Correlations of spheno-occipital synchondrosis, cervical vertebrae, midpalatal suture, and third molar maturation stages.

Objectives: To estimate the joint correlations among cervical vertebrae maturation (CVM), spheno-occipital synchondrosis (SOS), midpalatal suture maturation (MPS), and third molar mineralization (TMM) and to assess the predictive potential of SOS on CVM and MPS.

Materials And Methods: 570 pretreatment cone-beam computed tomogram (CBCT) scans from three private practices were analyzed, and MPS, CVM, SOS, and TMM stages were categorized and recorded by two independent investigators. Intra- and inter-rater reliability tests were evaluated with weighted Cohen's kappa tests.

A fully automated classification of third molar development stages using deep learning.

Accurate classification of tooth development stages from orthopantomograms (OPG) is crucial for dental diagnosis, treatment planning, age assessment, and forensic applications. This study aims to develop an automated method for classifying third molar development stages using OPGs. Initially, our data consisted of 3422 OPG images, each classified and curated by expert evaluators.

Clinical evaluation of Artificial Intelligence Driven Remote Monitoring technology for assessment of patient oral hygiene during orthodontic treatment.

Introduction: This study aimed to clinically evaluate the accuracy of Dental Monitoring's (DM) artificial intelligence (AI) image analysis and oral hygiene notification algorithm in identifying oral hygiene and mucogingival conditions.

Methods: Twenty-four patients seeking orthodontic therapy were monitored by DM oral hygiene protocol during their orthodontic treatment. During the bonding appointment and at each of 10 subsequent adjustment visits, a total of 232 clinical oral examinations were performed to assess the presence of the 3 oral hygiene parameters that DM monitors.

Evaluation of upper airway characteristics in patients with and without sleep apnea using cone-beam computed tomography and computational fluid dynamics.

Objective: To determine if upper airway characteristics and airway pressure change significantly between low risk, healthy non-OSA subjects, and OSA subjects during respiration using cone-beam computed tomography (CBCT) imaging and steady-state k-ω model computational fluid dynamics (CFD) fluid flow simulations, respectively.

Materials And Methods: CBCT scans were collected at both end-inhalation and end-exhalation for 16 low-risk non-OSA subjects and compared to existing CBCT data from 7 OSA subjects. The CBCT images were imported into Dolphin Imaging and the upper airway was segmented into stereolithography (STL) files for area and volumetric measurements.

Call for algorithmic fairness to mitigate amplification of racial biases in artificial intelligence models used in orthodontics and craniofacial health.

Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of this narrative review is to provide an overview of how AI/ML models perpetuate racial biases and how we can mitigate this situation.

Novel Machine Learning Algorithms for Prediction of Treatment Decisions in Adult Patients With Class III Malocclusion.

Background: Management of Class III (Cl III) dentoskeletal phenotype is often expert-driven.

Purpose: The aim is to identify critical morphological features in postcircumpubertal Cl III treatment and appraise the predictive ability of innovative machine learning (ML) algorithms for adult Cl III malocclusion treatment planning.

Study Design: The Orthodontics Department at the University of Illinois Chicago undertook a retrospective cross-sectional study analyzing Cl III malocclusion cases (2003-2020) through dental records and pretreatment lateral cephalograms.

Robert M. Ricketts and Rudolf Slavicek: dentistry by the rules of nature.

The stomatognathic structures act as a complex and integrated system, thereby accomplishing several essential functions of the body. Aside from participating in food digestion, they are key for respiration and swallowing and play a central role in social interaction and stress management. The lifeworks of Robert M.

In-vivo evaluation of Artificial Intelligence Driven Remote Monitoring technology for tracking tooth movement and reconstruction of 3-dimensional digital models during orthodontic treatment.

Introduction: An in-vivo evaluation of the Dental Monitoring (DM; Paris, France) Artificial Intelligence Driven Remote Monitoring technology was conducted in an active clinical setting. Our objectives were to compare the accuracy and validity of the 3-dimensional (3D) digital models remotely generated from the DM application to 3D Digital Models generated from the iTero Element 5D intraoral scanner (Align Technologies, San Jose, Calif) of patients' dentition during in-vivo fixed orthodontic treatment.

Methods: The orthodontic treatment of 24 patients (aged 14-55 years) was tracked across an average of 13.

Effectiveness of AI-driven remote monitoring technology in improving oral hygiene during orthodontic treatment.

Objective: This study aimed to evaluate the effectiveness of Dental Monitoring™ (DM™) Artificial Intelligence Driven Remote Monitoring Technology (AIDRM) technology in improving the patient's oral hygiene during orthodontic treatment through AI-based personalized active notifications.

Methods: A prospective clinical study was conducted on two groups of orthodontic patients. DM Group: (n = 24) monitored by DM weekly scans and received personalized notifications on the DM smartphone application regarding their oral hygiene status.

Blockchain technology and federated machine learning for collaborative initiatives in orthodontics and craniofacial health.

There is a paucity of largescale collaborative initiatives in orthodontics and craniofacial health. Such nationally representative projects would yield findings that are generalizable. The lack of large-scale collaborative initiatives in the field of orthodontics creates a deficiency in study outcomes that can be applied to the population at large.

AggregateNet: A deep learning model for automated classification of cervical vertebrae maturation stages.

Objective: A study of supervised automated classification of the cervical vertebrae maturation (CVM) stages using deep learning (DL) network is presented. A parallel structured deep convolutional neural network (CNN) with a pre-processing layer that takes X-ray images and the age as the input is proposed.

Methods: A total of 1018 cephalometric radiographs were labelled and classified according to the CVM stages.

Cone-beam computed tomography assessment of maxillary anterior alveolar bone remodelling in extraction and non-extraction orthodontic cases using stable extra-alveolar reference.

Objective: To explore alveolar cortical positional change in response to tooth movement in extraction and non-extraction orthodontic cases, using cone-beam computed tomography (CBCT) and stable extra-alveolar references.

Materials And Methods: The pre-treatment (T1) and post-treatment (T2) CBCT scans of 25 extraction (EXT) and matched 25 non-extraction (Non-EXT) orthodontic cases were imported into Dolphin Imaging 3D, and oriented uniformly. Sagittal and axial CBCT cross-sections were traced using customized software-generated guides.

Fully automated determination of the cervical vertebrae maturation stages using deep learning with directional filters.

Introduction: We aim to apply deep learning to achieve fully automated detection and classification of the Cervical Vertebrae Maturation (CVM) stages. We propose an innovative custom-designed deep Convolutional Neural Network (CNN) with a built-in set of novel directional filters that highlight the edges of the Cervical Vertebrae in X-ray images.

Methods: A total of 1018 Cephalometric radiographs were labeled and classified according to the Cervical Vertebrae Maturation (CVM) stages.

Assessment of Handicapping Labio-Lingual Deviation index scoring methods and their effect on orthodontic treatment coverage by Medicaid.

Background: The purpose of this study was to assess the validity and reliability of Handicapping Labio-Lingual Deviation index (HLDI) scoring methods as calculated by digital models (DM) and visual inspection (VI) and their agreement to either meet or fail to meet the Medicaid coverage threshold. An additional objective was to assess the agreement with Medicaid managed care organizations (MCO) coverage decisions.

Methods: The study included the orthodontic records of 401 patients who applied for Medicaid coverage.

Alveolar cortical plate changes associated with incisor retraction and its influence on the limits of orthodontic tooth movement.

Objective: The extent to which the modelling behaviour of the anterior alveolus limits tooth movement remains unclear. Will the labial and lingual cortical plates model as incisors retract, or will they remain unchanged, therefore limiting the extent of possible tooth movement?

Setting And Sample Population: Pre- and post-treatment lateral cephalometric radiographs of 29 bimaxillary protrusive patients of South Korean descent were examined. Treatment consisted of two premolar extractions in one or both arches with en masse retraction of the incisors using miniscrew anchorage.

Improving the accuracy of publicly available search engines in recognizing and classifying dental visual assets using convolutional neural networks.

Aim: To assess the accuracy of DigiBrain4, Inc (DB4) Dental Classifier and DB4 Smart Search Engine* in recognizing, categorizing, and classifying dental visual assets as compared with Google Search Engine, one of the largest publicly available search engines and the largest data repository.

Materials And Methods: Dental visual assets were collected and labeled according to type, category, class, and modifiers. These dental visual assets contained radiographs and clinical images of patients' teeth and occlusion from different angles of view.

Digital Workflow for Combined Orthodontics and Orthognathic Surgery.

This article provides an overview of the digital workflow process for Combined orthodontics and Orthognathic surgery treatment starting from data acquisition (3-dimensional scanning, cone-beam computed tomography), data preparation, processing and Creation of a three-dimensional virtual augmented model of the head. Establishing a Proper Diagnosis and Quantification of the Dentofacial Deformity using 3D diagnostic model. Furthermore, performance of 3-dimensional Virtual orthognathic surgical treatment, and the construction of a surgical splint (via 3-dimensional printing) to allow transfer of the treatment plan to the actual patient during surgery.

Temporary Skeletal Anchorage Techniques.

As orthodontic treatment has advanced in complexity and in frequency, more recent techniques, using temporary skeletal anchorage, were developed to help correct more severe occlusal and dentofacial discrepancies that were treated with orthognathic surgery alone previously. These techniques have allowed the orthodontist to move teeth against a rigid fixation, allowing for more focused movements of teeth and for orthopedic growth modification. These types of treatments using rigid fixation have allowed for greater interaction between the orthodontist and the oral and maxillofacial surgeon, and have vastly enhanced the treatment planning for the orthodontist in today's society.

Accuracy of Dental Monitoring 3D digital dental models using photograph and video mode.

Introduction: This study aimed to test the accuracy of the 3-dimensional (3D) digital dental models generated by the Dental Monitoring (DM) smartphone application in both photograph and video modes over successive DM examinations in comparison with 3D digital dental models generated by the iTero Element intraoral scanner.

Methods: Ten typodonts with setups of class I malocclusion and comparable severity of anterior crowding were used in the study. iTero Element scans along with DM examination in photograph and video modes were performed before tooth movement and after each set of 10 Invisalign aligners for each typodont.

Three-dimensional assessment of soft tissue changes associated with bone-anchored maxillary protraction protocols.

Introduction: The aim of this study was to assess the 3-dimensional soft tissue changes in growing Class III patients with maxillary deficiency associated with 2 bone-anchored maxillary protraction protocols in relation to an untreated control group of Class III patients.

Methods: Growing skeletal Class III patients between the ages of 10 and 14 years participated in this study. In group 1 (n = 10), skeletally anchored facemasks were used with miniplates placed at the zygomatic buttress.

Dentoalveolar and arch dimension changes in patients treated with miniplate-anchored maxillary protraction.

Introduction: The aim of this study was to evaluate dentoalveolar and arch dimension changes in 2 miniplate-anchored maxillary protraction protocols in relation to an untreated control group using 3-dimensional digital models.

Methods: Thirty growing Class III subjects with maxillary deficiency in the late mixed or early permanent dentition phase were randomly divided into 3 groups. In group 1 (n = 10), patients were treated with skeletally anchored facemasks anchored with miniplates placed at the zygomatic buttress.

Comparative evaluation of 2 skeletally anchored maxillary protraction protocols.

Introduction: The aim of this study was to evaluate and compare the effects of 2 protocols of bone-anchored maxillary protraction with an untreated control group.

Methods: Thirty growing Class III subjects with maxillary deficiency in the late mixed or early permanent dentition were included in the study. In group 1 (n = 10), skeletally anchored facemasks were used with miniplates placed at the zygomatic buttress.