Dento Maxillo Facial Radiology

PURPOSE: This study aimed to assess the performance of a deep learning algorithm (YOLOv5) in detecting different mandibular fracture types in panoramic images. METHODS: This study utilized a dataset of panoramic radiographic images with mandibular fractures. The dataset was divided into training, validation, and testing sets, with 60%, 20%, and 20% of the images, respectively. An equal number of control panoramic radiographs, which did not contain any fractures, were also randomly distributed among the three sets...

OBJECTIVES: Preoperative diagnosis of oral ameloblastoma (AME) and odontogenic keratocyst (OKC) has been a challenge in dentistry. This study uses radiomics approaches and machine learning (ML) algorithms to characterize cone beam computed tomography (CBCT) image features for the preoperative differential diagnosis of AME and OKC and compares ML algorithms to expert radiologists to validate performance. METHODS: We retrospectively collected the data of 326 patients with AME and OKC, where all diagnoses were confirmed by histopathologic tests...

OBJECTIVE: To compare digital panoramic radiography (DPR) and cone beam computed tomography (CBCT) in the detection and classification of pulp calcifications in posterior teeth in relation to tooth condition and its location. METHODS: 250 patients with simultaneous DPR and CBCT scans were selected from a dental image bank. For each posterior tooth, its condition was registered (healthy, restored, or decayed). The presence of calcifications was assessed and classified according to location (coronal or radicular) and type (total obliteration, partial obliteration, narrowing, and no calcification)...

OBJECTIVES: This study aimed to establish a method for differentiating radicular cysts from granulomas via texture analysis (TA) of multi-slice computed tomography (CT) images. METHODS: A total of 222 lesions with multi-slice computed tomography images acquired at our hospital between 2013 and 2022 that were pathologically diagnosed were included in this study. Cases of contrast-enhanced images, severe metallic artifacts, and lesions that were not sufficiently large to be analyzed were excluded...

OBJECTIVES: To investigate the imaging and anatomic features of the anterior lobe (AL) of the superficial parotid gland. METHODS: Computed tomographic sialography examinations were undertaken for 142 parotid glands in 77 patients. Whole computer tomography (CT) data were analyzed using multi-planar reformation and maximum intensity projection to generate sialographic CT images. The tributary ducts of the superficial parotid gland were analyzed to classify the parotid morphology...

OBJECTIVES: Panoramic radiography is one of the most commonly used diagnostic modalities in dentistry. Automatic recognition of panoramic radiography helps dentists in decision support. In order to improve the accuracy of the detection of dental structural problems in panoramic radiographs, we have improved the YOLO network and verified the feasibility of this new method in aiding the detection of dental problems. METHODS: We propose a Deformable Multi-scale Adaptive Fusion Net (DMAF-Net) to detect five types of dental situations (impacted teeth, missing teeth, implants, crown restorations and root canal-treated teeth) in panoramic radiography by improving the You Only Look Once (YOLO) network...

OBJECTIVES: The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in Cone Beam Computed Tomography (CBCT) volumes and to evaluate the performance of this model. METHODS: In 101 CBCT scans, MS were annotated using the CranioCatch labelling software (Eskisehir, Turkey) The dataset was divided into three parts: 80 CBCT scans for training the model, 11 CBCT scans for model validation, and 10 CBCT scans for testing the model...

OBJECTIVES: Differentiation among benign salivary gland tumors, Warthin tumors, and malignant salivary gland tumors is crucial to treatment planning and predicting patient prognosis. However, differentiation of those tumors using imaging findings remains difficult. This study evaluated the usefulness of elasticity determined from Diffusion-weighted image (DWI)-based virtual MR elastography (MRE) compared with conventional MRI findings in differentiating the tumors. METHODS: This study included 17 benign salivary gland tumors, six Warthin tumors, and 11 malignant salivary gland tumors scanned on neck MRI...

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OBJECTIVES: This study evaluated the effect of metal artifact reduction (MAR) level and tube current on the assessment of dental implant positioning relative to the mandibular canal (MC) through cone-beam computed tomography (CBCT). MATERIALS AND METHODS: Titanium dental implants were placed in dried mandibles at 0.5 mm superior to the MC (Group 1/n = 8), 0.5 mm inside the MC with perforation of the cortex (Group 2/n = 10)...

OBJECTIVES: The aim of this systematic review was to verify the accuracy of linear measurements performed on low-dose CBCT protocols for implant planning, in comparison with those performed on standard and high-resolution CBCT protocols. METHODS: The literature search included four databases (Pubmed, Web of Science, Embase, and Scopus). Two reviewers independently screened titles/abstracts and full texts according to eligibility criteria, extracted the data, and examined the methodological quality...

OBJECTIVES: Preoperative identification of different stromal subtypes of pleomorphic adenoma (PA) of the salivary gland is crucial for making treatment decisions. We aimed to developed and validated a model based on histogram analysis (HA) of ultrasound (US) images for predicting tumor stroma ratio (TSR) in SPA. METHODS: A total of 219 PA patients were divided into low-TSR (stroma-low) and high-TSR (stroma-high) groups, and enrolled in a training cohort (n = 151) and a validation cohort (n = 68)...

OBJECTIVES: Automating the digital workflow for diagnosing impacted canines using panoramic radiographs (PRs) is challenging. This study explored feature extraction, automated cropping, and classification of impacted and non-impacted canines as a first step. METHODS: A convolutional neural network (CNN) with SqueezeNet architecture was first trained to classify two groups of PRs (91with, and 91without impacted canines) on the MATLAB programming platform. Based on results, the need to crop the PRs was realized...

OBJECTIVES: To evaluate the feasibility of frozen soft tissues in simulating fresh soft tissues of pig mandibles using cone beam computed tomography (CBCT). METHODS: Two fresh pig mandibles with soft tissues containing two tubes filled with a radiopaque homogeneous solution were scanned using four CBCT units and two field-of-view sizes each. The pig mandibles were deep-frozen and scanned again. Three cross-sections were exported from each CBCT volume and grouped into pairs, with one cross-section representing a fresh and one a frozen mandible...

PURPOSE: This study investigated the differences in subjective and objective image parameters as well as dose exposure of photon-counting CT (PCCT) compared to cone-beam CT (CBCT) in paranasal sinus imaging for the assessment of rhinosinusitis and sinonasal anatomy. METHODS: This single-centre retrospective study included 100 patients, who underwent either clinically indicated PCCT or CBCT of the paranasal sinus. Two blinded experienced ENT radiologists graded image quality and delineation of specific anatomical structures on a 5-point Likert scale...

OBJECTIVES: To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models. METHODS: This systematic literature followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and used three databases. Keywords were selected from relevant literature. ELIGIBILITY CRITERIA: PAN studies that used ML models and mentioned image quality concerns. RESULTS: Out of 400 articles, 41 papers satisfied the inclusion criteria...

OBJECTIVES: The purpose of this study is to investigate the morphological changes that occur when mesiodens is located within the nasopalatine canal, as well as clinical characteristics. METHODS: Clinical records and computed tomography (CT) images of patients who had mesiodens in the nasopalatine canal were retrospectively analyzed. In addition to demographic information, clinical symptoms and complications associated with extraction of mesiodens were recorded...

Applications of cone-beam computed tomography (CBCT) in orthodontics have been increasingly discussed and evaluated in science and practice over the last two decades. The present work provides a comprehensive summary of current consolidated practice guidelines, cutting-edge innovative applications, and future outlooks about potential use of CBCT in orthodontics with a special focus on upper airway analysis in patients with sleep-disordered breathing (SDB). The present scoping review reveals that clinical applications of CBCT in orthodontics are broadly supported by evidence for the diagnosis of dental anomalies, temporomandibular joint disorders, and craniofacial malformations...

OBJECTIVES: To compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations. METHODS: The study included 95 craniofacial CT scans from patients aged 18-30 years. The degree of asymmetry was measured based on AI platform-predefined anatomical landmarks: sella (S), condylion (Co), anterior nasal spine (ANS), and menton (Me). The concordance between the results of automatic asymmetry reports and manual linear 3D measurements was calculated...

OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ML algorithms to evaluate the efficacy of pulp/tooth area ratio (PTR) in cone-beam CT (CBCT) images to predict dental age classification in adults. METHODS: CBCT images of 236 Turkish individuals (121 males and 115 females) from 18 to 70 years of age were included...