Artifacts of orthodontic materials on cone beam computed tomography images.

BACKGROUND

This study aimed to compare the artifact expression of various materials used in orthodontic treatment on cone beam computed tomography (CBCT) images. It was hypothesized that three-dimensional (3D) printing resins and polyetheretherketone (PEEK), owing to their relatively low density and low effective atomic number, would generate fewer artifacts than conventional materials.

METHODS

Ten orthodontic materials and an empty phantom control (Temporary CB, Permanent Crown, Biomed Clear, Glass Ionomer Cement, Composite, Resin-Modified Glass Ionomer Cement, PEEK, Titanium Grade 2, Stainless Steel, and Monolithic Zirconia) were placed in a phantom model and scanned using the Planmeca ProMax 3D system. Each material was scanned three times, and grayscale standard deviation was measured in eight peripheral regions of interest (ROIs) per scan. Data were analyzed using the Kruskal-Wallis test with Dunn-Bonferroni pairwise comparisons (α = 0.05), supplemented by scan-level and mixed-effects sensitivity analyses to account for the non-independence of ROIs within the same scan.

RESULTS

A statistically significant difference in artifact expression was observed among the materials (P < 0.001). The lowest artifact expression was found in Biomed Clear (BC) and PEEK, whereas the highest artifact expression was observed in stainless steel (SS). Both PEEK and BC produced significantly fewer artifacts than many conventional materials. The scan-level and mixed-effects sensitivity analyses confirmed the robustness of the primary findings.

CONCLUSIONS

BC and PEEK materials produced significantly lower artifact expression than conventional metallic and ceramic materials in CBCT imaging, potentially contributing to improved image quality. However, the present study evaluated grayscale standard deviation only; further studies assessing diagnostic performance (e.g., sensitivity/specificity) are required to determine whether the observed reduction in artifact expression translates into improved clinical diagnostic accuracy.