title: The efficacy of dynamic irrigation using a commercially available system (RinsEndo) determined by removal of a collagen 'bio-molecular film' from an ex vivo model.
abstract: OBJECTIVE
  To compare the efficacy of three irrigation protocols using an established ex vivo bio-molecular film model.
  
  
  METHODS
  Thirty human teeth with single straight canals were randomly allocated to three groups [static, manual-dynamic, automated-dynamic (RinsEndo]; each with a sub-group (n = 5) for needle position at 4 or 10 mm short of the working length (WL). The root canals were prepared to apical size 40, taper 0.08. The teeth were split longitudinally into two halves and a standard coat of stained-collagen was applied to the canal surfaces. The re-assembled teeth were irrigated using one of the protocols with the irrigation needle at one of two positions. Digital images of the canal surfaces, before and after irrigation with 18 mL of 2.5% NaOCl, were used to score surface coverage with stained-collagen using image-analyses (ipWin4). The data were analysed using linear regression models.
  
  
  RESULTS
  The canal area covered with stained-collagen was significantly (P < 0.001) less after dynamic irrigation (manual/automated) compared with static irrigation; but automated-dynamic irrigation was significantly (P = 0.037) less effective than manual-dynamic irrigation. The 'orientation of needle port', 'corono-apical level of canal' and 'apical extent of needle placement' were significant (P < 0.001) factors influencing efficacy of irrigation. Residual collagen was most evident in the coronal third. Deeper penetration of the needle tip resulted in significantly (P < 0.001) more effective collagen removal.
  
  
  CONCLUSIONS
  Automated-dynamic irrigation was significantly more effective (16%) than static irrigation but significantly less effective (5%) than manual-dynamic irrigation. Irrigation was more effective (7%) when the needle was placed closer to WL.
authors.affiliation: Unit of Endodontology, UCL Eastman Dental Institute, University College London, London, UK.
authors.forename: S
authors.initials: S
authors.lastname: McGill
authors.forename: K
authors.initials: K
authors.lastname: Gulabivala
authors.forename: N
authors.initials: N
authors.lastname: Mordan
authors.forename: Y-L
authors.initials: YL
authors.lastname: Ng
mesh_terms: D018441:Biofilms / Q000187:drug effects*; D003094:Collagen; D003786:Dental Pulp Cavity / Q000382:microbiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D008954:Models, Biological; D012388:Root Canal Irrigants / Q000008:administration & dosage* / Q000494:pharmacology; D018915:Root Canal Preparation / Q000379:methods*; D016369:Smear Layer; D012973:Sodium Hypochlorite / Q000008:administration & dosage* / Q000494:pharmacology; D007507:Therapeutic Irrigation / Q000379:methods
chemical_list: D012388:Root Canal Irrigants; D003094:Collagen; D012973:Sodium Hypochlorite