Dimensional accuracy of extrusion- and photopolymerization-based 3D printers: In vitro study comparing printed casts.

STATEMENT OF PROBLEM: Reliable studies comparing the accuracy of complete-arch casts from 3D printers are scarce. PURPOSE: The purpose of this in vitro study was to investigate the accuracy of casts printed by using various extrusion- and photopolymerization-based printers. MATERIAL AND METHODS: A master file was sent to 5 printer manufacturers and distributors to print 37 identical casts. This file consisted of a standardized data set of a maxillary cast in standard tessellation language (STL) format comprising 5 reference points for the measurement of 3 distances that served as reference for all measurements: intermolar width (IMW), intercanine width (ICW), and dental arch length (AL). The digital measurement of the master file obtained by using a surveying software program (Convince Premium 2012) was used as the control. Two extrusion-based (M2 and Ultimaker 2+) and 3 photopolymerization-based printers (Form 2, Asiga MAX UV, and myrev140) were compared. The casts were measured by using a multisensory coordinate measuring machine (O-Inspect 422). The values were then compared with those of the master file. The Mann-Whitney U test and Levene tests were used to determine significant differences in the trueness and precision (accuracy) of the measured distances. RESULTS: The deviations from the master file at all 3 distances for the included printers ranged between 12 µm and 240 µm (trueness), with an interquartile range (IQR) between 17 µm and 388 µm (precision). Asiga MAX UV displayed the highest accuracy, considering all the distances, and Ultimaker 2+ demonstrated comparable accuracy for shorter distances (IMW and ICW). Although myrev140 operated with high precision, it displayed high deviations from the master file. Similarly, although Form 2 exhibited high IQR, it did not deviate significantly from the master file in the longest range (AL). M2 performed consistently. CONCLUSIONS: Both extrusion-based and photopolymerization-based printers were accurate. In general, inexpensive printers were no less accurate than more expensive ones.

Clustering effects of oral conditions based on clinical and radiographic examinations.

OBJECTIVES: The intra-class correlation coefficient (ICC) is a measure of intra-subject clustering effects. A priori estimates of the ICC and the associated design effect (DE) are required for sample size estimation in clustered studies, and should be considered during their analysis, too. We aimed to determine the clustering effects of carious lesions, apical lesions, periodontal bone loss, and periodontal pocketing, assessed in clinical or radiographic examinations. METHODS: A subsample of patients (n = 175) enrolled in the fifth German Oral Health Study provided data on clinically determined carious teeth (i.e., with untreated carious lesions, WHO method) as well as teeth with periodontal pocketing (i.e., with maximum probing-pocket-depths ≥ 4 mm). A sample of panoramic radiographs (n = 85) from randomly chosen patients, examined from 2010 to 2017 at the Charité dental hospital, provided data on radiographically determined carious teeth (i.e., with lesions extending into dentine or enamel), teeth with apical lesions (determined by dentists via majority vote), and teeth with periodontal bone loss (≥ 20% of root-length). The ICC and its 95% confidence interval (95% CI) were determined. RESULTS: There were 3839 and 1961 teeth assessed in clinical and radiographic evaluations, respectively. For clinically or radiographically determined carious lesions, the ICC (95% CI) was 0.20 (0.16-0.24) or 0.19 (0.14-0.25), respectively. For clinical pocketing or radiographic bone loss, the ICC was 0.40 (0.35-0.46) or 0.30 (0.24-0.38), respectively. The lowest ICC was found for apical lesions at 0.08 (0.06-0.13). CONCLUSIONS: The ICC varied between assessment methods and conditions. Clustered trials should account for this during study planning and data analysis. CLINICAL RELEVANCE: Within the limitations of this study, and considering the risk of selection bias and the limited sample sizes of both datasets, clustering effects were substantial but varied between dental conditions. Studies not accounting for this during planning and analysis may yield misleading estimates if clustering is present.