Maxillary protraction anchored on miniplates versus miniscrews: three-dimensional dentoskeletal comparison.

Objective: This retrospective study aimed to compare the three-dimensional (3D) outcomes of the novel miniscrew-anchored maxillary protraction (MAMP) therapy and the bone-anchored maxillary protraction (BAMP) therapy.

Methods: The sample comprised growing patients with skeletal Class III malocclusion treated with two skeletal anchored maxillary protraction protocols. The MAMP group comprised 22 patients (9 female, 13 male; 10.

Automated Orientation and Registration of Cone-Beam Computed Tomography Scans.

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 <2mm of angular and linear errors when compared to expert clinicians).

ShapeAXI: Shape Analysis Explainability and Interpretability.

ShapeAXI represents a cutting-edge framework for shape analysis that leverages a multi-view approach, capturing 3D objects from diverse viewpoints and subsequently analyzing them via 2D Convolutional Neural Networks (CNNs). We implement an automatic N-fold cross-validation process and aggregate the results across all folds. This ensures insightful explainability heat-maps for each class across every shape, enhancing interpretability and contributing to a more nuanced understanding of the underlying phenomena.

DENTALMODELSEG: FULLY AUTOMATED SEGMENTATION OF UPPER AND LOWER 3D INTRA-ORAL SURFACES.

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 a UNET.

Automated artificial intelligence-based three-dimensional comparison of orthodontic treatment outcomes with and without piezocision surgery.

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.

Asymmetry in Class II subdivision malocclusion: Assessment based on 3D surface models.

Introduction: There is currently no consensus in the literature whether the aetiology of a Class II subdivision is dental, skeletal or both. The aim of this study was to identify and quantify skeletal and dental asymmetries in Class II subdivision malocclusions.

Methods: CBCTs from 33 Class II subdivision malocclusion patients were used to construct 3D volumetric label maps.

Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate.

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.

Clear aligner mandibular advancement in growing patients with Class II malocclusion.

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 changes after maxillary molar distalization with a miniscrew-anchored cantilever.

Objectives: To evaluate the changes after maxillary molar distalization in Class II malocclusion using the miniscrew-anchored cantilever with an extension arm.

Materials And Methods: The sample included 20 patients (9 male, 11 female; mean age 13.21 ± 1.

Automatic landmark identification in cone-beam computed tomography.

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.

Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR.

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.

Presurgical orthodontic decompensation with clear aligners.

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.

Three-dimensional dentoalveolar changes in open bite treatment in mixed dentition, spurs/posterior build-ups versus spurs alone: 1-year follow-up randomized clinical trial.

This randomized clinical trial aimed to compare the three-dimensional dentoalveolar maxillary changes after anterior open bite treatment with bonded spurs and build-ups versus bonded spurs alone. Patients from 7 to 11 years of age with anterior open bite were randomly allocated into two groups. Bonded spurs and posterior build-ups were used in the experimental group and only bonded spurs were used in the comparison group.

Three-dimensional comparison of bone-borne and tooth-bone-borne maxillary expansion in young adults with maxillary skeletal deficiency.

Objective: To compare the transverse dental and skeletal changes in patients treated with bone-anchored palatal expander (bone-borne, BB) compared to patients treated with tooth and bone-anchored palatal expanders (tooth-bone-borne, TBB) using cone-beam computer tomography (CBCT) and 3D image analysis.

Methods: The sample comprised 30 patients with transverse maxillary discrepancy treated with two different types of appliances: bone-borne (Group BB) and tooth-bone-borne (Group TBB) expanders. CBCT scans were acquired before (T1) and after completion of maxillary expansion (T2); the interval was 5.

Interdisciplinary dental management of patient with oligodontia and maxillary hypoplasia: a case report.

Background: The craniofacial developmental abnormality can significantly complicate the oral rehabilitation of patients with oligodontia. This case report describes an interdisciplinary approach that took 7 years to successfully treat a young patient with non-syndromic oligodontia and midface deficiency.

Case Presentation: A 14-year-old patient with complex oral and maxillofacial conditions and diagnosis of oligodontia presented to our clinic.

Three-dimensional evaluation of skeletal and dental effects of treatment with maxillary skeletal expansion.

Introduction: The objective was to determine the skeletal and dental changes with microimplant assisted rapid palatal expansion (MARPE) appliances in growing (GR) and nongrowing (NG) patients using cone-beam computed tomography and 3-dimensional imaging analysis.

Methods: The sample consisted of 25 patients with transverse maxillary discrepancy treated with a maxillary skeletal expander, a type of MARPE appliance. Cone-beam computed tomography scans were taken before and after maxillary expansion; the interval was 6.

Automatic Segmentation of Dental Root Canal and Merging with Crown Shape.

In this paper, machine learning approaches are proposed to support dental researchers and clinicians to study the shape and position of dental crowns and roots, by implementing a Patient Specific Classification and Prediction tool that includes RootCanalSeg and DentalModelSeg algorithms and then merges the output of these tools for intraoral scanning and volumetric dental imaging. RootCanalSeg combines image processing and machine learning approaches to automatically segment the root canals of the lower and upper jaws from large datasets, providing clinical information on tooth long axis for orthodontics, endodontics, prosthodontic and restorative dentistry procedures. DentalModelSeg includes segmenting the teeth from the crown shape to provide clinical information on each individual tooth.

Temporomandibular Joint Osteoarthritis Diagnosis Using Privileged Learning of Protein Markers.

Diagnosis of temporomandibular joint (TMJ) Osteoarthritis (OA) before serious degradation of cartilage and subchondral bone occurs can help prevent chronic pain and disability. Clinical, radiomic, and protein markers collected from TMJ OA patients have been shown to be predictive of OA onset. Since protein data can often be unavailable for clinical diagnosis, we harnessed the learning using privileged information (LUPI) paradigm to make use of protein markers only during classifier training.

Radiographic interpretation using high-resolution Cbct to diagnose degenerative temporomandibular joint disease.

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.

Decision Support Systems in Temporomandibular Joint Osteoarthritis: A review of Data Science and Artificial Intelligence Applications.

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.