In vitro calculus detection with a moved smart ultrasonic device

Development of subgingival calculus detector utilizing optical fiber: Verification of its potential for clinical application

The removal of subgingival deposits, especially calculus, plays a crucial role in basic periodontal therapy. However, manual detection methods affect accuracy owing to the operator's skill. To avoid this uncertainty, we have developed a calculus detection device named "Sensor probe" and evaluated its ability to detect calculus for future clinical applications. The Sensor probe consisted of a 635 nm-wavelength semiconductor laser and a 0.5 mm-diameter single-mode optical fiber. Initially, the performance of the device was evaluated using clinically obtained extracted teeth with calculus covered with a stainless-steel shielding plate with pinhole. Then, the effect of the optical fiber's end shape on calculus detection performance was analyzed. Lastly, the performance of the Sensor probe was compared to that of a conventional periodontal probe in terms of accuracy, sensitivity, and specificity for calculus detection using calculus-covered extracted teeth. The results indicated that Sensor probe detected dental calculus through the pinhole with a diameter of 300 μm or more when applied from a distance of 100 μm. The results analyzing the effect of the optical fiber's end shape on calculus detection performance showed that cutting the fiber end at an angle of 45° resulted in the most effective calculus detection. This may be because the laser light refracted on the cut surface and concentrated on the fiber side. Moreover, by comparing the performance of this device to a conventional periodontal probe revealed that the Sensor probe showed improved calculus detection accuracy in deeper periodontal pockets. This improvement was particularly significant in the apical third, where detection is typically difficult. In conclusion, a Sensor probe that uses an optical fiber with a 45° angled end may facilitate subgingival calculus detection. In future clinical applications, Sensor probes could lead to more accurate and efficient calculus removal, especially for deeper periodontal pockets.

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review

OBJECTIVE

The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.

MATERIALS AND METHODS

Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted.

RESULTS

The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics.

CONCLUSION

The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

Application of artificial intelligence in the dental field: A literature review

PURPOSE

The purpose of this study was to comprehensively review the literature regarding the application of artificial intelligence (AI) in the dental field,focusing on the evaluation criteria and architecture types.

STUDY SELECTION

Electronic databases (PubMed, Cochrane Library, Scopus) were searched. Full-text articles describing the clinical application of AI for the detection, diagnosis, and treatment of lesions and the AI method/architecture were included.

RESULTS

The primary search presented 422 studies from 1996 to 2019, and 58 studies were finally selected. Regarding the year of publication, the oldest study, which was reported in 1996, focused on "oral and maxillofacial surgery." Machine-learning architectures were employed in the selected studies, while approximately half of them (29/58) employed neural networks. Regarding the evaluation criteria, eight studies compared the results obtained by AI with the diagnoses formulated by dentists, while several studies compared two or more architectures in terms of performance. The following parameters were employed for evaluating the AI performance: accuracy, sensitivity, specificity, mean absolute error, root mean squared error, and area under the receiver operating characteristic curve.

CONCLUSIONS

Application of AI in the dental field has progressed; however, the criteria for evaluating the efficacy of AI have not been clarified. It is necessary to obtain better quality data for machine learning to achieve the effective diagnosis of lesions and suitable treatment planning.

Evaluation of calculus imaging on root surfaces by spectral-domain optical coherence tomography

OBJECTIVE

The aim of this in vitro study was to evaluate the ability of optical coherence tomography (OCT) to display calculus on root surfaces.

MATERIAL AND METHODS

Ten teeth with calculus on the root surface were embedded in resin, omitting the root surface. A region of interest (ROI) was marked by small drill holes coronally and apically of the calculus and imaged by spectral-domain optical coherence tomography ([SD OCT], Telesto SP5, centre wavelength 1310 nm) and light microscopy (LM). To evaluate the impact of different fluids on calculus visualisation, using OCT, root surfaces were covered by a layer of NaCl and blood and displayed by OCT. Subsequently, teeth were completely covered with resin and sectioned for histological evaluation. Within the ROI, lengths of root surface and calculus were measured by LM and OCT, and the ratio [%] was calculated. In addition, at three sites of each ROI, agreement of presence and length of calculus was evaluated. Both methods were compared using Pearson's correlation.

RESULTS

Regarding the presence of calculus, agreement between LM and OCT was strong (κ_i = 0.783, p = 0.033), and measurements regarding the length of the calculus were strongly correlated (r_i >0.906; p_i <0.001). However, the values differed for dry (p = 0.023) and NaCl-covered root surfaces (p = 0.035).

CONCLUSION

Calculus on the root surface can be displayed by SD-OCT, which therefore may be suited as imaging technology for subgingival calculus in periodontal pockets.

Synthesis and spectral characterization of silver/magnesium co-substituted hydroxyapatite for biomedical applications

The present work is aimed at the synthesis of antibacterial and bioactive silver/magnesium co-substituted hydroxyapatite (Ag/Mg-HAP) powders. For this purpose, firstly, different concentrations (0.5, 1.5, 2.5wt.%) of silver substituted HAP (Ag-HAP) powders were prepared by ultrasonic irradiation technique and were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDAX). Secondly, magnesium (Mg) is co-substituted as secondary material into Ag-HAP to offset the potential cytotoxicity of Ag, as higher concentration of Ag is toxic. The antibacterial activity of as-synthesized powders was evaluated by Escherichia coli (E. coli) and was found to be effectively high against bacterial colonization. Also, the in vitro cell-material interaction is evaluated with human osteosarcoma MG63 (HOS MG63) cells for cell proliferation. The results showed the evidence of cytotoxic effects of the higher concentration of Ag-HAP characterized by poor cellular viability whereas, Ag/Mg-HAP showed better cell viability indicating that co-substitution of Mg in Ag-HAP effectively offset the negative effects of Ag and improve performance compared with pure HAP. Thus, the as synthesized Ag/Mg-HAP will serve as a better candidate for biomedical applications with good antibacterial property and bone bonding ability.

Thermal and ultrasonic influence in the formation of nanometer scale hydroxyapatite bio-ceramic

Hydroxyapatite (HAP) is a widely used biocompatible ceramic in many biomedical applications and devices. Currently nanometer-scale forms of HAP are being intensely investigated due to their close similarity to the inorganic mineral component of the natural bone matrix. In this study nano-HAP was prepared via a wet precipitation method using Ca(NO₃)₂ and KH₂PO₄ as the main reactants and NH₄OH as the precipitator under ultrasonic irradiation. The Ca/P ratio was set at 1.67 and the pH was maintained at 9 during the synthesis process. The influence of the thermal treatment was investigated by using two thermal treatment processes to produce ultrafine nano-HAP powders. In the first heat treatment, a conventional radiant tube furnace was used to produce nano-particles with an average size of approximately 30 nm in diameter, while the second thermal treatment used a microwave-based technique to produce particles with an average diameter of 36 nm. The crystalline structure and morphology of all nanoparticle powders produced were investigated using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and Fourier transform infrared spectroscopy (FT-IR). Both thermal techniques effectively produced ultrafine powders with similar crystalline structure, morphology and particle sizes.

Synthesis and characterisation of nanohydroxyapatite using an ultrasound assisted method

Nanostructured hydroxyapatite (HAP) was prepared by a wet precipitation method using Ca(NO(3)) and KH(2)PO(4) as the main material and NH(3) as the precipitator under ultrasonic irradiation. The Ca/P ratio was set at 1.67 and the pH maintained at a minimum of 9. The temperature conditions and ultrasound influences were investigated using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and Fourier transform infrared spectroscopy (FT-IR). The results showed that Nano-HAP can be obtained by this method and the particles were achieved to around 30 nm.