Influence of operator experience, scanner type, and scan size on 3D scans.

STATEMENT OF PROBLEM: Intraoral scanners (IOSs) have some inherent distortions caused by optical and/or software imperfections. However, how other factors such as operator experience, scan time, scanner type, and scan size influence scan accuracy is not clear. PURPOSE: The purpose of this in vitro study was to evaluate the trueness and precision of scans performed by 3 professionals with different levels of experience by using 2 IOSs. MATERIAL AND METHODS: Three operators with low, medium, and high levels of experience scanned a master model 10 times by using 2 IOSs (CEREC Omnicam; Dentsply Sirona and TRIOS 3; 3Shape), resulting in 10 standard tessellation language files for each group (N=60). Each standard tessellation language file was divided into 2 areas (prepared teeth and complete arch). Precision was evaluated by comparing the 10 scans from each examiner for each system. Trueness was evaluated by comparing each scan file with a reference scan obtained from a laboratory scanner (D2000; 3Shape). A 3D analysis software program (Geomagic Control; 3D Systems) was used to perform all the comparisons and superimpositions. The 3-way ANOVA test followed by the Tukey HSD test were used to assess precision and trueness. The 2-way ANOVA followed by the Tukey HSD test was used to assess scan time. The Pearson correlation test was performed between scan time and trueness for both scanners. An additional correlation was performed between scan time and number of images, as well as between number of images and trueness for the TRIOS 3. RESULTS: Statistically significant influences of operator (P<.001), scanner (P<.001), scan size (P<.001), operator and scan size (P<.001), and scanner and scan size (P<.001) were observed. The TRIOS 3 group reported higher precision than the CEREC Omnicam group for complete-arch scans (P<.001), although no difference was observed for scans of the prepared tooth. Medium- (P=.002) and low-experience operators (P<.001) reported lower precision for complete-arch scans performed with CEREC Omnicam when compared with TRIOS 3. The low-experience operator reported significantly worse results for complete-arch scans in comparison with the medium- (P=.008 and P<.001) and high-experience operators (P<.001 and P=.001), by using TRIOS 3 and CEREC Omnicam, respectively. Medium- and high-experience operators reported similar results among themselves. The CEREC Omnicam scanner reported lower trueness for complete-arch scans when compared with the prepared tooth (P<.001); for TRIOS 3, a difference was only observed for the low-experience operator when compared with the high-experience operator (P<.001). The CEREC Omnicam reported lower trueness than the TRIOS 3, except for the medium-experience operator with the prepared tooth scan. Comparing the trueness between operators and considering the same scanner and scan size, all groups were similar. The low-experience operator had a longer scanning time than the medium- and high-experience operators. For TRIOS 3, the low-experience operator obtained the highest number of images during each scan. CONCLUSIONS: The accuracy of intraoral scans was influenced by operator experience, type of IOSs, and scan size. More experienced operators and smaller scan sizes made for more accurate scans. In addition, more experienced operators made faster scans, and the TRIOS 3 was more accurate than the CEREC Omnicam for complete-arch scans.

Accuracy of Conventional and 3D-Printed Casts for Partial Fixed Prostheses.

PURPOSE: To evaluate and compare the accuracy of conventional and 3D-printed casts using five different 3D printers. MATERIALS AND METHODS: In the control group (CG group, n = 5), five conventional impressions using light- and heavy-body polyvinyl siloxane were obtained from the master model, resulting in five stone models. In the test groups, five different scans were performed by a well-trained and experienced clinician using a TRIOS intraoral scanner. All data were exported in STL file format, processed, and sent to five 3D printers. Five casts were manufactured in each printer group: SG (CARES P20, Straumann); FG (Form 2, Formlabs); WG (Duplicator 7, Wanhao); ZG (Zenith D, Zenith); and MG (Moonray S100, Moonray). Measurements of the accuracy (trueness and precision) of the casts obtained from conventional elastomeric impressions and 3D-printing methods were accomplished using a 3D analysis software (Geomagic Control). RESULTS: The FG group showed the lowest values for trueness (indicating a value closer to real dimensions), which were similar to the SG group only (P > .05). MG, WG, and ZG groups presented higher values and were similar compared to each other. Data on precision demonstrated that all 3D-printed groups showed lower values for precision (smaller deviation) when compared to the CG. CONCLUSIONS: The trueness depends on the chosen 3D printer. All of the tested 3D printers were more precise than cast models obtained from conventional elastomeric impressions.

Prevalence of non-carious cervical lesions and orthodontic treatment: a retrospective study.

BACKGROUND: This study aimed to assess the distribution of non-carious cervical lesions (NCCLs) by tooth type, investigate the prevalence of NCCLs in patients undergoing orthodontic treatment, and identify the possible associated factors. MATERIAL AND METHODS: A total of 160 patients were enrolled in this retrospective study. Data on the following variables were collected from pre-and post-orthodontic treatment records: age, sex, Angle's malocclusion, facial pattern, number of activation sessions, compensatory treatment, and retreatment. Frontal, right and left lateral intraoral photographs of each patient were evaluated to identify the presence or absence of NCCLs in each tooth and assess the distribution of NCCLs in the 3840 teeth from the enrolled patients. Furthermore, patients were classified as NCCLs present, irrespective of the number of NCCLs on the teeth or NCCL absent. Bivariate and multivariate Poisson regression analyses with robust variance were used to assess the association between the NCCLs and each independent variable. Prevalence ratio and 95% confidence intervals were calculated and p < 0.05 was considered statistically significant. RESULTS: The prevalence of NCCLs before and after orthodontic treatment was 22.71% and 30.91%, respectively. Premolars were the most affected teeth, followed by the first molars, canines, and incisors. After statistical analysis, age was found to be the variable factor that influenced the prevalence ratio, with NCCL being the most prevalent when orthodontic treatment was performed in adulthood. CONCLUSIONS: Premolars were most commonly affected by NCCLs. Furthermore, age seemed to contribute to the increased prevalence of NCCLs in adults undergoing orthodontic treatment.