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In vitro quantification of changes in human dentine tubule parameters using SEM and digital analysis.

Authors
  • Ahmed, T R
  • Mordan, N J
  • Gilthorpe, M S
  • Gillam, D G
Type
Published Article
Journal
Journal of oral rehabilitation
Publication Date
Aug 01, 2005
Volume
32
Issue
8
Pages
589–597
Identifiers
PMID: 16011638
Source
Medline
License
Unknown

Abstract

Dentine hypersensitivity is recognized as a pain arising from fluid movement within dentine tubules that are open to the oral environment. Blocking the tubules is considered to be the principal aim of treatment, and the accurate assessment of tubule occlusion is the primary goal of many in vitro studies. This assessment usually comprises either measuring tubule permeability or scanning electron microscope examination of the dentine surface. Several scanning microscopy studies have claimed to quantify tubule occlusion, but are descriptive, qualitative or semi-quantitative evaluations. The present study was undertaken to assess the use of digital image analysis in quantifying the effectiveness of a selected desensitizing agent from micrographs of control and treated dentine surfaces. Using a dentine disc model, an accurate methodology was sought to investigate the occluding potential of Butler Protect (J.O. Butler, Chicago, IL, USA). Subjective examination of the images indicated there was little difference after a single application, but considerable effect after 20 applications. Quantitative digital analysis of a test image, demonstrated reproducibility between two examiners when used in fully- and semi-automated mode. After a single application of Butler Protect, multilevel statistical modelling demonstrated decreases in tubule area and maximum, minimum and mean diameter measurements (P < 0.001), whereas single level analysis showed increases in area and maximum and mean diameters. Multiple application of Butler Protect demonstrated even greater decreases in all parameters (P < 0.001). This quantitative methodology was reproducible between examiners and, when combined with good controls and multilevel statistical modelling, was able to discriminate a single application of desensitizing agent.

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