Abstract
Introduction: The aim of the study is to investigate whether the 3-dimensional dynamic navigation system (3D-DNS) can improve experienced endodontists' (EEs') and novice endodontists' (NEs’) accuracy and efficiency in osteotomy and root-end resection (RER) and to verify that the 3D-DNS enables NEs to perform osteotomy and RER as accurately and efficiently as EEs. Methods: Seventy-six roots in cadaver heads were randomly divided into 4 groups: 3D-DNS-NE, 3D-DNS-EE, freehanded (FH)-NE, and FH-EE (all, n = 19). Cone-beam computed tomography scans were taken preoperatively and postoperatively. Osteotomy and RER were planned virtually in the X-guided software (X-Nav Technologies, Lansdale). Accuracy was calculated by measuring the 2-dimensional and 3D virtual deviations and angular deflection using superimposing software (X-Nav technologies). Efficiency was determined by the time of operation and the number of mishaps. Results: Accuracy deviations were significantly fewer in the 3D-DNS-EE group than those in the FH-EE group (P < .05). We found less 2-dimensional and 3D accuracy deviations comparing the 3D-DNS-NE group to the FH-NE group (P < .05). The time required for osteotomy and RER with the 3D-DNS was ∼ ½ of that required for the FH method for both EEs and NEs (P < .05). We found no difference in the number of mishaps between the 3D-DNS and FH groups for EEs and NEs (P > .05). Conclusions: The 3D-DNS improved EEs' and NEs' accuracy and efficiency in osteotomy and RER. The NEs were as efficient as the EEs using the 3D-DNS. Notably, the 3D-DNS improved the NEs’ accuracy compared to the FH method, but the 3D-DNS did not enable the NEs to perform osteotomy and RER as accurately as the EEs.
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Martinho, F. C., Aldahmash, S. A., Cahill, T. Y., Gupta, S., Dianat, O., Mostoufi, B., … Tordik, P. A. (2022). Comparison of the Accuracy and Efficiency of a 3-Dimensional Dynamic Navigation System for Osteotomy and Root-end Resection Performed by Novice and Experienced Endodontists. Journal of Endodontics, 48(10), 1327-1333.e1. https://doi.org/10.1016/j.joen.2022.07.001
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