Impact of room lighting and image display device in the radiographic appearances of the endodontic treatments

AI-Assisted Diagnostics in Dentistry: An Eye-Tracking Study on User Behavior

Background

Artificial Intelligence (AI) has increasingly been integrated into dental practices, notably in radiographic imaging like Orthopantomograms (OPGs), transforming diagnostic protocols. Eye tracking technology offers a method to understand how dentists' visual attention may differ between conventional and AI-assisted diagnostics, but its integration into daily clinical practice is challenged by the cost and complexity of traditional systems.

Material and Methods

Thirty experienced practitioners and dental students participated to evaluate the effectiveness of two low-budget eye-tracking systems, including the Peye Tracker (Eye Tracking Systems LTD, Southsea, UK) and Webgazer.js (Brown University, Providence, Rhode Island) in a clinical setting to assess their utility in capturing dentists' visual engagement with OPGs. The hardware and software setup, environmental conditions, and the process for eye-tracking data collection and analysis are illustrated.

Results

The study found significant differences in eye-tracking accuracy between the two systems, with Webgazer.js showing higher accuracy compared to Peye Tracker (p<0.001). Additionally, the influence of visual aids (glasses vs. contact lenses) on the performance of eye-tracking systems revealed significant differences for both Peye Tracker (p<0.05) and Webgazer.js (p<0.05).

Conclusions

Low-budget eye-tracking devices present challenges in achieving the desired accuracy for analyzing dentists' visual attention in clinical practice, highlighting the need for continued innovation and improvement in this technology. Key words:Artificial intelligence, Eye-tracking device, low-budget, dentistry.

Smartphone use for tomographic evaluation: application in endodontic diagnosis

INTRODUCTION

Portable equipment that allows quick exchanges of information, such as smartphones, is increasingly important in Dentistry. Thus, they have become frequently used, with the potential to contribute to the tomographic evaluation. This study aimed to evaluate the accuracy of smartphone applications for diagnosing the root canal system (RCS) and measuring the root canal length.

METHODS

DICOM files of 92 lower incisor teeth were evaluated by two trained and calibrated examiners using the CS 3D Imaging software and two smartphone applications (DroidRender and Horos Mobile). The RCS was assessed according to Vertucci's classification, and the tooth length was measured using linear cusp-apex measurements. The diagnostic reference standard was obtained by the mode and the mean of the evaluations made by three experienced examiners using the CS 3D Imaging software. The diagnostic performance of RCS was evaluated using sensitivity (Se), specificity (Sp), and overall accuracy (Ac). The Bland-Altman analysis was used to assess the agreement of linear measurements.

RESULTS

The diagnostic tests showed similar performance between the smartphone applications (DroidRender: Se = 1.00; Sp = 0.95; Ac = 0.97; Horos: Se = 0.95; Sp = 0.94; Ac = 0.95) and the computer software (Se = 0.97 - 0.95; Sp = 0.93 - 0.96; Ac = 0.95 - 0.96). The smartphone applications showed discrepancies greater than 1.0 mm for the dental lengths, which may signal relevant differences in some clinical situations.

CONCLUSION

Smartphone applications offered similar diagnostic performance in comparison to the computer software for the RCS evaluation.

Visual Illusions in Radiology: Untrue Perceptions in Medical Images and Their Implications for Diagnostic Accuracy

Errors in radiologic interpretation are largely the result of failures of perception. This remains true despite the increasing use of computer-aided detection and diagnosis. We surveyed the literature on visual illusions during the viewing of radiologic images. Misperception of anatomical structures is a potential cause of error that can lead to patient harm if disease is seen when none is present. However, visual illusions can also help enhance the ability of radiologists to detect and characterize abnormalities. Indeed, radiologists have learned to exploit certain perceptual biases in diagnostic findings and as training tools. We propose that further detailed study of radiologic illusions would help clarify the mechanisms underlying radiologic performance and provide additional heuristics to improve radiologist training and reduce medical error.

Impact of viewing conditions on the performance assessment of different computer monitors used for dental diagnostics

Purpose

This study aimed to assess the computer monitors used for analysis and interpretation of digital radiographs within the clinics of the Oral Health Centre of Western Australia.

Materials and Methods

In total, 135 computer monitors (3 brands, 6 models) were assessed by analysing the same radiographic image of a combined 13-step aluminium step wedge and the Artinis CDDent 1.0® (Artinis Medical Systems B.V.®, Elst, the Netherlands) test object. The number of steps and cylindrical objects observed on each monitor was recorded along with the monitor's make, model, position relative to the researcher's eye level, and proximity to the nearest window. The number of window panels blocked by blinds, the outside weather conditions, and the number of ceiling lights over the surgical suite/cubicle were also recorded. MedCalc® version 19.2.1 (MedCalc Software Ltd®, Ostend, Belgium, https://www.medcalc.org; 2020) was used for statistical analyses (Kruskal-Wallis test and stepwise regression analysis). The level of significance was set at P<0.05.

Results

Stepwise regression analysis showed that only the monitor brand and proximity of the monitor to a window had a significant impact on the monitor's performance (P<0.05). The Kruskal-Wallis test showed significant differences (P<0.05) in monitor performance for all variables investigated, except for the weather and the clinic in which the monitors were placed.

Conclusion

The vast performance variation present between computer monitors implies the need for a review of monitor selection, calibration, and viewing conditions.