Purpose: Lateral cephalograms are conventionally used for landmark identification and cephalometric analysis, butexpose patients to ionizing radiation. Magnetic resonance imaging (MRI) is increasingly employed to evaluate various tissue types, with dental-dedicated MRI (ddMRI) emerging as a promising modality in clinical dentistry. High-quality MRI could offer a radiation-free alternative for orthodontic diagnosis and treatment planning. This pilot study aimed to evaluate the reliability of ddMRI for 2-dimensional (2D) orthodontic cephalometric landmark identification and annotation. Materials and Methods: Thirteen volunteers (7 men, 6 women; mean age 33±5.2 years) underwent ddMRI. Threeindependent raters identified 2D cephalometric landmarks and annotated their positions on the same ddMRI datasetstwice. The 3D Slicer application was used to identify key orthodontic cephalometric landmarks on multiplanar reconstruction images in the sagittal plane. Intra-rater and inter-rater reproducibility were assessed using intraclass correlation coefficients (ICCs), and reliability was evaluated by nominal differences in linear distance (mm) between annotated points. Results: Intra-rater ICCs ranged from 0.909 to 0.999, and inter-rater ICCs ranged from 0.988 to 0.999, indicating excellent intra- and inter-rater reliability. Bland-Altman plots were used to display mean differences (mm) and limits of agreement (±1.96 standard deviations) between annotations to assess potential biases. Conclusion ddMRI is a feasible imaging modality for 2D orthodontic landmark identification. Based on intra- andinter-rater reproducibility values, ddMRI demonstrates high reliability in identifying key orthodontic cephalometric landmarks, providing a radiation-free alternative for orthodontic diagnosis and treatment planning.

Purpose: This study proposes an ex vivo imaging protocol using a dental-dedicated magnetic resonance imaging (ddMRI) system and qualitatively and quantitatively evaluates the effects of phosphate-buffered saline (PBS) washing on image quality. Materials and Methods: Four half-maxillae and 4 half-mandibles from human cadaveric donors were scanned using a ddMRI system with a dental-specific coil. Two pulse sequences (“anatomy” and “inflammation”) were applied. Each specimen was imaged at 4 time points: immediately after PBS immersion and after 24, 48, and 72hours of washing, totaling 64 images. Image quality was evaluated using signal-to-noise ratio (SNR), contrast-tonoise ratio (CNR), and conspicuity of anatomical structures: cortical bone, medullary bone, root contour, soft tissue,and the sinus floor/mandibular canal. Conspicuity was rated by 3 observers and analyzed using the Cochran Q test (α = 0.05). Results: Cortical bone, medullary bone, and the sinus floor were depicted in all images; root contours (91.1%) and soft tissue (85.9%) were visible in most images. PBS washing did not significantly impact conspicuity (P>0.05).Signal intensity was higher in “anatomy” than “inflammation.” In the “anatomy” sequence, both SNR and CNRinitially declined, then stabilized from 24 hours onward. CNR between medullary bone and soft tissue showed thegreatest improvement with extended PBS washing, especially for the “inflammation” sequence. Conclusion The proposed ddMRI protocol enabled consistent visualization of dentomaxillofacial structures in ex vivo samples. PBS represented a suitable carrier. Although PBS washing did not influence conspicuity, at least 24hours of washing may improve image quality, as reflected by SNR and CNR.

Purpose: This ex vivo study was performed to determine the optimal energy level for virtual monoenergetic images (VMIs) generated with photon-counting detector computed tomography (PCD-CT) to minimize metal artifacts from dental implants. Materials and Methods: Twelve implants from various manufacturers were placed in 6 pig mandibles and scanned with PCD-CT. VMIs were reconstructed at energy levels from 70 keV to 150 keV in 20-keV increments. Three readers with varying experience qualitatively assessed the image quality, artifact burden, and diagnostic interpretability of peri-implant soft and hard tissues using a 5-point discrete visual scale. Objective analyses included quantitative line profileanalysis of implant-induced artifacts. Descriptive statistics were calculated, and inter-reader agreement was assessedusing percentage agreement and the Krippendorff alpha coefficient. Results: Qualitative analysis demonstrated excellent image quality for VMIs at ≥110 keV (median = 5), with minimal artifacts observed at 130-150 keV. In contrast, lower-energy VMIs (70-90 keV) showed inferior performance due to artifact-related limitations in diagnostic interpretability. Inter-reader agreement ranged from moderate to perfect, with perfect reliability (α = 1) for VMIs ≥110 keV. Quantitative line-profile analysis confirmed reduced artifact burden at higher energy levels, particularly for VMIs ≥110 keV. Conclusion VMI at energy levels ≥110 keV on PCD-CT reduced dental implant-related metal artifacts and offeredexcellent image quality, including assessment of both peri-implant soft and hard tissues. These findings suggest thatoptimized PCD-CT VMI may enhance postoperative follow-up imaging. Future in vivo studies are warranted tovalidate these findings in clinical practice.

In addition to well-known side effects such as rash, redness, and bone resorption, unexpected facial complications may occasionally occur several years after certain medical procedures. This report presents rare cases of orofacialsymptoms that developed as delayed responses to cosmetic filler injections. Three separate patients presented to theauthors’ institution with varying severities of orofacial symptoms. These symptoms, initially diagnosed clinically asinflammation or neoplasms of the parotid gland, were later identified through magnetic resonance imaging as diseases potentially associated with filler materials injected approximately 4-8 years earlier. The primary goal of this report was to inform specialists in the oral and maxillofacial field about the possibility of such complications, enabling them tomanage patient symptoms effectively and develop appropriate treatment strategies.

Purpose: This study evaluated the nasopharyngeal anatomy, particularly the fossa of Rosenmüller (FoR), on cone-beam computed tomography (CBCT) in a Korean population to establish normative reference data by sex and age. Materials and Methods: In CBCT images, FoR was classified into three types (A-C) for image analysis. Measurements of nasopharyngeal dimensions were performed in Types B and C. Sex- and age-related differences were evaluatedusing chi-square and independent t-tests, and reliability was assessed using the intraclass correlation coefficient. Results: In total, 492 CBCTs (244 males, 248 females; 20-69 years) were included. Type C was the most frequent morphology and increased with age. Types A and B were more prevalent among males than among females, whereas Type C was predominant among females (57.3%) compared with males (34.4%). Asymmetry was more frequent in males (13.9%) than in females (10.1%). Significant sex differences due to the larger males were found in the distance of the torus levatorius, the distance between the sphenopalatine notch and the right torus levatorius, and the horizontaland vertical dimensions of the FoR. No significant side-to-side differences were observed. Reliability was excellent(ICC = 0.97). Conclusion Type C was the most frequent morphology in both sexes, whereas Types A and B were more frequently observed in males than in females. These differences may indirectly contribute to sex-related disparities in nasopharyngeal carcinoma (NPC) incidence. The normative reference values may aid early detection in dental imaging, and further prospective studies including NPC patients are needed to clarify the role of nasopharyngeal morphology.

Purpose: This systematic review evaluated the diagnostic performance of optical coherence tomography (OCT) forthe early detection of oral cancer, particularly emphasizing sensitivity, specificity, and overall diagnostic accuracy. Materials and Methods: A comprehensive literature search was conducted across PubMed, ScienceDirect, and Wiley Online Library covering publications from 2015 to 2025, supplemented by manual hand-searching of relevant references. Studies were selected using the Population, Intervention, Comparison, Outcome, Study Design (PICOS) framework. Eligible studies evaluated the diagnostic accuracy of OCT using histopathology as the reference standard. Risk of bias was assessed using the QUADAS-2 tool, and the review methodology followed PRISMA 2020 and PRISMA-DTA guidelines. The review protocol was registered in PROSPERO (CRD420251112254). Results: Seven studies met the predefined inclusion criteria. OCT demonstrated high diagnostic performance (sensitivity: 81.5%-100%, specificity: 68.8%-100%), with diagnostic accuracy reaching up to 100% in certain settings. Studies that incorporated machine learning approaches, including convolutional neural networks and support vector machines, consistently achieved superior diagnostic performance compared with conventional OCT interpretation alone. Overall methodological quality was generally low, with several studies exhibiting moderate tohigh risk of bias in specific domains. Conclusion OCT, particularly when augmented with artificial intelligence, demonstrates high diagnostic accuracy as anon-invasive imaging modality for the early detection of oral cancer. Its capability to identify dysplastic and malignant changes at the microstructural level offers meaningful diagnostic advantages over conventional examination methods.Nevertheless, larger-scale studies employing standardized protocols are required to confirm its clinical utility and support integration into routine oral cancer screening and diagnostic pathways.

Purpose: Vertical root fractures (VRFs) remain a major diagnostic challenge in endodontics due to image noise and artifacts in cone-beam computed tomography (CBCT), particularly those caused by intracanal posts. This study evaluated the effect of an advanced noise reduction (ANR) algorithm on CBCT performance in detecting VRFs inmaxillary second premolars and examined how different post materials influenced diagnostic outcomes. Materials and Methods: Seventy extracted maxillary second premolars with single canals were divided into 5groups according to post material (cast, fiberglass, titanium, stainless steel, and brass). VRFs were induced in half of the specimens using a universal testing machine under standardized conditions. CBCT scans were obtainedusing a Carestream 9600 device with fixed parameters, both with and without ANR. Two experienced radiologists independently evaluated the images using a 5-point scale. Sensitivity, specificity, predictive values, and interobserveragreement were analyzed using SPSS version 21 (IBM Corp., Armonk, NY, USA). Results: The application of ANR increased overall sensitivity and interobserver agreement compared with conventional images. Specificity varied by post material: fiberglass posts demonstrated the highest diagnostic accuracy, while stainless steel and brass produced stronger artifacts and lower sensitivity. Conclusion Incorporating ANR into CBCT imaging improves VRF detection by improving sensitivity and observerconsistency, especially in cases with minimal metallic interference. These findings highlight the clinical benefits of ANR and support further research integrating noise and metal artifact reduction techniques with artificial intelligenceto optimize diagnostic precision.

Purpose: The present study aimed to develop 2 deep learning (DL) systems incorporating detection functions for the diagnosis of carotid artery calcifications (CACs) on panoramic radiographs and to compare their diagnostic performances using CAC-based, side-based, and patient-based evaluations. Materials and Methods: Panoramic radiographs from 290 patients with CACs and 290 control patients without CACs were used to develop 2 detection models: one designed to detect individual CACs across the entire radiograph (System 1) and another designed to detect CACs within the limited bilateral cervical areas (System 2). CAC-based performance was evaluated using recall, precision, and F1-score. Side-based and patient-based performances were assessed usingsensitivity, specificity, positive predictive value, negative predictive value, accuracy, and the area under the receiveroperating characteristic curve (AUC). Results: For System 1, CAC-based recall, precision, and F1-score were 0.81, 0.68, and 0.74, respectively. For System 2,the corresponding values were 0.90, 0.67, and 0.77. Side-based sensitivity, specificity, and AUC were 0.87, 0.80, and 0.83 for System 1, and 0.93, 0.84, and 0.89 for System 2. Patient-based sensitivity, specificity, and AUC were 0.93, 0.73,and 0.83 for System 1, and 0.95, 0.70, and 0.83 for System 2. Although a relatively large number of false positives were observed in CAC-based assessments, side-based and patient-based performances showed improvement. Conclusion Side-based and patient-based performances were sufficient when calculated on the basis of CAC-basedevaluations for diagnosing CACs on panoramic radiographs. When conducting studies of this type, performance assessments should include side-based and patient-based evaluations in addition to CAC-based analyses.

Purpose: This study was performed to establish a procedure for simulated low-dose cone-beam computed tomography (CBCT) scans and to investigate whether the resulting images are comparable in diagnostic accuracy to those obtained using a clinical low-dose protocol. Materials and Methods: ImageJ was used to manipulate the sinogram data from CBCT scans acquired at 5 mA to mimic a technical setting of 2 mA by adding noise to the Radon-transformed projection data before image reconstruction. Four observers compared the simulated 2 mA CBCT scans with original clinical 2 mA CBCT scans acquired previously. The CBCT images were analysed using a protocol with a ranking scale, and the observers were required to select only 1 category for each variable. The Wilcoxon signed-rank test was used to assess differences between the 2 CBCT scan types, with a significance level of P<0.05. Intra-observer agreement was evaluated using the Cohen kappa. Results: Pairwise observer comparisons of the simulated and clinical low-dose CBCT scans showed no significantdifferences in image quality. Intra-observer agreement was acceptable, and in 5 comparisons, the results indicated a high degree of agreement. Conclusion Simulated low-dose CBCT scans can be generated using ImageJ. No significant differences in imagequality were observed between simulated and clinical low-dose CBCT scans when evaluating mandibular third molars. These findings suggest that manipulation of sinogram data is a promising radiation-free approach for simulating low-dose images in optimisation efforts.

Purpose: This study evaluated the performance of the YOLOv8m-seg model in detecting and delineating interproximal caries and cervical burnout on bitewing radiographs and examined whether increasing the number of training epochs improved segmentation accuracy and consistency. Materials and Methods: In total, 1,410 bitewing radiographs were annotated using polygon-based masks by a trained dental clinician. The YOLOv8m-seg model was trained for 50, 100, and 150 epochs on 1,128 images and validated on 282 images using the Ultralytics segmentation framework. Model performance was assessed using precision, recall, and mean average precision at intersection-over-union thresholds of 0.5 and 0.5 to 0.95 (mAP0.5, mAP0.5-0.95) for both bounding box and mask outputs. Additional evaluation was conducted on a non-augmented validation subset. Results: Extended training duration was associated with improved segmentation performance. The highest mask mAP0.5-0.95 value was 0.828 at epoch 150. Both box-based precision and recall increased with longer training, whereas mask-based evaluation more accurately reflected the model’s ability to delineate the boundaries of caries and cervical burnout. Performance appeared consistent across both classes in the augmented validation split but was reduced in the non-augmented validation subset. Conclusion The YOLOv8m-seg model demonstrated high diagnostic accuracy in distinguishing proximal caries from cervical burnout on bitewing radiographs. Its mask-based outputs may assist clinicians in early lesion recognition and support improved diagnostic decision-making. Future studies should evaluate model generalizability across broader populations and diverse clinical environments and should prioritize assessment using non-augmented validation sets and independent test datasets.