Panoramic radiographs (PANs) are a commonly used dental imaging modality and are complex to evaluate. This study aimed to use mouse-tracking technology to identify the visualization characteristics of experienced Oral & Maxillofacial Radiology (OMR) faculty when reviewing PANs and to assess relationships with detection accuracy.

To evaluate the diagnostic accuracy and generalizability of artificial-intelligence (AI) models for radiographic classification of jawbone cysts and tumours, and to propose a Clinical Interpretation Score (CIS) that rates the transparency and real-world readiness of published AI tools.

This technical report presents a novel CBCT-Based Grading System for Oropharyngeal Airway Narrowing, designed to provide clinicians with a standardised, objective method to assess oropharyngeal airway narrowing using Cone-Beam Computed Tomography (CBCT). The grading system is developed based on the least surface area on axial section measurements/minimal cross-sectional area (MCA) on CBCT. It classifies oropharyngeal narrowing into five distinct grades (Grade 0 to 4). Each grade also has subcategories that correspond to specific anatomical regions-distal to the soft palate (P), distal to the base of the tongue (T), or distal to both the soft palate and the tongue (B) - and includes precise surface area ranges, contributing to better understanding. Traditional methods have commonly relied upon lateral cephalometry or supine CT; however, CBCT offers 3D mapping in a natural upright position, ensuring functional relevance of the airway assessment. Owing to its high spatial resolution, adequate contrast between the soft tissue and empty space, relatively low radiation dose compared to multidetector row CT and visibility of the upper airway by utilising a large field of view (FOV) protocol, makes CBCT a useful diagnostic tool for evaluation of the airway. The fact that CBCT is taken in a sitting or standing position, where the head is in equilibrium and orofacial, neck musculature is in voluntary control, vis-à-vis the supine position, where this control is taken over by the autonomic nervous system, and the distal part of the soft palate compresses the already narrowed airway further adds to its usefulness. CBCT imaging, with its three-dimensional mapping capabilities, allows for precise visualisation of the airway from the level of the posterior nasal spine, where the hard palate ends, extending to the epiglottis-thus measuring the oropharyngeal airway. The system is particularly useful for early detection and evaluation of conditions such as obstructive sleep apnoea, hypertrophy of the nasopharyngeal tonsils (adenoids), predicting difficult airways for ease of intubation, guiding orthognathic surgical interventions, craniofacial anomalies, and complex orthognathic surgical planning. It holds promise for integration into AI-enabled diagnostic platforms and digital imaging software, offering consistency in research and practice. This report details the rationale, grading criteria, anatomical references, and potential applications of this classification. The system offers a streamlined approach for identifying airway compromise, ultimately aiding multidisciplinary use in optimising patient outcomes.

The objective was to assess the accuracy of different AI tools in providing the right responses for multiple choice questions (MCQs) and the time taken to complete the responses.

This study proposes a deep convolutional neural network model that integrates B-mode and D-mode ultrasound images to classify metastatic lymph nodes in patients with oral squamous cell carcinoma.

This study aimed to evaluate the diagnostic performance of machine learning (ML) algorithms based on radiomic features extracted from cone-beam computed tomography (CBCT) images in differentiating the nasopalatine duct (NPD) from the nasopalatine duct cyst (NPDC), and to compare their performance with that of a dentomaxillofacial radiologist.

Reliable cancellous bone segmentation in Cone Beam CT (CBCT) images is essential for post-orthognathic assessment of condylar resorption. However, challenges such as edge blurring and low contrast in CBCT images make effective segmentation difficult. This study aims to overcome these issues, providing a foundation for accurate bone quantification to enhance surgical planning and patient outcomes.

This study aimed to develop and evaluate an artificial intelligence (AI) framework for detecting dental restorations and prosthesis devices on panoramic radiographs (PRs). Detecting these elements is essential for enhancing automated reporting, improving the accuracy of dental assessments, and reducing manual examination time.

This study aimed to compare crestal facial bone measurements obtained from ultrasonography (USG) and cone-beam computed tomography (CBCT).

This study aimed to evaluate the diagnostic ability of relative values of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) quantitative parameters for salivary gland tumors (SGTs).

In dental radiography, where fine details need to be recognizable, image quality and spacial resolution play an important role. This is particularly the case in 3d imaging (CBCT), because the radiation exposure is significantly higher compared to any 2d imaging method. The gold standard for measuring spatial resolution and especially for relating it with contrast is the measurement of the modulation transfer function (MTF). The usual procedure to obtain the MTF is to take a CBCT scan of a test phantom, which consists of different materials. The MTF is then measured at the interface of two materials. In this work, we propose an approach in which we determine the MTF in clinical CBCT-scans at the boundary of physiological, implanted, or restored tooth as well as surrounding tissue structures of different density. It is assumed that all CBCTs inhibit some kind of interface between a radio-dense and radio-translucent area. Following the methodology used by the German standard DIN 6868-161 we developed our own numerical software for the computation of the MTF. The method enables a stable estimation of spatial resolution (MTF) in clinical CBCT-images.

This study aimed to investigate the vertical magnification ratios of various digital panoramic radiography devices and assess their consistency. It also examined the relationship between magnification ratios and Digital Imaging and Communications in Medicine (DICOM) header information to determine the potential use of key metadata in inferring or standardizing magnification corrections.

Radiographic imaging is essential in dental diagnostics, yet concerns persist regarding its genotoxic impact. While digital advancements have reduced radiation doses, the effects of X-ray exposure on oral mucosal cells remain debated. This study systematically reviews and quantitatively analyzes the effects of X-ray exposure on micronucleus (MN) formation in oral epithelial cells, examining potential age-related variations.

The aim of this study is to provide an overview of current cone beam CT (CBCT) practices in European dental clinics.

Sjögren disease (SD) is characterized by lymphocytic infiltration and fibrosis of the salivary glands. Shear wave elastography (SWE), an ultrasound-based modality that quantifies tissue stiffness, may assist in SD diagnosis. This study aimed to systematically review and meta-analyze the diagnostic performance of SWE in evaluating major salivary glands in individuals with SD, based on studies applying the 2016 ACR/EULAR classification criteria.

To investigate the impact of disinfecting a photostimulable phosphor plate (PSP) receptor with peracetic acid on proximal carious lesions diagnosis. Additionally, to evaluate and to measure artifacts caused by disinfection.

To evaluate the impact of ambient exposure of photostimulable phosphor (PSP) plates and digital enhancement on detecting internal root resorption (IRR).

External root resorption is a destructive process that usually develops without any symptoms and, when diagnosed, can lead to tooth extraction because it causes serious tooth tissue loss. Therefore, it is aimed to develop artificial intelligence algorithms that can assist in the diagnosis of external root resorption.

Inferior alveolar nerve (IAN) injury is a critical complication of mandibular third molar extraction. This study aimed to construct and evaluate a deep learning framework that integrates contrastive learning and Bayesian optimization to enhance predictive performance on cone-beam computed tomography (CBCT) and panoramic radiographs.

To evaluate artifact-reducing filters as a means to optimize and ensure the accuracy of carious lesion diagnosis testing two experimental models (presence and absence of adjacent metallic objects).

This retrospective study aimed to investigate and evaluate the signal intensity ratio (SIR) on magnetic resonance imaging (MRI) and maximum Standard Uptake Value (SUVmax) and Hounsfield Unit (HU) values on Single-photon emission computed tomography/computed tomography (SPECT/CT) in relation to the diagnosis of Temporomandibular joint osteoarthritis (TMJ OA).