Objectives: Alignment procedures have yet to be standardised and may influence the measurement outcome. This investigation assessed the accuracy of commonly used alignment techniques and their impact on measurement metrics.
Methods: Datasets of 10 natural molar teeth were created with a structured-light model-scanner (Rexcan DS2, Europac 3D, Crewe). A 300μm depth layer was then digitally removed from the occlusal surface creating a defect of known size. The datasets were duplicated, randomly repositioned and re-alignment attempted using a "best-fit" alignment, landmark-based alignment or reference alignment in Geomagic Control (3D Systems, Darmstadt, Germany). The re-alignment accuracy was mathematically assessed using the mean angular and translation differences between the original alignment and the re-aligned datasets. The effect of the re-alignment on conventional measurement metrics was calculated by analysing differences between the known defect size and defect size after re-alignment. Data were analysed in SPSS v24(ANOVA, post hoc Games Howell test, p<0.05).
Results: The mean translation error (SD) was 139μm (42) using landmark alignment, 130μm (26) for best-fit and 22μm (9) for reference alignment (p<0.001). The mean angular error (SD) between the datasets was 2.52 (1.18) degrees for landmark alignment, 0.56 (0.38) degrees for best-fit alignment and 0.26 (0.12) degrees for reference alignment (p<0.001). Using a reference alignment statistically reduced the mean profilometric change, volume change and percentage of surface change errors (p<0.001).
Significance: Reference alignment produced significantly lower alignment errors and truer measurements. Best-fit and landmark-based alignment algorithms significantly underestimated the size of the defect. Challenges remain in identifying reference surfaces in a robust, clinically relevant method.
Keywords: Dental technology; Diagnostic imaging; Tooth erosion; Tooth wear.
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