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Objective: To compare the accuracy, duration, and certainty of diagnosing approximal caries in bitewing radiographs displayed in 3 monitors under 2 luminance conditions., Methods: A total of 39 teeth without evident caries were selected from 11 patients undergoing partial jaw resection. Before the operation, 13 bitewing radiographs were captured by a digital imaging system. Eight observers evaluated the images under dark (9 lux) and bright (200 lux) conditions, using 2 medical-grade monitors and a commercial monitor. Using histological results as the gold standard, the areas under the receiver operating characteristic curves under different conditions were compared using the Z-test. Multivariate analysis of variance was conducted to assess the impact of various factors on diagnostic duration, while ordinal logistic regression was used to examine factors influencing diagnostic certainty level. It was considered significant when P < .05., Results: No significant difference was found in the diagnostic accuracy or duration for diagnosis of approximal caries under 2 luminance conditions with the 3 distinct monitors (P > .05). Ambient light, clinical experience, and the pathological grade of approximal caries have influence on the degree of diagnostic confidence (P < .05)., Conclusions: Different monitors and ambient luminance didn't influence the diagnostic accuracy or evaluation duration. Ambient luminance, clinical experience, and the depth of caries affect the degree of diagnostic confidence., Advances in Knowledge: The study employing bitewing radiographs from real patients indicates that ambient luminance, clinical experience, and the depth of caries affect the degree of diagnostic confidence., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology and the International Association of Dentomaxillofacial Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Traditional tooth image analysis methods primarily focus on feature extraction from individual images, often overlooking critical tooth shape and position information. This paper presents a novel computer-aided diagnosis method, Collaborative learning with Mask Region-based Convolutional Neural Network (Co-Mask R-CNN), designed to enhance tooth image analysis by leveraging the integration of complementary information. First, image enhancement is employed to generate an edge-enhanced tooth edge image. Then, a collaborative learning strategy combined with Mask R-CNN is introduced, where the original and edge images are input simultaneously, and a two-stream encoder extracts feature maps from complementary images. By utilizing an attention mechanism, the output features from the two branches are dynamically fused, quantifying the relative importance of the two complementary images at different spatial positions. Finally, the fused feature map is utilized for tooth instance segmentation. Extensive experiments are conducted using a proprietary dataset to evaluate the effectiveness of Co-Mask R-CNN, and the results are compared against those of an alternative segmentation network. The results demonstrate that Co-Mask R-CNN outperforms the other networks in terms of both segmentation accuracy and robustness. Consequently, this method holds considerable promise for providing medical professionals with precise tooth segmentation results, establishing a reliable foundation for subsequent tooth disease diagnosis and treatment., Competing Interests: The authors declare no conflict of interest., (©2024 The Author(s). Published by MRE Press.)

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 to identify individual teeth accurately. This system boasts an impressive precision rate of 97.48%, a recall (sensitivity) of 96.81%, and a specificity rate of 98.25%. Furthermore, this study introduces a novel approach to enhancing interdental edges through an advanced image-enhancement algorithm. This algorithm combines the use of a median filter and bilateral filter to refine the accuracy of convolutional neural networks in classifying dental calculus. Before image enhancement, the accuracy achieved using GoogLeNet stands at 75.00%, which significantly improves to 96.11% post-enhancement. These results hold the potential for streamlining dental consultations, enhancing the overall efficiency of dental services.

Purpose: To evaluate the proximal caries progression in primary molars using the radiographic International Caries Detection and Assessment System (ICDAS)., Methods: A study was conducted on 196 children aged 3-9 years old who underwent the clinical examination and bitewing radiography during baseline and 6-month (and over) follow-up visits. The primary molars bitewing radiographs with initial enamel caries (RA1 and RA2) or outer dentine caries (RA3) of proximal surfaces were included. Caries advancement was scored using ICDAS criteria and statistical analyses with the chi-square test. Median survival time was evaluated using Kaplan-Meier survival curves and log-rank tests., Results: A total of 439 surfaces of primary molars were included in this study and an averaged follow-up period of enamel and dentine caries group were 18.3 ± 9.6 months and 16.5 ± 9.5 months respectively. The progression of proximal enamel lesions significantly differed between primary maxillary and mandibular molars (p = 0.002) and among each patient's primary mandibular second molar and the others (p = 0.002). On the contrary, the outer dentine caries of each group of primary molars was not different. The median survival time of the initial enamel proximal caries (23.30 months) was non-significantly longer than that of the dentine (20.80 months)., Conclusions: Progressions of the initial enamel proximal caries were significantly different among primary molars at the average 18.3-month follow-up. The median survival period of the enamel proximal caries was more extended than that of dentine but without statistical difference. These results provide essential information for dentists regarding an appropriate appointment for bitewing examinations., (© 2024. The Author(s), under exclusive licence to European Academy of Paediatric Dentistry.)

Objectives: Dental radiographs, particularly bitewing radiographs, are widely used in dental diagnosis and treatment Dental image segmentation is difficult for various reasons, such as intricate structures, low contrast, noise, roughness, and unclear borders, resulting in poor image quality. Recent developments in deep learning models have improved performance in analyzing dental images. In this research, our primary objective is to determine the most effective segmentation technique for bitewing radiographs based on different metrics: accuracy, training time, and the number of training parameters as a reflection of architectural cost., Methods: In this research, we employ several deep learning models, namely Resnet-18, Resnet-50, Xception, Inception Resnet v2, and Mobilenetv2, to segment bitewing radiographs. The process begins by importing the radiographs into MATLAB®(MathWorks Inc), where the images are first improved, then segmented using the graph cut method based on regions to produce a binary mask that distinguishes the background from the original X-ray., Results: The deep learning models were trained on 298 and 99 radiograph training and validation sets and were evaluated using 99 images from the testing set. We also compare the segmentation model using several criteria, including accuracy, speed, and size, to determine which network is superior. Furthermore, we compare our findings with prior research to provide a comprehensive understanding of the advancements made in dental image segmentation. The accurate segmentation achieved was 93.67% and 94.42% by the Resnet-18 and Resnet-50 models, respectively., Conclusion: This research advances dental image analysis and facilitates more accurate diagnoses and treatment planning by determining the best segmentation technique. The outcomes of this study can guide researchers and practitioners in selecting appropriate segmentation methods for practical dental image analysis., (© 2023. The Author(s) under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology.)

Diagnosis of proximal caries is a difficult task. Artificial intelligence (AI) enabled diagnosis is gaining momentum. Therefore, it is of interest to evaluate the effectiveness of an artificial intelligence (AI) smart phone application for bitewing radiography towards real-time caries lesion detection. The Efficient Det-Lite1 artificial neural network was used after training 100 radiographic images obtained from the department of Oral Medicine. Trained model was then installed in a Google Pixel 6 (GP6) smartphone as artificial intelligence app. The back-facing mobile phone video camera of GP6 was utilised to detect caries lesions on 100 bitewing radiographs (BWR) with 80 carious lesion in real-time. Two different techniques such as scanning the static BWR on laptop with a moving mobile and scanning the moving radiograph on the laptop with stationery mobile were used. The average value of sensitivity/precision/F1 scores for both the techniques was 0.75/0.846 and 0.795 respectively. AI programme using the rear-facing mobile phone video camera was found to detect 75% of caries lesions in real time on 100 BWR with a precision of 84.6%. Thus, the use of AI with smart phone app is useful for caries diagnosis which is readily accessible, easy to use and fast., (© 2024 Biomedical Informatics.)

The study aimed to evaluate the impact of image size, area of detection (IoU) thresholds and confidence thresholds on the performance of the YOLO models in the detection of dental caries in bitewing radiographs. A total of 2575 bitewing radiographs were annotated with seven classes according to the ICCMS ™ radiographic scoring system. YOLOv3 and YOLOv7 models were employed with different configurations, and their performances were evaluated based on precision, recall, F1-score and mean average precision (mAP). Results showed that YOLOv7 with 640 × 640 pixel images exhibited significantly superior performance compared to YOLOv3 in terms of precision (0.557 vs. 0.268), F1-score (0.555 vs. 0.375) and mAP (0.562 vs. 0.458), while the recall was significantly lower (0.552 vs. 0.697). The following experiment found that the overall mAPs did not significantly differ between 640 × 640 pixel and 1280 × 1280 pixel images, for YOLOv7 with an IoU of 50% and a confidence threshold of 0.001 (p = 0.866). The last experiment revealed that the precision significantly increased from 0.570 to 0.593 for YOLOv7 with an IoU of 75% and a confidence threshold of 0.5, but the mean-recall significantly decreased and led to lower mAPs in both IoUs. In conclusion, YOLOv7 outperformed YOLOv3 in caries detection and increasing the image size did not enhance the model's performance. Elevating the IoU from 50% to 75% and confidence threshold from 0.001 to 0.5 led to a reduction of the model's performance, while simultaneously improving precision and reducing recall (minimizing false positives and negatives) for carious lesion detection in bitewing radiographs., (© 2023. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Objectives: To assess the feasibility of the YOLOv3 model under the intersection over union (IoU) thresholds of 0.5 (IoU 50 ) and 0.75 (IoU 75 ) for caries detection in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™)., Materials and Methods: We trained the YOLOv3 model by feeding 994 annotated radiographs with the IoU 50 and IoU 75 thresholds. The testing procedure (n = 175) was subsequently conducted to evaluate the model's prediction metrics on caries classification based on the ICCMS™ radiographic scoring system., Results: Regarding the 4-class classification representing caries severity, YOLOv3 could accurately detect and classify enamel caries and initial dentin caries (class RA) (IoU 50 vs IoU 75 : precision, 0.75 vs 0.71; recall, 0.67 vs 0.64). Concerning the 7-class classification signifying specific caries depth (class 0, healthy tooth; classes RA1-3, initial caries affecting outer half, inner half of enamel, and the outer 1/3 of dentin; class RB4, caries extending to the middle 1/3 of dentin; classes RC5-6, extensively cavitated caries affecting the inner 1/3 of dentin and involving the pulp chamber), YOLOv3 could accurately detect and classify caries with pulpal exposure (class RC6) (IoU 50 vs IoU 75 : precision, 0.77 vs 0.73; recall, 0.61 vs 0.57) but it failed to predict the outer half of enamel caries (class RA1) (IoU 50 vs IoU 75 : precision, 0.35 vs 0.32; recall, 0.23 vs 0.21)., Conclusions: YOLOv3 yielded acceptable performances in both IoU 50 and IoU 75 . Although the performance metrics decreased in the 7-class detection, the two thresholds revealed comparable results. However, the model could not consistently detect initial-stage caries affecting the outermost surface of the enamel., Clinical Relevance: YOLOv3 could be implemented to detect and classify dental caries according to the ICCMS™ classification with acceptable performances to assist dentists in making treatment decisions., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The aim of this study was to assess the reliability of three diagnostic methods (near-infrared transillumination (NIRT), bitewing radiographs (BW), and clinical images (CI)) to detect occlusal carious lesions in a low caries risk population. This retrospective analysis included one hundred and eighty-eight occlusal surfaces, scored as sound surface, early lesion, or distinct lesion. We evaluated the agreement between and within the methods over time. Kappa statistics tested the correlation between the methods. Examiners detected occlusal early lesions more frequently with visual examination and NIRT and the same lesions were confirmed on the 2-year follow-up. Within the limitations of this study, we were able to establish that early occlusal lesions can be detected and monitored over time using NIRT and visual exam, while BW scores showed mostly sound surfaces at both examinations. NIRT combined with clinical examination can be considered appropriate to detect and monitor early enamel caries on the occlusal surface in low caries-risk populations.

Introduction The dental students are trained to identify the proximal carious lesion using clinical tools and radiography over three years of academic curriculum. During these years the students are expected to learn detection of incipient carious lesions and take appropriate preventive/restorative measure. Method This study aimed at evaluating the ability of the students and interns to detect only-enamel proximal caries on the five digital bitewing radiographs. The digital bitewing radiographs were having incipient carious lesions involving enamel on proximal surface of mandibular first molars. Results A total of 101 participants (M = 29, F = 72) from fifth (D5) and sixth (D6) years of dentistry evaluated the radiographs and the KR 20 values for D5, D6, and total sample were 0.79, 0.64, and 0.41 respectively. Conclusion Overall students' assessment of detection of incipient carious lesion was low. There is need to enhance clinical and radiological cognitive skills among students with emphasis on interdisciplinary learning objectives., Competing Interests: The authors have declared financial relationships, which are detailed in the next section., (Copyright © 2022, Elnawawy et al.)

Objective: The objective of this retrospective study was to find out (i) the prevalence of deep carious lesions, both untreated and previously treated, among 14- and 15-year olds and (ii) how deep carious lesions were managed in a Finnish public health care setting., Materials and Methods: A random sample of 278 patients was taken from 3990 patients at the oral health care of the City of Helsinki. Radiographic subsample consisted of patients with bitewing and periapical radiographs (n = 128, 46% of the total sample). Deep carious lesions (extending to at least the inner half of dentine), deep restorations, direct pulp cappings, root canal treatments, and extractions in permanent premolars and molars were recorded from the radiographs. Patients with untreated deep carious lesions were followed up for 24 months., Results: In the total sample 12% had at least one untreated deep carious lesion, 10% at least one deep restoration, and 19% at least one untreated or previously treated deep carious lesion. The follow-up cohort included 48 deep carious lesions in 26 patients. Complete excavation was the most frequently chosen method (81% for lesions reaching the inner half of dentine and 56% the inner third or deeper), followed by stepwise excavation (19% and 37%, respectively)., Conclusions: One-fifth of 14-15-year-olds had at least one untreated or previously treated deep carious lesion. The choice for the carious tissue removal did not follow the current recommendations for less invasive methods., Clinical Relevance: Continuing education is needed to improve the diagnostics and management of deep carious lesions., (© 2022. The Author(s).)

Objective: To create and validate two new Image Receptor-Holding devices (IRHDs) to reduce proximal surfaces overlapping in bitewing radiography in comparison to a regular well-established and commercially available IRHD., Methods: Two IRHDs for bitewing radiographs with a wedge on the biting surface were designed and 3D-printed. These IRHDs, with a large wedge (Pr-Lw) and small wedge (Pr-Sw), were compared with a regular commercially available IRHD (Rinn XCP ® ) during image acquisition of bitewing radiographs of four posterior regions (one upper region and three lower regions) in two dry skulls and mandibles. A total of 156 interproximal regions on bitewing radiographs were radiographed by 13 oral radiology graduate students and independently assessed by two oral radiologists (10 years of experience). IRHDs were compared by Cochran's Q test regarding the number of overlapped proximal surfaces in the acquired radiographs with a significance level of 5%., Results: The observers were in perfect agreement (κ = 1.0) to classify the proximal surfaces overlapping. The Pr-Lw IRHD presented the lowest number of surfaces overlapping (19.2%) followed by the Pr-Sw IRHD (48.1%) and the XCP ® IRHD with the highest surfaces overlapping (71.2%). The Pr-Lw IRHD surfaces overlapping was statistically different from the XCP IRHD ( p < 0.001), and the Pr-Sw IRHD ( p = 0.014)., Conclusions: The Pr-Lw IRHD demonstrated the most efficient performance in overlapping surfaces reduction, compared with the Pr-Sw IRHD and the XCP ® IRHD in adult dry skulls and mandibles.

The aim of this study was to present an optimal diagnostic protocol by comparing and analyzing a conventional examination and the quantitative light-induced fluorescence (QLF) technique. Selected were 297 teeth of 153 patients to take QLF images and bitewing radiographs. Occlusal dental caries, proximal dental caries and cracks were evaluated and scored using QLF, X-ray and/or visual criteria. The sensitivity, specificity, and area under the curve (AUC) of a receiver operating characteristic analysis were calculated. Two fluorescence parameters (|ΔFmax| and ΔRmax) were utilized to evaluate the fluorescence pattern according to the severity of lesions based on QLF or X-ray criteria. QLF showed higher scores for detecting occlusal dental caries and cracks than the conventional method. ΔRmax increased more clearly than ΔFmax did with occlusal dental caries. The |ΔFmax| values of occlusal dental caries, proximal dental caries and cracks showed good AUC levels (0.84, 0.81 and 0.83, respectively). The ΔRmax of occlusal dental caries showed the highest AUC (0.91) and the ΔRmax of proximal dental caries showed a fail level (0.59) compared to bitewing radiographs. The QLF image could visualize and estimate the degree of occlusal dental caries or cracks. Consequently, the QLF technique may be an adjunct tool to conventional methods for the detection of occlusal caries and peripheral cracks.

Objectives: The aim of this study is to assess the accuracy of bitewing radiograph interpretation of predoctoral students, residents and general dentists who work under different core curriculum of dental education and healthcare policy., Methods: A total of 118 examiners including predoctoral dental students, residents and general dentists from USA and Japan were tasked with evaluating a series of bitewing radiographs and diagnosing interproximal carious lesions. This study was approved by the Harvard Medical School Institutional Review Board (IRB). Participants graded interproximal aspects of those images and categorized the following criteria; "intact", "enamel caries <1/2 width", "enamel caries >1/2 width" or "caries into dentin". The gold-standard was determined by the consensus of two HSDM full-time faculty., Results: There was significant difference in the sensitivity for all three caries levels between the two groups but there was no significant difference on specificity. The positive-predictive and negative-predictive values of the USA group for the enamel caries (<1/2 of enamel) were significantly higher than the Japanese group. The average of AUC (ROC) was significantly higher in the USA group (0.885 ± 0.04) than the Japanese group (0.785 ± 0.08, p<0.01)., Conclusion: Teaching and adopting BW radiographs for diagnosis of interproximal caries is integral for dental providers to accurately and efficiently use them in their practices. It is critical that all dental educators approach policymakers to explain the importance of BW radiographs and promote their efficacy for prevention and early diagnosis of interproximal caries.

Objective: To assess the dimensions of root trunk lengths (RTL) in maxillary and mandibular molars and evaluate their correlation with the mesio-distal (MD) width of the tooth at the level of cemento enamel junction and Inter-Radicular Angle (IRA) at the point of roots separation., Materials and Methods: Radiographic measurements of a total of 955 molars from 120 study subjects satisfying the inclusion criteria were analyzed. The sampling frame consisted of radiographs from the outpatient dental clinic of the College of Dentistry, King Saud University, Riyadh, Saudi Arabia. The linear measurements, including the width, length and depth of the root trunks under investigation were made using flexible translucent plastic grid while; the angles were measured by rotary German caliper protractor., Result: The mean RTL dimension for molars were 4.31 mm (3-8 mm). The mean MD width of the molars was 10.02 mm and the mean measured IRA was 34.12°. The longest RT was observed in maxillary 1st molar (4.40 mm) while the shortest radiographic RT length was recorded for the mandibular 2nd molars (4.13 mm). Statictically insignificant correlation (p = 0.090) was observed between RTL with the MD width of the tooth, whereas appreciable significance resulted between RTL and IRA (p < 0.001)., Conclusion: Knowledge about the molar teeth RT length of the study population will aid the dental clinician in better decision making during management of periodontal disease conditions.

Background and Objective: Proximal caries detection is of great importance because of the rapid rate of caries progression and the difficulty in determining the absence or presence of a lesion in primary dentition. Although, various methods for caries diagnosis offer good diagnostic performances, they provide varying sensitivities for detecting proximal carious lesions. The objective of this study was to compare, in vivo, the accuracy of DIAGNOdent and bitewing radiography at detecting proximal caries in primary teeth., Materials and Methods: One Hundred and one primary maxillary and mandibular molars without obvious cavities of children between the age group of 3 and 10 years were included. The teeth were first subjected to DIAGNOdent examination followed by bitewing radiography. The specificity and sensitivity of the systems were calculated., Results: At the dentin caries (D3) level, the sensitivity of DIAGNOdent and bitewing radiography was 78.5%; at the enamel caries (D1 and D2) level it was 39.12% and for the sound teeth (D0) it was found to be 76.52%. A strong association was observed between the DIAGNOdent and the bitewing radiograph (p < 0.001)., Conclusion: The DIAGNOdent can be used as an alternative diagnostic method in detection of proximal caries in primary teeth. But when seen at the each caries level, the DIAGNOdent is more accurate at the D0 and D3 threshold. How to cite this article: Mepparambath R, Bhat SS, Hegde SK, Anjana G, Sunil M, Mathew S. Comparison of Proximal Caries Detection in Primary Teeth between Laser Fluorescence and Bitewing Radiography: An in vivo Study. Int J Clin Pediatr Dent 2014;7(3):163-167.

The aim of this study was to determine the diagnostic accuracy of swept-source optical coherent tomography (SS-OCT) in detecting and estimating the depth of proximal caries in posterior teeth in vivo. SS-OCT images and bitewing radiographs were obtained from 86 proximal surfaces of 53 patients. Six examiners scored the locations according to a caries lesion depth scale (0-4) using SS-OCT and the radiographs. The results were compared with clinical observations obtained after the treatment. SS-OCT could detect the presence of proximal caries in tomograms that were synthesized based on the backscatter signal obtained from the proximal carious lesion through occlusal enamel. SS-OCT showed significantly higher sensitivity and larger area under the receiver operating characteristic curve than radiographs for the detection of cavitated enamel lesions and dentin caries (Student's t -test, p < 0.05). SS-OCT appears to be a more reliable and accurate method than bitewing radiographs for the detection and estimation of the depth of proximal lesions in the clinical environment., (Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)