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.

Is teledentistry effective to monitor the evolution of orthodontic treatment? A systematic review and meta-analysis

INTRODUCTION

With the advent of COVID-19, teledentistry and remote monitoring have become an imminent reality that allows orthodontists to monitor orthodontic treatment through virtual checkups, which complement in-office appointments.

OBJECTIVE

To evaluate the effectiveness of using teledentistry in monitoring the evolution of orthodontic treatment.

MATERIAL AND METHODS

Searches were performed in on-line databases. PECO strategy focused on comparing orthodontic patients exposed and not exposed to teledentistry. Searches and data extraction followed PRISMA guidelines. The assessment of the risk of bias and the certainty of the evidence was performed using the ROBINS-I and GRADE tools, respectively. A meta-analysis was also performed.

RESULTS

Out of 1,178 records found, 4 met the criteria and were included in the qualitative analysis. The risk of bias for follow-up assesment in aligner treatment was low to moderate; while for interceptive treatment, it was high. Studies are favorable to the use of teledentistry. The meta-analysis was performed with aligners studies only, due to heterogeneity. The certainty of the evidence was considered very low.

CONCLUSION

With very low certainty of evidence, teledentistry using Dental Monitoring® software is effective as an aid in monitoring the evolution of interceptive orthodontic treatment (high risk of bias) and, especially, treatment performed with aligners (low to moderate risk of bias). The meta-analysis evidenced a reduction in the number of face-to-face appointments (mean difference = -2.75[-3.95, -1.55]; I2=41%; p<0.00001) and the time for starting refinement (mean difference = -1.21[-2.35, -0.08]; I2=49%; p=0.04). Additional randomized studies evaluating corrective orthodontic treatment with brackets and wires are welcome.

Teleorthodontics: Where Are We Going? From Skepticism to the Clinical Applications of a New Medical Communication and Management System

Teleorthodontics represents the orthodontic care system involving remote management of orthodontic treatment. Despite skepticism, there are several advantages of including teleorthodontics in the clinical orthodontic practice. In the present review, we discuss the lights and shadows of this new communication healthcare system and its applications in the field of orthodontics that is destined to change the future of our clinical practice. For this purpose, we have provided a point-to-point analysis based on data from the most valuable scientific evidence on this topic. The information and data discussed in the present paper were obtained from the most relevant studies evaluating the performance of teleorthodontics and remote monitoring systems in clinical practice.

Artificial intelligence in orthodontics: Where are we now? A scoping review

OBJECTIVE

This scoping review aims to determine the applications of Artificial Intelligence (AI) that are extensively employed in the field of Orthodontics, to evaluate its benefits, and to discuss its potential implications in this speciality. Recent decades have witnessed enormous changes in our profession. The arrival of new and more aesthetic options in orthodontic treatment, the transition to a fully digital workflow, the emergence of temporary anchorage devices and new imaging methods all provide both patients and professionals with a new focus in orthodontic care.

MATERIALS AND METHODS

This review was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The electronic literature search was performed through MEDLINE/PubMed, Scopus, Web of Science, Cochrane and IEEE Xplore databases with a 11-year time restriction: January 2010 till March 2021. No additional manual searches were performed.

RESULTS

The electronic literature search initially returned 311 records, and 115 after removing duplicate references. Finally, the application of the inclusion criteria resulted in 17 eligible publications in the qualitative synthesis review.

CONCLUSION

The analysed studies demonstrated that Convolution Neural Networks can be used for the automatic detection of anatomical reference points on radiological images. In the growth and development research area, the Cervical Vertebral Maturation stage can be determined using an Artificial Neural Network model and obtain the same results as expert human observers. AI technology can also improve the diagnostic accuracy for orthodontic treatments, thereby helping the orthodontist work more accurately and efficiently.

Attitude towards Telemonitoring in Orthodontists and Orthodontic Patients

The purpose of this study was to analyze the attitude of dentists and patients towards the use of Dental Monitoring^TM (DM), an orthodontic telemonitoring software. Thus, two different specially prepared specific questionnaires were administered to 80 dentists (40 were general dentists and 40 orthodontists) and 80 orthodontic patients. All dentists judged positively telemonitoring, as 96.25% of them considered telemonitoring indicative of high tech and high-quality treatment; 100% considered it a way to reduce the number of in-office visits; 17.5% agreed on a weekly telemonitoring frequency, 40% on a biweekly, and 42.5% on a lower frequency. Further, 97.5% of patients judged positively telemonitoring; 81.25% of them considered telemonitoring indicative of high-tech treatment; 81.25% declared to be interested in reducing the number of in-office visits through telemonitoring; 27.5% agreed on taking self-picture every week, 57.5% every two weeks, and 15% on a lower frequency. Both patients and dentists positively judged telemonitoring, considering it a technologically advanced tool increasing the perception of quality and accuracy of the treatment. Both groups were interested in reducing the number of in-office visits, although not all of them revealed to be ready to invest more money and time in it.

An evidence-based review of the scope and potential ethical concerns of teleorthodontics

PURPOSE

The aim was to evaluate the scope and potential ethical concerns related to the use of teledentistry in clinical orthodontics.

METHODS

Indexed databases were searched up to and including October 2020. The eligibility criteria were as follows: (a) original clinical studies, and (b) case reports/series. Historic reviews, commentaries, experimental studies, and letters to the editor, were excluded. The pattern of the present review was customized to summarize the relevant information.

RESULTS

A total of 4 clinical studies (out of 1016) were included in the present evidence-based review. Three studies reported that teledentistry is useful in clinical orthodontics. In 1 study, a clear conclusion could not be derived regarding the benefits of teledentistry in clinical orthodontics. Two out of 4 studies did not obtain prior approval from an Institutional Review Board or Ethical Committee. Three studies did not report any measures that were undertaken to safeguard the electronic transfer of patient-related health information.

CONCLUSIONS

Teleorthodontics facilitates treatment planning/monitoring by sharing orthodontics-based patient records among oral healthcare providers; however, the importance of direct patient supervision and routine follow-ups during orthodontic therapy cannot be overlooked. Further studies are needed to establish ethical guidelines and a standard of care in this emerging field.

Available Technologies, Applications and Benefits of Teleorthodontics. A Literature Review and Possible Applications during the COVID-19 Pandemic

Background: COVID-2019 spread rapidly throughout the world from China. This infection is highly contagiousness, has a high morbidity, and is capable of evolving into a potentially lethal form of interstitial pneumonia. Numerous countries shut-down various activities that were considered “not essential.” Dental treatment was in this category and, at the time of writing, only non-deferrable emergencies are still allowed in many countries. Therefore, follow-up visits of ongoing active therapies (e.g., orthodontic treatment) must be handled taking special precautions. This literature review aims at reducing in-office appointments by providing an overview of the technologies available and their reliability in the long-distance monitoring of patients, i.e., teledentistry. Methods: A literature review was made according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines. Randomized clinical trials, cross sectional, observational, and case-control studies were evaluated with the Mixed Methods Appraisal Tool for quality assessment and study limitations. Results: A primary search found 80 articles, 69/80 were excluded as non-relevant on the basis of: the abstract, title, study design, bias, and/or lack of relevance. Twelve articles were included in the qualitative analysis. Conclusions: Teleorthodontics can manage most emergencies, reassuring and following patients remotely. The aim set by dental teleassistance was met as it reduced patients’ office visits whilst maintaining regular monitoring, without compromising the results. Although our preliminary findings should be further investigated to objectively evaluate the efficacy, cost-effectiveness, and long-term results, we are confident that teleassistance in orthodontics will have a role to play in the near future.

Clinical outcomes and patient perspectives of Dental Monitoring® GoLive® with Invisalign®-a retrospective cohort study

Background

The aims of the study were to compare the effects of Invisalign® with and without Dental Monitoring® (DM) GoLive® on the following parameters: treatment duration, number of appointments, number of refinements, total number of refinement aligners, and time to initial refinement. The patients’ perspectives on Dental Monitoring® were also evaluated using an online questionnaire. A sample of 155 consecutively treated Invisalign® patients (67 control, 88 DM) fit the inclusion and exclusion criteria.

Results

The two groups were homogeneous (P > .05) for age, gender, angle classification, Little’s Irregularity Index, and number of initial aligners. The DM group had significantly fewer office visits compared to the control (7.56 vs 9.82; P < .001). There were no significant differences between the DM and control groups respectively pertaining to treatment duration (14.58 vs 13.91), number of refinements (1.00 vs 0.79), number of refinement aligners (19.91 vs 19.85), and time to first refinement (9.46 vs 9.97). Questionnaire results showed that 68.8% (44 respondents) indicate that DM scans were “easy” or “very easy” to perform while 16 responders (25%) found it “difficult” or “very difficult.” 71.9% (46 responders) were “satisfied or very satisfied” with the level of communication with the orthodontist using DM and 16% (10 responders) were “dissatisfied” or “very dissatisfied.” The mean duration observed by patients to take a scan was 5.16 ± 3.6 min. Eighty-eight percent (56 responders) of patients prefer few office visits as possible, while 12% (8 responders) would actually prefer additional office visits. Overall, the mean satisfaction of patients with DM was 4.25 on the 5-point Likert scale.

Conclusion

The DM group had a significantly reduced number of appointments (7.56) compared with the control group (9.82) (a reduction of 23%) over the treatment duration. There were no significant differences between the two groups in treatment duration, number of refinements, number of refinement aligners, or time to 1st refinement. Overall, DM was well received by patients. However, there was a small percentage (usually less than 15%) that was generally unsatisfied with DM in varying aspects and preferred more frequent, traditional office visits.

Machine Learning for the Diagnosis of Orthodontic Extractions: A Computational Analysis Using Ensemble Learning

Extraction of teeth is an important treatment decision in orthodontic practice. An expert system that is able to arrive at suitable treatment decisions can be valuable to clinicians for verifying treatment plans, minimizing human error, training orthodontists, and improving reliability. In this work, we train a number of machine learning models for this prediction task using data for 287 patients, evaluated independently by five different orthodontists. We demonstrate why ensemble methods are particularly suited for this task. We evaluate the performance of the machine learning models and interpret the training behavior. We show that the results for our model are close to the level of agreement between different orthodontists.

Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making - A systematic review

Background/purpose

In the recent years artificial intelligence (AI) has revolutionized in the field of dentistry. The aim of this systematic review was to document the scope and performance of the artificial intelligence based models that have been widely used in orthodontic diagnosis, treatment planning, and predicting the prognosis.

Materials and methods

The literature for this paper was identified and selected by performing a thorough search for articles in the electronic data bases like Pubmed, Medline, Embase, Cochrane, and Google scholar, Scopus and Web of science, Saudi digital library published over the past two decades (January 2000–February 2020). After applying the inclusion and exclusion criteria, 16 articles were read in full and critically analyzed. QUADAS-2 were adapted for quality analysis of the studies included.

Results

AI technology has been widely applied for identifying cephalometric landmarks, determining need for orthodontic extractions, determining the degree of maturation of the cervical vertebra, predicting the facial attractiveness after orthognathic surgery, predicting the need for orthodontic treatment, and orthodontic treatment planning. Most of these artificial intelligence models are based on either artificial neural networks (ANNs) or convolutional neural networks (CNNs).

Conclusion

The results from these reported studies are suggesting that these automated systems have performed exceptionally well, with an accuracy and precision similar to the trained examiners. These systems can simplify the tasks and provide results in quick time which can save the dentist time and help the dentist to perform his duties more efficiently. These systems can be of great value in orthodontics.

New approach for the diagnosis of extractions with neural network machine learning

INTRODUCTION

The decision to extract teeth for orthodontic treatment is important and difficult because it tends to be based on the practitioner's experiences. The purposes of this study were to construct an artificial intelligence expert system for the diagnosis of extractions using neural network machine learning and to evaluate the performance of this model.

METHODS

The subjects included 156 patients. Input data consisted of 12 cephalometric variables and an additional 6 indexes. Output data consisted of 3 bits to divide the extraction patterns. Four neural network machine learning models for the diagnosis of extractions were constructed using a back-propagation algorithm and were evaluated.

RESULTS

The success rates of the models were 93% for the diagnosis of extraction vs nonextraction and 84% for the detailed diagnosis of the extraction patterns.

CONCLUSIONS

This study suggests that artificial intelligence expert systems with neural network machine learning could be useful in orthodontics. Improved performance was achieved by components such as proper selection of the input data, appropriate organization of the modeling, and preferable generalization.