Radiation exposure during orthodontic treatment: risk to children and adolescents.

OBJECTIVES: To estimate radiation risk to children and adolescents during orthodontic treatment by retrieving number and type of radiographs from the patient records. MATERIAL AND METHODS: Radiographs, along with justifications for radiation exposure, were obtained retrospectively from the patient records of 1,790 children and adolescents referred to two Swedish orthodontic clinics. Data were grouped according to treatment stage: treatment planning, treatment, and follow-up. Estimated risk was calculated using the concept of effective dose. RESULTS: Each patient had received around seven radiographs for orthodontic purposes. The most common exposures during treatment planning were one panoramic, one lateral, and three intraoral periapical radiographs. A small number of patients received a tomographic examination (8.2%). Few justifications for treatment planning and follow-up, but more in the actual treatment stage, had been recorded. The most common examinations were to assess root resorption and the positions of unerupted teeth, or simply carry out an unspecified control. The estimated risk of developing fatal cancer was considered low. The radiation risk from orthodontic treatment was equivalent to about 5-10 days of natural background radiation. CONCLUSIONS: Children and adolescents sometimes undergo multiple radiographic examinations, but despite the low radiation burden, accumulated radiation exposure should be considered and justified in young patients.

Artificial intelligence in age and sex determination using maxillofacial radiographs: A systematic review.

In the past few years, there has been an enormous increase in the application of artificial intelligence and its adoption in multiple fields, including healthcare. Forensic medicine and forensic odontology have tremendous scope for development using AI. In cases of severe burns, complete loss of tissue, complete or partial loss of bony structure, decayed bodies, mass disaster victim identification, etc., there is a need for prompt identification of the bony remains. The mandible, is the strongest bone of the facial region, is highly resistant to undue mechanical, chemical or physical impacts and has been widely used in many studies to determine age and sexual dimorphism. Radiographic estimation of the jaw bone for age and sex is more workable since it is simple and can be applied equally to both dead and living cases to aid in the identification process. Hence, this systematic review is focused on various AI tools for age and sex determination in maxillofacial radiographs. The data was obtained through searching for the articles across various search engines, published from January 2013 to March 2023. QUADAS 2 was used for qualitative synthesis, followed by a Cochrane diagnostic test accuracy review for the risk of bias analysis of the included studies. The results of the studies are highly optimistic. The accuracy and precision obtained are comparable to those of a human examiner. These models, when designed with the right kind of data, can be of tremendous use in medico legal scenarios and disaster victim identification.

Deep learning for determining the difficulty of endodontic treatment: a pilot study.

BACKGROUND: To develop and validate a deep learning model for automated assessment of endodontic case difficulty from periapical radiographs. METHODS: A dataset of 1,386 periapical radiographs was compiled from two clinical sites. Two dentists and two endodontists annotated the radiographs for difficulty using the "simple assessment" criteria from the American Association of Endodontists' case difficulty assessment form in the Endocase application. A classification task labeled cases as "easy" or "hard", while regression predicted overall difficulty scores. Convolutional neural networks (i.e. VGG16, ResNet18, ResNet50, ResNext50, and Inception v2) were used, with a baseline model trained via transfer learning from ImageNet weights. Other models was pre-trained using self-supervised contrastive learning (i.e. BYOL, SimCLR, MoCo, and DINO) on 20,295 unlabeled dental radiographs to learn representation without manual labels. Both models were evaluated using 10-fold cross-validation, with performance compared to seven human examiners (three general dentists and four endodontists) on a hold-out test set. RESULTS: The baseline VGG16 model attained 87.62% accuracy in classifying difficulty. Self-supervised pretraining did not improve performance. Regression predicted scores with ± 3.21 score error. All models outperformed human raters, with poor inter-examiner reliability. CONCLUSION: This pilot study demonstrated the feasibility of automated endodontic difficulty assessment via deep learning models.

An Artificial Intelligence model for implant segmentation on periapical radiographs.

OBJECTIVE: To segment dental implants on PA radiographs using a Deep Learning (DL) algorithm. To compare the performance of the algorithm relative to ground truth determined by the human annotator. Methodology: Three hundred PA radiographs were retrieved from the radiographic database and consequently annotated to label implants as well as teeth on the LabelMe annotation software. The dataset was augmented to increase the number of images in the training data and a total of 1294 images were used to train, validate and test the DL algorithm. An untrained U-net was downloaded and trained on the annotated dataset to allow detection of implants using polygons on PA radiographs. RESULTS: A total of one hundred and thirty unseen images were run through the trained U-net to determine its ability to segment implants on PA radiographs. The performance metrics are as follows: accuracy of 93.8%, precision of 90%, recall of 83%, F-1 score of 86%, Intersection over Union of 86.4% and loss = 21%. CONCLUSIONS: The trained DL algorithm segmented implants on PA radiographs with high performance similar to that of the humans who labelled the images forming the ground truth.

Efficacy of electronic apex locators in comparison with intraoral radiographs in working length determination- a systematic review and meta-analysis.

BACKGROUND: Successful endodontic treatment needs accurate determination of working length (WL). Electronic apex locators (EALs) were presented as an alternative to radiographic methods; and since then, they have evolved and gained popularity in the determination of WL. However, there is insufficient evidence on the post-operative pain, adequacy, and accuracy of EALs in determining WL. OBJECTIVE: The systematic review and meta-analysis aims to gather evidence regarding the effectiveness of EALs for WL determination when compared to different imaging techniques along with postoperative pain associated with WL determination, the number of radiographs taken during the procedure, the time taken, and the adverse effects. METHODS: For the review, clinical studies with cross-over and parallel-arm randomized controlled trials (RCTs) were searched in seven electronic databases, followed by cross-referencing of the selected studies and related research synthesis. Risk of bias (RoB) assessment was carried out with Cochrane's RoB tool and a random-effects model was used. The meta-analysis was performed with the RevMan software 5.4.1. RESULTS: Eleven eligible RCTs were incorporated into the review and eight RCTs into the meta-analysis, of which five had high RoB and the remaining six had unclear RoB. Following meta-analysis, no significant difference in postoperative pain was found among the EAL and radiograph groups (SMD 0.00, CI .29 to .28, 354 participants; P value = 0.98). Radiograph group showed better WL accuracy (SMD 0.55, CI .11 to .99, 254 participants; P value = 0.02), while the EAL group had 10% better WL adequacy (RR 1.10, CI 1.03-1.18, 573 participants; P value = 0.006). CONCLUSION: We found very low-certainty evidence to support the efficacy of different types of EAL compared to radiography for the outcomes tested. We were unable to reach any conclusions about the superiority of any type of EAL. Well-planned RCTs need to be conducted by standardizing the outcomes and outcome measurement methods.

Relato de caso clínico de infecção odontogênica resultando em complicação cervicofacial / Reporte de caso clínico de infección odontogênica com resultado de complicación cervicofacial / Clinical case reportof odontogenic infectionresulting cervicofacial complication

Introdução: A saúde bucal é um aspecto que não deve ser subestimado pelos pacientes, principalmente se considerar que as infecções odontogênicas podem levar a quadros graves, incluindo complicações cervicotorácicas, como Mediastinite e cervicofaciais, como Angina de Ludwig. Para tanto, é imprescindível que os profissionais da odontologia saibam reconhecer os principais sinais e sintomas dessas infecções, sua evolução, conhecer as complicações associadas e qual o manejo adequado. Objetivo: Assim, é objetivo deste trabalho, relatar, discutir um caso clínico de uma infecção odontogênica grave que acarretou em complicação cervical, com trajeto em direção ao mediastino, necessitando manejo multidisciplinar, e explorar os principais aspectos desse quadro e a conduta necessária, que exige, no mínimo, intervenção cirúrgica, antibioticoterapia e manutenção das vias aéreas. Relato de caso: O caso trata de um paciente com infecção odontogênica, iniciada como uma pericoronarite do dente 38 semieruptado, que evoluiu para a área cervical, demandando imediata drenagem nesta região pois encaminhava-se para uma mediastinite. Após a drenagem cervical e antibioticoterapia e, assim que houve redução do trismo, foi removido o dente 38, evoluindo para a cura.Conclusões:As infecções odontogênicas, principalmente as que acometem os espaços fasciais e cervicais profundos, são potencialmente graves e devem ter suas principais manifestações clínicas entre os domínios de conhecimento dos profissionais Bucomaxilofaciais, pois necessitam de diagnóstico preciso, manejo rápido e tratamento adequado e precoce, considerando a velocidade com que podem evoluir (AU).

Introduction: Oral healthis an aspect that should not be underestimated by patients, especially considering that dental infections can lead to serious symptoms, including cervicothoracic complications, such as Mediastinitis and cervicofacial complications, such as Ludwig's Angina. Therefore, it is essential that dental professionals know how to recognize the main signs and symptoms of these infections, their evolution, know the associated complications and appropriate management.Objective: Thus, this work aims to report and discuss a clinical case of a serious odontogenic infection that resulted in a cervical complication, with a path towards the mediastinum, requiring multidisciplinary management, and to explore the main aspects of this condition and the necessary conduct, which requires, at least, surgical intervention, antibiotic therapy and airway maintenance.Case report: The case concerns a patient with odontogenic infection, which began as pericoronitis of semi-erupted tooth 38, which progressed to the cervical area, requiring immediate drainage in this region as it was heading towards mediastinitis. After cervical drainage and antibiotic therapy and, as soon as the trismus was reduced, tooth 38 was removed, progressing towards healing.Conclusions: Odontogenic infections, especially those that affect the fascial and deep cervical spaces, are potentially serious and should have their main clinical manifestations among the domains of knowledge ofOral and Maxillofacial professionals, as they require accurate diagnosis, rapid management and adequate and early treatment, considering the speed at which they can evolve (AU).

Introducción: La salud bucal es un aspecto que los pacientes no deben subestimar, especialmente considerando que las infecciones odontógenas pueden derivar en afecciones graves, incluidas complicaciones cervicotorácicas, como la mediastinitis, y complicaciones cervicofaciales, como la angina de Ludwig.Para ello, es fundamental que los profesionales odontológicos sepan reconocer las principales señalesy síntomas de estas infecciones, su evolución, conocer las complicaciones asociadas y el manejo adecuado.Objetivo: Así,el objetivo de este trabajo es reportar y discutir un caso clínico de infección odontogénica grave que resultó en una complicación cervical, con trayecto hacia el mediastino, que requirió manejo multidisciplinario, y explorar los principales aspectos de esta condicióny las medidas necesarias, que requiere, como mínimo, intervención quirúrgica, terapia con antibióticos y mantenimiento de las vías respiratorias.Reporte de caso: El caso se trata de un paciente con una infección odontogénica, que comenzó como pericoronaritis del diente 38 semi-erupcionado, la cual progresó hacia la zona cervical, requiriendo drenaje inmediato en esta región ya que se encaminaba para una mediastinitis.Después del drenaje cervical y la terapia antibiótica y, una vez reducido el trismo, se extrajo el diente 38, evolucijjonando hacia la cura.Conclusiones: Las infecciones odontogénicas, especialmente aquellas que afectan los espacios fasciales y cervicales profundos, son potencialmente graves y deben tener sus principales manifestaciones clínicas entre los dominios del conocimiento de los profesionales Orales y Maxilofaciales, pues requieren de un diagnóstico certero, un manejo rápido y un tratamiento adecuado y temprano, considerando la velocidad a la que pueden evolucionar (AU).

Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the caries detection performances of recent multifarious deep networks with clinical dentist level as a bridge. METHODS: Based on the self-collected periapical radiograph dataset in clinic, four most popular deep networks in two types, namely YOLOv5 and DETR object detection networks, and UNet and Trans-UNet segmentation networks, were included in the comparison study. Five dentists carried out the caries detection on the same testing dataset for reference. Key tooth-level metrics, including precision, sensitivity, specificity, F1-score and Youden index, were obtained, based on which statistical analysis was conducted. RESULTS: The F1-score order of deep networks is YOLOv5 (0.87), Trans-UNet (0.86), DETR (0.82) and UNet (0.80) in caries detection. A same ranking order is found using the Youden index combining sensitivity and specificity, which are 0.76, 0.73, 0.69 and 0.64 respectively. A moderate level of concordance was observed between all networks and the gold standard. No significant difference (p > 0.05) was found between deep networks and between the well-trained network and dentists in caries detection. CONCLUSIONS: Among investigated deep networks, YOLOv5 is recommended to be priority for caries detection in terms of its high metrics. The well-trained deep network could be used as a good assistance for dentists to detect and diagnose caries. CLINICAL SIGNIFICANCE: The well-trained deep network shows a promising potential clinical application prospect. It can provide valuable support to healthcare professionals in facilitating detection and diagnosis of dental caries.

Optimizing radiation safety in dentistry: Clinical recommendations and regulatory considerations.

BACKGROUND: The value of dental radiographs to oral health care decision making must be balanced with radiation safety to minimize patient exposure and occupational risk of oral health care providers. This review summarizes recommendations and regulatory guidance regarding dental radiography and cone-beam computed tomography. An expert panel presents recommendations on radiation safety, appropriate imaging practices, and reducing radiation exposure. TYPES OF STUDIES REVIEWED: A systematic search run in Ovid MEDLINE, Embase, and Cochrane Database of Systematic Reviews identified relevant topical systematic reviews, organizational guidelines, and regulatory reviews published in the peer-reviewed literature since 2010. A supplemental search of the gray literature (eg, technical reports, standards, and regulations) identified topical nonindexed publications. Inclusion criteria required relevance to primary oral health care (ie, general or pediatric dentistry). RESULTS: A total of 95 articles, guidance documents, and regulations met the inclusion criteria. Resources were characterized as applicable to all modalities, operator and occupational protection, dose reduction and optimization, and quality assurance and control. PRACTICAL IMPLICATIONS: Understanding factors affecting imaging safety and applying fundamental principles of radiation protection consistent with federal, state, and local requirements are essential for limiting patient ionizing radiation exposure, in conjunction with implementing optimal imaging procedures to support prudent use of dental radiographs and cone-beam computed tomographic imaging. The regulatory guidance and best practice recommendations summarized in this article should be followed by dentists and other oral health care providers.

Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis.

OBJECTIVES: Improved tools based on deep learning can be used to accurately number and identify teeth. This study aims to review the use of deep learning in tooth numbering and identification. METHODS: An electronic search was performed through October 2023 on PubMed, Scopus, Cochrane, Google Scholar, IEEE, arXiv, and medRxiv. Studies that used deep learning models with segmentation, object detection, or classification tasks for teeth identification and numbering of human dental radiographs were included. For risk of bias assessment, included studies were critically analysed using quality assessment of diagnostic accuracy studies (QUADAS-2). To generate plots for meta-analysis, MetaDiSc and STATA 17 (StataCorp LP, College Station, TX, USA) were used. Pooled outcome diagnostic odds ratios (DORs) were determined through calculation. RESULTS: The initial search yielded 1618 studies, of which 29 were eligible based on the inclusion criteria. Five studies were found to have low bias across all domains of the QUADAS-2 tool. Deep learning has been reported to have an accuracy range of 81.8%-99% in tooth identification and numbering and a precision range of 84.5%-99.94%. Furthermore, sensitivity was reported as 82.7%-98% and F1-scores ranged from 87% to 98%. Sensitivity was 75.5%-98% and specificity was 79.9%-99%. Only 6 studies found the deep learning model to be less than 90% accurate. The average DOR of the pooled data set was 1612, the sensitivity was 89%, the specificity was 99%, and the area under the curve was 96%. CONCLUSION: Deep learning models successfully can detect, identify, and number teeth on dental radiographs. Deep learning-powered tooth numbering systems can enhance complex automated processes, such as accurately reporting which teeth have caries, thus aiding clinicians in making informed decisions during clinical practice.

Australian Dentist's Knowledge and Perceptions of Factors Affecting Radiographic Interpretation.

BACKGROUND: Errors of interpretation of radigraphic images, also known as interpretive errors, are a critical concern as they can have profound implications for clinical decision making. Different types of interpretive errors, including errors of omission and misdiagnosis, have been described in the literature. These errors can lead to unnecessary or harmful treat/or prolonged patient care. Understanding the nature and contributing factors of interpretive errors is important in developing solutions to minimise interpretive errors. By exploring the knowledge and perceptions of dental practitioners, this study aimed to shed light on the current understanding of interpretive errors in dentistry. METHODS: An anonymised online questionnaire was sent to dental practitioners in New South Wales (NSW) between September 2020 and March 2022. A total of 80 valid responses were received and analysed. Descriptive statistics and bivariate analysis were used to analyse the data. RESULTS: The study found that participants commonly reported interpretive errors as occurring 'occasionally', with errors of omission being the most frequently encountered type. Participants identified several factors that most likely contribute to interpretive errors, including reading a poor-quality image, lack of clinical experience and knowledge, and excessive workload. Additionally, general practitioners and specialists held different views regarding factors affecting interpretive errors. CONCLUSION: The survey results indicate that dental practitioners are aware of the common factors associated with interpretive errors. Errors of omission were identified as the most common type of error to occur in clinical practice. The findings suggest that interpretive errors result from a mental overload caused by factors associated with image quality, clinician-related, and image interpretation. Managing and identifying solutions to mitigate these factors are crucial for ensuring accurate and timely radiographic diagnoses. The findings of this study can serve as a foundation for future research and the development of targeted interventions to enhance the accuracy of radiographic interpretations in dentistry.

Two-Dimensional Radiographs and Cone-beam Computed Tomography Assessment of Concentrated Growth Factor and Platelet-Rich Fibrin Scaffolds in Regenerative Endodontic Treatment of Immature Incisors with Periapical Radiolucency: A Randomized Clinical Trial.

INTRODUCTION: The primary aim of this study was to compare the radiographic changes of immature incisors with periapical radiolucency after treatment with platelet-rich fibrin (PRF) and concentrated growth factor (CGF) platelet concentrate scaffolds as well as assessment of the clinical success rate over 12 months. The secondary aim was to monitor the radiographic changes in terms of reduction of periapical lesion diameter (PALD), root dentine thickness (RDT), root length (RL), and apical foramen width (AFW). The tertiary aim was to assess and pulp responses, after 12 months. METHODS: Fifty six children with seventy necrotic, single-rooted maxillary incisors with periapical radiolucency were treated with either CGF or PRF scaffolds (35 teeth per group). Two patients with 4 teeth (2 teeth in each group) failed to attain the follow-up recalls. Radiographic changes in terms of reduction of PALD, RDT, RL, and AFW were monitored using a 2-dimensional (2D) radiograph and cone-beam computed tomography (CBCT) scan. The clinical performance of teeth receiving both scaffolds was assessed after 6 and 12 months. Categorical and continuous data were analyzed using the chi-square test and the t test, respectively. The time and group effects on the means of different radiographic dimensions were tested using the general linear model. Bland-Altman plots were used to assess the level of agreement between the 2D radiographs and CBCT. The level of significance was defined at 0.05 and a 95% confidence interval. RESULTS: The means of PALD and RL showed significant enhancement in the CGF group compared to the PRF group (P < .05). While the difference between the 2 scaffolds in terms of RDT and AFW was not significant (P > .05). The findings of the 2D radiograph and CBCT were consistent. Clinically, both scaffold success rates were similar (93.9%) over the follow-up intervals. The influence of study independent variables had no significant effect on the success of the regenerative endodontic procedures outcome (P > .05). There was no significant difference in the positive pulp responses to the thermal and electric pulp tests after one year of treatment (P > .05). CONCLUSIONS: According to the short-term follow-up, PRF and CGF were successful in treating immature teeth with periapical radiolucency by regenerative endodontics. Both scaffold systems induced periapical healing and root lengthening with significant superiority of CGF.

AAPM Task Group Report 261: Comprehensive quality control methodology and management of dental and maxillofacial cone beam computed tomography (CBCT) systems.

Cone-beam computed tomography (CBCT) systems specifically designed and manufactured for dental, maxillofacial imaging (MFI) and otolaryngology (OLR) applications have been commercially available in the United States since 2001 and have been in widespread clinical use since. Until recently, there has been a lack of professional guidance available for medical physicists about how to assess and evaluate the performance of these systems and about the establishment and management of quality control (QC) programs. The owners and users of dental CBCT systems may have only a rudimentary understanding of this technology, including how it differs from conventional multidetector CT (MDCT) in terms of acceptable radiation safety practices. Dental CBCT systems differ from MDCT in several ways and these differences are described. This report provides guidance to medical physicists and serves as a basis for stakeholders to make informed decisions regarding how to manage and develop a QC program for dental CBCT systems. It is important that a medical physicist with experience in dental CBCT serves as a resource on this technology and the associated radiation protection best practices. The medical physicist should be involved at the pre-installation stage to ensure that a CBCT room configuration allows for a safe and efficient workflow and that structural shielding, if needed, is designed into the architectural plans. Acceptance testing of new installations should include assessment of mechanical alignment of patient positioning lasers and x-ray beam collimation and benchmarking of essential image quality performance parameters such as image uniformity, noise, contrast-to-noise ratio (CNR), spatial resolution, and artifacts. Several approaches for quantifying radiation output from these systems are described, including simply measuring the incident air-kerma (Kair) at the entrance surface of the image receptor. These measurements are to be repeated at least annually as part of routine QC by the medical physicist. QC programs for dental CBCT, at least in the United States, are often driven by state regulations, accreditation program requirements, or manufacturer recommendations.

Assessment of the Occupational Radiation Dose from a Handheld Portable X-ray Unit During Full-mouth Intraoral Dental Radiographs in the Dog and the Cat - A Pilot Study.

Occupational radiation protection is an important consideration in small animal clinics world-wide. With the increased use of portable handheld X-ray devices in veterinary dentistry, concerns related to occupational radiation protection are being raised. Annual occupational dose limits for dental workers are expressed as Total Dose Equivalent (TDE) or Effective Dose. The permitted TDE can vary depending on the anatomical region, ranging from 50 millisieverts (mSv) for the external whole body exposure dose to 500 mSv for external exposure of the skin or an extremity. Although several studies have been performed in human dentistry to establish the amount of backscatter radiation produced using portable handheld X-ray devices, no similar research has been conducted in veterinary dentistry. This study aimed to determine the TDE while acquiring a full mouth intraoral radiograph set in dogs and cats and to estimate the TDE for a handheld X-ray device's operator. For this, the backscatter radiation dose recorded by three sets of monitoring dosimeters located in strategic anatomical areas of the operator was assessed after taking one hundred intraoral radiographs in each group. The study concluded that the backscatter radiation levels were far below the permitted annual occupational doses in the three patient groups of this study. Even though the portable handheld X-ray unit was demonstrated to be a safe dental radiographic unit regarding backscattering radiation, the operator's eye, ovary, and breast regions were exposed to unnecessary radiation.

Sydney Blackman (1898-1971): a pioneer in dental radiology and radiography.

Sydney Blackman, was a consultant radiologist at the Royal Dental Hospital of London between 1931 and 1967. He contributed much to the advance of dento-maxillofacial radiology. His development of the 'rotograph' as the first commercially available dental panoramic machine established dental radiology on a level with medical radiology. Sydney was a major contributor to the establishment of the British Society of Dental and Maxillofacial Radiology.

Fully automated film mounting in dental radiography: a deep learning model.

BACKGROUND: Dental film mounting is an essential but time-consuming task in dental radiography, with manual methods often prone to errors. This study aims to develop a deep learning (DL) model for accurate automated classification and mounting of both intraoral and extraoral dental radiography. METHOD: The present study employed a total of 22,334 intraoral images and 1,035 extraoral images to train the model. The performance of the model was tested on an independent internal dataset and two external datasets from different institutes. Images were categorized into 32 tooth areas. The VGG-16, ResNet-18, and ResNet-101 architectures were used for pretraining, with the ResNet-101 ultimately being chosen as the final trained model. The model's performance was evaluated using metrics of accuracy, precision, recall, and F1 score. Additionally, we evaluated the influence of misalignment on the model's accuracy and time efficiency. RESULTS: The ResNet-101 model outperformed VGG-16 and ResNet-18 models, achieving the highest accuracy of 0.976, precision of 0.969, recall of 0.984, and F1-score of 0.977 (p < 0.05). For intraoral images, the overall accuracy remained consistent across both internal and external datasets, ranging from 0.963 to 0.972, without significant differences (p = 0.348). For extraoral images, the accuracy consistently achieved the highest value of 1 across all institutes. The model's accuracy decreased as the tilt angle of the X-ray film increased. The model achieved the highest accuracy of 0.981 with correctly aligned films, while the lowest accuracy of 0.937 was observed for films exhibiting severe misalignment of ± 15° (p < 0.001). The average time required for the tasks of image rotation and classification for each image was 0.17 s, which was significantly faster than that of the manual process, which required 1.2 s (p < 0.001). CONCLUSION: This study demonstrated the potential of DL-based models in automating dental film mounting with high accuracy and efficiency. The proper alignment of X-ray films is crucial for accurate classification by the model.

Evaluating cone cut in rectangular collimation in intraoral radiography: application of ALADA and radiation stewardship.

OBJECTIVE: Rectangular collimation is a popular method used in intraoral radiography to reduce patient exposure to ionizing radiation. One of the perceived drawbacks of rectangular collimation is the possibility of an increase in cone cut errors ultimately impacting the diagnostic value of the radiographs. Thus, the aim of this study was to explore the frequency of cone cut errors in radiographs taken using a rectangular collimator. MATERIALS AND METHODS: Radiographs taken using PSP plates at Academic Center for Dentistry Amsterdam in the Netherlands by staff and students from January to December 2015 were assessed for cone cut errors. The radiographs were grouped as bitewings, front teeth, inferior premolars and molars, and superior premolars and molars and categorized as no cone cut, cone cut but diagnostically usable, and cone cut but diagnostically not usable. The results were entered into Microsoft Excel and analyzed thereafter. RESULTS: A total of 53,684 radiographs were assessed, 79% had no cone cut errors and consequently 21% had some degree of cone cut. However, the diagnostic value was unaffected in 18% of the radiographs with cone cut. Only 3% of the radiographs were deemed diagnostically unusable due to cone cut. The most common area of cone cut was in the premolar and molar areas while cone cut in the front teeth was least likely to be diagnostically unusable. CONCLUSION: Cone cut from the use of a rectangular collimator does not seem to result in an increase of diagnostically unusable radiographs. Thus, rectangular collimation should be preferred as it decreases the amount of radiation exposure to the patient while producing diagnostically usable radiographs and thus allowing the dental professional to adhere to the ALADA principle and practice radiation stewardship. CLINICAL RELEVANCE: Scientific rationale for the study: rectangular collimation is a method used to reduce patient exposure to ionizing radiation; however, this benefit is negligible if radiographs must be retaken due to cone cut errors that make the radiograph diagnostically unusable. Therefore, the aim of this study was to explore the frequency of cone cut in radiographs taken using a rectangular collimator. PRINCIPAL FINDINGS: cone cut was observed in 21% of the radiographs; however, only 3% of the radiographs were considered diagnostically unusable. PRACTICAL IMPLICATIONS: rectangular collimation does not result in a high number of diagnostically unusable radiographs and should be used to reduce patient exposure to ionizing radiation.

Patient shielding during dentomaxillofacial radiography: Recommendations from the American Academy of Oral and Maxillofacial Radiology.

BACKGROUND: The American Academy of Oral and Maxillofacial Radiology established an ad hoc committee to draft evidence-based recommendations and clinical guidance for the application of patient contact shielding during dentomaxillofacial imaging. TYPES OF STUDIES REVIEWED: The committee reviewed monographs and reports from radiation protection organizations and studies that reported radiation dose to gonads, breasts, and thyroid gland from dentomaxillofacial imaging. RESULTS: Considering the absence of radiation-induced heritable effects in humans and the negligible dose to the gonads and fetus from dentomaxillofacial imaging, the committee recommends discontinuing shielding of the gonads, pelvic structures, and fetuses during all dentomaxillofacial radiographic imaging procedures. On the basis of radiation doses from contemporaneous maxillofacial imaging, the committee considered that the risks from thyroid cancer are negligible and recommends that thyroid shielding not be used during intraoral, panoramic, cephalometric, and cone-beam computed tomographic imaging. PRACTICAL IMPLICATIONS: This position statement informs and educates the reader on evolving radiation protection practices and provides simple, unequivocal guidance to dental personnel to implement these guidelines. State and local authorities should be contacted to update regulations to reflect these recommendations.

An application of the density standard and scaled-pixel-counting protocol to assess the radiodensity of equine incisor teeth affected by resorption and hypercementosis: preliminary advancement in dental radiography.

BACKGROUND: Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) syndrome is a dental disease where the radiographic signs may be quantified using radiographic texture features. This study aimed to implement the scaled-pixel-counting protocol to quantify and compare the image structure of teeth and the density standard in order to improve the identification of the radiographic signs of tooth resorption and hypercementosis using the EOTRH syndrome model. METHODS AND RESULTS: A detailed examination of the oral cavity was performed in 80 horses and maxillary incisor teeth were evaluated radiographically, including an assessment of the density standard. On each of the radiographs, pixel brightness (PB) was extracted for each of the ten steps of the density standard (S1-S10). Then, each evaluated incisor tooth was assigned to one of 0-3 EOTRH grade-related groups and annotated using region of interest (ROI). For each ROI, the number of pixels (NP) from each range was calculated. The linear relation between an original X-ray beam attenuation and PB was confirmed for the density standard. The NP values increased with the number of steps of the density standard as well as with EOTRH degrees. Similar accuracy of the EOTRH grade differentiation was noted for data pairs EOTRH 0-3 and EOTRH 0-1, allowing for the differentiation of both late and early radiographic signs of EOTRH. CONCLUSION: The scaled-pixel-counting protocol based on the use of density standard has been successfully implemented for the differentiation of radiographic signs of EOTRH degrees.