Haidar Alalawi,Faisal D. Al-Qarni,Mohammed M. Gad
Comparative evaluation of the accuracy of 3D-printed denture teeth
3D Printing,Denture teeth,Removable dental prosthesis
Objective This in vitro study compares the accuracy and trueness of various 3D-printed denture teeth. Methods A total of 30 specimens were created using various 3D-printed resins, 10 each using Asiga DentaTOOTH resin (Asiga, Australia), Formlabs Denture Teeth Resin (Formlabs GmbH, Germany), and NextDent C&B MFH (Micro Filled Hybrid) resin (Nextdent B.V., Netherlands), respectively. A prefabricated mandibular first molar was scanned using a desktop laser scanner (E3, 3Shape A/S) to create a standard tessellation language file, which served as a “reference tooth” scan. That file was sent to each corresponding printer for printing according to manufacturer recommendations. The printed teeth were scanned with an intraoral scanner (TRIOS 3, 3shape, Copenhagen, Denmark). Trueness and precision were assessed using 3D morphometric analysis software (Geomagic Control X, 3D Systems, Rock Hill, SC, USA). One-way ANOVA was used to analyze the data (α = 0.05). Root mean square error and mean deviations were also calculated. Data analysis was carried out using SPSS (IBM Corp., New York, NY, USA) software. One-way ANOVA with Tukey’s post hoc analysis was used. P-values of<0.05 were regarded as statistically significant. Results The overall trueness of teeth followed a similar pattern, with the highest trueness recorded with NextDent specimens, while ASIGA specimens had the lowest. When precision was assessed, there were significant differences in occlusal areas between FormLabs and NextDent specimens (p = 0.01) and between FormLabs and ASIGA specimens (p = 0.002). However, ASIGA and NextDent did not differ from one another (p = 0.9). The precision analysis shows that all tested groups had similar values, with no significant differences among them. Conclusion The trueness values of the tested printing systems varied, although the precision values were similar. All evaluated printing systems achieved printing accuracy falling within the clinically acceptable range.
Comparative evaluation of the accuracy of 3D-printed denture teeth

This in vitro study compares the accuracy and trueness of various 3D-printed denture teeth.

A total of 30 specimens were created using various 3D-printed resins, 10 each using Asiga DentaTOOTH resin (Asiga, Australia), Formlabs Denture Teeth Resin (Formlabs GmbH, Germany), and NextDent C&B MFH (Micro Filled Hybrid) resin (Nextdent B.V., Netherlands), respectively. A prefabricated mandibular first molar was scanned using a desktop laser scanner (E3, 3Shape A/S) to create a standard tessellation language file, which served as a “reference tooth” scan. That file was sent to each corresponding printer for printing according to manufacturer recommendations. The printed teeth were scanned with an intraoral scanner (TRIOS 3, 3shape, Copenhagen, Denmark). Trueness and precision were assessed using 3D morphometric analysis software (Geomagic Control X, 3D Systems, Rock Hill, SC, USA). One-way ANOVA was used to analyze the data (α = 0.05). Root mean square error and mean deviations were also calculated. Data analysis was carried out using SPSS (IBM Corp., New York, NY, USA) software. One-way ANOVA with Tukey’s post hoc analysis was used. P-values of<0.05 were regarded as statistically significant.

The overall trueness of teeth followed a similar pattern, with the highest trueness recorded with NextDent specimens, while ASIGA specimens had the lowest. When precision was assessed, there were significant differences in occlusal areas between FormLabs and NextDent specimens (p = 0.01) and between FormLabs and ASIGA specimens (p = 0.002). However, ASIGA and NextDent did not differ from one another (p = 0.9). The precision analysis shows that all tested groups had similar values, with no significant differences among them.

The trueness values of the tested printing systems varied, although the precision values were similar. All evaluated printing systems achieved printing accuracy falling within the clinically acceptable range.

Digital dentures are fabricated using two methods; subtractive (milled) or additive (3D-printed) (Wagner and Kreyer, 2021). The milled denture base has performed better than the 3D-printed one. However, 3D printing has some benefits, such as less waste and improved reproducibility of numerous prostheses (Abduo et al., 2014, Tahayeri et al., 2018). Furthermore, the development and widespread utilization of printing systems, printing technology, and printing resins has contributed to reducing total costs, which are expected to continue to drop in the future as printed product quality improves (Tahayeri et al., 2018). Due to the popularity of 3D printing technology and the increased number of manufacturers of printing systems (printers and printed materials), a comparison between different resin types printed with different technologies has been recommended (Yoon et al., 2018, Dong et al., 2020, Revilla-Leon and Ozcan, 2019, Lin et al., 2020, Yoshidome et al., 2021). Stereolithography (SLA) and digital light processing (DLP) are the two most common types of denture printing technologies. A rise in the number and availability of SLA-based printers in recent years can be attributed to SLA’s excellent printing resolution and rapid printing speed (Yoon et al., 2018). DLP, a specific type of SLA printing technology, involves projecting a planar image of light onto a photopolymerized resin (Dong et al., 2020). Furthermore, DLP offers lower cost, quick processing, and excellent resolution (Revilla-Leon and Ozcan, 2019). A 3D printer produces energy to polymerize photosensitive materials utilizing light from a DLP projector (Lin et al., 2020). These variations between both SLA and DLP technologies can affect the accuracy of printed objects (Yoshidome et al., 2021). In 3D-printed technology, dentures are printed as separate denture bases and printed artificial teeth and then bonded with different systems (Anadioti et al., 2020). Many researchers have examined the accuracy and adaptability of denture bases and found 3D-printed dentures advantageous, in terms of proper fit and adaptability; however, a recent review has recommended further investigations to confirm this conclusion (Wang et al., 2021). Regarding the adaptability and retention of various denture bases, Tasaka et al. (2019) found that the 3D-printed denture base was more precise and had a higher retentive force than the experimental denture base made using a heat-processing technique. Just as CAD/CAM (milled and 3D-printed) reportedly showed greater adaptability and overcame the drawbacks of conventional denture bases, the 3D printing process appears to be a promising method that needs to be adopted and improved (Masri et al., 2020). The configurations of the printed object affect accuracy, as do the printing parameters determining the characteristics of the object, e.g., light intensity, output position, build angle, thickness, and the number of layers (Anadioti et al., 2020, Shin et al., 2021). Regarding the accuracy of denture base specimens (plate-shaped specimens), a recent study reported that material types significantly affect the accuracy of printed resin (Al-Qarni et al., 2022). This this could be due to the aforementioned factors; printing axis, resolution of different planes, and post-curing parameters depended on the printed resin and the recommended printing system (Al-Qarni and Gad, 2022, Keßler et al., 2021, Chen et al., 2021). Given the importance of the denture base, the denture teeth must also be printed with acceptable, dimensionally stable accuracy so as to ensure adequate occlusal function. Accuracy of denture teeth could affect occlusion and according to Landa (Landa, 1962), balanced occlusion and balanced articulation are the most significant contributing variables to denture stability and retention and subsequently to a successful prosthesis; however, the accuracy of denture teeth was not investigated. Earlier studies investigated the accuracy of 3D-printed teeth reproductions, revealing that extremely accurate 3D-printed tooth models could be manufactured (Sokolowski et al., 2019). Furthermore, it has been reported that 3D printing exhibits superior accuracy, even when compared with the milling method (Jeong et al., 2018). Further research was required to confirm the accuracy of 3D-printed teeth, as teeth are the major functional component of 3D-printed dentures. With recent advances in digital technology, 3D superimposition analysis has proven to be a reliable method for evaluating accuracy. Previous studies (Camardella et al., 2017, Emir and Ayyildiz, 2021) have found that this analysis method is more precise than conventional methods. Moreover, 3D superimposition and measurements were performed using a computer, which eliminates human errors (Dong et al., 2020, Yoshidome et al., 2021). Additionally, the accuracy of various locations can be calculated in the digital model, and any variations in the 3-dimensional model will be recorded (Yoshidome et al., 2021). Although widespread 3D printing technologies and multiple systems have been introduced, no study has evaluated the accuracy of printed resin teeth while comparing different printing systems using 3D superimposing analysis. Accordingly, this study compares the accuracy of different 3D-printed denture teeth in terms of trueness and precision. The null hypothesis here states that no significance in the trueness or precision of printed teeth obtains between the different printing systems.

The sample size was set using sample size calculation (n = 10/group) based on a prior study (Jeon et al., 2018), while maintaining a confidence interval of 95% and a 5% margin of error. A denture mandibular right first molar tooth (Major Dent-V, Moncalieri (TO), Italy) was mounted on a pink wax base (KRL Baseplate Wax Pink Hard, Kerr Dental Lab, California, United States). This model was scanned using a desktop laser scanner (E3; 3Shape A/S, Copenhagen, Denmark) and 3Shape Dental Software to create a standard tessellation language (STL) file. That STL file, labeled as “reference tooth,” was then printed with three different teeth resin materials and with different 3D printers. Asiga DentaTOOTH resin (Photopolymerized Methacrylate) was used with an Asiga MAX printer (Asiga, Alexandria NSW 2015, Australia), Formlabs Denture Teeth Resin (Dimethacrylate Photopolymer) was applied using a Formlabs 2 printer (Formlabs GmbH, Berlin, Germany), and NextDent C&B MFH (Micro Filled Hybrid) resin (Methacrylic oligomers Phosphine oxides) was used in conjunction with a NextDent 5100 printer (Nextdent B.V., Soesterberg, Netherlands). A total of 30 printed teeth (10 for each group) were printed in accordance with the manufacturer’s guidelines and prepared for analysis. In accordance with the manufacturer guidelines, the liquid resins were mixed before being poured into resin trays for NextDent and ASIGA, while the FormLabs tank was connected directly to the FormLabs printer. The printing parameters were standardized for all three materials. The printing layer thickness was 50 µm, and the printing orientation was 90 degrees. Following printing, the supporting structures at the base were removed and specimens were washed with 99% isopropyl alcohol, in order to remove unpolymerized resin. A final curing cycle was then performed using LC-3DPRINT BOX (3D Systems Corporation, Rock Hill, South Carolina, United States) for 10 min at 60 degreesC, to complete the polymerization of the samples. Each experimental tooth was then directly scanned using an intraoral scanner (TRIOS 3, 3shape, Copenhagen, Denmark), so as to obtain the printed teeth STL scan data (labeled as “printed teeth”). The ISO 5725–1 standard was used to evaluate the accuracy and trueness of the scanned and printed denture teeth (International Organization for Standardization. ISO 5725-1, 1994). A morphometric analysis software was used to accomplish the 3D analyses (Geomagic Control X, 3D Systems, Rock Hill, South Carolina, United States). Trueness was assessed by superimposing the STL file from the “reference tooth” scan onto the scan of the “printed tooth” STL file from each individual experimental group (n = 10 per group). In order to determine the precision, the data obtained by repeatedly scanning each printed crown material (nine times per group) was superimposed in a paired fashion. To evaluate the accuracy of the various materials and fabrication techniques, three comparison groups were established. Each sample was measured in three different regions and was assigned an overall measurement. Initial alignment was performed with enhanced alignment accuracy with feature recognition. Following the ideal mesh alignment, the scanned data files were compared using the best-fit algorithm. To ensure proper alignment, several cross-sectional views were generated. The “3D Compare” process was then performed, with a tolerance of 0.05 mm and a color bar range of 0.1 mm. The variance between the reference group and the test group was determined by employing the formula as the root mean square (RMS) error (Nedelcu et al., 2018, Park and Son, 2019, Wulfman et al., 2020, Latham et al., 2020, Lee et al., 2020): In the above, n is the total number of measurements recorded for each dataset, X1,i is the measurement point of the reference dataset, X2,i is the measurement point of the scan data. To enable clear comparisons, the overall deviations were presented as color maps, with tolerance values shown in the color map from −50 to + 50 µm and deviations presented from −100 to + 100 µm. Data analysis was carried out for the trueness and precision evaluations using SPSS (IBM Corp., New York, NY, USA) software. Initial analysis of data distribution using the Shapiro–Wilk test showed mixed distributions. One-way ANOVA with Tukey’s post hoc analysis was used to assess normally distributed data, whereas the Kruskal-Wallis test was used to analyze skewed distributions. P-values of<0.05 were regarded as statistically significant for all analyses.

The color-coded 3D surface deviation and accuracy maps of 3D-printed teeth superimposed on various printed materials and technologies are shown in Fig. 1, Fig. 2. The degree and location of the divergence between the printed teeth and the STL reference tooth are represented by the distribution variations in color. Mean RMS values for trueness analysis are shown in Table 1. All 3D printed specimens showed similar trueness in the occlusal area (p = 0.09), while the cervical area differed only between FormLabs and NextDent (p = 0.04). Axial surface trueness showed significant differences between all groups; it was found to be highest (low RMS) for NextDent, followed by FormLabs, then ASIGA specimens (p < 0.001). Analysis of trueness for the entire crown showed a similar trend, with NextDent specimens being the highest, while ASIGA specimens showed the lowest trueness values (highest RMS). Analysis of trueness through mean deviation is shown in Table 2. Trueness of the entire crown surfaces, as well as for the axial surface alone, were significantly different among all three tested groups (p < 0.001). The occlusal surface showed a similar deviation between ASIGA and NextDent specimens; on the cervical area, similar deviations were observed in ASIGA and FormLabs. The lowest deviation value was observed for FormLabs specimens at the occlusal (3.61 μm) and the cervical (10.48 μm) surfaces. NextDent specimens had the lowest deviation in the entire crown surfaces (10.48 μm) and in the axial surface (10.48 μm). Evaluation of precision with RMS showed significant differences in occlusal areas between FormLabs and NextDent (p = 0.01) and between FormLabs and ASIGA (p = 0.002); the difference between ASIGA and NextDent was insignificant (p = 0.9). All tested groups showed similar RMS values in all other tested areas. Mean RMS values for precision are shown in Table 3. Analysis of precision through mean deviation is shown in Table 4. All tested groups had similar values, with no significant differences among them.

The accuracy of printed teeth may affect the outcome of printed prostheses. With the increasing number of new 3D printed systems, the accuracy of different 3D printed teeth resin and corresponding printing systems have not been compared. This study’s aim is to compare the accuracy of different 3D printed denture teeth, in terms of trueness and precision. The null hypothesis is partly confirmed, as the 3D-printed teeth evaluated in the study generally exhibited no differences in precision, while trueness differed significantly among the tested resins and printing systems. Precision is a measurement of repeatability that indicates the closeness of different measured values, whereas trueness describes how far the measured value deviates from the true or actual value (CAD design) of the object being investigated (International Organization for Standardization. ISO 5725-1, 1994). In terms of trueness testing, the printed model of each material type was compared to the CAD design; to assess precision, the scans of the printed models were compared to one another. Complete dentures must have balanced occlusion and balanced articulation in the vertical, lateral, and anteroposterior planes (Landa, 1962). The trueness of printed denture teeth will affect the occlusal contacts and contribute to balanced articulation. Balanced articulation improves denture retention, which is the most significant factor in the success of complete dentures. Segmenting the teeth into several sections was done for this study’s 3D analysis. The accuracy measurements in this study were performed using best-fit alignment, as it has been used to evaluate 3D data sets in other studies (Ender and Mehl, 2013, Güth et al., 2013). The 3D analysis program reports provided measured points numbers, highest and lowermost limits of deviation, mean deviations, deviation distribution, and color maps for each sample. According to Güth et al. (2013) trueness, which reflects the spatial proximity between a test model and a specific reference, can be assessed by examining the mean positive or negative deviation for each alignment. Data analysis becomes more complicated, since the positive numbers will overtake the negative numbers when the average is determined, because the values are split into positive and negative ranges. To address this, the RMS value of all the absolute distances measured between the test and reference surfaces was determined for each group, regardless of whether they were placed above or below the reference surface. Rossini et al. (2016) have suggested that a deviation error of<200 µm should be regarded as clinically acceptable. Conversely, Hiroqaki et al. (2001) has contended that a deviation of 300 µm seems sufficient for a printed diagnostic cast. In this investigation, the mean deviation error values across all experimental groups were lower than the levels considered clinically acceptable in the two studies mentioned above. The accuracy of 3D-printed models produced by continuous liquid interface production and by digital light processing (DLP) technologies was investigated by Rungrojwittayakul et al. (2020). They claimed that dimensional accuracy was higher (45 mm) for continuous liquid interface production technology than for DLP technology (77 mm) and stated that it is preferable to have a discrepancy of<100 µm (Rungrojwittayakul et al., 2020). Moon et al. (2021)33 compared different 3D-printing technology for temporary restorations and observed differences between DLP and liquid crystal display (LCD) printing in larger restorations, with DLP printing having a lower degree of error. DLP-printed prostheses were less prone to shrinkage, which was evident on the occlusal surfaces. In this study, both ASIGA and NextDent had DLP-based printing systems, while the FormLabs printing system was SLA-based. Although the results are inconclusive as to which printing system is more accurate, all printing systems produced specimens within the clinically acceptable range. The labial and buccal surfaces of the 3D-printed teeth in the NextDent and ASIGA groups revealed a uniform pattern of the blue regions, which reflected shrinkage, whereas FormLabs groups showed the reverse, which may be due to an inconsistent pattern of shrinkage. This could be attributed to the surface characteristics of these regions, which were typically smooth and allowed the polymers to contact equally (Chuang et al., 2016). Based on the present study’s findings, wide variations and deviations in occlusal surfaces may be attributable to the complex morphology and features of printed teeth (e.g., deep pits and fissures). Other surfaces are relatively smooth-flat compared to occlusal morphology. Occlusal pits and fissures in the posterior teeth tend to cause accumulation of the fluid resin, which must be removed prior to post-print curing with ultraviolet light. Improper or delayed cleaning of the occlusal surfaces may cause complete curing of the resin stuck in pits and fissures, which in turn results in greater deviation (Dong et al., 2020). The accuracy of 3D printing technology can be influenced by several factors (Gad and Fouda, 2023). An in vitro investigation evaluated the accuracy of 3D-printed models with various printing layer thicknesses (25, 50, or 100 μm) and reported that a 25-μm thickness resulted in greater deviation, while the 100-μm thickness group had the least deviations (Favero et al., 2017). Different printing orientations have also been reported as affecting the accuracy of 3D-printed provisional crown and bridge dental materials (Tahayeri et al., 2018). Furthermore, a recent study evaluated the accuracy of 3D-printed denture specimens with various printing systems and reported significant differences in specimens’ length, width, and thickness (Al-Qarni et al., 2022). Other factors affecting the accuracy of 3D-printed materials include post-print curing, effects of support structures, printing resolution, and surface finish (Choi et al., 2002). The present study used standardized printing orientation, layer thickness, and post-print processing, as recommended by the printing systems manufacturers. Additional studies evaluating different printing parameters are needed to maximize the benefits of 3D printing in dentistry. Although variations exist in the trueness and precision of the 3D-printed teeth produced in the present study, the resultant values were all clinically acceptable. Further investigations are needed to confirm the influence of various materials and printing systems on the accuracy of 3D-printed denture teeth. The in vitro nature of the study is considered one of its limitations, due to the absence of oral environment factors. A lack of water aging or thermal challenges are other factors that could contribute to dimensional changes. Variations in scanners and printing factors not included in this study also constitute limitations of the present study. Further studies with high sample sizes and more printing systems with different printing parameters are required.

The evaluated printing systems exhibited different trueness values, while precision measurements were generally similar. NextDent specimens achieved the highest trueness at the axial surface and the entire crown surface, while FormLabs specimens had higher trueness in occlusal and cervical surfaces. All evaluated printing systems achieved printing accuracy falling within the clinically acceptable range.

No funding support.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.