Gillian Layton1, Wen-I Wu2, Ponnambalam Ravi Selvaganapathy2, Shimon Friedman1, Anil Kishen3. 1. Discipline of Endodontics, University of Toronto, Toronto, Ontario, Canada. 2. Department of Mechanical Engineering, McMaster University, Hamilton, Ontario, Canada. 3. Discipline of Endodontics, University of Toronto, Toronto, Ontario, Canada. Electronic address: akishen@gmail.com.
Abstract
INTRODUCTION: Thorough understanding of fluid dynamics in root canal irrigation and corresponding antibiofilm capacity will support improved disinfection strategies. This study aimed to develop a standardized, simulated root canal model that allows real-time analysis of fluid/irrigation dynamics and its correlation with biofilm elimination. METHODS: A maxillary incisor with an instrumented root canal was imaged with micro-computed tomography. The canal volume was reconstructed in 3 dimensions and replicated in soft lithography-based models microfabricated from polyethylene glycol-modified polydimethylsiloxane. Canals were irrigated by using a syringe (SI) and 2 ultrasonic-assisted methods, intermittent (IUAI) and continuous (CUAI). Real-time fluid movement within the apical 3 mm of canals was imaged by using microparticle image velocimetry. In similar models, canals were inoculated with Enterococcus faecalis to grow 3-week-old biofilms. Biofilm reduction by irrigation with SI, CUAI, and IUAI was assessed by using a crystal violet assay and compared with an untreated control. RESULTS: SI generated higher velocity and shear stress in the apical 1-2 mm than 0-1 and 2-3 mm. IUAI generated consistently low shear stress in the apical 3 mm. CUAI generated consistently high levels of velocity and shear stress; it was the highest of the groups in the apical 0-1 and 2-3 mm. Biofilm was significantly reduced compared with the control only by CUAI (two-sample permutation test, P = .005). CONCLUSIONS: CUAI exhibited the highest mechanical effects of fluid flow in the apical 3 mm, which correlated with significant biofilm reduction. The soft lithography-based models provided a novel model/method for study of correlations between fluid dynamics and the antibiofilm capacity of root canal irrigation methods.
INTRODUCTION: Thorough understanding of fluid dynamics in root canal irrigation and corresponding antibiofilm capacity will support improved disinfection strategies. This study aimed to develop a standardized, simulated root canal model that allows real-time analysis of fluid/irrigation dynamics and its correlation with biofilm elimination. METHODS: A maxillary incisor with an instrumented root canal was imaged with micro-computed tomography. The canal volume was reconstructed in 3 dimensions and replicated in soft lithography-based models microfabricated from polyethylene glycol-modified polydimethylsiloxane. Canals were irrigated by using a syringe (SI) and 2 ultrasonic-assisted methods, intermittent (IUAI) and continuous (CUAI). Real-time fluid movement within the apical 3 mm of canals was imaged by using microparticle image velocimetry. In similar models, canals were inoculated with Enterococcus faecalis to grow 3-week-old biofilms. Biofilm reduction by irrigation with SI, CUAI, and IUAI was assessed by using a crystal violet assay and compared with an untreated control. RESULTS: SI generated higher velocity and shear stress in the apical 1-2 mm than 0-1 and 2-3 mm. IUAI generated consistently low shear stress in the apical 3 mm. CUAI generated consistently high levels of velocity and shear stress; it was the highest of the groups in the apical 0-1 and 2-3 mm. Biofilm was significantly reduced compared with the control only by CUAI (two-sample permutation test, P = .005). CONCLUSIONS: CUAI exhibited the highest mechanical effects of fluid flow in the apical 3 mm, which correlated with significant biofilm reduction. The soft lithography-based models provided a novel model/method for study of correlations between fluid dynamics and the antibiofilm capacity of root canal irrigation methods.
Authors: Saifalarab A Mohmmed; Morgana E Vianna; Matthew R Penny; Stephen T Hilton; Nicola Mordan; Jonathan C Knowles Journal: Microbiologyopen Date: 2017-02-28 Impact factor: 3.139
Authors: T C Pereira; C Boutsioukis; R J B Dijkstra; X Petridis; M Versluis; F B de Andrade; W J van de Meer; P K Sharma; L W M van der Sluis; M V R So Journal: Int Endod J Date: 2020-11-18 Impact factor: 5.264