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.

Purpose: Physiological dentin sclerosis is a distinctive phenomenon observed in transverse sections of the tooth root as a tooth ages. Since this effect has only been visualized 2-dimensionally, this pilot proof-of-concept study aimed to propose a novel method to visualize and quantify physiological sclerotic dentin 3-dimensionally using density-based micro-computed tomography (CT)-generated gray values. Materials and Methods: Forty single-rooted premolars of known chronological age from the Malay male population were scanned with a micro-CT scanner. The X-ray source was operated at 160 kV, 100 μA, and a voxel size of 48.8 μm.Three-dimensional volume datasets for each tooth were reconstructed, and volumetric analysis was performed on the root dentin region using the open-source software FIJI (ImageJ) (ver. 1.54k, National Institutes of Health, Bethesda, USA). Results: Micro-CT imaging enabled the selection, isolation, and quantification of high-density areas in the tooth rootthat correspond to physiological sclerotic dentin. The generated gray value profile also reflected the characteristicbutterfly-shaped pattern seen in transverse root sections. A comparison of premolars from different age groups revealedthat individuals aged 31-60 years exhibited a larger butterfly-shaped area, reflecting the increase in high-density sclerotic dentin, compared with younger premolars. Conclusion In this pilot proof-of-concept study, visualization and measurement of physiological sclerotic dentin were shown to be feasible using micro-CT. However, the method is highly dependent on the capability of the micro-CT scanner and the performance of the image-processing software. Further research is needed to improve image quality using advanced micro-CT scanning techniques.

Purpose: The objective of this study was to determine the minimum number of teeth in the anterior dental arch that would yield accurate results for individual identification in forensic contexts. Materials and Methods: The study involved the analysis of 28 sets of 3-dimensional (3D) point cloud data, focused on the labial surface of the anterior teeth. These datasets were superimposed within each group in both genuine and imposter pairs. Group A incorporated data from the right to the left central incisor, group B from the right to the left lateral incisor, and group C from the right to the left canine. A comprehensive analysis was conducted, including the evaluation of root mean square error (RMSE) values and the distances resulting from the superimposition of dental arch segments. All analyses were conducted using CloudCompare version 2.12.4 (Telecom ParisTech and R&D, Kyiv, Ukraine). Results: The distances between genuine pairs in groups A, B, and C displayed an average range of 0.153 to 0.184 mm. In contrast, distances for imposter pairs ranged from 0.338 to 0.522 mm. RMSE values for genuine pairs showed an average range of 0.166 to 0.177, whereas those for imposter pairs ranged from 0.424 to 0.638. A statistically significant difference was observed between the distances of genuine and imposter pairs (P<0.05). Conclusion The exceptional performance observed for the labial surfaces of anterior teeth underscores their potential as a dependable criterion for accurate 3D dental identification. This was achieved by assessing a minimum of 4 teeth.

Immediate implant placement into fresh extraction sockets has gained a lot of attention in implant dentistry. Besides proper risk assessment, the evaluation of tooth anatomy aids the clinicians to select the finest treatment protocol. Cone Beam Computed Tomography (CBCT) imaging was frequently used for alveolar bone analysis prior to tooth extraction in immediate implant placement. As an ideal position is required to prevent a buccally tilted implant or too palatal implant placement, various authors have proposed the treatment guidelines for immediate implant placement in the anterior maxilla. Although insightful, the previous classification was lacking anatomic variant and key anatomical features of alveolar bone and tooth angulation. Furthermore, there is no standardization method of measuring the specific degree of tooth angulation in CBCT scans that could possibly be used in clinical setting for appropriate treatment protocol. Thus, it is essential for the clinician to have adequate knowledge on the role of facial alveolar bone, palatal alveolar bone and tooth angulation related to immediate implant before selecting the appropriate treatment guidelines based on the classification reviewed. In this review, the previous quantitative measurements were categorized, and the previous classification was listed for the sake of familiarity by the dental practitioner with the major updates on implant placement strategy, patient selection and to reduce the rate of surgical complications.

ABSTRACT Dental caries is a commonly progressive disease that proceeds through various degrees of severity that a dentist can detect. The aims of the in vivo study were to assess the accuracy of the individual model (near-infrared light transillumination [NILT] device, visual and radiographic examinations) in detecting occlusal caries, and to evaluate the performance of visual and NILT device combination for occlusal caries detection in deciding the treatment options. Fifty-two non-cavitated occlusal surfaces from 16 patients were assessed with three different diagnostic devices in random order. Identified lesions were prepared and validated. Logistic regression analysis was performed for each method. The sensitivity and specificity values for each method and the combined models were statistically measured using RStudio version 0.97.551. At the enamel level, visual detection was the most sensitive method (0.88), while NILT was the most specific (0.93). NILT scored the highest for sensitivity (0.93) at the dentine level and visual detection scored the highest for specificity (0.88). Visual detection + NILT model was significantly better (p = 0.04) compared to visual detection or NILT alone (df = 1). The visual-NILT combination is a superior model in detecting occlusal caries on permanent teeth. The model provided surplus value in caries detection hence improving the treatment decision-making in occlusal surfaces.
Dental Caries Activity Tests

Introduction: Identification of remains recovered at advanced stages of decomposition can be problematic due to the lack of physical evidence. Nonetheless, human dentition is least susceptible to decomposition and as such carry a significant value in personal identification of decomposed remains. Demirjian’s method of age estimation was developed specifically for children with developing dentition. In this article, a method on adapting the Demirjian’s method for Malay ethnic-specific age estimation using the third molar development is presented. Methods: Orthopantomograms of Malay subjects aged 18 to 25 were obtained from UiTM Sungai Buloh. Total of 318 samples were taken, comprising of 123 and 195 images from male and female subjects. Development of right and left mandibular third molar was classified according to the eight stages of development as illustrated in Demirjian’s method. Data obtained were subjected to statistical analysis such as descriptive statistics and analysis of variance. The intra- and inter-gender variation between left and right mandibular third molar was evaluated using independent student t-test and analysis of variance, respectively. Results: Intra-gender comparison analysis revealed a significant difference in the female and male with a p-value of 0.000 and 0.003, respectively. Regression equation to estimate age based on third molar development were formulated according to dental age and maturity score. Conclusion: The Demirjian’s method was successfully adapted for age estimation of individuals of Malay ethnicity. These findings can help with victim identification in cases of poor skeletal framework recovery and highly decomposed remains.

PURPOSE: This study was performed to quantify the repeat rate of imaging acquisitions based on different clinical examinations, and to assess the prevalence of error types in intraoral bitewing and periapical imaging using a digital complementary metal-oxide-semiconductor (CMOS) intraoral sensor. MATERIALS AND METHODS: A total of 8,030 intraoral images were retrospectively collected from 3 groups of undergraduate clinical dental students. The type of examination, stage of the procedure, and reasons for repetition were analysed and recorded. The repeat rate was calculated as the total number of repeated images divided by the total number of examinations. The weighted Cohen's kappa for inter- and intra-observer agreement was used after calibration and prior to image analysis. RESULTS: The overall repeat rate on intraoral periapical images was 34.4%. A total of 1,978 repeated periapical images were from endodontic assessment, which included working length estimation (WLE), trial gutta-percha (tGP), obturation, and removal of gutta-percha (rGP). In the endodontic imaging, the highest repeat rate was from WLE (51.9%) followed by tGP (48.5%), obturation (42.2%), and rGP (35.6%). In bitewing images, the repeat rate was 15.1% and poor angulation was identified as the most common cause of error. A substantial level of intra- and interobserver agreement was achieved. CONCLUSION: The repeat rates in this study were relatively high, especially for certain clinical procedures, warranting training in optimization techniques and radiation protection. Repeat analysis should be performed from time to time to enhance quality assurance and hence deliver high-quality health services to patients.
Calibration ; Gutta-Percha ; Health Services ; Humans ; Prevalence ; Radiation Protection ; Radiographic Image Enhancement ; Radiography, Dental, Digital ; Retrospective Studies ; Semiconductors* ; Students, Dental