Barriers and Enablers for Artificial Intelligence in Dental Diagnostics: A Qualitative Study

The present study aimed to identify barriers and enablers for the implementation of artificial intelligence (AI) in dental, specifically radiographic, diagnostics. Semi-structured phone interviews with dentists and patients were conducted between the end of May and the end of June 2020 (convenience/snowball sampling). A questionnaire developed along the Theoretical Domains Framework (TDF) and the Capabilities, Opportunities and Motivations influencing Behaviors model (COM-B) was used to guide interviews. Mayring's content analysis was employed to point out barriers and enablers. We identified 36 barriers, conflicting themes or enablers, covering nine of the fourteen domains of the TDF and all three determinants of behavior (COM). Both stakeholders emphasized chances and hopes for AI. A range of enablers for implementing AI in dental diagnostics were identified (e.g., the chance for higher diagnostic accuracy, a reduced workload, more comprehensive reporting and better patient-provider communication). Barriers related to reliance on AI and responsibility for medical decisions, as well as the explainability of AI and the related option to de-bug AI applications, emerged. Decision-makers and industry may want to consider these aspects to foster implementation of AI in dentistry.

Incorporating Antimicrobial Nanomaterial and its Effect on the Antimicrobial Activity, Flow and Radiopacity of Endodontic Sealers

Objective:

This preliminary study aimed to evaluate the antimicrobial activity, flow and radiopacity of endodontic sealers with nanostructured silver vanadate decorated with silver nanoparticles (AgVO3).

Methods:

The minimum inhibitory concentration (MIC) of AgVO3 was evaluated against Enterococcus faecalis, Pseudomonas aeruginosa and Escherichia coli. Specimens were prepared from the following endodontic sealers: AH Plus (DENTSPLY DeTrey GmbH, Konstanz, Germany), Sealapex (Sybron Endo, Orange, CA, USA), Sealer 26 (DENTSPLY, Petrópolis, Brazil) and Endofill (DENTSPLY, Petrópolis, Brazil), with concentrations of 0%, 2.5%, 5% and 10% of AgVO3. Agar diffusion was used to evaluate the materials after 48 hours and 7 days (n=6). Flow (n=6) and radiopacity (n=9) were evaluated. The data were analysed by analysis of variance (ANOVA) and the Tukey honestly significant difference (HSD) (α=0.05).

Results:

The MIC of AgVO3 was 500 μg/mL for E. faecalis and 31.25 μg/mL for P. aeruginosa and E. coli. The AgVO3 did not influence the antimicrobial activity of AH Plus against E. faecalis (P>0.05) but did promote this activity for Sealapex (P<0.01). Moreover, this activity increased for Endofill from 2.5% and for Sealer 26 from 5% (P<0.05). Against P. aeruginosa, only AH Plus and Endofill 10% inhibited zone formation (P<0.01). The antimicrobial activity of Endofill increased from 2.5% against E. coli (P<0.01). Sealapex 5% and 10% (P<0.01), Sealer 26 10% and AH Plus promoted antimicrobial activity against E. coli. An increase in the zone of inhibition occurred between 48 hours and 7 days in the Sealapex 10% and Endofill 5% groups against E. coli. The flow of AH Plus and Endofill decreased with the increase of AgVO3 (P<0.05), and the flow of Sealer 26 and Sealapex was not affected (P>0.05). The radiopacity of AH Plus increased with AgVO3 (P<0.05). Endofill 5% and 10% did not differ from the control Endofill (P>0.05). The incorporation of AgVO3 did not influence the radiopacity of Sealer 26 (P>0.05). The incorporation of 2.5% and 5% AgVO3 reduced the radiopacity of Sealapex (P<0.05).

Conclusion:

Adding AgVO3 may increase the antimicrobial effect of endodontic sealers without major changes in their physicochemical properties.