The effect of supplementary methods on root canal cleaning: a study using 3D-printed mandibular molar models

This study investigated the cleaning effect of different irrigation and activation techniques in removing residual tissue from the root canal system using 3D-printed resin models based on micro-CT scans of natural teeth. Eleven first mandibular molars with different anatomies were selected, scanned, and replicated six times each, resulting in 66 3D resin models. A hydrogel-based like pulp tissue was injected into the canals to simulate tissue. The samples were divided into six groups: (1) irrigation with saline solution without activation (control), (2) use of positive pressure with NaOCl, (3) sonic activation, (4) wireless PUI activation, (5) conventional wired PUI activation, and (6) XP-Endo finisher agitation. Cleaning efficiency was evaluated by comparing the images before and after irrigation using ImageJ software, quantifying the percentage of remaining tissue. Statistical analysis was performed using one-way ANOVA and post-hoc Tukey's test (p < 0.05). Rinsing with saline solution showed the worst cleaning performance in all canal thirds (p < 0.05). XP-Endo Finisher, Sonic Activation, Wireless PUI, Conventional PUI, and Conventional Syringe Irrigation with NaOCl significantly outperformed saline irrigation. In the apical third, XP-Endo Finisher achieved the lowest residual tissue percentage (5.79%), while saline had the highest (53.82%). No significant differences were found among activation techniques (p > 0.05), not even between the activation techniques and positive pressure irrigation with NaOCl. Sonic Activation and XP-Endo Finisher eliminated tissue in some samples of the middle third. NaOCl irrigation alone effectively dissolves the hydrogel tissue even without activation. Although activation techniques do not provide a consistent statistical advantage, they remain valuable in complex anatomies. Complete tissue removal, particularly in the apical third, remains a challenge. Future research should validate these results in clinical settings and optimize irrigation protocols for improved outcomes.