Abstract
ObjectivesOur ability to detect dental wear on sequential scans is improving. This experiment aimed to determine if widely used surface registration methods were sufficiently accurate to distinguish differences between intervention groups on early wear lesions. MethodsBaseline measurements were taken on human molar buccal enamel samples (n = 96) with a confocal scanning profilometer (Taicaan, UK). Samples were randomly assigned to subgroups of brushing (30 linear strokes 300 g force) before or after an acid challenge (10 min citric acid 0.3% immersion) for four test dentifrices (medium abrasivity NaF, medium abrasivity SnF2, low abrasivity NaF and a water control). Post-experimental profilometry was repeated. 3D step height was analysed using WearCompare (www.leedsdigitaldentistry.co.uk/wearcompare, UK). Percentage Sa change was calculated using Boddies (Taicaan Technologies, Southampton, UK). Data were analysed in SPSS (IBM, USA). ResultsThe mean 3D step height (SD) observed when samples were brushed before the erosive challenge was −2.33 µm (3.46) and after was −3.5 µm (5.6). No significant differences were observed between timing of toothbrushing or dentifrice used. The mean % Sa change for the low abrasivity group (water control and low abrasivity NaF) was −10.7% (16.8%) and +28.0% (42.0%) for the medium abrasivity group (medium abrasivity NaF and SnF2). ConclusionsDetectable wear scars were observed at early stages of wear progression. However standard deviations were high and the experiment was underpowered to detect significant changes. Brushing with a low abrasivity dentifrice or water control produced a smoother surface whereas brushing with a high abrasivity dentifrice produced a rougher surface. Clinical SignificanceThe methodology currently used to align sequential scans of teeth and measure change is too imprecise to measure early wear on natural enamel surfaces unless a large sample size is used. Further improvements are required before we can fully assess early wear processes on natural teeth using profilometry.
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