Clinical subgingival calculus detection with a smart ultrasonic device: a pilot study

Promises and perils of artificial intelligence in dentistry

Artificial intelligence (AI) is a subdiscipline of computer science that has made substantial progress in medicine and there is a growing body of AI research in dentistry. Dentists should have an understanding of the foundational concepts and the ability to critically evaluate dental research in AI. Machine learning (ML) is a subfield of AI that most dental AI research is dedicated to. The most prolific area of ML research is automated interpretation of dental imaging. Other areas include providing treatment recommendations, predicting future disease and treatment outcomes. The research impact is limited by small datasets that do not harness the positive correlation between very large datasets and ML performance. There is also a need to standardize research methodologies and utilize performance metrics that are appropriate for the clinical context. In addition to research challenges, this article discusses the ethical, legal and logistical considerations associated with implementation in clinical practice. This includes explainable AI, model bias, data privacy and security. The future implications of AI in dentistry involve a promise for a novel form of practicing dentistry however, the effect of AI on patient outcomes is yet to be determined.

How to train periodontal endoscopy? Results of a pilot study removing simulated hard deposits in vitro

OBJECTIVES

There is uncertainty regarding the benefits of periodontal endoscopy (PE) for subgingival instrumentation. Moreover, the influence of operators' experience and training with such a device on treatment results is unclear. Therefore, we compared in an in vitro study the use of PE for scaling and root planing (SRP) with the conventional non-surgical therapy, hypothesizing that using a PE allows to remove more simulated hard deposits than without (nPE), influenced by the operators' experience and training.

MATERIAL AND METHODS

A sonic device and Gracey curettes were utilized by 11 operators (six dentists, five dental hygienists) in periodontitis manikins heads. The time required for treatment and the proportion of removed simulated hard deposits by SRP were measured.

RESULTS

Using the PE led to a significant difference in removal of simulated hard deposits (%) (mean ± SD) irrespective of operators' experience (PE 90.78 ± 12.10% (range 58.80-100%); nPE 79.98 ± 22.15% (range 38.10-100%, p < 0.001)), sub-analyses for different tooth types demonstrated a significant difference in favor of PE for front teeth (p < 0.001) and in the upper jaw independent of the tooth type (p < 0.001). Comparison of treatment times for two quadrants with and without PE showed a significantly longer treatment time with PE (∆22.27 ± 17.98 mins, p <0.001).

CONCLUSIONS

Within the present pilot study, the use of PE led to more removal of simulated hard deposits but was concomitantly related to more time and financial effort. Using PE was most beneficial in the front area.

CLINICAL RELEVANCE

PE may provide additional benefits for the removal of hard deposits compared to traditional SRP. The beneficial effect of PE seems not to be influenced by operators experience nor by pocket probing depth.

Comparison of calculus detection among dental hygienists using an explorer and ultrasonic insert

INTRODUCTION

Periodontal therapy disrupts the biofilm harbouring calculus that triggers inflammation. The explorer is primarily used for calculus detection, and the ultrasonic instrument is primarily used for calculus removal. The efficiency in dental hygiene care may improve if the ultrasonic instrument could be used in both calculus detection and removal.

PURPOSE

The purpose of this study was to validate the effectiveness of calculus detection between the Thinsert® ultrasonic insert and the 11/12 explorer.

METHODS

Upon IRB approval, this validation study involved three dental hygiene faculty from the Ohio State University Dental Hygiene Program and 30 patient participants from the Ohio State University community. Using both instruments, calculus was evaluated on Ramfjord index teeth and on four possible surfaces per tooth. Data were analysed to evaluate for interrater reliability, intrarater reliability, sensitivity, and specificity.

RESULTS

For interrater reliability, the average measure of intraclass coefficient (ICC) value was 0.782 with a 95% confidence interval (CI) of 0.749-0.810 (F_{(1439, 2878)}  = 4.852, P < 0.01). For intrarater reliability, mean Kappa averages were in the full agreement range (κ = 0.726, n = 2160, P < 0.01). When using the Thinsert® for calculus detection, the sensitivity was 75%, specificity was 97%, PPV was 81%, and NPV was 94%.

CONCLUSION

Since calculus evaluation was comparable when using the ODU 11/12 explorer and the Thinsert®, efforts can be focused on developing the tactile sensitivity when using the Thinsert® ultrasonic instrument in the assessment, treatment, and maintenance of periodontal disease and the support of oral health. The efficiency in dental hygiene care may improve by using the Thinsert® ultrasonic instrument in both the detection and removal of calculus.

Reliability of recordings of subgingival calculus detected using an ultrasonic device

OBJECTIVES

To assess the intra-examiner reliability of recordings of subgingival calculus detected using an ultrasonic device, and to investigate the influence of subject-, tooth- and site-level factors on the reliability of these subgingival calculus recordings.

MATERIALS AND METHODS

On two occasions, within a 1-week interval, 147 adult periodontitis patients received a full-mouth clinical periodontal examination by a single trained examiner. Duplicate subgingival calculus recordings, in six sites per tooth, were obtained using an ultrasonic device for calculus detection and removal.

RESULTS

Agreement was observed in 65 % of the 22,584 duplicate subgingival calculus recordings, ranging 45 % to 83 % according to subject. Using hierarchical modeling, disagreements in the subgingival calculus duplicate recordings were more likely in all other sites than the mid-buccal, and in sites harboring supragingival calculus. Disagreements were less likely in sites with PD ≥  4 mm and with furcation involvement  ≥  degree 2. Bleeding on probing or suppuration did not influence the reliability of subgingival calculus. At the subject-level, disagreements were less likely in patients presenting with the highest and lowest extent categories of the covariate subgingival calculus.

CONCLUSIONS AND CLINICAL RELEVANCE

The reliability of subgingival calculus recordings using the ultrasound technology is reasonable. The results of the present study suggest that the reliability of subgingival calculus recordings is not influenced by the presence of inflammation. Moreover, subgingival calculus can be more reliably detected using the ultrasound device at sites with higher need for periodontal therapy, i.e., sites presenting with deep pockets and premolars and molars with furcation involvement.

Detection, removal and prevention of calculus: Literature Review

Dental plaque is considered to be a major etiological factor in the development of periodontal disease. Accordingly, the elimination of supra- and sub-gingival plaque and calculus is the cornerstone of periodontal therapy. Dental calculus is mineralized plaque; because it is porous, it can absorb various toxic products that can damage the periodontal tissues. Hence, calculus should be accurately detected and thoroughly removed for adequate periodontal therapy. Many techniques have been used to identify and remove calculus deposits present on the root surface. The purpose of this review was to compile the various methods and their advantages for the detection and removal of calculus.

Dental optical coherence tomography

This review paper describes the applications of dental optical coherence tomography (OCT) in oral tissue images, caries, periodontal disease and oral cancer. The background of OCT, including basic theory, system setup, light sources, spatial resolution and system limitations, is provided. The comparisons between OCT and other clinical oral diagnostic methods are also discussed.

Subgingival calculus imaging based on swept-source optical coherence tomography

We characterized and imaged dental calculus using swept-source optical coherence tomography (SS-OCT). The refractive indices of enamel, dentin, cementum, and calculus were measured as 1.625 ± 0.024, 1.534 ± 0.029, 1.570 ± 0.021, and 2.097 ± 0.094, respectively. Dental calculus leads strong scattering properties, and thus, the region can be identified from enamel with SS-OCT imaging. An extracted human tooth with calculus is covered with gingiva tissue as an in vitro sample for tomographic imaging.