Effect of smart endodontic motors (AI-based torque control) on file separation and dentinal damage

INTRODUCTION. Implementation of artificial intelligence (AI) in the endodontic motor technology offers improved safety due to real-time torque monitoring and adaptive control. Nevertheless, there is little comparative evidence on their clinical effectiveness in preventing instrument separation and reduction of iatrogenic dentinal damage.

MATERIALS AND METHODS. Ninety human mandibular molars with mesial canals (curvature 25–35°) were randomly divided to three groups (n = 30) Group A (AI-based smart motor with adaptive torque control), Group B (conventional motor with preset torque limits), and Group C (conventional motor with auto-reverse operation). ProTaper Next rotary files were used to prepare the standardized canals. The main variables were file separation rate and dentinal microcracks incidence evaluated through micro-computed tomography (micro-CT). Preparation time, apical transportation, canal centering ratio, and motor operational parameters were the secondary outcomes.

RESULTS. Group A exhibited a much lower file separation rate (0% vs. 10.0% vs. 13.3% in Group B vs. Group C, p = 0.038) and fewer dentinal microcracks formed (16.7% vs. 43.3% vs. 50.0% p = 0.006). Group A recorded significantly lower peak of mean torque (2.1 + 0.4 Ncm compared to 2.8 + 0.6 Ncm in Group B compared to 2.9 + 0.7 Ncm in Group C, p < 0.001). Apical transportation (p = 0.284) and canal centering ratio (p = 0.412) showed no significant differences. Time of preparation did not differ among groups (p = 0.156).

CONCLUSIONS. Smart endodontic motors with adaptive torque control powered by AI allow a significantly lower file separation and dentinal microcrack formation than using conventional motors and offer similar shaping efficiency and preparation quality. Based on these findings, AI-based motor technology can be clinically adopted to improve the safety of the procedures.

1. Hülsmann M., Peters O.A., Dummer P.M.H. Mechanical preparation of root canals: shaping goals, techniques and means. Endod Topics. 2005;10(1):30–76. https://doi.org/10.1111/j.1601-1546.2005.00152.x

2. Parashos P, Gordon I, Messer HH. Factors influencing defects of rotary nickel-titanium endodontic instruments after clinical use. J Endod. 2004;30(10):722–725. https://doi.org/10.1097/01.don.0000129963.42882.c9

3. Sattapan B., Nervo G.J., Palamara J.E., Messer H.H. Defects in rotary nickel-titanium files after clinical use. J Endod. 2000;26(3):161–165. https://doi.org/10.1097/00004770-200003000-00008

4. Spili P., Parashos P., Messer H.H. The impact of instrument fracture on outcome of endodontic treatment. J Endod. 2005;31(12):845–850. https://doi.org/10.1097/01.don.0000164127.62864.7c

5. Plotino G., Grande N.M., Cordaro M., Testarelli L., Gambarini G. A review of cyclic fatigue testing of nickel-titanium rotary instruments. J Endod. 2009;35(11):1469–1476. https://doi.org/10.1016/j.joen.2009.06.015

6. Shen Y., Coil J.M., Zhou H., Zheng Y., Haapasalo M. HyFlex nickel-titanium rotary instruments after clinical use: Metallurgical properties. Int Endod J. 2013;46(8):720–729. https://doi.org/10.1111/iej.12049

7. Yared G.M., Bou Dagher F.E., Machtou P. Influence of rotational speed, torque and operator’s proficiency on ProFile failures. Int Endod J. 2001;34(1):47–53. https://doi.org/10.1046/j.1365-2591.2001.00352.x

8. Bier C.A., Shemesh H., Tanomaru-Filho M., Wesselink P.R., Wu M.K. The ability of different nickel-titanium rotary instruments to induce dentinal damage during canal preparation. J Endod. 2009;35(2):236–238. https://doi.org/10.1016/j.joen.2008.10.021

9. De-Deus G., Silva E.J., Marins J., Souza E., Neves Ade A., Gonçalves Belladonna F. et al. Lack of causal relationship between dentinal microcracks and root canal preparation with reciprocation systems. J Endod. 2014;40(9):1447–1450. https://doi.org/10.1016/j.joen.2014.02.019

10. Wilcox L.R., Roskelley C., Sutton T. The relationship of root canal enlargement to finger-spreader induced vertical root fracture. J Endod. 1997;23(8):533–534. https://doi.org/10.1016/S0099-2399(97)80316-0

11. Shemesh H., Wesselink P.R., Wu M.K. Incidence of dentinal defects after root canal filling procedures. Int Endod J. 2010;43(11):995–1000. https://doi.org/10.1111/j.1365-2591.2010.01740.x

12. Schwendicke F., Samek W., Krois J. Artificial intelligence in dentistry: Chances and challenges. J Dent Res. 2020;99(7):769–774. https://doi.org/10.1177/0022034520915714

13. Hung K., Montalvao C., Tanaka R., Kawai T., Bornstein M.M. The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review. Dentomaxillofac Radiol. 2020;49(1):20190107. https://doi.org/10.1259/dmfr.20190107

14. Gambarini G., Galli M., Stefanelli L.V., Di Nardo D., Morese A., Seracchiani M. et al. Endodontic microsurgery using dynamic navigation system: A case report. J Endod. 2019;45(11):1397-1402.e6. https://doi.org/10.1016/j.joen.2019.07.010

15. Khanagar S.B., Al-Ehaideb A., Maganur P.C., Vishwanathaiah S., Patil S., Baeshen H.A. et al. Developments, application, and performance of artificial intelligence in dentistry – A systematic review. J Dent Sci. 2021;16(1):508–522. https://doi.org/10.1016/j.jds.2020.06.019

16. Peters O.A., Morgental R.D., Schulze K.A., Paqué F., Kopper P.M., Vier-Pelisser F.V. Determining cutting efficiency of nickel-titanium coronal flaring instruments used in lateral action. Int Endod J. 2014;47(6):505–513. https://doi.org/10.1111/iej.12177

17. Capar I.D., Ertas H., Ok E., Arslan H., Ertas E.T. Comparative study of different novel nickel-titanium rotary systems for root canal preparation in severely curved root canals. J Endod. 2014;40(6):852–856. https://doi.org/10.1016/j.joen.2013.10.010

18. Paqué F., Musch U., Hülsmann M. Comparison of root canal preparation using RaCe and ProTaper rotary Ni-Ti instruments. Int Endod J. 2005;38(1):8–16. https://doi.org/10.1111/j.1365-2591.2004.00889.x