Nasal myiasis is an infestation by dipterous larvae within the nasal cavity, where they feed on both living tissue andfluid. This condition predominantly occurs in rural areas of tropical countries, where inadequate sanitation and ahot, humid climate create an ideal environment for larvae development. A 57-year-old, otherwise healthy male ruralworker presented with a toothache in the region of the maxillary incisors. Imaging studies identified a punctiformradiopaque/hyperdense area near the nasal septum in the left nasal fossa. The larva was surgically excised andsent for histopathological analysis. Histologic sections confirmed the clinical diagnosis, and the patient remainedasymptomatic after a 2-month follow-up. Nasal myiasis can mimic the symptoms of a toothache in the anterior region of the maxilla. This condition can affect even immunocompetent patients, and complementary imaging studies may be decisive in diagnosing it.

Purpose: This study demonstrated the feasibility of obtaining mandible bone mineral density (BMD) scores using spectral panoramic imaging. Materials and Methods: Areal BMD scores were measured from the body and angle of the mandible in 3 anthropomorphic head phantoms using a spectral panoramic system (Planmeca Promax Mid, Planmeca Oy, Helsinki, Finland) equipped with a DC-Vela detector (Varex Imaging Corporation, Salt Lake City, USA). These results were compared to synthetic panoramic images generated from dual-energy CT acquisitions. Reproducibility was evaluated by repeatedly scanning 1 phantom with minor patient positioning errors, and the linearity of the BMD scores was assessed using calcium inserts in a Gammex 472 phantom (Sun Nuclear, Melbourne, USA). Results: The experimental and synthetic panoramic images appeared visually similar. The mean synthetic score was 0.640 g/cm2 , and the anthropomorphic phantoms produced a root mean squared error of 0.0292 g/cm2 with a correlationcoefficient of 0.969. Typical patient positioning errors did not substantially increase the error, which measured 0.0296g/cm2 and 0.0474 g/cm2 for the left and right sides, respectively. Linearity tests using the Gammex phantom yielded a correlation coefficient of 0.998 for BMD scores ranging from 0.03 to 2.7 g/cm2 . Conclusion The BMD data obtained from spectral panoramic imaging are consistent with both dual-energy CT and Gammex phantom measurements. Consequently, spectral panoramic imaging shows potential as a method for osteoporosis screening, leveraging the widespread use of panoramic imaging.

Basal cell adenocarcinoma, considered to be the malignant counterpart of basal cell adenoma, is a rare, low-grade malignant tumor of the salivary glands, accounting for 1-2% of salivary gland malignancies. It predominantly affects the parotid gland, while involvement of the minor salivary glands is exceptionally rare. This report presented a case of basal cell adenocarcinoma involving the left retromolar trigone in a 54-year-old woman. The initial provisional diagnosis suggested a benign or low-grade malignant salivary tumor. Advanced magnetic resonance imagingtechniques, including diffusion-weighted imaging and apparent diffusion coefficient analysis, aided in the preoperative prediction of malignancy, and an incisional biopsy confirmed the diagnosis of basal cell adenocarcinoma. This caseunderscored the challenge of distinguishing basal cell adenocarcinoma from benign salivary tumors, as clinical and imaging features often overlap. Surgical excision remains the primary treatment, yielding favorable outcomes;however, long-term follow-up is crucial due to the risk of recurrence.

Purpose: X-ray scattering adversely affects cone-beam computed tomography (CBCT) image quality, generating image artifacts, causing inaccurate tissue density representation, and reducing contrast. This study evaluated the performance of a 2-dimensional antiscatter grid (2D grid) prototype in a dental CBCT system. Materials and Methods: A focused 2D grid prototype was fabricated from tungsten and integrated with the detector of a dental CBCT system. Residual scatter transmitted through the 2D grid was corrected using a measurement-based scatter correction method. Phantom imaging experiments were performed in anatomical regions relevant to dentaland head imaging with and without this grid. Following image reconstruction via filtered back projection, attenuation coefficients were converted to Hounsfield units (HU). Subsequently, scatter suppression performance, HU consistency, image artifacts, and contrast resolution were evaluated. Results: The 2D grid reduced scatter intensity by a factor of 10-20 in CBCT projections. Consequently, the grid substantially increased contrast, reduced image artifacts, and improved HU consistency. The contrast increased by 27% and 48% in bone- and soft tissue-equivalent regions, respectively. HU value deviations among teeth decreasedfrom 510 to 146 HU. These results indicate improved visualization and tissue density representation fidelity in CBCTimages acquired with the 2D grid. Conclusion Use of a 2D grid could substantially improve the accuracy of tissue density representation and the contrast of dental and head anatomy in 3-dimensional images obtained with dental CBCT. Such improvements may translate to better quantitative evaluation of bone quality, enhanced tissue visualization, and more accurate model generation for surgical planning and guidance.

Purpose: This study was performed to assess the performance and accuracy of artificial intelligence (AI) in the detection and diagnosis of maxillary sinus pathologies using computed tomography (CT)/cone-beam computed tomography (CBCT) imaging. Materials and Methods: A comprehensive literature search was conducted across 4 databases: Google Scholar, BioMed Central (BMC), ProQuest, and PubMed. Combinations of keywords such as “DCNN,” “deep learning,” “convolutional neural network,” “machine learning,” “predictive modeling,” and “data mining” were used to identify relevant articles. The study included articles that were published within the last 5 years, written in English, available in full text, and focused on diagnostic accuracy. Results: Of an initial 530 records, 12 studies with a total of 3,349 patients (7,358 images) were included. All articles employed deep learning methods. The most commonly tested pathologies were maxillary rhinosinusitis and maxillary sinusitis, while the most frequently used AI models were convolutional neural network architectures, including ResNet and DenseNet, YOLO, and U-Net. DenseNet and ResNet architectures have demonstrated superior precision in detecting maxillary sinus pathologies due to their capacity to handle deeper networks without overfitting. The performance in detecting maxillary sinus pathology varied, with an accuracy ranging from 85% to 97%, a sensitivityof 87% to 100%, a specificity of 87.2% to 99.7%, and an area under the curve of 0.80 to 0.91. Conclusion AI with various architectures has been used to detect maxillary sinus abnormalities on CT/CBCT images, achieving near-perfect results. However, further improvements are needed to increase accuracy and consistency.

Purpose: The aim of this study was to identify, compile, and report the technical specifications of current and historical intraoral digital radiographic systems and recommend standardised reporting practices for production companies. Materials and Methods: A comprehensive report was prepared on 150 intraoral digital radiographic systems, comprising 105 sensor-based (70%) and 45 phosphor storage plate (PSP)-based systems (30%). Technical specifi cations were obtained from official company sources and scientific articles to ensure a complete collection of available data. Results: These systems were produced by 55 companies across 11 countries, with the United States leading (35.3%), followed by France (12%). Among the sensor systems, 76.2% used complementary metal-oxide-semiconductor (CMOS) technology, with notable variations in sizes and resolutions. PSP systems were available in 7 plate sizes and displayed diverse resolutions and scanning times. Twenty-one companies produced both sensor- and PSP-based systems, 33 produced only sensor-based systems, and 1 produced exclusively PSP-based systems. Conclusion This report identified 150 digital radiographic systems, revealing wide variability in technicalspecifications and a lack of standardised reporting protocols. The comprehensive summary and recommendations forconsistent documentation provided here can help clinicians make informed decisions and encourage manufacturers and production companies to adopt uniform reporting standards aligned with local regulatory frameworks.

Purpose: Bone grafts can be challenging to assess on cone-beam computed tomography (CBCT) examinations due to their discreet appearance and the potential introduction of metallic artifacts from implant screws. This study aimed to evaluate the effect of CBCT milliamperage (mA) on detecting bone graft dehiscence adjacent to titanium (Ti) and zirconia (Zr) implants. Materials and Methods: Twenty Ti and 20 Zr implants were installed in bovine rib blocks. Gaps of at least 2 mmwere created between the implant and the bone and filled with particulate autogenous bone grafts. In half of the blocks, the gap was completely filled, while in the other half, the grafting material was removed up to the thirdimplant thread. CBCT images were acquired at 4, 6.3, and 10 mA and evaluated by 5 observers to detect bone graftdehiscence. The area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity werecalculated. These values were then compared across various dental implant materials and mA levels using 2-wayanalysis of variance with a significance level of 5%. Results: No statistically significant differences were observed in the diagnostic values for bone graft dehiscencebetween implant types (P>0.05) or mA settings (P>0.05). Conclusion Although a protocol with lower radiation exposure (that is, lower mA) could be employed, the use of CBCT for evaluating bone graft dehiscence adjacent to different types of dental implants should be approached with caution.

Purpose: This study employed a convolutional neural network (CNN) algorithm to develop an automated dental age estimation method based on the London Atlas of Tooth Development and Eruption. The primary objectives were to create and validate CNN models trained on panoramic radiographs to achieve accurate dental age predictions using a standardized approach. Materials and Methods: A dataset of 801 panoramic radiographs from outpatients aged 5 to 15 years was used. A CNN model for dental age estimation was developed using a 16-layer CNN architecture implemented in Python with TensorFlow and Scikit-learn, guided by the London Atlas of Tooth Development. The model included 6 convolutional layers for feature extraction, each followed by a pooling layer to reduce the spatial dimensions of the feature maps. A confusion matrix was used to evaluate key performance metrics, including accuracy, precision, recall, and F1 score. Results: The proposed model achieved an overall accuracy, precision, recall, and F1 score of 74% on the validation set. The highest F1 scores were observed in the 10-year and 12-year age groups, indicating superior performancein these categories. In contrast, the 6-year age group demonstrated the highest misclassification rate, highlightingpotential challenges in accurately estimating age in younger individuals. Conclusion: Integrating a CNN algorithm for dental age estimation represents a significant advancement in forensic odontology. The application of AI improves both the precision and efficiency of age estimation processes, providing results that are more reliable and objective than those obtained via traditional methods.

Purpose: The bisecting angle technique (BAT) encounters difficulties in positioning the X-ray cone and aligningthe central beam with the tooth. To address this, a rectangular laser featuring a pointed light was integrated into theintraoral X-ray cone. This study evaluated its effectiveness in improving radiograph quality and minimizing errors. Materials and Methods: Fifty fifth-year Bachelor of Dental Surgery students were divided into 3 groups. Group1 (n = 16) used the paralleling technique, group 2 (n = 17) employed the conventional BAT, and group 3 (n = 17) utilized the laser-assisted BAT on mannequins. Two independent oral radiologists assessed the quality of the radiographs, categorizing the images as either diagnostically acceptable or not acceptable. Inter-group comparisons of quality and error rates were conducted using the chi-square test (significance level: P<0.05). Results: The paralleling technique group produced 77.5% diagnostically acceptable radiographs and 22.5% that were not diagnostically acceptable. These percentages were 65.3% and 34.7%, respectively, in the conventional BAT group and 75.3% and 24.7%, respectively, in the laser-assisted BAT group, showing results similar to the paralleling technique group. The quality of radiographs differed significantly among the groups (P<0.05). The percentage of error-free radiographs was 38.1% in the paralleling technique group, 20.6% in the conventional BAT group, and 40.0% in the laser-assisted BAT group, with these differences being statistically significant (P<0.05). Conclusion The device produced higher acceptability and fewer radiographic errors than the conventional BATtechnique, suggesting accurate adjustment of the X-ray cone and central beam to the desired teeth.

Purpose: This study was conducted to compare the objective image quality of radiographs acquired with a handheld X-ray device to those obtained with a wall-mounted X-ray device. Materials and Methods: Brightness, noise, uniformity, and contrast were evaluated. To assess the first 3 parameters,radiographs of an acrylic block were acquired with an unused photostimulable phosphor (PSP) plate from the VistaScan system (Mini Easy, Dürr Dental, Bietigheim-Bissingen, Germany). Initially, 6 radiographs were taken with a Focus X-ray wall-mounted device (Instrumentarium, Tuusula, Finland) operating at 60 kVp, 7 mA, and 0.125 s.Another 6 radiographs were captured using an Eagle handheld X-ray device (Alliage, São Paulo, Brazil) at 60 kVp, 2.5 mA, and 0.35 s. The means and standard deviations of the gray values for all radiographs were calculated using ImageJ (National Institutes of Health, Bethesda, MD, USA). For contrast assessment, radiographs of an aluminum step wedge were obtained using the same PSP plate, X-ray devices, and acquisition parameters. The percentage of contrast variation was determined. The impacts of the devices on image quality were compared using the Student t-test, with a significance level of 5% (P<0.05). Results: Compared with the wall-mounted device, the handheld device produced radiographs with higher brightness and noise, as indicated by mean values of 6.57 (0.49) and 3.49 (0.02), respectively. Furthermore, it demonstrated lower uniformity and contrast, with respective means of 3.75 (0.02) and 35.48 (0.09) (P<0.05). Conclusion Radiographs obtained using a handheld X-ray device exhibit lower theoretical image quality than those acquired with a wall-mounted device.