Background: The aim of this study was to compare and evaluate three AI-assisted cephalometric analysis platforms—CephX, WeDoCeph, and WebCeph—with the traditional digital tracing method using NemoCeph software. Material and method: A total of 1500 lateral cephalometric films that met the inclusion criteria were classified as Class I, Class II, and Class III. Subsequently, 40 patients were randomly selected from each class. These selected films were uploaded to 3 AI-assisted cephalometric analysis platforms and analyzed without any manual intervention. The same films were also analyzed by an orthodontist using the NemoCeph program. Results: The results revealed significant differences in key angular measurements (ANB, FMA, IMPA, and NLA) across Class I, II, and III patients when comparing the four cephalometric analysis methods (WebCeph, WeDoCeph, CephX, and NemoCeph). Notably, ANB (p < 0.05), FMA (p < 0.001), IMPA (p < 0.001), and NLA (p < 0.001) varied significantly. Linear measurements also differed, with significant differences in U1-NA (p = 0.002) and Co-A (p = 0.002) in certain classes. Repeated measurement analysis revealed variation in SNA (p = 0.011) and FMA (p = 0.030), particularly in the Class II NemoCeph group, suggesting method-dependent variability. Conclusion: AI-assisted cephalometric analysis platforms such as WebCeph, WeDoCeph, and CephX give rise to notable variation in accuracy and reliability compared to traditional manual digital tracing, specifically in terms of angular and linear measurements. These results emphasize the importance of meticulous selection and assessment of analysis methods in orthodontic diagnostics and treatment planning.

This study aimed to evaluate the cytotoxicity of two resin materials, Tera Harz TC-85 DAC and Clear-A, along with the effects of two different post-printing protocols applied to Clear-A. Samples were produced using the Ackuretta Sol printer. The following three groups were formed based on the resins used and the post-curing methods applied: Group 1: Tera Harz TC-85 DAC resin + Tera Harz Cure; Group 2: Clear-A resin + Curie machine; and Group 3: Clear-A resin + Tera Harz Cure. All samples were sterilized in 70% ethanol for 5 min, rinsed with sterile deionized water, and incubated in Dulbecco’s Modified Eagle Medium at 37 °C for 72 h. Cytotoxicity assessment was performed by the XTT and RTCA methods using the human gingival fibroblast cell line. According to the XTT assay, undiluted resin extracts exhibited approximately 75–80% cell viability at 24 h, while further dilutions resulted in a viability exceeding 90%. No significant differences in viability were observed among the groups at any dilution at 48 and 72 h. The xCELLigence RTCA results aligned with the XTT findings, showing a transient decrease in cell viability within the first 24 h, followed by continued cell growth. This study demonstrated that extracts from all tested 3D-printed resins exhibited biocompatibility with human gingival fibroblasts. These findings support their potential for further applications in the dental and biomedical fields.

This study aimed to evaluate the effect of resin type and printing design on the dimensional accuracy of three dimensional (3D) printed orthodontic models, considering their clinical relevance for applications such as in-house aligner fabrication. Since low-cost Liquid Crystal Display (LCD) printers have been increasingly adopted in practice but data on their trueness and precision with different resins and print designs were limited, the study sought to provide evidence-based insights into their reliability. A mandibular model was designed using Blenderfordental (B4D, version 1.1.2024; Dubai, United Arab Emirates) software and fabricated with the Anycubic Photon Mono 7 Pro 14K (Anycubic, Shenzhen, China) LCD printer. The model was printed in vertical orientation using three different print designs at two layer thicknesses (50 µm and 100 µm). Four resins (Elegoo, Anycubic, eSUN, and Phrozen) were used, and each resin was printed with all three designs, yielding 126 models per resin and a total of 504 printed models. Dimensional deviations between the printed and reference models were assessed using root mean square (RMS) values and color-coded deviation maps. Significant differences in trueness were found among resins and print designs at both layer thicknesses (p < 0.001). At a layer thickness of 50 µm, eSUN and Anycubic showed superior trueness, whereas Phrozen exhibited the highest deviations. At a layer thickness of 100 µm, Anycubic, eSUN, and Phrozen generally performed better than Elegoo. Overall, printing at 100 µm yielded better performance than at 50 µm. Precision analysis revealed resin-dependent differences, with eSUN showing significantly higher precision than Elegoo at both layer thicknesses (p = 0.006 at 100 µm, p < 0.001 at 50 µm) and superior precision compared to Phrozen at 50 µm (p = 0.019). Both resin selection and print design significantly affect the dimensional accuracy of 3D-printed dental models.

Background: Artificial intelligence (AI) is increasingly integrated into orthodontic workflows, including digital model analysis modules embedded in orthodontic software. While these systems offer efficiency and automation, the accuracy and clinical reliability of AI-generated measurements and diagnostic assessments remain unclear. Therefore, to use AI systems safely and effectively in clinical orthodontics, it is important to check their results by comparing them with those of experienced orthodontists. Methods: Digital models of 48 patients were analyzed by the Orthodontist group and two AI platforms: Titan (full) and SoftSmile (Bolton only). Three orthodontists independently measured all variables using 3Shape OrthoAnalyzer, and group means were used for comparison. A subset of models was reanalyzed after two weeks to assess consistency. Data distribution was evaluated, and appropriate statistical tests were applied. Reliability was assessed using intraclass correlation coefficients (ICC) and Cohen’s kappa. Results: Almost perfect agreement was observed between the orthodontists and Titan AI in molar classification (κ = 0.955 right, κ = 0.900 left; p < 0.001), with perfect agreement reported across all groups—including between the orthodontists themselves—for Angle classification (κ = 1.00). In anterior and overall Bolton analyses, no meaningful agreement was found between the orthodontists and AI platforms. However, in a subset of patients where all three methods identified the tooth size discrepancy in the same arch (either maxilla or mandible), no significant differences were found in anterior (p = 0.226) or overall Bolton values (p = 0.795). Overjet, overbite, and space analysis values showed significant differences between the orthodontist and Titan groups (p < 0.001). ICC analysis indicated good to excellent intra- and inter-rater reliability within the orthodontist group (≥0.77), while both AI systems demonstrated excellent internal consistency, with ICC values exceeding 0.95. Conclusions: AI-based platforms showed high agreement with orthodontists only in Angle classification. While their performance in Bolton analysis was limited, significant differences were observed in other linear measurements, indicating the need for further refinement before clinical use.

Background/Objectives: This study evaluated the trueness and precision of three low-cost 3D printers compared to a professional-grade printer in fabricating orthodontic models. Methods: Two upper dental models, one crowded and one non-crowded, were designed using Blenderfordental and Autolign. The models were printed with Anycubic M3 Premium, Anycubic Photon D2, Phrozen Sonic Mini 8K, and Ackuretta Sol at 45° and 90° using Elegoo orthodontic and Ackuretta Curo resins. A total of 384 models were produced: 256 crowded (128 at 90° and 128 at 45°) and 128 non-crowded (all at 45°). Chitubox Dental Slicer and ALPHA AI slicer were used for slicing. Post-processing involved cleaning with Ackuretta Cleani and curing in Ackuretta Curie. The models were scanned with Smartoptics Vinyl Open Air. Trueness was assessed using RMS deviation analysis in CloudCompare and linear measurements. Results: One-way ANOVA showed significant differences in trueness among the printers at 45° (p < 0.001) and 90° (p < 0.001). The Ackuretta Sol (LCD) exhibited the highest trueness, with the lowest mean RMS values at 45° (0.095 ± 0.008 mm) and 90° (0.115 ± 0.010 mm). The Anycubic M3 Premium (LCD) had the lowest trueness, with RMS values at 45° (0.136 ± 0.015 mm) and 90° (0.149 ± 0.012 mm). The 45° build angle resulted in significantly better trueness than 90° (p < 0.001). In linear measurements, deviations exceeding 0.25 mm were observed only in the R1 distance, except for the Ackuretta SOL, which remained below this threshold. Conclusions: The professional-grade printer demonstrated the best performance overall. Printing at a 45° build angle resulted in improved accuracy. Despite differences among devices, all printers produced results within clinically acceptable limits for orthodontic use.