ObjectivesThe purpose of this study was to assess the feasibility of 3D intraoral scanning for documentation of palatal soft tissue by evaluating the accuracy of shape, color, and curvature.Materials and methodsIntraoral scans of ten participants’ upper dentition and palate were acquired with the TRIOS® 3D intraoral scanner by two observers. Conventional impressions were taken and digitized as a gold standard. The resulting surface models were aligned using an Iterative Closest Point approach. The absolute distance measurements between the intraoral models and the digitized impression were used to quantify the trueness and precision of intraoral scanning. The mean color of the palatal soft tissue was extracted in HSV (hue, saturation, value) format to establish the color precision. Finally, the mean curvature of the surface models was calculated and used for surface irregularity.ResultsMean average distance error between the conventional impression models and the intraoral models was 0.02 ± 0.07 mm (p = 0.30). Mean interobserver color difference was − 0.08 ± 1.49° (p = 0.864), 0.28 ± 0.78% (p = 0.286), and 0.30 ± 1.14% (p = 0.426) for respectively hue, saturation, and value. The interobserver differences for overall and maximum surface irregularity were 0.01 ± 0.03 and 0.00 ± 0.05 mm.ConclusionsThis study supports the hypothesis that the intraoral scan can perform a 3D documentation of palatal soft tissue in terms of shape, color, and curvature.Clinical relevanceAn intraoral scanner can be an objective tool, adjunctive to the clinical examination of the palatal tissue.

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Post-processing analysis can provide valuable information for diagnosis and planning of orbital disorders. This cross-sectional study aims to evaluate the reliability of semi-automatic, orbital fat volumetry using magnetic resonance imaging (MRI). Two observers assessed the orbital fat volume using a standard MRI protocol (3T, T1w sequence) in 12 orbits diagnosed with Graves' orbitopathy (GO) and 10 healthy control orbits. MRI and computed tomography (CT) based analysis were compared. Intra-observer variability was good (intraclass correlation coefficient (ICC) 0.88; 95% confidence interval (CI) [0.70, 0.95]) and interobserver agreement was moderate (ICC 0.55; 95% CI [À0.09, 0.81]), which corresponds to a mean percentage difference of 1.3% and 17.9% of the total orbital fat volume. Mean differences between MRI and CT measurements were, respectively, 1.1 cm 3 (P= 0.064, 95% CI [À0.20, 2.43]) and 1.4 cm 3 (P=0.016, 95% CI [0.21, 2.56]) for the control and the GO group. MRI volumetry was strongly correlated with CT (Pearson's r= 0.7, P<0.001). We conclude that orbital fat volumetry is feasible with a semi-automatic segmentation procedure and standard MRI protocol. Correlation with CT volumetry is good, but considerable bias may derive from observer variability and these errors should be taken into account for the purpose of volumetric analysis. Better definition of error sources may increase measurement accuracy.

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