1.45-mm diameters and 8-mm lengths.

Torque control during lingual anterior retraction without posterior appliances.

Objective: To evaluate the factors that affect torque control during anterior retraction when utilizing the C-retractor with a palatal miniplate as an exclusive source of anchorage without posterior appliances.

Methods: The C-retractor was modeled using a 3-dimensional beam element (0.9-mm-diameter stainless-steel wire) attached to mesh bonding pads.

Three-dimensional finite element analysis of the deformation of the human mandible: a preliminary study from the perspective of orthodontic mini-implant stability.

Objective: The aims of this study were to investigate mandibular deformation under clenching and to estimate its effect on the stability of orthodontic mini-implants (OMI).

Methods: Three finite element models were constructed using computed tomography (CT) images of 3 adults with different mandibular plane angles (A, low; B, average; and C, high). An OMI was placed between #45 and #46 in each model.

Comparison of tooth displacement between buccal mini-implants and palatal plate anchorage for molar distalization: a finite element study.

The purposes of this study were to mechanically evaluate distalization modalities through the application of skeletal anchorage using finite element analysis. Base models were constructed from commercial teeth models. A finite element model was created and three treatment modalities were modified to make 10 models.

Factors controlling anterior torque during C-implant-dependent en-masse retraction without posterior appliances.

Introduction: Our objective was to evaluate the factors that affect effective torque control during en-masse incisor and canine retraction when using partially osseointegrated C-implants (Cimplant, Seoul, Korea) as the exclusive source of anchorage without posterior bonded or banded appliances.

Methods: Base models were constructed from a dental study model. No brackets or bands were placed on the maxillary posterior dentition during retraction.

Factors controlling anterior torque with C-implants depend on en-masse retraction without posterior appliances: biocreative therapy type II technique.

Introduction: Our objective was to evaluate the factors that affect effective torque control during en-masse anterior retraction by using intrusion overlay archwire and partially osseointegrated C-implants as the exclusive sources of anchorage without posterior bonded or banded attachments.

Methods: Base models were constructed from a dental study model. No brackets or bands were placed on the posterior maxillary dentition during retraction.

Nell-1, a key functional mediator of Runx2, partially rescues calvarial defects in Runx2(+/-) mice.

Mesenchymal stem cell commitment to an osteoprogenitor lineage requires the activity of Runx2, a molecule implicated in the etiopathology of multiple congenital craniofacial anomalies. Through promoter analyses, we have recently identified a new direct transcriptional target of Runx2, Nell-1, a craniosynostosis (CS)-associated molecule with potent osteogenic properties. This study investigated the mechanistic and functional relationship between Nell-1 and Runx2 in regulating osteoblast differentiation.