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Abstract ObjectivesDeterioration in anterior resin composite restorations placed in tooth wear patients was investigated after 36 months.Materials and methodsData collected prospectively for 47 participants of the Radboud Tooth Wear Project were used (41 ± 8 years, 90% male, n = 270 restorations). Restorations were individually evaluated using intraoral photographs and 3D scans to rate modified FDI scores and to record the presence of degradation features. Four groups with distinct combinations of composites and techniques were assessed, and multivariable logistic regression models were used to analyze the data (p < 0.05).ResultsFor all groups together, early degradation signs were present at 1 month: irregularities (41.5%) and ditching (7.4%) were observed at the surface and adhesive interfaces. The frequency of irregularities decreased in the 36-month evaluation (37%), but ditching (12.2%) and fractures (10.7%) were more common. The most frequent deterioration (based on photographs) was observed for staining (44%) and loss of luster (31%). In 3D scans, the most frequent were for wear (25%), marginal adaptation (24%), and the presence of irregularities (19%). Canines had 5.5 times more chances of deterioration by ditching than incisors (p < 0.001). The differences between composites and restorative techniques were minor.ConclusionsA continuous degradation process of restorations placed in tooth wear patients was observed in anterior teeth restored with different composites, with a progression of the deterioration over 36 months.Clinical relevanceWhen placing anterior resin composite restorations in tooth wear patients, it could be important to establish realistic expectations and the need for checkup appointments.

Three-dimensional scans are increasingly used to quantify biological topographical changes and clinical health outcomes. Traditionally, the use of 3D scans has been limited to specialized centers owing to the high cost of the scanning equipment and the necessity for complex analysis software. Technological advances have made cheaper, more accessible methods of data capture and analysis available in the field of dentistry, potentially facilitating a primary care system to quantify disease progression. However, this system has yet to be compared with previous high-precision methods in university hospital settings. The aim of this study was to compare a dental primary care method of data capture (intraoral scanner) with a precision hospital-based method (laser profilometer) in addition to comparing open source and commercial software available for data analysis. Longitudinal dental wear data from 30 patients were analyzed using a two-factor factorial experimental design. Bimaxillary intraoral digital scans (TrueDefinition, 3M, UK) and conventional silicone impressions, poured in type-4 dental stone, were made at both baseline and follow-up appointments (mean 36 months, SD 10.9). Stone models were scanned using precision laser profilometry (Taicaan, Southampton, UK). Three-dimensional changes in both forms of digital scans of the first molars (n=76) were quantitatively analyzed using the engineering software Geomagic Control (3D Systems, Germany) and freeware WearCompare (Leeds Digital Dentistry, UK). Volume change (mm ) was the primary measurement outcome. The maximum point loss (μm) and the average profile loss (μm) were also recorded. Data were paired and skewed, and were therefore compared using Wilcoxon signed-rank tests with Bonferroni correction. The median (IQR) volume change for Geomagic using profilometry and using the intraoral scan was -0.37 mm (-3.75-2.30) and +0.51 mm (-2.17-4.26), respectively (P<.001). Using WearCompare, the median (IQR) volume change for profilometry and intraoral scanning was -1.21 mm (-3.48-0.56) and -0.39 mm (-3.96-2.76), respectively (P=.04). WearCompare detected significantly greater volume loss than Geomagic regardless of scanner type. No differences were observed between groups with respect to the maximum point loss or average profile loss. As expected, the method of data capture, software used, and measurement metric all significantly influenced the measurement outcome. However, when appropriate analysis was used, the primary care system was able to quantify the degree of change and can be recommended depending on the accuracy needed to diagnose a condition. Lower-resolution scanners may underestimate complex changes when measuring at the micron level.