Application of deep learning in isolated tooth identification.

BACKGROUND: Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. METHODS: A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. RESULTS: This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen's Kappa demonstrated good agreement between model prediction and the test set. CONCLUSIONS: This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and fissure sealants in intraoral photos. METHODS: A total of 1020 intraoral photos were collected from 762 volunteers. Teeth, caries and sealants were annotated by two endodontists using the LabelMe tool. ToothNet was developed by modifying the YOLOX framework for simultaneous detection of caries and fissure sealants. The area under curve (AUC) in the receiver operating characteristic curve (ROC) and free-response ROC (FROC) curves were used to evaluate model performance in the following aspects: (i) classification accuracy of detecting dental caries and fissure sealants from a photograph (image-level); and (ii) localization accuracy of the locations of predicted dental caries and fissure sealants (tooth-level). The performance of ToothNet and dentist with 1year of experience (1-year dentist) were compared at tooth-level and image-level using Wilcoxon test and DeLong test. RESULTS: At the image level, ToothNet achieved an AUC of 0.925 (95% CI, 0.880-0.958) for caries detection and 0.902 (95% CI, 0.853-0.940) for sealant detection. At the tooth level, with a confidence threshold of 0.5, the sensitivity, precision, and F1-score for caries detection were 0.807, 0.814, and 0.810, respectively. For fissure sealant detection, the values were 0.714, 0.750, and 0.731. Compared with ToothNet, the 1-year dentist had a lower F1 value (0.599, p < 0.0001) and AUC (0.749, p < 0.0001) in caries detection, and a lower F1 value (0.727, p = 0.023) and similar AUC (0.829, p = 0.154) in sealant detection. CONCLUSIONS: The proposed deep learning model achieved multi-task simultaneous detection in intraoral photos and showed good performance in the detection of dental caries and fissure sealants. Compared with 1-year dentist, the model has advantages in caries detection and is equivalent in fissure sealants detection.

Parental use and acceptance of an accessible, commercially available intraoral camera for teledentistry in their children.

PURPOSE: The potential of combining teledentistry and engaging parents as underutilised resources to monitor paediatric dental health was emphasised during the COVID-19 pandemic and remains underexplored. This study aims to assess parental acceptance and use of a commercially available intraoral camera (IOC) for effective remote monitoring. METHODS: 47 child-parent dyads, where the parent was the main caregiver and the child was treated under general anaesthesia for early childhood caries, were recruited. Caregivers were trained to image their child's teeth on a commercially available IOC. Subsequently, submitted images were reviewed asynchronously by dentists for image quality, presence of dislodged fillings, abscesses, cavitation, and oral hygiene. Post-surgery monitoring was performed using teledentistry at 1 and 2 months and in-person at 4 months. A modified Telehealth Usability Questionnaire (TUQ) was used to record caregiver acceptance for study procedures. RESULTS: A mean TUQ of 6.09 out of 7 was scored by caregivers. Caregiver-reported issues were limited to problems with technique and child uncooperativeness. The number of clear images during the second teledentistry review was improved compared to the first (p = 0.007). 68% of children liked having images of their teeth taken. CONCLUSION: This study supports the feasibility of using an IOC as a clinically appropriate avenue for teledentistry with a high level of caregiver-child acceptance.

Exploring Digital Gingival Shade Matching in Students.

PURPOSE: To study the degree of accuracy in gingival shade matching of undergraduate students using a computer application. MATERIALS AND METHODS: In total, 76 undergraduate dental students' gingival shade selection abilities were evaluated using an in-house developed computer application. A total of 15 intraoral gingival photographs and 21 pink gingival color porcelain samples were used. The environmental conditions were standardized, and no time limit was set for answering in the computer application. RESULTS: Fourteen gingival color samples (66.6%) were not useful for representing the studied gingival shades. Not all natural gingival colors studied were represented within the 50.50% acceptability limits of the pink samples. There were no statistically significant differences between men and women in terms of "hit" percentages. The highest correlation coefficient (in absolute value) was for the L* coordinate (the darker the gingiva in the picture, the higher the hit rate for choosing the "ideal" shade tab); however, none of the linear correlation coefficients were statistically significant. CONCLUSIONS: Not all colors provided in the pink ceramic system were useful for subjective gingival selection. There were no statistically significant differences between male and female dental students in gingival color perception. The L* coordinate was the only one that influenced the correct perception of gingival color by dental students, and it did so more in women than in men.

Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study.

BACKGROUND: Deep learning model trained on a large image dataset, can be used to detect and discriminate targets with similar but not identical appearances. The aim of this study is to evaluate the post-training performance of the CNN-based YOLOv5x algorithm in the detection of white spot lesions in post-orthodontic oral photographs using the limited data available and to make a preliminary study for fully automated models that can be clinically integrated in the future. METHODS: A total of 435 images in JPG format were uploaded into the CranioCatch labeling software and labeled white spot lesions. The labeled images were resized to 640 × 320 while maintaining their aspect ratio before model training. The labeled images were randomly divided into three groups (Training:349 images (1589 labels), Validation:43 images (181 labels), Test:43 images (215 labels)). YOLOv5x algorithm was used to perform deep learning. The segmentation performance of the tested model was visualized and analyzed using ROC analysis and a confusion matrix. True Positive (TP), False Positive (FP), and False Negative (FN) values were determined. RESULTS: Among the test group images, there were 133 TPs, 36 FPs, and 82 FNs. The model's performance metrics include precision, recall, and F1 score values of detecting white spot lesions were 0.786, 0.618, and 0.692. The AUC value obtained from the ROC analysis was 0.712. The mAP value obtained from the Precision-Recall curve graph was 0.425. CONCLUSIONS: The model's accuracy and sensitivity in detecting white spot lesions remained lower than expected for practical application, but is a promising and acceptable detection rate compared to previous study. The current study provides a preliminary insight to further improved by increasing the dataset for training, and applying modifications to the deep learning algorithm. CLINICAL REVELANCE: Deep learning systems can help clinicians to distinguish white spot lesions that may be missed during visual inspection.

Photography or videography? A paradigm shift in dental clinical documentation.

Clinical documentation is critical in dental practices. Its influence reaches beyond diagnosis and treatment planning to patient education and evidence-based research. Historically, this documentation has relied mainly on photographic recordings. However, in the present era of rapid technical breakthroughs, a paradigm shift has occurred from photography to videography, driven by the transition from digital single-lens reflex (DSLR) cameras to mirrorless systems, which provide improved video capabilities. This article explores the technological journey from dental photography to videography, highlighting the need for revised and standardized clinical documenting methods to accommodate this changing landscape. It also includes a complete guide to maximizing the capabilities of mirrorless cameras and green screen technologies for the creation of high-quality video content. The essential element of protecting data privacy and security in the midst of these developments is also explored, providing a comprehensive view of the paradigm shift in dental clinical documentation.

Correção de sorriso gengival em paciente com displasia cemento óssea florida / Correction of gingival smile in patient with cemento bone dysplasia florida

Com os avanços tecnológicos na odontologia o planejamento digital se tornou algo mais presente na prática clinica. O objetivo desse trabalho é relatar uma experiência vivida em clínica sobre harmonização do sorriso através de uma gengivoplastia e remodelação óssea em paciente com displasia cemento óssea florida. Paciente 42 anos, autodeclarada do sexo feminino, não relatou nenhuma alteração sistêmica, uso de medicamento ou tabagismo, entretanto relatou ter displasia cemento óssea florida com diagnóstico de periodonto saudável. Compareceu a clínica escola de uma instituição de Ensino Superior para realização de tratamento odontológico queixando-se da aparência de seus dentes. Neste caso, foi utilizado escaneamento digital, tomografia computadorizada para tecidos moles, Digital Smile Design (DSD) e Perioguide (guia cirúrgico) para a realização do procedimento de harmonização do sorriso através da cirurgia periodontal. Em suma, apesar da displasia óssea ser um fator limitante ao sucesso ideal do procedimento, o resultado final alcançado foi satisfatório sob ótica do paciente e profissional não havendo recidiva(AU)

With technological advances in dentistry, digital planning has become something more present in clinical practice. The objective of this work is to report a clinical experience on smile harmonization through gingivoplasty and bone remodeling in a patient with florid cemento-osseous dysplasia. Patient 42 years old, self-reported female, did not report any systemic changes, use of medication or smoking, however she reported having florid cemento-osseous dysplasia with a diagnosis of healthy periodontium. He attended the school clinic of a Higher Education institution for dental treatment, complaining about the appearance of his teeth. In this case, digital scanning, soft tissue computed tomography, Digital Smile Design (DSD) and Perioguide (surgical guide) were used to perform the smile harmonization procedure through periodontal surgery. In short, despite bone dysplasia being a limiting factor for the ideal success of the procedure, the final result achieved was satisfactory from the perspective of the patient and professional, with no recurrence(AU)

Comparative Evaluation of Various Lens and Ring Flash Combination for Intraoral Photography.

BACKGROUND: Extraoral and intraoral dental photographs serve as preoperative records and document the entire treatment. Correctly composed orthodontic photographs are crucial for remote diagnosis and may serve as a bulwark against medicolegal challenges. MATERIALS AND METHODS: In this prospective study, intraoral frontal photographs of patients with ideal occlusion were taken using two types of lenses (EF-S 18-55 mm f/3.5-5.6 IS STM lens (Canon, Tokyo, JP), SP 90 mm F/2.8 MACRO VC lens (Model F017 Tamron, NY, USA)) and two different ring flash systems (Meike FC-100 Macro Ring LED Light (Meike, China), Macro Ring flash Lite YN-14EX (Yongnuo digital, China)). The combination of lens and flash used was grouped into four groups. Twenty-eight intraoral photographs of patients were taken. An image quality assessment survey was distributed among two groups - 50 orthodontists and 50 other dental specialists. RESULTS: The participants were asked to assess all the intraoral images and subjectively score them on a scale of one to ten, with one being very poor and ten being excellent, considering the sharpness, color, brightness, contrast, and overall quality of the image. The general dentists rated the images taken with a 90-mm macro lens and ring flash as the best quality photographs. Images obtained using an 18-55 mm lens and ring LED received significantly lesser scores and were graded good by dentists. CONCLUSION: This combination of lens and flash may prove a valuable investment in the long-term aiding in excellent dental images for diagnosis and treatment monitoring.

Clinical Tooth Color Matching: In Vivo Comparisons of Digital Photocolorimetric and Spectrophotometric Analyses.

OBJECTIVE: This study aimed to compare the tooth color matching of two dental colorimetric methods: the spectrophotometric analysis (SPM) and the standardized digital photocolorimetric analysis (DPC). METHODS: The color of 60 maxillary central incisors of 30 volunteers (22.5 ± 7.6 years) was analyzed. In the DPC method, tooth photographs were standardized with the eLABor_aid protocol, processed with Adobe Photoshop Lightroom software, and the values of L*, a*, and b* were obtained with a Digital Color Meter software. For the SPM, L*, a*, and b* were measured directly with a handheld spectrophotometer. Data were submitted to paired t-test and Pearson correlation test (α=0.05). Mean color difference between the two methods was calculated with CIELAB formula. RESULTS: All color coordinates revealed different values when comparing DPC to SPM in the same tooth (p<0.0001). Mean color difference (ΔEab) between SPM and DPC was 11.5 ±3.1. A positive correlation was observed for L* (R2=0.73,p<0.0001), a* (R2=0.31, p=0.017), and b* (R2=0.83, p<0.0001). CONCLUSIONS: Even though the color coordinate values were different in both methods, they were correlated, revealing that the DPC is a viable alternative to determine the tooth color matching.

An evaluation of gingival phenotype and thickness as determined by indirect and direct methods.

OBJECTIVES: To evaluate gingival phenotype (GP) and thickness (GT) using visual, probing, and ultrasound (US) methods and to assess the accuracy and consistency of clinicians to visually identify GP. MATERIALS AND METHODS: The GP and GT of maxillary and mandibular anterior teeth in 29 orthodontic patients (mean age 25 ± 7.5 years) were assessed using probing and US by a single examiner. General dentist and dental specialist assessors (n = 104) were shown intraoral photographs of the patients, including six repeated images, and asked to identify the GP via a questionnaire. RESULTS: An increasing trend in GT values of thin, medium, and thick biotype probe categories was found, though this was not statistically significant (P = .188). Comparison of probing method to determinations of GT made by US yielded slight agreement (κ = 0.12). Using the visual method, assessors' identification of the second GP determination ranged from poor to moderate agreement (κ = 0.29 to κ = 0.53). CONCLUSIONS: The probe method is sufficient in differentiating between different categories of GP. However, further research is required to assess the sensitivity of the probe method in recognizing phenotypes in the most marginal of cases. Assessors using the visual method lack the ability to identify GP accurately and consistently among themselves.

Detecting representative characteristics of different genders using intraoral photographs: a deep learning model with interpretation of gradient-weighted class activation mapping.

BACKGROUND: Sexual dimorphism is obvious not only in the overall architecture of human body, but also in intraoral details. Many studies have found a correlation between gender and morphometric features of teeth, such as mesio-distal diameter, buccal-lingual diameter and height. However, it's still difficult to detect gender through the observation of intraoral photographs, with accuracy around 50%. The purpose of this study was to explore the possibility of automatically telling gender from intraoral photographs by deep neural network, and to provide a novel angle for individual oral treatment. METHODS: A deep learning model based on R-net was proposed, using the largest dataset (10,000 intraoral images) to support the automatic detection of gender. In order to reverse analyze the classification basis of neural network, Gradient-weighted Class Activation Mapping (Grad-CAM) was used in the second step, exploring anatomical factors associated with gender recognizability. The simulated modification of images based on features suggested was then conducted to verify the importance of characteristics between two genders. Precision (specificity), recall (sensitivity) and receiver operating characteristic (ROC) curves were used to evaluate the performance of our network. Chi-square test was used to evaluate intergroup difference. A value of p < 0.05 was considered statistically significant. RESULTS: The deep learning model showed a strong ability to learn features from intraoral images compared with human experts, with an accuracy of 86.5% and 82.5% in uncropped image data group and cropped image data group respectively. Compared with hard tissue exposed in the mouth, gender difference in areas covered by soft tissue was easier to identify, and more significant in mandibular region than in maxillary region. For photographs with simulated removal of lips and basal bone along with overlapping gingiva, mandibular anterior teeth had similar importance for sex determination as maxillary anterior teeth. CONCLUSIONS: Deep learning method could detect gender from intraoral photographs with high efficiency and accuracy. With assistance of Grad-CAM, the classification basis of neural network was deciphered, which provided a more precise entry point for individualization of prosthodontic, periodontal and orthodontic treatments.

Facetas diretas em resina composta utilizando o fluxo digital para planejamento: relato de caso / Direct facets in composite resin using digital flow for planning: case report / Facetas directas en resina compuesta utilizando flujo digital para planificación: reporte de caso

Introdução:O aprimoramento das resinas compostas nos últimosanos em associação com a difusão de informações nas redes sociais tornou as facetas diretas tratamentos populares na dentística restauradora. No entanto, são procedimentos que exigem ampla destreza manual e conhecimento técnico. O fluxo digital através doescaneamento, enceramento digital e prototipagem 3D para construção de guias tem se tornado uma excelente alternativa para aumentar a previsibilidade e aumentar a longevidade destes trabalhos. Objetivo:Descrever o protocolo de confecção de facetas diretas em resina composta, através de um relato de caso, utilizando como auxílio o planejamento digital para confecção de modelo 3D, guia de silicone e paredes palatinas. Descrição do Caso:Paciente do gênero masculino, 43 anos, queixava-se do formato dos seus dentes. Ao exame clínico percebeu-se desgaste dental nos incisivos centrais e linha do sorriso levemente invertida. Após duas sessões de clareamento de consultório com Peróxido de hidrogênio (35%) e mockup direto com resina composta, foi realizada a moldagem e escaneamento do modelo de gesso no laboratório. O enceramento digital foi aprovado, o modelo 3D foi impresso para confecção da guia de silicone. Com auxílio da guia foram executadas facetas diretas nos elementos 13, 12, 11, 21, 22 e 23. Conclusão:O fluxo digital pode ser uma alternativa viável para minimizar as falhas na confecção de facetas diretas em resina composta (AU).

Introduction:The improvement of composite resins in recent years, together with information disseminated on social media, has made direct veneers popular treatments in restorative dentistry. However, these procedures require significant manual dexterity and technical knowledge. Digital work flow using scanning, digital wax-up and 3D prototyping for the construction of guides has become an excellent alternative to increase predictability and the longevity of these procedures. Objective:Describe the manufacturing protocol for direct composite resin veneers, using a case report and digital to construct the 3D model, silicone guide and palatine walls. Case description:Male patient, 43 years old, complained of the shape of his teeth. Clinical examination revealed tooth wear on the central incisors and a slightly inverted smile line. After two whitening sessions with hydroigen peroxide (35%) and direct mockup with composite resin, the plaster model was molded and scanned in the laboratory. Digital wax-up was approved, and the 3D model was printed to manufacture the silicone guide. With the help of the guide, the direct veneers were applied to elements 13, 12, 11, 21, 22 and 23.Conclusions:Digital flow may be a feasible alternative to minimize manufacturing flaws in direct composite resin veneers (AU).

Introducción: La mejora de las resinas compuestas en los últimos años, y la difusión de información en las redes sociales, ha popularizado las facetas directas en los tratamientos en odontología restauradora. Sin embargo, son procedimientos que requieren demasiado destreza manual y conocimientos técnicos. El flujo digital usando escaneo, encerado digital y prototipado 3D para la construcción de guías se ha convertido en una excelente alternativa para aumentar la previsibilidad y la longevidad de estos procedimientos. Objetivo: Describir el protocolo para la realización de carillas directas en resina compuesta, a través de un reporte de caso, utilizando el planeo digital como ayuda para la realización de un modelo 3D, guía de silicona y paredes palatinas. Descripción del caso: Paciente masculino, 43 años, se quejó de la forma de sus dientes. El examen clínico reveló desgaste dental en los incisivos centrales y una línea de sonrisa levemente invertida. Después de dos sesiones de blanqueamiento en consultorio con peróxido de hidrógeno (35%) y maqueta directa con resina compuesta, el modelo de yeso fue moldeado y escaneado en el laboratorio. El encerado digital fue aprovado, el modelo 3D fue impreso para hacer la guía de silicona. Con la ayuda de la guía se realizaron carillas directas en los elementos 13, 12, 11, 21, 22 y 23. Conclusiones: El fluxo digital puede ser una alternativa viable para minimizar fallas en la fabricación de carillas directas en resina compuesta (AU).

Evaluation of artificial intelligence model for crowding categorization and extraction diagnosis using intraoral photographs.

Determining the severity of dental crowding and the necessity of tooth extraction for orthodontic treatment planning are time-consuming processes and there are no firm criteria. Thus, automated assistance would be useful to clinicians. This study aimed to construct and evaluate artificial intelligence (AI) systems to assist with such treatment planning. A total of 3,136 orthodontic occlusal photographs with annotations by two orthodontists were obtained. Four convolutional neural network (CNN) models, namely ResNet50, ResNet101, VGG16, and VGG19, were adopted for the AI process. Using the intraoral photographs as input, the crowding group and the necessity of tooth extraction were obtained. Arch length discrepancy analysis with AI-detected landmarks was used for crowding categorization. Various statistical and visual analyses were conducted to evaluate the performance. The maxillary and mandibular VGG19 models showed minimum mean errors of 0.84 mm and 1.06 mm for teeth landmark detection, respectively. Analysis of Cohen's weighted kappa coefficient indicated that crowding categorization performance was best in VGG19 (0.73), decreasing in the order of VGG16, ResNet101, and ResNet50. For tooth extraction, the maxillary VGG19 model showed the highest accuracy (0.922) and AUC (0.961). By utilizing deep learning with orthodontic photographs, dental crowding categorization and diagnosis of orthodontic extraction were successfully determined. This suggests that AI can assist clinicians in the diagnosis and decision making of treatment plans.

Use of Images and Clinical Experience to Calibrate Dental Surgeons for the Diagnosis of Molar Incisor Hypomineralization

ABSTRACT Objective: To evaluate an imaging protocol for use as a diagnostic and calibration tool for dentists before and after practical activity. Material and Methods: Thirty photos of children's teeth with or without changes in dental enamel were selected and evaluated by a group of experienced dentists previously calibrated to establish the diagnosis defined as the gold standard. After instructions, the images were shown to a group of postgraduate dentists for free identification of dental changes. Subsequently, a lecture on molar incisor hypomineralization (MIH) was carried out, and, at 14 days and all calibration was performed using the criteria previously. The retest was performed at 28 days. After experience in clinical activity in the following two weeks, the post-test was performed at 49 days. Data were analyzed using Cohen's kappa coefficient. Results: Theoretical learning on the subject showed low inter-examiner agreement when the diagnosis of defects was made from images obtained from intraoral photographs. After clinical practice, there was greater intra-examiner agreement. After theoretical training, dentists started to identify different types of enamel alteration, although with low agreement between them. Conclusion: Clinical experience in theoretical and imaging training favored the identification of defects. However, it is necessary to improve the protocol to establish a reliable and viable diagnostic method for calibration in MIH.

Reproducibility and comparison between methods for gingival color evaluation: a validation study

Aim This study aims to evaluate and validate the sensibility and the level of agreement between different gingival color measures obtained by a spectrophotometer (SPECTRO) and a photography (PHOTO) method. Methods Among 40 patients, the color was measured 2 mm apical to the gingival margin by CIE L*, a*, b* system using a reflectance spectrophotometer and the photography's plus software. The level of agreement between three different measures (m1, m2, m3) in parameters L*, a*, b*, and ∆E (color variation) was evaluated by random and systematic errors, as well as the limits and coefficient of concordance. A comparison between the methods was performed by the Bland-Altman test and the sensibility level was evaluated accordingly to the ∆E: 3.7 thresholds with p<0.05 as the level of significance for these comparisons. Results The SPECTRO method has not presented the systematic error (p>0.05) and had reproducibly and agreement level in three variable measures L* (r: 0.6), a* (r: 0.3), and b* (r: 0.5) as to the PHOTO method L* (r: 0.6), a* (r: 0.5), and b* (r: 0.5), which presented systematic error in L* values (p<0.05). The means of ∆E between measurements were: 6.5 SPECTRO and 5.9 PHOTO. There was no good level of sensitivity ∆E> 3.7 and agreement between the methods, mainly for the a* values. On the other hand, for the L* and in for the most comparisons of b* values, the level of agreement was higher. Conclusion Both methods could quantify the gingival color from the coordinates L *, a *, and b *, which has shown greater reliability between the measurements acquired by the SPECTRO method.

Evaluation of the marginal adaptation and gingival status of full-crown restorations using an intraoral camera.

OBJECTIVE: The purpose of this study was to compare the usefulness of intraoral photographs, acquired with a household intraoral camera operating in conventional, calibrated, and polarized modes, with clinical examinations for assessing the marginal adaptation and gingival status of full-crown restorations. METHODS: Clinical examinations were performed by a prosthodontist who classified the marginal adaptation of full-crown restorations according to FDI World Dental Federation criteria, and a periodontal expert who classified gingival status according to the Modified Gingival Index (MGI). The margins and gingival status of the conventional, calibration, and polarization groups of full-crown restorations were independently assessed by three evaluators who obtained photographs using an intraoral camera. Cases where at least two of three assessors were in agreement were analyzed using Cohen's kappa coefficient and the chi-square test, and the sensitivity and specificity were calculated. RESULTS: The conventional, calibration, and polarization groups differed significantly in marginal and gingival status of full-crown restorations. In the calibration group, there was good agreement between the camera-based and oral clinical examinations in terms of the gingival status of full-crown restorations (kappa = 0.945), with 100% sensitivity and 91.67% specificity; this was also the case in the polarization group with respect to the margins of full-crown restorations (kappa = 0.917, sensitivity = 97.22%, specificity = 94.44%). CONCLUSIONS: An intraoral camera with black and white calibrated images is useful to assess the gingival status of full-crown restorations. Polarization mode can be used to assess the marginal adaptation of full-crown restorations. The camera is a feasible and valid diagnostic aid.

Telediagnosis of dental caries: Possible or impossible? A pilot cross-sectional study.

OBJECTIVES: The aims of this study were to evaluate the effectiveness of teledentistry (based on a home intraoral imaging protocol) in detecting dental caries and to assess the accuracy of this method compared to clinical examination. METHODS: Forty-three patients were recruited for the study. Using a protocol for taking intraoral photographs at home with a smartphone proposed by the Dental School of Verona, a remote diagnosis of dental caries (TD) was performed by an experienced dentist. The same caries sites were also assessed by clinical diagnosis (CD) by a second experienced dentist. Ten photos were taken at home in five different perspectives, with and without flash, and emailed to one of the authors. The best five photos were selected for telediagnosis. The International Caries Detection and Assessment System (ICDAS II) score was used for caries diagnosis. Statistical tests were performed: Sensitivity and specificity of TD, the positive and negative predictive value of TD (PPV-NPV), and Spearman correlation to evaluate the relationship between the scores of TD and CD. RESULTS: A total of 430 photographs were submitted; TD was performed on 215 photographs and 43 patients were visited. A total of 1201 teeth were analyzed. The sensitivity of TD was 74.0, the specificity was 99.1, the PPV of TD was 91.7, and the NPV was 96.4. The Spearman correlation was 0.816, showing a very strong correlation between the values obtained with TD and CD. CONCLUSIONS: The study showed good potential for TD, which proved to be a feasible method to combine with routine caries diagnosis in daily preventive dentistry practice.

A Standardized Approach to Extra-Oral and Intra-Oral Digital Photography.

Contemporary dentistry mandates a more comprehensive and personalized analysis of each patient. Technological advances in digital photography have played vital roles in diagnostic accuracy, treatment planning, execution of therapies, and outcome evaluations, including esthetic enhancement. Digital photography also provides an excellent platform for patient education, communication, and co-management of cases with other healthcare providers. However, intra-oral photography often faces challenges such as inaccessibility of areas to be captured, different moveable vs. fixed tissues involved, contamination with saliva or blood, and differing illumination needs on various locations. Thus, a more standardized and systematic approach is proposed for intra- and extra-oral documentation via digital photography to overcome the existing technical challenges. The current work will outline the appropriate equipment specifications (camera bodies, macro lens, and flashes), positions and postures of the operator and patients, proper techniques of tissue retraction, the use of appropriate intra-oral mirrors, and the essential elements such as aperture settings (F-stop), ISO, shutter speed, and white balance. This article aims to provide all dental professionals with an approachable linear array of guidelines to produce simplified and standardized visual tools for more efficient and effective documentation.

A New Approach to Diagnosis to Posterior Cross Bite: Intraoral Photography and Wala Ridge.

A posterior crossbite is an occlusion disorder that occurs in the transverse plane. It occurs when the buccal cusps of the upper premolars and molars engage lingually with the buccal cusps of the lower teeth. It can be unilateral or bilateral (involving one or more teeth) in the primary, mixed, or permanent dentition. A crossbite may appear in early dentition stages and it can be dental or functional. It can lead to skeletal crossbite in mixed dentition. Therefore, early diagnosis and treatment are crucial. MATERIAL AND METHODS: The selected sample included 204 patients in growing stage divided into two groups: a study group of 102 patients with posterior crossbite and a control group of 102 patients without malocclusion. To analyze the pathology, intraoral frontal photographs and study models were taken, in which the bone component was measured from the Wala Ridge. RESULTS: The use of the photographs to study the Wala Ridge was confirmed. The mean maxillary width was 57.8 mm (SD 1.7) and mandibular width was 56.4 mm (SD 1.7) for the control group, with a maxillomandibular difference of 1.4 mm (SD 0.7); and 52.7 mm (SD 3.7) and 55.5 mm (SD 3.6), respectively, with a maxillomandibular difference of -2.8 mm (SD 1.4) for the study group. A higher maxillomandibular discrepancy was observed in patients with a posterior crossbite that involved more than one tooth in addition to the permanent first molar. It was also higher in patients with bilateral posterior crossbite. CONCLUSIONS: Intraoral frontal photography can be used as a diagnostic method to measure the maxillomandibular difference using the Wala Ridge.

Influencia de la edad, sexo y ocupación sobre la percepción estética del perfil facial / Influence of age, sex and occupation on the aesthetic perception of the facial profile

Objective: To study the infuence of age, sex, and occupation in determining the aesthetic perception of the facial profle in the Chilean population through the analysis of silhouettes. Methods: From a profle photograph, a digital silhouette was designed, which was modifed with 2mm movements from the original position of the chin, simulating mandibular protrusion and retrusion. The use of silhouettes allows for eliminating various distractions, prejudices, and predispositions when making an aesthetic judgment. All participants accepted informed consent. Results: 112 participants with a mean age of 33.99 ± 8.28 years were surveyed. When analyzing the most aesthetic option was a straight profle, followed by a slight retrusion of -2mm and a protrusion of +2mm. The least esthetic option was a severe protrusion of +12mm. Both results were repeated in all the groups analyzed. Conclusions: The results present similarities with the literature, however, the low concordance in this study may be due to possible indirect infuences due to the contrast of the images that made up each set and the limited size of the studied sample. The present study was the frst of these characteristics in a Chilean population.

Objetivo: estudiar la infuencia de la edad, sexo y ocupación en la determinación de la percepción estética del perfl facial en la población chilena mediante el análisis de siluetas. Métodos: a partir de una fotografía de perfl se diseñó una silueta digital la cual se modifcó con movimientos de 2mm desde la posición original del mentón simulando una protrusión y retrusión mandibular. El uso de siluetas permite eliminar diversas distracciones, prejuicios y predisposiciones al momento de emitir un juicio estético. Todos los participantes aceptaron el consentimiento informado. Resultados: se encuestaron 112 participantes con una edad media de 33.99 ± 8.28 años. Al analizar la opción más estética fue un perfl recto, seguido de una leve retrusión de -2mm y una protrusión de +2mm. La opción menos estética fue una protrusión severa de +12mm. Ambos resultados se repitieron en todos los grupos analizados. Conclusiones: los resultados presentan similitudes con la literatura, sin embargo, la baja concordancia en este estudio puede deberse a posibles infuencias indirectas por contraste de las imágenes que compusieron cada set y el limitado tamaño de la muestra estudiada. El presente estudio fue el primero de estas características en la población chilena.