Accuracy of five intraoral scanners in single, partial-arch, and full-arch implant cases: A comparative in vitro study

Accuracy of five intraoral scanners in single, partial-arch, and full-arch implant cases: A comparative in vitro study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Accuracy of five intraoral scanners in single, partial-arch, and full-arch implant cases: A comparative in vitro study Mahmoud M. M. Nosser, Artur Ismatullaev, Çise Özal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9150259/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This in vitro study aimed to evaluate and compare the trueness and precision of five intraoral scanners (IOSs) for single crown (SC), three-unit fixed partial dentures (FPD), and full-arch (FA) implant cases. These findings may provide clinicians with evidence-based guidance for selecting devices that yield reliable outcomes, particularly for complex prosthetic rehabilitations. Methods Two maxillary resin models (partially dentulous and fully edentulous), containing implant analogs and scan bodies, were fabricated using a computer-aided design and computer-aided manufacturing (CAD/CAM) and three-dimensional (3D) printing workflow. The models were scanned 10 times with a desktop reference scanner (InEos X5), and each IOS under each scenario. Geomagic Control X was used to assess the dataset and calculate root mean square (RMS) deviation data for trueness and precision. Statistical analysis included one-way ANOVA with Tukey post hoc and Bonferroni-adjusted pairwise comparisons, as well as two-way ANOVA to evaluate the effects of scanner type, clinical scenario, and their interaction. Statistical significance was set at p < 0.05, and effect sizes were reported as partial eta squared (η²) Results Significant differences in RMS trueness values were found among scanners in the SC and FA scenarios ( p < .001), with limited differences in the FPD scenario. iTero Lumina and Helios 600 demonstrated lower trueness deviations, whereas Trios 5 showed greater deviations, especially in FA scanning. Precision analysis revealed significant differences in FPD and FA scenarios. Two-way ANOVA confirmed significant effects of scanner type and clinical scenario without interaction for trueness. Precision was also significantly influenced by scanner type, scanning scenario, and their interaction ( p < .001). Conclusion Both the scanner type and scanning scenario were found to influence trueness and precision. As scanning became increasingly complex, deviations also increased, emphasizing the need to assess IOSs more carefully when scanning complex clinical scenarios. These findings emphasize that intraoral scanner selection should be guided by scenario complexity, particularly for FA implant cases. Intraoral scanners Digital impressions Accuracy Trueness Precision Figures Figure 1 Figure 2 Figure 3 Figure 4 Background For many years, oral implants have enhanced the treatment of individuals who are partially or totally edentulous. Although implant-supported dental prostheses have proven to be a reliable long-term treatment option, their success largely depends on the accuracy of the impression, as an imprecise capture may fail to record the exact implant positions and their spatial relationships with adjacent oral structures, such as teeth, alveolar crests, and soft tissues [ 1 ]. For decades, conventional impression techniques were considered the gold standard; however, their accuracy may be influenced by material-related factors such as elastic recovery, stiffness or flexibility, dimensional stability, polymerization shrinkage, hydrophilicity, polymerization kinetics, or tear resistance, and their interaction with the impression technique itself [ 2 ]. Prosthodontics has changed significantly since the introduction of digital impressions and computer-aided design and manufacturing systems. Virtual treatment planning and simulation, combining digital impressions with three-dimensional (3D) imaging, have enhanced the precision and predictability of prosthesis fabrication. The multiple clinical benefits of digital impressions include increased operator efficiency and reduced chair time and number of patient visits, leading to enhanced comfort for patients and clinicians when compared with conventional impression techniques [ 3 – 6 ]. IOSs capture successive images of the patient's dental arches using structured light and/or lasers, which enables 3D surface reconstruction with dedicated reconstruction software. These software programs create triangulated point clouds that provide surface reconstructions, or meshes, which are the virtual representations of the patient's dental arches [ 7 , 8 ]. Additionally, depending on the manufacturer, IOSs use a variety of imaging technologies and operating principles, including laser and video capture, confocal microscopy, triangulation, structured light projection, interferometry, and wave sampling. The clarity and quality of the resulting images are strongly influenced by the imaging technology employed [ 9 , 10 ]. IOSs, now used routinely, enable the fabrication of implant-supported restorations through a fully digital workflow. Data recorded using a scan body are transferred to CAD software for designing the prosthetic restorations, which are directly sent for fabrication [ 11 ]. The accuracy of each step within this digital workflow is therefore critical to the success of the treatment. Consequently, a thorough understanding of the performance of different IOSs and the influencing factors of scanning technique and outcome is required to optimize their accuracy [ 12 ]. Accurate digital impressions are essential for fabricating restorations that fit implants correctly. The two main criteria of accuracy, as stated in ISO 5725, are precision and trueness. Trueness describes how closely the average of many test findings resembles the actual or recognized reference value. Precision refers to the degree of agreement between test results, or the consistency or repetition of the results [ 13 ]. The accuracy of intraoral scanning is influenced by numerous clinical and technical parameters. These include implant depth, ambient lighting conditions, the presence of moisture in the scanned area, the file format utilized during the design process (e.g., standard triangulation language (STL) or other specific formats), and differences in optical equipment. Assessing the quality of a digital scan necessitates a more complex method than evaluating the accuracy of a gypsum cast, which usually entails linear measurements between two predetermined points. Therefore, advanced three-dimensional (3D) reverse engineering software is frequently used to provide highly precise and comprehensive accuracy assessments [ 14 ]. Other important factors include the movement of the tongue and cheeks, the length of the edentulous ridge, the quantity and shape of keratinized gingiva, the number, position, and angulation of implants, as well as the unique features of scan bodies. These factors may contribute to cumulative distortion throughout the digital impression process when they adversely impact scan quality [ 15 – 17 ]. The accuracy of IOSs differs across different devices and also depends on the scanned area, whether partial or full arch [ 18 , 19 ]. However, comparative data evaluating multiple IOSs under different implant-supported prosthetic scenarios remain limited. The purpose of this in vitro study is to evaluate and compare the accuracy (precision and trueness) of five different IOSs in impressions for single crown (SC), three-unit fixed partial denture (FPD), and full-arch (FA) implant restorations. The null hypothesis states that there are no significant differences in the trueness and precision among the different IOSs across the evaluated scenarios. Materials And Methods Study Model Preparation. Two different maxillary sample models (fully edentulous and fully dentulous) were designed using CAD software programs (Exocad DentalCAD, v3.2 'Elefsina'; Exocad GmbH, Darmstadt, Germany). Implant sites were digitally prepared on the models to simulate various implant configurations. On the fully edentulous model, implant sites corresponding to teeth 12, 22, 14, 24, 16, and 26 were prepared to simulate a full-arch implant scenario. In the fully dentulous model, an implant site corresponding to tooth 13 was prepared to simulate a single-unit implant scenario. Additionally, teeth 24, 25, and 26 were included, with implant sites prepared at teeth 24 and 26 to simulate a three-unit implant fixed partial denture scenario. The models were printed using 3D Printer Asiga MAX UV (Asiga, NSW, Australia) with resin material (Alias model precise resin, Dokuz Kimya, İstanbul, Turkey). Implant sites corresponding to the digitally grooved regions were prepared using a parallelometer (Rotaks-Dent, Istanbul, Turkey) equipped with a micromotor and hard bur to ensure parallelism. Digital implant analogs (T6 32204; Nucleoss, Menderes/Izmir, Turkey) were then placed and fixed within the resin models under parallelometer guidance to simulate the clinical implant positions. High-precision non-reflective polyether-ether-ketone (PEEK) scanbodies (T6, 32898; Nucleoss, Menderes/Izmir, Turkey) were screwed onto the implant analogs and the models were scanned using a laboratory scanner (Autoscan DS-Mix; Shining 3D, Hangzhou, China). The acquired data were transferred to the Exocad software, where the digital gingival tissues were designed for the models, and new resin models were printed with spaces for the digital implant analogs and pink resin gingiva (Alias gingiva, Dokuz Kimya, İstanbul, Turkey). The implant analogs were then fixed to the models using screws, and the corresponding implant scanbodies were screwed to the implant analogs (Fig. 1 ). Scanning Process and Data Acquisition The two final master resin models with the scanbodies in position were scanned ten times for each model using a desktop scanner Cerec InEos X5 (Sirona Dental System, Bensheim, Germany). These scans were subsequently imported into a reverse engineering software (Geomagic Design X software 2024.3.2, 3D Systems, Rock Hill, SC, USA) and trimmed by using a preconfigured template cutting tool (in order to always reproduce the same cuts). The dentulous models were divided into two parts to represent two different scenarios. As a result, 10 preconfigured cuts corresponding to each clinical scenario - SC, FPD, and FA - were obtained. The superimposition of the 10 meshes prepared for each scenario was performed using reverse engineering software, and one reference model was generated for each scenario. The 3 face meshes were saved as STL files. The resin models were scanned using five intraoral scanners (IOSs) (Trios 5, 3Shape, Copenhagen, Denmark; The iTero Lumina, Align Technology, Santa Clara, CA, USA; Trios 4, 3Shape, Copenhagen, Denmark; CS 3600, Carestream Dental, Atlanta, Georgia USA; Helios 600 Eighteeth, Changzhou, China), each with varying characteristics shown in Table 1 . Table 1 Characteristics of the IOSs Used Intraoral Scanner Company Launch Year Working Principle Light Source Imaging Type Scan Options / Modes Output Formats Scan Tip / Field of View (FOV) iTero Lumina Align Technology 2024 Multi-Direct Capture (MDC) LED (white) Multiple still images Wide FOV, true color Proprietary/STL Large (17 × 15 mm) Trios 4 3Shape 2019 Confocal microscopy + fluorescence RGB LED spectrum Video (up to ~ 1,875 fps) True color, caries detection, Smart Tip, wired/wireless modes STL, PLY, DCM Standard (16 × 14 mm) Trios 5 3Shape 2022 Confocal microscopy + ScanAssist AI RGB LED Continuous video AI-guided scans, true color, calibration-free, wireless STL, PLY, DCM Standard (16 × 15 mm) CS 3600 Carestream Dental 2016 Optical triangulation (video) LED (amber, blue, green) Video stream True color; HD 3D; three autoclaveable tip types; implant & ortho workflows STL, PLY Normal/Side (13 × 13 mm), Posterior (13 × 7 mm) Helios 600 Eighteeth 2021/22 Structured-light triangulation + AI filtering RGB/white LED Continuous video stream True color; AI soft-tissue filter; auto-calibration STL, PLY Large (16 × 14 mm), Small (12 × 12 mm) LED, light-emitting diode; RGB, red–green–blue; FOV, field of view; AI, artificial intelligence; HD, high definition; 3D, three-dimensional; STL, standard tessellation language; PLY, polygon; DCM, digital imaging and communications in medicine. According to the power analysis, the minimum number of samples was calculated as 50 so that 10 scans were captured for each of the three scenarios (SC, FPD, FA) with each of the IOSs. All models were completely scanned using a standardized zig-zag scanning strategy, proceeding from the buccal to occlusal and palatal surfaces, with continuous overlap movements to ensure detailed data acquisition of teeth and scan bodies. All intraoral scanners were used under identical environmental conditions in order to standardize scan quality. All scanning procedures were performed by one operator (M.N.). All the models scanned with different IOSs were also imported into and cut by the reverse engineering software Geomagic Design X using a preconfigured template cutting tool to reproduce the same cuts. The dentulous models that were scanned by IOSs were also divided into two parts to represent two different scenarios. This resulted in 150 scans, divided into 50 scans for each scenario, with 10 scans from each IOS. All the 150 scans and their corresponding three RMs were imported into a 3D analysis software (Geomagic Control X software 2024.1.0, 3D Systems, Rock Hill, SC, USA) for inspection. The scans were then superimposed with an initial pre-alignment using global registration standardized orientation across all datasets, followed by a best-fit alignment algorithm to minimize spatial deviation against the reference geometry. For trueness assessment, all scans acquired using the different IOSs were superimposed onto their corresponding RMs, and a total of 150 inspection reports were generated. For Precision assessment, each scanner was evaluated by superimposing the scan with the highest overall trueness in each scenario onto the remaining scans within the same scenario and calculating the relative deviations between them, and a total of 135 inspection reports were generated. Each report included RMS deviation values and 3D color-deviation maps (scale − 1.0 to + 1.0 mm). Green regions represented areas within the defined tolerance band (± 0.1 mm), while blue (− 1.0 mm) and red (+ 1.0 mm) indicated negative and positive deviations (Figs. 2 and 3 ). The workflow of the study is summarized in the chart in Fig. 4 . All statistical analyses were performed in IBM SPSS Statistics (v28.0). Normality of the data was assessed using the Kolmogorov–Smirnov test. Trueness and precision values were analyzed to compare the five intraoral scanners across the different scenarios. One-way analysis of variance (ANOVA) with Tukey post hoc tests was applied, with Bonferroni correction used for pairwise comparisons between scanners and within each scanner across scenarios. In addition, two-way ANOVA was conducted to evaluate the main effects of scanner type and scenario, as well as their interaction. The level of statistical significance was set at p < 0.05. Effect sizes were expressed as partial eta squared (η²). Results RMS trueness values for the five scanners across the three clinical scenarios are given in Table 2 , where the lowest RMS values indicate the higher trueness. One-way ANOVA showed statistically significant differences among scanners in the SC ( p < 0.001) and FA ( p < 0.001) scenarios, as well as a limited significant difference in the FPD scenario ( p = 0.047). Table 2 Comparison of RMS Trueness values (mm) Mean ± SD Med (Min-Max) Fixed Partial Denture (FPD) Single Crown (SC) Full-arch (FA) p CS 3600 0.19 ± 0.13 0.14- (0.07–0.49) 0.1 ± 0.1 b 0.06- (0.04–0.31) 0.15 ± 0.04 0.14- (0.12–0.25) 0.166 iTero lumina 0.08 ± 0.05 1,2 0.09- (0.03–0.17) 0.02 ± 0.0001 1,b,c 0.02- (0.02–0.03) 0.05 ± 0.0001 2,c,d 0.05- (0.05–0.06) < 0.001 Helios 600 0.17 ± 0.13 1 0.17- (0.06–0.52) 0.043 ± 0.009 1,a 0.041- (0.03–0.058) 0.083 ± 0.014 a,b 0.084- (0.063–0.113) < 0.001 Trios 4 0.18 ± 0.09 1 0.17- (0.07–0.39) 0.07 ± 0.01 2,d 0.07- (0.05–0.08) 0.22 ± 0.1 1,2,a,c 0.18- (0.12–0.4) < 0 .001 Trios 5 0.23 ± 0.08 0.22- (0.12–0.4) 0.16 ± 0.05 a,c,d 0.15- (0.1–0.24) 0.26 ± 0.16 b,d 0.21- (0.13–0.66) 0.147 P 0.047 < 0.001 < 0.001 One-Way ANOVA test: Identical superscript numerals (1,2,3) in horizontal lines indicate statistically significant pairwise differences between scanning scenarios for each scanner (Tukey Bonferroni post hoc test, p < 0.016). Identical superscript letters (a, b, c, d, e) in vertical lines indicate statistically significant pairwise differences between scanners within each scenario (Tukey Bonferroni post hoc test, p < 0.005). In the FPD scenario, RMS trueness values ranged from 0.08 ± 0.05 mm (iTero Lumina) to 0.23 ± 0.08 mm (Trios 5). The remaining scanners (CS 3600, Helios 600, and Trios 4) showed intermediate RMS trueness values. Post-hoc pairwise comparisons revealed no statistically significant differences among these scanners ( p > 0.005). In the SC scenario, iTero Lumina, Helios 600, and Trios 4 demonstrated the lower RMS trueness values, followed by Trios 5 and CS 3600. Post-hoc analysis indicated that significant differences were found between Helios 600 and Trios 5, CS 3600 and iTero lumina, iTero lumina and Trios 5, and Trios 4 and Trios 5 ( p < 0.005). In the FA scenario, Trios 4 and Trios 5 exhibited significantly higher RMS trueness values compared to iTero Lumina and Helios 600, which demonstrated significantly lower RMS trueness values (< 0.10 mm). CS 3600 showed no statistically significant differences compared with other scanners. Post-hoc analysis indicated that significant differences were found between Helios 600 and Trios 4, Helios 600 and Trios 5, Trios 4 and iTero lumina, and Trios 5 and iTero lumina (p < 0.005). According to post hoc analyses, a significant difference was found between FPD and SC, and between FPD and FA for iTero lumina ( p < 0.016). A significant difference was found between FPD and SC for Helios 600 ( p < 0.016). A significant difference was found between FPD and FA, and between SC and FA for Trios 4 ( p < 0.016). As shown in Table 3 , two-way ANOVA indicated statistically significant differences in RMS trueness values according to both scanner type (F(4) = 16.488, p < 0.001, η² = 0.328) and scenario type (F(2) = 17.318, p < 0.001, η² = 0.204). The scanner × scenario interaction was not statistically significant (F(8) = 1.735, p = 0.096), indicating that differences between scanners were generally consistent across scenarios. Table 3 Two-Way ANOVA for RMS Trueness values Mean ± SD Med (Min-Max) df F p η 2 Scanner 4 16.488 < 0.001 0.328 Scenario 2 17.318 < 0.001 0.204 Interaction (scenario*scanner) 8 1.735 .0096 0.093 RMS precision comparisons are summarized in Table 4 . One-way ANOVA revealed significant differences among scanners in the FPD ( p = 0.009) and FA ( p < 0.001) scenarios, whereas no significant difference was observed in the SC scenario ( p = 0.349). Table 4 Comparison of RMS Precision values (mm) Mean ± SD Med (Min-Max) Fixed Partial Denture (FPD) Single Crown (SC) Full-arch (FA) p CS 3600 0.14 ± 0.12 a 0.09- (0.05–0.41) 0.12 ± 0.12 0.09- (0.03–0.41) 0.16 ± 0.05 0.15- (0.12–0.29) 0.719 iTero lumina 0.04 ± 0.02 1,a 0.03- (0.02–0.08) 0.14 ± 0.08 2 0.13- (0.06–0.25) 0.05 ± 0.01 1,2,a 0.04- (0.03–0.07) < 0 .001 Helios 600 0.06 ± 0.02 0.05- (0.04–0.09) 0.109 ± 0.08 0.066- (0.028–0.231) 0.11 ± 0.02 0.105- (0.08–0.147) 0.069 Trios 4 0.13 ± 0.05 0.12- (0.05–0.21) 0.08 ± 0.04 1 0.07- (0.03–0.15) 0.18 ± 0.06 1 0.18- (0.09–0.27) 0.002 Trios 5 0.09 ± 0.04 0.08- (0.05–0.17) 0.08 ± 0.04 1 0.06- (0.05–0.16) 0.22 ± 0.17 1, a 0.22- (0.09–0.63) 0.010 P 0.009 0.349 < 0.001 One-Way ANOVA test: Identical superscript numerals (1,2,3) in horizontal lines indicate statistically significant pairwise differences between scanning scenarios for each scanner (Tukey Bonferroni post hoc test, p < 0.016). Identical superscript letters (a, b, c, d, e) in vertical lines indicate statistically significant pairwise differences between scanners within each scenario (Tukey Bonferroni post hoc test, p < 0.005). In the FPD scenario, post hoc analysis revealed a statistically significant difference only between CS 3600 and iTero Lumina, with iTero Lumina demonstrating lower RMS precision values (0.04 ± 0.02 mm). No significant differences were detected among the remaining scanners. In the SC scenario, no statistically significant differences in RMS precision values were observed among scanners. RMS precision values ranged from (0.08 ± 0.04 mm) for Trios 4 and Trios 5 to (0.14 ± 0.08 mm) for iTero Lumina. In the FA scenario, post hoc analysis revealed statistically significant differences between iTero Lumina and Trios 5. iTero Lumina showed lower RMS precision value (0.05 ± 0.01 mm) compared with Trios 5. Additionally, within-scanner comparisons showed that iTero Lumina differed significantly between FPD and FA, and between SC and FA ( p < 0.016). For both Trios 4 and Trios 5, statistically significant differences were observed between the SC and FA scenarios ( p < 0.016). As shown in Table 5 , two-way ANOVA indicated statistically significant differences in RMS precision values according to both scanner type (F(4) = 3.377, p = 0.012, η² = 0.101) and scenario type (F(2) = 5.824, p = 0.004, η² = 0.088). The scanner × scenario interaction was also significant (F(8) = 3.765, p < 0.001, η² = 0.201), indicating that the repeatability of each scanner varied depending on the clinical condition. Table 5 Two-Way ANOVA for RMS Precision values Mean ± SD Med (Min-Max) df F p η 2 Scanner 4 3.377 0.012 0.101 Scenario 2 5.824 0.004 0.088 Interaction (scenario*scanner) 8 3.765 < 0.001 0.201 Discussion The purpose of this in vitro study was to evaluate and compare the trueness and precision of five intraoral scanners when used for different implant-supported clinical scenarios: single crown (SC), three-unit fixed partial denture (FPD), and full-arch (FA) rehabilitations. According to the study results, the RMS trueness values differed significantly across scanners and scanning scenarios, especially in the SC and FA scenarios ( p < 0.001). The RMS precision values varied significantly across scanners in the FPD ( p = 0.009) and FA ( p < 0.001) scenarios. As a result, the null hypothesis stating that there are no significant differences in the trueness and precision between the different IOSs across different scenarios was rejected. As IOSs record geometry using different optical principles, the optical characteristics of the object being scanned could have an impact on their accuracy [ 20 , 21 ]. The complexity of the scenario, either single implant or multiple implants, can also have an impact on the accuracy of IOS [ 22 , 23 ]. In this in vitro study, the Asiga MAX UV 3D printer and Asiga model precise resin were selected to optimize dimensional accuracy and stability from, as Asiga MAX UV achieved the lowest post-print deviations (12–240 µm) and the narrowest precision range (17–388 µm) among all extrusion and photopolymerization-based systems [ 24 , 25 ]. Additionally, Asiga model precise resin was used instead of conventional stone to enhance dimensional stability, as resin is less susceptible to water absorption and solubility [ 26 , 27 ]. The InEos X5 desktop scanner was used as a reference scanner for IOS evaluation, consistent with its usage as a reference scanner in a recent study [ 28 ]. The InEos X5 is a non-contact, high-precision optical scanner that uses blue light digital stripe projection technology, which provides an accuracy of up to 2.8 µm as verified in other studies [ 29 – 31 ]. For the IOSs, a single scanning pattern was used to ensure standardization. A zig-zag scanning strategy, previously adopted in other studies, was applied due to its advantages in improving accuracy and minimizing cumulative errors during the scanning phases [ 32 – 34 ]. Geomagic Control X was selected for all three-dimensional analysis. It is a professional metrology software program that has been recommended by the ISO 12836 standard to assess accuracy in dental impression systems [ 35 ]. Geomagic Control software accurately measured volume change in dental scans [ 36 ]. In precision assessment, the scan of every IOS within each scenario with the highest trueness was used as a RM. A similar methodology was reported by Negm et al., [ 37 ] who evaluated precision by comparing all scans to the scan exhibiting the highest trueness within the dataset. RMS values were used to quantify trueness and precision because RMS provides a global measure of cumulative three-dimensional discrepancies between the test scans and the reference dataset, allowing direct comparison of scanners when assessing overall digital accuracy and providing insight into the potential clinical reliability of digital impressions [ 38 , 39 ]. Osman et al. [ 40 ] compared three IOSs with different scanning technologies: Trios 3 (confocal), iTero Element (parallel confocal), and Medit i700 (triangulation), and reported that the confocal-based TRIOS 3 had the highest trueness and Medit i700 had the lowest accuracy in terms of trueness and precision. The iTero Element was fast at acquiring scans but had less trueness. This highlighted how different scanning technologies can impact intraoral impression accuracy. In the present study, significant differences in trueness were observed among scanners across all the scenarios, whereas significant differences in precision were observed only in the FPD and FA. Results from this investigation highlight the importance of considering both scanning technology and its potential for clinical application when selecting IOSs. In a 2025 study, Dönmez et al. [ 41 ] evaluated the accuracy of various wireless (Primescan 2 and Trios 5) and wired IOSs (Primescan and Trios 3) and reported that Trios 5 had the highest random 3D deviations. The authors suggested that wireless transmission of scanned data was a factor leading to possible errors, disrupting real-time stitching of images. Consistent with these findings, the present study demonstrated that Trios 5 in the SC showed significantly higher trueness deviations than iTero Lumina, Helios 600, and Trios 4 ( p < 0.005). Although Trios 5 showed numerically higher trueness deviations in FPD, these differences were not statistically significant when compared with the other scanners. This finding may be attributed to differences in image stitching, scan-body detection sensitivity, and the accumulation of minor alignment errors during real-time reconstruction, which can influence accuracy even in shorter-span scans depending on scanner-specific processing and acquisition stability. Schmalzl et al. [ 42 ] investigated the trueness of Trios 5 in a completely edentulous maxillary full-arch implant model with six implant analogs. The authors reported that short-span accuracy was acceptable; however, full-arch deviations exceeded clinically acceptable limits. These results are in line with the present study, where Trios 5 showed significantly greater deviations in trueness compared with iTero Lumina and Helios 600 ( p < 0.005) in the FA scenario. This highlights that the complexity of the FA scenario can have an impact on the accuracy and repeatability of the scanners. Another study by Schmidt et al. [ 43 ]investigated four IOSs (Medit i700, Primescan, Trios 4, and Trios 5), based on an analysis of coordinate differences. A maxillary implant model with 4 posterior implants. Deviations were compared to a reference dataset that was generated with X-ray computed tomography. The authors reported that Primescan and Medit i700 showed better performance, while Trios 4 and Trios 5 showed higher deviation values, and no difference was observed between Trios 4 and Trios 5, indicating limited technological advancement between the two systems. In the present study, relatively similar results were observed, as no statistically significant differences were seen between Trios 4 and Trios 5 in terms of trueness and precision in all scenarios except one; Trios 5 showed significantly inferior trueness in the SC scenario when compared with Trios 4. This suggests that there may have been no critical improvement seen in accuracy and may even show slightly reduced performance under certain conditions. A study by Pesce et al. [ 44 ] examined the trueness of two IOSs in different implant-supported prosthetic situations and reported that trueness tended to decrease as scanning complexity increased, with single-implant conditions showing the highest accuracy and full-arch rehabilitations presenting the greatest deviations. In the present study, scenario type also influenced accuracy outcomes; however, this effect was not uniform across all IOSs. While CS3600 and Trios 5 showed no significant difference in trueness values across scenarios, showing consistent results, others exhibited significant differences between specific conditions, indicating that the impact of scan span may be dependent on the scanner type. RMS precision values in the SC scenario showed no significant differences among scanners ( p = 0.349), which suggests that repeatability is generally similar for simpler clinical tasks. In contrast, significant differences in precision were observed in the FPD and FA scenarios, highlighting that complex implant scanning scenarios represent a more demanding condition for achieving consistent results. Mangano et al. [ 45 ] conducted a comparative in vitro study to test five IOSs in different implant restoration scenarios. The authors reported a statistically significant interaction between scanner type and complexity of restorations (P < 0.05), indicating that both trueness and precision declined as restoration complexity increased. In the present study, the two-way ANOVA results for trueness differed slightly. While both scanner type ( p < 0.001, η² = 0.328) and scanning scenario type ( p < 0.001, η² = 0.204) significantly influenced trueness, the interaction between the two factors was not significant ( p = 0.096, η² = 0.093). On the other hand, the precision results were more in line with Mangano et al. findings, as both scanner type ( p = 0.012, η² = 0.101) and scanning scenario ( p = 0.004, η² = 0.088) had significant effects, as well as a strong interaction effect ( p < 0.001, η² = 0.201). This indicates that scanner repeatability was more sensitive to clinical complexity, particularly in extended-span implant situations. Güzelce Sultanoğlu and Keleş Eroğlu [ 46 ] reported that Helios 600 demonstrated lower trueness and precision compared with Trios 3 and Medit i700 in a single-unit scanning scenario. In contrast, the present study found that Helios 600 showed relatively low RMS trueness values, showing significantly superior trueness than Trios 5 in the SC scenario ( p < 0.005) and significantly superior trueness than both Trios 4 and Trios 5 in the FA scenarios ( p < 0.005). However, Helios 600 showed no statistically significant differences in precision compared to other scanners. This discrepancy between studies may be attributed to variations in experimental design, scanning protocol, or potential software and firmware updates, as well as differences in the performance of structured-light triangulation under specific simulation environment. Supporting this conflict, Dönmez et al. [ 41 ] also reported reduced accuracy for Trios 5 compared with Trios 3 in certain FPD models. These findings suggest that accuracy improvements across Trios generations may not be stable and may depend on scanning span and reconstruction algorithms. Accordingly, Helios 600 performance relative to Trios 3, Trios 4, and Trios 5 appears to be dependent on the scenario rather than a fixed hierarchy among scanners. Akkal et al. [ 47 ]evaluated the accuracy of different IOSs (Primescan, Trios 4, and Carestream CS 3600) in edentulous implant patients, reporting that Primescan achieved the highest accuracy while CS 3600 showed significantly greater deviations ( p = 0.001). While those findings suggested that scanner selection inherently affects full-arch accuracy, the results of the present study indicated that CS 3600 performed comparably to the Trios 4 with no significant differences between the two scanners in trueness and precision. Furthermore, CS 3600 maintained consistent trueness (P = 0.166) and precision ( p = 0.719) across all clinical scenarios tested. This stability suggests CS 3600 provides consistent accuracy regardless of scan span. Discrepancies between these studies may be attributed to variations in methodology, scanning protocols, or software versions. In previous literature, the iTero scanners were found to have bulkier tips and a limited range of angulation. This makes it difficult to gain access to tight areas of structures, which may compromise data capture and subsequently stitching. These errors may build up as the scan progresses, causing lower precision values when scanning narrow edentulous areas, especially in the anterior region [ 48 , 49 ]. In the present investigation, iTero Lumina demonstrated significantly lower precision in the SC scenario compared with the FA scenario ( p < 0.016), which is consistent with previous literature suggesting that ergonomic limitations and tip design may compromise repeatability in confined intraoral regions despite overall high accuracy. However, iTero Lumina showed significantly improved trueness in the SC scenario compared with CS 3600 and Trios 5, as well as significantly superior trueness in the full-arch condition compared with Trios 4 and Trios 5 ( p < 0.005). In addition, iTero Lumina exhibited significantly superior precision than CS 3600 in the fixed partial denture scenario and significantly greater repeatability than Trios 5 in the FA scenario ( p < 0.005). These findings indicate that while iTero Lumina provides good performance in longer span implant applications, design-related factors may still contribute to variability under restricted scanning environments. It should be acknowledged that the in vitro design of the current study may not fully reflect intraoral conditions, such as lighting conditions, saliva, and humidity. Resin models are generally easier to scan than intraoral models, and the optical properties of oral tissues differ significantly from resin models, which may impact the in vivo performance of IOSs. Additionally, a desktop scanner was used to scan reference models; however, industrial scanners are considered the gold standard for this application. Another limitation is that this study does not evaluate restorations made from the scans using the IOSs. Clinical studies evaluating different restoratios marginal fit in different clinical scenarios (SC, FPD, and FA) may further support the findings obtained from STL file superimposition analyses. Therefore, future in vivo studies are needed to confirm the clinical significance of these findings. Conclusion Within the limitations of this comparative in vitro study, the accuracy was significantly influenced by both the scanner type and the clinical scenario. Significant differences in RMS trueness were detected among scanners in the SC, FPD, and FA conditions, whereas differences in precision were observed mainly in the FPD and FA scenarios. This finding suggests that scan repeatability becomes increasingly critical as the scanned area extends to larger spans. Trios 5 exhibited significantly higher deviations in specific comparisons, particularly in SC and FA implant situations, suggesting reduced reliability in extended-span scanning. iTero Lumina demonstrated significantly improved trueness compared with CS 3600 and Trios 5 in the SC condition and compared with Trios 4 and Trios 5 in the FA scenario and also showed significantly greater precision than CS 3600 in FPD and Trios 5 in FA scenarios. iTero Lumina presented significantly inferior precision in SC than in FA. CS 3600 maintained consistent performance across all the scenarios in precision and trueness, while Helios 600 showed significantly superior trueness than Trios systems in selected conditions. Scanner choice in a clinical setting should be based on a specific indication, with particular attention given to FA implant scenarios. Abbreviations AI artificial intelligence ANOVA analysis of variance CAD/CAM computer-aided design/computer-aided manufacturing DCM digital imaging and communications in medicine FA full arch FOV field of view FPD fixed partial denture HD high definition IOS intraoral scanner LED light-emitting diode PEEK polyetheretherketone PLY polygon file format RGB red–green–blue RM reference model RMS root mean square SC single crown STL standard tessellation language 3D three-dimensional Declarations Ethics approval and consent to participate The Institutional Review Board And The Research Ethics Commitee Of Cyprus Health And Social Sciences University reviewed and approved the research protocol (Approval No: KSTU//2025/007). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding None Author Contribution M.N. conducted the literature search and performed the material preparation, methodological procedures, and statistical analyses for data acquisition. Ç.Ö and A.I supervised the study and contributed to the critical review of the manuscript. All authors participated in data interpretation, revised the manuscript for important intellectual content, and approved the final version of the manuscript. Acknowledgements None. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Block MS. Dental Implants: The Last 100 Years. J Oral Maxillofac Surg. 2018;76:11–26. https://doi.org/10.1016/j.joms.2017.08.045 . Baldissara P, Koci B, Messias AM, Meneghello R, Ghelli F, Gatto MR, et al. Assessment of impression material accuracy in complete-arch restorations on four implants. J Prosthet Dent. 2021;126:763–71. https://doi.org/10.1016/j.prosdent.2020.10.017 . 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Influence of the scanning path on the accuracy of intraoral scanners in the implanted edentulous patient: an in vitro study. Int J Comput Dent. 2025;28:117–27. https://doi.org/10.3290/j.ijcd.b5036725 . Pattamavilai S, Ongthiemsak C. Accuracy of intraoral scanners in different complete arch scan patterns. J Prosthet Dent. 2024;131:155–62. https://doi.org/10.1016/j.prosdent.2021.12.026 . International Organization for Standardization. Dentistry — Digitizing devices for CAD/CAM systems for indirect dental restorations — Test methods for assessing accuracy. Geneva: International Organization for Standardization; 2015. O’Toole S, Bartlett D, Keeling A, McBride J, Bernabe E, Crins L, et al. Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design. J Med Internet Res. 2020;22:e17150. https://doi.org/10.2196/17150 . Negm EE, Patel M, Ryan P. Impact of the superimposition reference area on intraoral scanning accuracy in a partially dentate maxilla. J Prosthet Dent. 2024;132. https://doi.org/10.1016/j.prosdent.2024.03.018 . :189.e1-189.e11. Mourouzis P. Critical methodological factors influencing the accuracy of intraoral scanners in digital dentistry research. Comput Biol Med. 2025;187:109780. https://doi.org/10.1016/j.compbiomed.2025.109780 . Lyu M, Di P, Lin Y, Jiang X. Accuracy of impressions for multiple implants: A comparative study of digital and conventional techniques. J Prosthet Dent. 2022;128:1017–23. https://doi.org/10.1016/j.prosdent.2021.01.016 . Osman RB, Alharbi NM. Influence of scan technology on the accuracy and speed of intraoral scanning systems for the edentulous maxilla: An in vitro study. J Prosthodont. 2023;32:821–8. https://doi.org/10.1111/jopr.13633 . Dönmez MB, Çakmak G, Schimmel M, Bayadse M, Yilmaz B, Abou-Ayash S. Scan accuracy of recently introduced wireless intraoral scanners in different fixed partial denture situations. J Dent. 2025;153:105558. https://doi.org/10.1016/j.jdent.2025.105558 . Schmalzl J, Róth I, Borbély J, Vecsei B. Trueness of 3Shape Trios 5 on full arch implant impressions. J Dent. 2024;147:105156. https://doi.org/10.1016/j.jdent.2024.105156 . Schmidt A, Berschin C, Wöstmann B, Schlenz M. Update on the Accuracy of Digital Implant Impressions in 2023: A Coordinate-Based Analysis. Int J Prosthodont 2024:1–19. https://doi.org/10.11607/ijp.8843 Pesce P, Bagnasco F, Pancini N, Colombo M, Canullo L, Pera F, et al. Trueness of Intraoral Scanners in Implant-Supported Rehabilitations: An In Vitro Analysis on the Effect of Operators’ Experience and Implant Number. JCM. 2021;10:5917. https://doi.org/10.3390/jcm10245917 . Mangano FG, Hauschild U, Veronesi G, Imburgia M, Mangano C, Admakin O. Trueness and precision of 5 intraoral scanners in the impressions of single and multiple implants: a comparative in vitro study. BMC Oral Health. 2019;19:101. https://doi.org/10.1186/s12903-019-0792-7 . Güzelce Sultanoğlu E, Keleş Eroğlu B. Evaluating the accuracy of intraoral scanners used in single-unit implant prosthesis construction. Int Dent Res. 2023;13:32–7. https://doi.org/10.5577/idr.2023.vol13.s1.5 . Akkal O, Korkmaz IH, Bayindir F. Comparison of 3D accuracy of three different digital intraoral scanners in full-arch implant impressions. J Adv Prosthodont. 2023;15:179. https://doi.org/10.4047/jap.2023.15.4.179 . Revilla-León M, Aragoneses R, Arroyo Valverde EM, Gómez‐Polo M, Kois JC. Classification of Scanning Errors of Digital Scans Recorded by Using Intraoral Scanners. J Esthet Restor Dent. 2025;37:1363–71. https://doi.org/10.1111/jerd.13419 . Anh J, Park J-M, Chun Y-S, Kim M, Kim M. A comparison of the precision of three-dimensional images acquired by 2 digital intraoral scanners: effects of tooth irregularity and scanning direction. Korean J Orthod. 2016;46:3. https://doi.org/10.4041/kjod.2016.46.1.3 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9150259","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623689317,"identity":"24f8b86d-3f63-4830-a15b-c86bf1c0257c","order_by":0,"name":"Mahmoud M. M. Nosser","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYFACHhDBDOPZGEBoNuK1pBlAVLNBJYjQcpiwFt32s0c3fGyzZjBnb3/84eOe88by83sMGD6UHWawlz6AVYvZmby0mzPb0hkse86YSc54dtvM4BiPAeOMc4cZePgSsGs5kGN2m7ftMIPBjRw2Zp4Dt20M2HgMmEEiPDhcZnb+DUxL+uPPfw6cs5FvA2r5i0/LDbgtCQbSDAcOmDEAHcbMiFfLG7ObM86l8xicAfql50CyscGxtIKDPUARnjO4HJZjduNDmbWcwXFgiP04YGc4v/nwxgc/gCLsPdi1wACqIw5giIyCUTAKRsEoIAkAAP/qXExdTX4GAAAAAElFTkSuQmCC","orcid":"","institution":"Cyprus Health and Social Sciences University","correspondingAuthor":true,"prefix":"","firstName":"Mahmoud","middleName":"M. M.","lastName":"Nosser","suffix":""},{"id":623689318,"identity":"1e3ec788-6c42-438a-b9f1-8b4586bf7898","order_by":1,"name":"Artur Ismatullaev","email":"","orcid":"","institution":"Cyprus Health and Social Sciences University","correspondingAuthor":false,"prefix":"","firstName":"Artur","middleName":"","lastName":"Ismatullaev","suffix":""},{"id":623689319,"identity":"c45c08ac-9d0c-4ad2-ba91-0f8a89174b55","order_by":2,"name":"Çise Özal","email":"","orcid":"","institution":"Cyprus Health and Social Sciences University","correspondingAuthor":false,"prefix":"","firstName":"Çise","middleName":"","lastName":"Özal","suffix":""}],"badges":[],"createdAt":"2026-03-17 14:54:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9150259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9150259/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107258700,"identity":"5501ad58-aebd-4767-a4f2-241565cdac6a","added_by":"auto","created_at":"2026-04-19 12:40:07","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":163116,"visible":true,"origin":"","legend":"\u003cp\u003eMaster resin models used in the study. (A) Edentulous maxillary model with implant scanbodies in teeth number 12, 22, 14, 24, 16, and 26 to simulate a full-arch (FA) scenario. (B) Dentulous maxillary model with an implant scanbody in tooth number 13 to simulate a single unit (SC) implant scenario, and two implant scanbodies in teeth number 24 and 26 to simulate a fixed partial denture (FPD) implant scenario.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9150259/v1/9226ed51ba49c708ea6e5ecc.jpeg"},{"id":107258715,"identity":"9764be77-8391-4c9b-ad1a-f2c0906b9125","added_by":"auto","created_at":"2026-04-19 12:40:11","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":212447,"visible":true,"origin":"","legend":"\u003cp\u003eThe trueness of five IOSs across three scenarios. color-deviation maps (scale −1.0 to +1.0 mm). Green regions define a tolerance band (±0.1 mm), while blue (−1.0 mm) and red (+1.0 mm) indicate negative and positive deviations, respectively.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9150259/v1/459eb4f534500f7efb6d342c.jpeg"},{"id":107258711,"identity":"756c050c-1944-4da8-914f-4300051cfadf","added_by":"auto","created_at":"2026-04-19 12:40:10","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":198161,"visible":true,"origin":"","legend":"\u003cp\u003eThe precision of five intraoral across three scenarios. color-deviation maps (scale −1.0 to +1.0 mm). Green regions define a tolerance band (±0.1 mm), while blue (−1.0 mm) and red (+1.0 mm) indicate negative and positive deviations, respectively.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9150259/v1/316e6514b464726dce86e1c1.jpeg"},{"id":107258742,"identity":"b5ab2d50-0ef8-45d3-8bcf-264bc2cb426e","added_by":"auto","created_at":"2026-04-19 12:40:14","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":138172,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow summarizing the study steps.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9150259/v1/f11287de54570c606bd4aff7.jpeg"},{"id":109436162,"identity":"8759fd33-5c06-480f-9a0a-8baf757da1b6","added_by":"auto","created_at":"2026-05-18 06:10:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1029553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9150259/v1/55e0beaf-e640-4967-9c97-c305dcb1340a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Accuracy of five intraoral scanners in single, partial-arch, and full-arch implant cases: A comparative in vitro study","fulltext":[{"header":"Background","content":"\u003cp\u003eFor many years, oral implants have enhanced the treatment of individuals who are partially or totally edentulous. Although implant-supported dental prostheses have proven to be a reliable long-term treatment option, their success largely depends on the accuracy of the impression, as an imprecise capture may fail to record the exact implant positions and their spatial relationships with adjacent oral structures, such as teeth, alveolar crests, and soft tissues [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For decades, conventional impression techniques were considered the gold standard; however, their accuracy may be influenced by material-related factors such as elastic recovery, stiffness or flexibility, dimensional stability, polymerization shrinkage, hydrophilicity, polymerization kinetics, or tear resistance, and their interaction with the impression technique itself [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eProsthodontics has changed significantly since the introduction of digital impressions and computer-aided design and manufacturing systems. Virtual treatment planning and simulation, combining digital impressions with three-dimensional (3D) imaging, have enhanced the precision and predictability of prosthesis fabrication. The multiple clinical benefits of digital impressions include increased operator efficiency and reduced chair time and number of patient visits, leading to enhanced comfort for patients and clinicians when compared with conventional impression techniques [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIOSs capture successive images of the patient's dental arches using structured light and/or lasers, which enables 3D surface reconstruction with dedicated reconstruction software. These software programs create triangulated point clouds that provide surface reconstructions, or meshes, which are the virtual representations of the patient's dental arches [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, depending on the manufacturer, IOSs use a variety of imaging technologies and operating principles, including laser and video capture, confocal microscopy, triangulation, structured light projection, interferometry, and wave sampling. The clarity and quality of the resulting images are strongly influenced by the imaging technology employed [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. IOSs, now used routinely, enable the fabrication of implant-supported restorations through a fully digital workflow. Data recorded using a scan body are transferred to CAD software for designing the prosthetic restorations, which are directly sent for fabrication [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The accuracy of each step within this digital workflow is therefore critical to the success of the treatment. Consequently, a thorough understanding of the performance of different IOSs and the influencing factors of scanning technique and outcome is required to optimize their accuracy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccurate digital impressions are essential for fabricating restorations that fit implants correctly. The two main criteria of accuracy, as stated in ISO 5725, are precision and trueness. Trueness describes how closely the average of many test findings resembles the actual or recognized reference value. Precision refers to the degree of agreement between test results, or the consistency or repetition of the results [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The accuracy of intraoral scanning is influenced by numerous clinical and technical parameters. These include implant depth, ambient lighting conditions, the presence of moisture in the scanned area, the file format utilized during the design process (e.g., standard triangulation language (STL) or other specific formats), and differences in optical equipment. Assessing the quality of a digital scan necessitates a more complex method than evaluating the accuracy of a gypsum cast, which usually entails linear measurements between two predetermined points. Therefore, advanced three-dimensional (3D) reverse engineering software is frequently used to provide highly precise and comprehensive accuracy assessments [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Other important factors include the movement of the tongue and cheeks, the length of the edentulous ridge, the quantity and shape of keratinized gingiva, the number, position, and angulation of implants, as well as the unique features of scan bodies. These factors may contribute to cumulative distortion throughout the digital impression process when they adversely impact scan quality [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe accuracy of IOSs differs across different devices and also depends on the scanned area, whether partial or full arch [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, comparative data evaluating multiple IOSs under different implant-supported prosthetic scenarios remain limited. The purpose of this in vitro study is to evaluate and compare the accuracy (precision and trueness) of five different IOSs in impressions for single crown (SC), three-unit fixed partial denture (FPD), and full-arch (FA) implant restorations. The null hypothesis states that there are no significant differences in the trueness and precision among the different IOSs across the evaluated scenarios.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e \u003cb\u003eStudy Model Preparation.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTwo different maxillary sample models (fully edentulous and fully dentulous) were designed using CAD software programs (Exocad DentalCAD, v3.2 'Elefsina'; Exocad GmbH, Darmstadt, Germany). Implant sites were digitally prepared on the models to simulate various implant configurations. On the fully edentulous model, implant sites corresponding to teeth 12, 22, 14, 24, 16, and 26 were prepared to simulate a full-arch implant scenario. In the fully dentulous model, an implant site corresponding to tooth 13 was prepared to simulate a single-unit implant scenario. Additionally, teeth 24, 25, and 26 were included, with implant sites prepared at teeth 24 and 26 to simulate a three-unit implant fixed partial denture scenario. The models were printed using 3D Printer Asiga MAX UV (Asiga, NSW, Australia) with resin material (Alias model precise resin, Dokuz Kimya, İstanbul, Turkey). Implant sites corresponding to the digitally grooved regions were prepared using a parallelometer (Rotaks-Dent, Istanbul, Turkey) equipped with a micromotor and hard bur to ensure parallelism. Digital implant analogs (T6 32204; Nucleoss, Menderes/Izmir, Turkey) were then placed and fixed within the resin models under parallelometer guidance to simulate the clinical implant positions. High-precision non-reflective polyether-ether-ketone (PEEK) scanbodies (T6, 32898; Nucleoss, Menderes/Izmir, Turkey) were screwed onto the implant analogs and the models were scanned using a laboratory scanner (Autoscan DS-Mix; Shining 3D, Hangzhou, China). The acquired data were transferred to the Exocad software, where the digital gingival tissues were designed for the models, and new resin models were printed with spaces for the digital implant analogs and pink resin gingiva (Alias gingiva, Dokuz Kimya, İstanbul, Turkey). The implant analogs were then fixed to the models using screws, and the corresponding implant scanbodies were screwed to the implant analogs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eScanning Process and Data Acquisition\u003c/h2\u003e \u003cp\u003eThe two final master resin models with the scanbodies in position were scanned ten times for each model using a desktop scanner Cerec InEos X5 (Sirona Dental System, Bensheim, Germany). These scans were subsequently imported into a reverse engineering software (Geomagic Design X software 2024.3.2, 3D Systems, Rock Hill, SC, USA) and trimmed by using a preconfigured template cutting tool (in order to always reproduce the same cuts). The dentulous models were divided into two parts to represent two different scenarios.\u003c/p\u003e \u003cp\u003eAs a result, 10 preconfigured cuts corresponding to each clinical scenario - SC, FPD, and FA - were obtained. The superimposition of the 10 meshes prepared for each scenario was performed using reverse engineering software, and one reference model was generated for each scenario. The 3 face meshes were saved as STL files.\u003c/p\u003e \u003cp\u003eThe resin models were scanned using five intraoral scanners (IOSs) (Trios 5, 3Shape, Copenhagen, Denmark; The iTero Lumina, Align Technology, Santa Clara, CA, USA; Trios 4, 3Shape, Copenhagen, Denmark; CS 3600, Carestream Dental, Atlanta, Georgia USA; Helios 600 Eighteeth, Changzhou, China), each with varying characteristics shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the IOSs Used\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraoral Scanner\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompany\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLaunch Year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWorking Principle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLight Source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eImaging Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eScan Options / Modes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOutput Formats\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eScan Tip / Field of View (FOV)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eiTero Lumina\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlign Technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMulti-Direct Capture (MDC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLED (white)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultiple still images\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWide FOV, true color\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eProprietary/STL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLarge (17 \u0026times; 15 mm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrios 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3Shape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConfocal microscopy\u0026thinsp;+\u0026thinsp;fluorescence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRGB LED spectrum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVideo (up to ~\u0026thinsp;1,875 fps)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTrue color, caries detection, Smart Tip, wired/wireless modes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSTL, PLY, DCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStandard (16 \u0026times; 14 mm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrios 5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3Shape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConfocal microscopy\u0026thinsp;+\u0026thinsp;ScanAssist AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRGB LED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eContinuous video\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAI-guided scans, true color, calibration-free, wireless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSTL, PLY, DCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStandard (16 \u0026times; 15 mm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCS 3600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarestream Dental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOptical triangulation (video)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLED (amber, blue, green)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVideo stream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTrue color; HD 3D; three autoclaveable tip types; implant \u0026amp; ortho workflows\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSTL, PLY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNormal/Side (13 \u0026times; 13 mm), Posterior (13 \u0026times; 7 mm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHelios 600\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEighteeth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2021/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStructured-light triangulation\u0026thinsp;+\u0026thinsp;AI filtering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRGB/white LED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eContinuous video stream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTrue color; AI soft-tissue filter; auto-calibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSTL, PLY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLarge (16 \u0026times; 14 mm), Small (12 \u0026times; 12 mm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLED, light-emitting diode; RGB, red\u0026ndash;green\u0026ndash;blue; FOV, field of view; AI, artificial intelligence; HD, high definition; 3D, three-dimensional; STL, standard tessellation language; PLY, polygon; DCM, digital imaging and communications in medicine.\u003c/p\u003e \u003cp\u003eAccording to the power analysis, the minimum number of samples was calculated as 50 so that 10 scans were captured for each of the three scenarios (SC, FPD, FA) with each of the IOSs. All models were completely scanned using a standardized zig-zag scanning strategy, proceeding from the buccal to occlusal and palatal surfaces, with continuous overlap movements to ensure detailed data acquisition of teeth and scan bodies. All intraoral scanners were used under identical environmental conditions in order to standardize scan quality. All scanning procedures were performed by one operator (M.N.).\u003c/p\u003e \u003cp\u003eAll the models scanned with different IOSs were also imported into and cut by the reverse engineering software Geomagic Design X using a preconfigured template cutting tool to reproduce the same cuts. The dentulous models that were scanned by IOSs were also divided into two parts to represent two different scenarios. This resulted in 150 scans, divided into 50 scans for each scenario, with 10 scans from each IOS. All the 150 scans and their corresponding three RMs were imported into a 3D analysis software (Geomagic Control X software 2024.1.0, 3D Systems, Rock Hill, SC, USA) for inspection. The scans were then superimposed with an initial pre-alignment using global registration standardized orientation across all datasets, followed by a best-fit alignment algorithm to minimize spatial deviation against the reference geometry. For trueness assessment, all scans acquired using the different IOSs were superimposed onto their corresponding RMs, and a total of 150 inspection reports were generated. For Precision assessment, each scanner was evaluated by superimposing the scan with the highest overall trueness in each scenario onto the remaining scans within the same scenario and calculating the relative deviations between them, and a total of 135 inspection reports were generated. Each report included RMS deviation values and 3D color-deviation maps (scale\u0026thinsp;\u0026minus;\u0026thinsp;1.0 to +\u0026thinsp;1.0 mm). Green regions represented areas within the defined tolerance band (\u0026plusmn;\u0026thinsp;0.1 mm), while blue (\u0026minus;\u0026thinsp;1.0 mm) and red (+\u0026thinsp;1.0 mm) indicated negative and positive deviations (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The workflow of the study is summarized in the chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAll statistical analyses were performed in IBM SPSS Statistics (v28.0). Normality of the data was assessed using the Kolmogorov\u0026ndash;Smirnov test. Trueness and precision values were analyzed to compare the five intraoral scanners across the different scenarios. One-way analysis of variance (ANOVA) with Tukey post hoc tests was applied, with Bonferroni correction used for pairwise comparisons between scanners and within each scanner across scenarios. In addition, two-way ANOVA was conducted to evaluate the main effects of scanner type and scenario, as well as their interaction. The level of statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Effect sizes were expressed as partial eta squared (η\u0026sup2;).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eRMS trueness values for the five scanners across the three clinical scenarios are given in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, where the lowest RMS values indicate the higher trueness. One-way ANOVA showed statistically significant differences among scanners in the SC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and FA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) scenarios, as well as a limited significant difference in the FPD scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of RMS Trueness values (mm)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMed (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixed Partial Denture\u003c/p\u003e \u003cp\u003e(FPD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingle Crown\u003c/p\u003e \u003cp\u003e(SC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull-arch\u003c/p\u003e \u003cp\u003e(FA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCS 3600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003cp\u003e0.14- (0.07\u0026ndash;0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.06- (0.04\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003cp\u003e0.14- (0.12\u0026ndash;0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiTero lumina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003e1,2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.09- (0.03\u0026ndash;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003csup\u003e1,b,c\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.02- (0.02\u0026ndash;0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0001\u003csup\u003e2,c,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.05- (0.05\u0026ndash;0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelios 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.17- (0.06\u0026ndash;0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.043\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003csup\u003e1,a\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.041- (0.03\u0026ndash;0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.083\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.084- (0.063\u0026ndash;0.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrios 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.17- (0.07\u0026ndash;0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003e2,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.07- (0.05\u0026ndash;0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003e1,2,a,c\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.18- (0.12\u0026ndash;0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0 .001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrios 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003cp\u003e0.22- (0.12\u0026ndash;0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea,c,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.15- (0.1\u0026ndash;0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eb,d\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.21- (0.13\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOne-Way ANOVA test: Identical superscript numerals (1,2,3) in horizontal lines indicate statistically significant pairwise differences between scanning scenarios for each scanner (Tukey Bonferroni post hoc test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). Identical superscript letters (a, b, c, d, e) in vertical lines indicate statistically significant pairwise differences between scanners within each scenario (Tukey Bonferroni post hoc test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eIn the FPD scenario, RMS trueness values ranged from 0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 mm (iTero Lumina) to 0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 mm (Trios 5). The remaining scanners (CS 3600, Helios 600, and Trios 4) showed intermediate RMS trueness values. Post-hoc pairwise comparisons revealed no statistically significant differences among these scanners (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eIn the SC scenario, iTero Lumina, Helios 600, and Trios 4 demonstrated the lower RMS trueness values, followed by Trios 5 and CS 3600. Post-hoc analysis indicated that significant differences were found between Helios 600 and Trios 5, CS 3600 and iTero lumina, iTero lumina and Trios 5, and Trios 4 and Trios 5 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eIn the FA scenario, Trios 4 and Trios 5 exhibited significantly higher RMS trueness values compared to iTero Lumina and Helios 600, which demonstrated significantly lower RMS trueness values (\u0026lt;\u0026thinsp;0.10 mm). CS 3600 showed no statistically significant differences compared with other scanners. Post-hoc analysis indicated that significant differences were found between Helios 600 and Trios 4, Helios 600 and Trios 5, Trios 4 and iTero lumina, and Trios 5 and iTero lumina (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eAccording to post hoc analyses, a significant difference was found between FPD and SC, and between FPD and FA for iTero lumina (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). A significant difference was found between FPD and SC for Helios 600 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). A significant difference was found between FPD and FA, and between SC and FA for Trios 4 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, two-way ANOVA indicated statistically significant differences in RMS trueness values according to both scanner type (F(4)\u0026thinsp;=\u0026thinsp;16.488, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.328) and scenario type (F(2)\u0026thinsp;=\u0026thinsp;17.318, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.204). The scanner \u0026times; scenario interaction was not statistically significant (F(8)\u0026thinsp;=\u0026thinsp;1.735, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.096), indicating that differences between scanners were generally consistent across scenarios.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTwo-Way ANOVA for RMS Trueness values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMed (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScanner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction (scenario*scanner)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.0096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRMS precision comparisons are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. One-way ANOVA revealed significant differences among scanners in the FPD (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) and FA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) scenarios, whereas no significant difference was observed in the SC scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.349).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of RMS Precision values (mm)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMed (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixed Partial Denture\u003c/p\u003e \u003cp\u003e(FPD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingle Crown\u003c/p\u003e \u003cp\u003e(SC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull-arch\u003c/p\u003e \u003cp\u003e(FA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCS 3600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.09- (0.05\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003cp\u003e0.09- (0.03\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003e0.15- (0.12\u0026ndash;0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiTero lumina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003e1,a\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.03- (0.02\u0026ndash;0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.13- (0.06\u0026ndash;0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003e1,2,a\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.04- (0.03\u0026ndash;0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0 .001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelios 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003cp\u003e0.05- (0.04\u0026ndash;0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.109\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003cp\u003e0.066- (0.028\u0026ndash;0.231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003cp\u003e0.105- (0.08\u0026ndash;0.147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrios 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003e0.12- (0.05\u0026ndash;0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.07- (0.03\u0026ndash;0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.18- (0.09\u0026ndash;0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrios 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003cp\u003e0.08- (0.05\u0026ndash;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.06- (0.05\u0026ndash;0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003e1, a\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e0.22- (0.09\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOne-Way ANOVA test: Identical superscript numerals (1,2,3) in horizontal lines indicate statistically significant pairwise differences between scanning scenarios for each scanner (Tukey Bonferroni post hoc test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). Identical superscript letters (a, b, c, d, e) in vertical lines indicate statistically significant pairwise differences between scanners within each scenario (Tukey Bonferroni post hoc test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eIn the FPD scenario, post hoc analysis revealed a statistically significant difference only between CS 3600 and iTero Lumina, with iTero Lumina demonstrating lower RMS precision values (0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 mm). No significant differences were detected among the remaining scanners. In the SC scenario, no statistically significant differences in RMS precision values were observed among scanners. RMS precision values ranged from (0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 mm) for Trios 4 and Trios 5 to (0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 mm) for iTero Lumina.\u003c/p\u003e \u003cp\u003eIn the FA scenario, post hoc analysis revealed statistically significant differences between iTero Lumina and Trios 5. iTero Lumina showed lower RMS precision value (0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 mm) compared with Trios 5. Additionally, within-scanner comparisons showed that iTero Lumina differed significantly between FPD and FA, and between SC and FA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016). For both Trios 4 and Trios 5, statistically significant differences were observed between the SC and FA scenarios (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, two-way ANOVA indicated statistically significant differences in RMS precision values according to both scanner type (F(4)\u0026thinsp;=\u0026thinsp;3.377, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012, η\u0026sup2; = 0.101) and scenario type (F(2)\u0026thinsp;=\u0026thinsp;5.824, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, η\u0026sup2; = 0.088). The scanner \u0026times; scenario interaction was also significant (F(8)\u0026thinsp;=\u0026thinsp;3.765, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.201), indicating that the repeatability of each scanner varied depending on the clinical condition.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTwo-Way ANOVA for RMS Precision values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMed (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eη\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScanner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScenario\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction (scenario*scanner)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this in vitro study was to evaluate and compare the trueness and precision of five intraoral scanners when used for different implant-supported clinical scenarios: single crown (SC), three-unit fixed partial denture (FPD), and full-arch (FA) rehabilitations. According to the study results, the RMS trueness values differed significantly across scanners and scanning scenarios, especially in the SC and FA scenarios (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The RMS precision values varied significantly across scanners in the FPD (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) and FA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) scenarios. As a result, the null hypothesis stating that there are no significant differences in the trueness and precision between the different IOSs across different scenarios was rejected. As IOSs record geometry using different optical principles, the optical characteristics of the object being scanned could have an impact on their accuracy [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The complexity of the scenario, either single implant or multiple implants, can also have an impact on the accuracy of IOS [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this in vitro study, the Asiga MAX UV 3D printer and Asiga model precise resin were selected to optimize dimensional accuracy and stability from, as Asiga MAX UV achieved the lowest post-print deviations (12\u0026ndash;240 \u0026micro;m) and the narrowest precision range (17\u0026ndash;388 \u0026micro;m) among all extrusion and photopolymerization-based systems [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, Asiga model precise resin was used instead of conventional stone to enhance dimensional stability, as resin is less susceptible to water absorption and solubility [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe InEos X5 desktop scanner was used as a reference scanner for IOS evaluation, consistent with its usage as a reference scanner in a recent study [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The InEos X5 is a non-contact, high-precision optical scanner that uses blue light digital stripe projection technology, which provides an accuracy of up to 2.8 \u0026micro;m as verified in other studies [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For the IOSs, a single scanning pattern was used to ensure standardization. A zig-zag scanning strategy, previously adopted in other studies, was applied due to its advantages in improving accuracy and minimizing cumulative errors during the scanning phases [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGeomagic Control X was selected for all three-dimensional analysis. It is a professional metrology software program that has been recommended by the ISO 12836 standard to assess accuracy in dental impression systems [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Geomagic Control software accurately measured volume change in dental scans [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In precision assessment, the scan of every IOS within each scenario with the highest trueness was used as a RM. A similar methodology was reported by Negm et al., [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] who evaluated precision by comparing all scans to the scan exhibiting the highest trueness within the dataset. RMS values were used to quantify trueness and precision because RMS provides a global measure of cumulative three-dimensional discrepancies between the test scans and the reference dataset, allowing direct comparison of scanners when assessing overall digital accuracy and providing insight into the potential clinical reliability of digital impressions [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOsman et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] compared three IOSs with different scanning technologies: Trios 3 (confocal), iTero Element (parallel confocal), and Medit i700 (triangulation), and reported that the confocal-based TRIOS 3 had the highest trueness and Medit i700 had the lowest accuracy in terms of trueness and precision. The iTero Element was fast at acquiring scans but had less trueness. This highlighted how different scanning technologies can impact intraoral impression accuracy. In the present study, significant differences in trueness were observed among scanners across all the scenarios, whereas significant differences in precision were observed only in the FPD and FA. Results from this investigation highlight the importance of considering both scanning technology and its potential for clinical application when selecting IOSs.\u003c/p\u003e \u003cp\u003eIn a 2025 study, D\u0026ouml;nmez et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] evaluated the accuracy of various wireless (Primescan 2 and Trios 5) and wired IOSs (Primescan and Trios 3) and reported that Trios 5 had the highest random 3D deviations. The authors suggested that wireless transmission of scanned data was a factor leading to possible errors, disrupting real-time stitching of images. Consistent with these findings, the present study demonstrated that Trios 5 in the SC showed significantly higher trueness deviations than iTero Lumina, Helios 600, and Trios 4 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Although Trios 5 showed numerically higher trueness deviations in FPD, these differences were not statistically significant when compared with the other scanners. This finding may be attributed to differences in image stitching, scan-body detection sensitivity, and the accumulation of minor alignment errors during real-time reconstruction, which can influence accuracy even in shorter-span scans depending on scanner-specific processing and acquisition stability.\u003c/p\u003e \u003cp\u003eSchmalzl et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] investigated the trueness of Trios 5 in a completely edentulous maxillary full-arch implant model with six implant analogs. The authors reported that short-span accuracy was acceptable; however, full-arch deviations exceeded clinically acceptable limits. These results are in line with the present study, where Trios 5 showed significantly greater deviations in trueness compared with iTero Lumina and Helios 600 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005) in the FA scenario. This highlights that the complexity of the FA scenario can have an impact on the accuracy and repeatability of the scanners.\u003c/p\u003e \u003cp\u003eAnother study by Schmidt et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]investigated four IOSs (Medit i700, Primescan, Trios 4, and Trios 5), based on an analysis of coordinate differences. A maxillary implant model with 4 posterior implants. Deviations were compared to a reference dataset that was generated with X-ray computed tomography. The authors reported that Primescan and Medit i700 showed better performance, while Trios 4 and Trios 5 showed higher deviation values, and no difference was observed between Trios 4 and Trios 5, indicating limited technological advancement between the two systems. In the present study, relatively similar results were observed, as no statistically significant differences were seen between Trios 4 and Trios 5 in terms of trueness and precision in all scenarios except one; Trios 5 showed significantly inferior trueness in the SC scenario when compared with Trios 4. This suggests that there may have been no critical improvement seen in accuracy and may even show slightly reduced performance under certain conditions.\u003c/p\u003e \u003cp\u003eA study by Pesce et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] examined the trueness of two IOSs in different implant-supported prosthetic situations and reported that trueness tended to decrease as scanning complexity increased, with single-implant conditions showing the highest accuracy and full-arch rehabilitations presenting the greatest deviations. In the present study, scenario type also influenced accuracy outcomes; however, this effect was not uniform across all IOSs. While CS3600 and Trios 5 showed no significant difference in trueness values across scenarios, showing consistent results, others exhibited significant differences between specific conditions, indicating that the impact of scan span may be dependent on the scanner type. RMS precision values in the SC scenario showed no significant differences among scanners (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.349), which suggests that repeatability is generally similar for simpler clinical tasks. In contrast, significant differences in precision were observed in the FPD and FA scenarios, highlighting that complex implant scanning scenarios represent a more demanding condition for achieving consistent results.\u003c/p\u003e \u003cp\u003eMangano et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] conducted a comparative in vitro study to test five IOSs in different implant restoration scenarios. The authors reported a statistically significant interaction between scanner type and complexity of restorations (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that both trueness and precision declined as restoration complexity increased. In the present study, the two-way ANOVA results for trueness differed slightly. While both scanner type (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.328) and scanning scenario type (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.204) significantly influenced trueness, the interaction between the two factors was not significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.096, η\u0026sup2; = 0.093). On the other hand, the precision results were more in line with Mangano et al. findings, as both scanner type (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012, η\u0026sup2; = 0.101) and scanning scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, η\u0026sup2; = 0.088) had significant effects, as well as a strong interaction effect (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2; = 0.201). This indicates that scanner repeatability was more sensitive to clinical complexity, particularly in extended-span implant situations.\u003c/p\u003e \u003cp\u003eG\u0026uuml;zelce Sultanoğlu and Keleş Eroğlu [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] reported that Helios 600 demonstrated lower trueness and precision compared with Trios 3 and Medit i700 in a single-unit scanning scenario. In contrast, the present study found that Helios 600 showed relatively low RMS trueness values, showing significantly superior trueness than Trios 5 in the SC scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005) and significantly superior trueness than both Trios 4 and Trios 5 in the FA scenarios (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). However, Helios 600 showed no statistically significant differences in precision compared to other scanners. This discrepancy between studies may be attributed to variations in experimental design, scanning protocol, or potential software and firmware updates, as well as differences in the performance of structured-light triangulation under specific simulation environment. Supporting this conflict, D\u0026ouml;nmez et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] also reported reduced accuracy for Trios 5 compared with Trios 3 in certain FPD models. These findings suggest that accuracy improvements across Trios generations may not be stable and may depend on scanning span and reconstruction algorithms. Accordingly, Helios 600 performance relative to Trios 3, Trios 4, and Trios 5 appears to be dependent on the scenario rather than a fixed hierarchy among scanners.\u003c/p\u003e \u003cp\u003eAkkal et al. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]evaluated the accuracy of different IOSs (Primescan, Trios 4, and Carestream CS 3600) in edentulous implant patients, reporting that Primescan achieved the highest accuracy while CS 3600 showed significantly greater deviations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). While those findings suggested that scanner selection inherently affects full-arch accuracy, the results of the present study indicated that CS 3600 performed comparably to the Trios 4 with no significant differences between the two scanners in trueness and precision. Furthermore, CS 3600 maintained consistent trueness (P\u0026thinsp;=\u0026thinsp;0.166) and precision (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.719) across all clinical scenarios tested. This stability suggests CS 3600 provides consistent accuracy regardless of scan span. Discrepancies between these studies may be attributed to variations in methodology, scanning protocols, or software versions.\u003c/p\u003e \u003cp\u003eIn previous literature, the iTero scanners were found to have bulkier tips and a limited range of angulation. This makes it difficult to gain access to tight areas of structures, which may compromise data capture and subsequently stitching. These errors may build up as the scan progresses, causing lower precision values when scanning narrow edentulous areas, especially in the anterior region [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In the present investigation, iTero Lumina demonstrated significantly lower precision in the SC scenario compared with the FA scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.016), which is consistent with previous literature suggesting that ergonomic limitations and tip design may compromise repeatability in confined intraoral regions despite overall high accuracy. However, iTero Lumina showed significantly improved trueness in the SC scenario compared with CS 3600 and Trios 5, as well as significantly superior trueness in the full-arch condition compared with Trios 4 and Trios 5 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). In addition, iTero Lumina exhibited significantly superior precision than CS 3600 in the fixed partial denture scenario and significantly greater repeatability than Trios 5 in the FA scenario (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005). These findings indicate that while iTero Lumina provides good performance in longer span implant applications, design-related factors may still contribute to variability under restricted scanning environments.\u003c/p\u003e \u003cp\u003eIt should be acknowledged that the in vitro design of the current study may not fully reflect intraoral conditions, such as lighting conditions, saliva, and humidity. Resin models are generally easier to scan than intraoral models, and the optical properties of oral tissues differ significantly from resin models, which may impact the in vivo performance of IOSs. Additionally, a desktop scanner was used to scan reference models; however, industrial scanners are considered the gold standard for this application. Another limitation is that this study does not evaluate restorations made from the scans using the IOSs. Clinical studies evaluating different restoratios marginal fit in different clinical scenarios (SC, FPD, and FA) may further support the findings obtained from STL file superimposition analyses. Therefore, future in vivo studies are needed to confirm the clinical significance of these findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWithin the limitations of this comparative in vitro study, the accuracy was significantly influenced by both the scanner type and the clinical scenario. Significant differences in RMS trueness were detected among scanners in the SC, FPD, and FA conditions, whereas differences in precision were observed mainly in the FPD and FA scenarios. This finding suggests that scan repeatability becomes increasingly critical as the scanned area extends to larger spans. Trios 5 exhibited significantly higher deviations in specific comparisons, particularly in SC and FA implant situations, suggesting reduced reliability in extended-span scanning. iTero Lumina demonstrated significantly improved trueness compared with CS 3600 and Trios 5 in the SC condition and compared with Trios 4 and Trios 5 in the FA scenario and also showed significantly greater precision than CS 3600 in FPD and Trios 5 in FA scenarios. iTero Lumina presented significantly inferior precision in SC than in FA. CS 3600 maintained consistent performance across all the scenarios in precision and trueness, while Helios 600 showed significantly superior trueness than Trios systems in selected conditions. Scanner choice in a clinical setting should be based on a specific indication, with particular attention given to FA implant scenarios.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eartificial intelligence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAD/CAM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputer-aided design/computer-aided manufacturing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDCM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edigital imaging and communications in medicine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efull arch\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFOV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efield of view\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efixed partial denture\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehigh definition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraoral scanner\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLED\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elight-emitting diode\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePEEK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolyetheretherketone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLY\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolygon file format\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRGB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ered\u0026ndash;green\u0026ndash;blue\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereference model\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eroot mean square\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esingle crown\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard tessellation language\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e3D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethree-dimensional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe Institutional Review Board And The Research Ethics Commitee Of Cyprus Health And Social Sciences University reviewed and approved the research protocol (Approval No: KSTU//2025/007).\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eM.N. conducted the literature search and performed the material preparation, methodological procedures, and statistical analyses for data acquisition. \u0026Ccedil;.\u0026Ouml; and A.I supervised the study and contributed to the critical review of the manuscript. All authors participated in data interpretation, revised the manuscript for important intellectual content, and approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBlock MS. Dental Implants: The Last 100 Years. 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Korean J Orthod. 2016;46:3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4041/kjod.2016.46.1.3\u003c/span\u003e\u003cspan address=\"10.4041/kjod.2016.46.1.3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Intraoral scanners, Digital impressions, Accuracy, Trueness, Precision","lastPublishedDoi":"10.21203/rs.3.rs-9150259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9150259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis in vitro study aimed to evaluate and compare the trueness and precision of five intraoral scanners (IOSs) for single crown (SC), three-unit fixed partial dentures (FPD), and full-arch (FA) implant cases. These findings may provide clinicians with evidence-based guidance for selecting devices that yield reliable outcomes, particularly for complex prosthetic rehabilitations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTwo maxillary resin models (partially dentulous and fully edentulous), containing implant analogs and scan bodies, were fabricated using a computer-aided design and computer-aided manufacturing (CAD/CAM) and three-dimensional (3D) printing workflow. The models were scanned 10 times with a desktop reference scanner (InEos X5), and each IOS under each scenario. Geomagic Control X was used to assess the dataset and calculate root mean square (RMS) deviation data for trueness and precision. Statistical analysis included one-way ANOVA with Tukey post hoc and Bonferroni-adjusted pairwise comparisons, as well as two-way ANOVA to evaluate the effects of scanner type, clinical scenario, and their interaction. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and effect sizes were reported as partial eta squared (η\u0026sup2;)\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSignificant differences in RMS trueness values were found among scanners in the SC and FA scenarios (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), with limited differences in the FPD scenario. iTero Lumina and Helios 600 demonstrated lower trueness deviations, whereas Trios 5 showed greater deviations, especially in FA scanning. Precision analysis revealed significant differences in FPD and FA scenarios. Two-way ANOVA confirmed significant effects of scanner type and clinical scenario without interaction for trueness. Precision was also significantly influenced by scanner type, scanning scenario, and their interaction (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBoth the scanner type and scanning scenario were found to influence trueness and precision. As scanning became increasingly complex, deviations also increased, emphasizing the need to assess IOSs more carefully when scanning complex clinical scenarios. These findings emphasize that intraoral scanner selection should be guided by scenario complexity, particularly for FA implant cases.\u003c/p\u003e","manuscriptTitle":"Accuracy of five intraoral scanners in single, partial-arch, and full-arch implant cases: A comparative in vitro study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:38:55","doi":"10.21203/rs.3.rs-9150259/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5db009ec-58ac-4731-871e-873b164d1228","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-18T05:59:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T15:48:27+00:00","index":33,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T06:10:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:38:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9150259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9150259","identity":"rs-9150259","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}