Understanding the genetic basis of medication-related osteonecrosis of the jaw: A systematic review.

Medication-related osteonecrosis of the jaw (MRONJ) is an adverse event often associated with the use of antiresorptive drugs. This systematic review aims to identify genes and their polymorphisms associated with the risk of developing MRONJ in patients with oncological or skeletal-related diseases treated with antiresorptive drugs. A systematic literature review was conducted in accordance with PRISMA guidelines.

A systematic review on volumetric analysis in orbital MRI.

Aim: Volumetric analysis of orbital soft tissues using magnetic resonance imaging (MRI) offers valuable diagnostic and pathophysiological insights into orbital inflammation, trauma, and tumors. However, the optimal MRI protocols and post-processing methods for specific conditions remain unclear.

Methods: A systematic search was performed in PubMed/MEDLINE, Web of Science, and Cochrane Library for all studies published before November 2024.

Multifunctional nanoparticles in endodontics: applications, challenges, and future directions.

Nanoparticles are emerging as transformative agents in endodontics, addressing challenges in treating the dentin-pulp complex. This scoping review aims to explore multifunctional applications of nanoparticles in endodontics, with a focus on their roles in promoting tissue regeneration through therapeutic effects, enhancing material properties, and serving a carrier function. Following PRISMA-Scoping Review guidelines, a comprehensive literature search was conducted across Web of Science, PubMed, and Scopus.

Summary of the Veterans Health Administration's First International Symposium on Artificial Intelligence in Dentistry.

Background: The Veterans Health Administration's First International Symposium on Artificial Intelligence in Dentistry, held virtually on October 11, 2024, marked a step toward improving oral health care for veterans through the adoption of cutting-edge artificial intelligence (AI) technologies. AI offers the potential to transform dental diagnostics, treatment planning, and care delivery; however, its clinical application in dentistry remains limited. The symposium addressed this gap by means of highlighting innovations and implementation strategies to help clinicians prepare for the technological changes reshaping oral health care.

Clear aligner therapy for minimally invasive dentistry: A scoping review.

Objective: To conduct a scoping review on the current applications of clear aligner therapy (CAT) in minimally invasive restorative and esthetic dentistry, and to explore available software for pre-restorative and esthetic CAT treatments.

Data And Sources: A systematic electronic literature search was performed in PubMed, Embase, Web of Science, Cochrane Library, and Scopus, alongside grey literature up to May 2024. Studies on CAT were included based on independent evaluation by two reviewers.

SealPrint: The anatomically replicated seal-and-support socket abutment technique A Proof-of-Concept with 12 months of follow-up.

Objectives: This study aimed at investigating a novel technique for designing and manufacturing a sealing socket abutment (SSA) using artificial intelligence (AI)-driven tooth segmentation and 3D printing technologies.

Methods: A validated AI-powered module was used to segment the tooth to be replaced on the presurgical Cone Beam Computed Tomography (CBCT) scan. Following virtual surgical planning, the CBCT and intraoral scan (IOS) were imported into Mimics software.

Rethinking Ameloblastic Fibroma and Fibro-odontoma: A Serie of 6 Cases and Reclassification Proposal.

Purpose: The classification of mixed odontogenic tumors-specifically ameloblastic fibroma (AF), ameloblastic fibro-odontoma (AFO), and odontoma-remains controversial. The current WHO classification emphasizes the presence of dental hard tissues but overlooks the distinction between aberrant inductive activity and maturation resembling normal odontogenesis. This has led to diagnostic ambiguity and inconsistent management strategies.

Comparison of AI-Powered Tools for CBCT-Based Mandibular Incisive Canal Segmentation: A Validation Study.

Objective: Identification of the mandibular incisive canal (MIC) prior to anterior implant placement is often challenging. The present study aimed to validate an enhanced artificial intelligence (AI)-driven model dedicated to automated segmentation of MIC on cone beam computed tomography (CBCT) scans and to compare its accuracy and time efficiency with simultaneous segmentation of both mandibular canal (MC) and MIC by either human experts or a previously trained AI model.

Materials And Methods: An enhanced AI model was developed based on 100 CBCT scans using expert-optimized MIC segmentation within the Virtual Patient Creator platform.

Three-Dimensional Facial Imaging: A Comparative Assessment of the Clinical Applicability of State-of-the-Art Technologies for Three-Dimensional Facial Imaging.

To compare the clinical applicability in terms of observer perception, patient perception, and clinical usability of stereophotogrammetry (SPG) and both static and portable structured light (SL) three-dimensional (3D) face scanners. This comparison was based on the perception of medical observers, nonmedical observers, and patients themselves, using two-dimensional (2D) photographs as clinical reference. Facial images of 20 patients (12 females and eight males) were obtained using a professional camera (clinical reference) and three facial scanners: Vectra H1 (SPG), RAYFace RFS200 (static SL), and iReal 2E (portable SL).

Cone beam computed tomography in dentistry: Clinical recommendations and indication-specific features.

Objectives: To provide a narrative overview of commercially available CBCT devices, highlight the wide range of technical features and their impact on image quality and diagnostic performance, and develop decision support charts to guide clinicians in selecting appropriate CBCT parameters for different dental specialties.

Data And Sources: Data collection involved reviewing published articles on CBCT devices and accessing manufacturer websites. Additional manufacturers were identified through a literature search and by attending scientific and commercial events held in 2023 and 2024.

Dose Reduction by Field of View Optimisation in Cone-Beam Computed Tomography of Unilateral Alveolar Clefts.

Objective: This study aimed to investigate how much the field of view (FOV) can be decreased while still depicting the necessary anatomical structures. A secondary aim was to assess how many incidental findings were missed with a reduced FOV.

Material And Methods: In this retrospective study, 170 CBCT volumes from children with a mean age of 9.

Long-term three-dimensional skeletal effects of hybrid hyrax with facemask versus mentoplate in growing Class III patients: a randomized controlled trial.

Background: Early intervention in Class III malocclusion aims to prevent the need for surgery in adulthood by enhancing upper jaw growth while limiting lower jaw development. Although traditional facemask treatment remain common, bone-anchored devices are increasingly used, claiming better skeletal control and patient compliance. However, strong evidence supporting these advantages is limited.

The proteome of osteoblasts in a 3D culture perfusion bioreactor model compared with static conditions.

Bone disorders represent a significant global burden. Currently, animal models are used to develop and screen novel treatments. However, interspecies variations and ethical concerns highlight the need for a more complex 3D bone model.

Automated orofacial virtual patient creation using two cohorts of MSCT vs. CBCT scans.

Background: Virtual simulation has advanced in dental healthcare, but the impact of different tomographic techniques on virtual patient (VP) creation remains unclear. This study primarily aimed to automatically create VP from facial scans (FS), intraoral scans (IOS), multislice (MSCT), and cone beam computed tomography (CBCT); Secondarily, to quantitatively compare artificial intelligence (AI)-driven, AI-refined and semi automatically registered (SAR) VP creation from MSCT and CBCT and to compare the effect of soft tissue on the registration with MSCT and CBCT.

Methods: A dataset of 20 FS, IOS, and (MS/CB)CT scans was imported into the Virtual Patient Creator platform to generate automated VPs.

Long-term comparison of maxillary protraction with hybrid hyrax-facemask vs. hybrid hyrax-mentoplate protocols using Alt-RAMEC: a 5-year randomized controlled trial.

Background: The study aimed to compare the short- and long-term effectiveness of hybrid Hyrax (HH) -Facemask (FM) and HH-mentoplate (MP) treatment protocols for maxillary protraction using Alt-RAMEC.

Methods: A single-center 2-arm parallel randomized controlled trial. Participants: 28 skeletal class III patients (female: 14, male: 14; average age: 9.

Automated classification of panoramic radiographs with inflammatory periapical lesions using a CNN-LSTM architecture.

Objectives: Considering Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network approaches have shown promising image classification performance, the aim of this study was to compare the performance of novel Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) architectures with a classic CNN for classification of panoramic radiographs with inflammatory periapical lesions.

Methods: A dataset of 356 panoramic radiographs with periapical lesions and 769 control images were retrospectively collected and divided into training, validation, and testing sets. Next, four different models were constructed: a classic CNN, a classic LSTM, a cascaded CNN-LSTM, and parallel CNN-LSTM architecture.

Artificial Intelligence Versus Human Intelligence in Presurgical Implant Planning: A Preclinical Validation.

Objectives: To validate an innovative artificial intelligence (AI)-driven tool for automated virtual implant placement by comparing its accuracy, implant dimension selection, time efficiency, and consistency with a human intelligence (HI)-based approach for single posterior tooth replacement.

Materials And Methods: A dataset of 50 time-matched cone-beam computed tomography and intraoral scans with a single missing posterior mandibular tooth was selected to validate a pre-trained AI model for virtual implant placement against a HI-based approach. A quantitative comparison of implant location and implant dimension selection was conducted between AI and HI, and a qualitative three-dimensional evaluation was conducted by three implant dentistry specialists using a visual analog scale and a Turing test to assess and distinguish between AI and HI.

Demonstration of virtual imaging trial applications for optimization and education of dento-maxillofacial CBCT imaging.

Background: A number of studies have suggested that there is a need for improved understanding of dento-maxillofacial cone beam computed tomography (CBCT) technology, and to establish optimized imaging protocols. While several ex vivo/in vitro studies, along with a few in vivo studies, have addressed this topic, virtual imaging trials could form a powerful alternative but have not yet been introduced within the field of dento-maxillofacial imaging.

Purpose: To introduce and illustrate the potential of utilizing a virtual imaging trial (VIT) platform for dento-maxillofacial CBCT imaging through a number of case studies.

An AI-based tool for prosthetic crown segmentation serving automated intraoral scan-to-CBCT registration in challenging high artifact scenarios.

Statement Of Problem: Accurately registering intraoral and cone beam computed tomography (CBCT) scans in patients with metal artifacts poses a significant challenge. Whether a cloud-based platform trained for artificial intelligence (AI)-driven segmentation can improve registration is unclear.

Purpose: The purpose of this clinical study was to validate a cloud-based platform trained for the AI-driven segmentation of prosthetic crowns on CBCT scans and subsequent multimodal intraoral scan-to-CBCT registration in the presence of high metal artifact expression.

A novel cone beam-CT approach for quantifying maxillary changes following secondary alveolar bone grafting in unilateral cleft patients.

Objectives: To quantify longitudinal bone changes in the maxilla after secondary alveolar bone grafting (SABG) in patients with unilateral cleft lip and/or cleft palate (CL/P), and to describe the maxillary dimensions before and after SABG in all orthogonal planes using a Cone Beam Computed Tomography (CBCT)-based methodology.

Methods: Ethical approval was obtained to retrospectively analyze CBCT scans of children treated for unilateral alveolar clefts. Inclusion criteria encompassed individuals who underwent SABG before the eruption of the cleft-side permanent lateral incisor or, if absent, the permanent ca-nine, and had both preoperative and postoperative CBCT scans.

A unique AI-based tool for automated segmentation of pulp cavity structures in maxillary premolars on CBCT.

To develop and validate an artificial intelligence (AI)-driven tool for the automatic segmentation of pulp cavity structures in maxillary premolars teeth on cone-beam computed tomography (CBCT). One hundred and eleven CBCT scans were divided into training (n = 55), validation (n = 14), and testing (n = 42) sets, with manual segmentation serving as the ground truth. The AI tool automatically segmented the testing dataset, with errors corrected by an operator to create refined 3D (R-AI) models.

Alveolar socket surface area as a local risk factor for MRONJ development in oncologic patients on polypharmacy.

Objectives: To determine the impact of alveolar socket surface area and number of root extractions for developing medication-related osteonecrosis of the jaw (MRONJ) in polypharmacy patients following multiple tooth extractions.

Materials And Methods: A retrospective sample of 40 patients was recruited, including 20 polypharmacy patients (109 tooth extractions) who developed MRONJ in at least one of the extraction sites, matched with 20 controls (100 tooth extractions). Tooth-specific alveolar socket surface areas were assessed using CBCT scans from the control group to establish reference values for alveolar socket surface areas in polypharmacy patients with MRONJ.

Volumetric Assessment of Resorption Patterns of Bilateral Alveolar Clefts in Cone-Beam Computed Tomography in Two- Stage Bone Graft.

Objective: Few studies have analysed the outcome of bone grafts in bilateral alveolar clefts and the bone fill with a two-step surgery method. The currently applied three-dimensional method used in this study enables a comprehensive description of the bone fill of bilateral clefts after bone grafting. The study aimed to describe alveolar cleft volume and bone fill after alveolar bone grafting of bilateral alveolar clefts treated with two-step bone grafting, with a comparison between the first and the second bone graft site.

A novel artificial intelligence-powered tool for automated root canal segmentation in single-rooted teeth on cone-beam computed tomography.

Aim: To develop and validate an artificial intelligence (AI)-powered tool based on convolutional neural network (CNN) for automatic segmentation of root canals in single-rooted teeth using cone-beam computed tomography (CBCT).

Methodology: A total of 69 CBCT scans were retrospectively recruited from a hospital database and acquired from two devices with varying protocols. These scans were randomly assigned to the training (n = 31, 88 teeth), validation (n = 8, 15 teeth) and testing (n = 30, 120 teeth) sets.

Application of orthodontic force in autotransplanted teeth: a longitudinal study.

Objectives: To longitudinally follow up a cohort of patients with autotransplanted teeth, assessing how the timing of starting orthodontic treatment impacts root length.

Materials And Methods: Patients under 18 with at least one open-apex autotransplanted premolar (AP) replaced to a central incisor position were included. Root/crown ratio (RCR) was calculated on periapical radiographs taken at intervals of 3-6 months after transplantation.