Comparative analysis of root canal changes after preparation with three systems using Cone-Beam Computed Tomography

Published: 30 November 2017
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Introduction: The aim of this study was to investigate the morphological changes in the root canal trajectory on extracted teeth after preparation with Endoflare/Revo-S1, Endoflare/ HeroShaper1 and ProTaper1 using Cone-Beam Computed Tomography (CBCT). Methods: 39 root canals with similar curvatures were divided into three homogeneous groups (n = 13). Root canals in Group 1 were shaped with Endoflare/Revo-S1; Group 2 with Endoflare/ Hero Shaper1, and Group 3 with ProTaper1. All specimens were scanned pre- and postoperatively using the Kodak1 9000C 3D imaging system. Changes in both degree and position of the root canal curvature were assessed. Canal transportation was calculated for each slice by comparing the position of the root canal centroid before and after instrumentation. Statistical analysis was carried out by the non-parametric Kruskal-Wallis test ( p < 0.05), and Mann-Whitney test applying the Bonferroni correction (p < 0.05). Results: The mean of curvature degree decreases significantly (p < 0.003) for each group, with no statistical differences between the three groups. Mean canal transportation scores ranged from 52 mm (Revo-S1) to 85 mm (ProTaper1) in the apical third; 51 mm (Revo-S1) to 87 mm (ProTaper1) in the middle third, and 77 mm (HEROShaper1) to 119 mm (ProTaper1) in the cervical third. In the apical and the middle parts, Revo-S1 produced statistically less transportation than HEROShaper1 (respectively p = 0.01708, p = 0.01328) and ProTaper1 (respectively p = 0.02402, p = 0.0202). Conclusion: All instruments produced a small curvature deviation and mild canal transportation. Revo-S1 resulted in less transportation in the apical and middle thirds.

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Oget, D., Braux, J., Compas, C., & Guigand, M. (2017). Comparative analysis of root canal changes after preparation with three systems using Cone-Beam Computed Tomography. Giornale Italiano Di Endodonzia, 31(2), 83–88. https://doi.org/10.32067/gie.2017.31.02.04