Investigating the Efficacy of the Metal Artifact Reduction Algorithm in Cone-Beam Computed Tomography Images for Endodontic and Restorative Materials

Abstract

Aim: This study aimed to assess the effectiveness of metal artifact reduction (MAR) algorithms in cone-beam computed tomography (CBCT) images, specifically for various common dental materials. Metal restorations, posts, and gutta-percha frequently cause artifacts due to their high density, impacting image quality. Methodology: Researchers used 11 extracted human mandibular teeth with different dental materials (amalgam, metal posts, porcelain-fused-to-metal (RFM) crowns, gutta-percha) and three intact teeth. CBCT scans were performed using a Galileos scanner on a mandible in water to simulate soft tissue. Images were acquired both with and without MAR activation across various tooth positions. Contrast-to-noise ratio (CNR) was calculated at multiple distances and angles. Statistical analysis was conducted using the Wilcoxon test. Results: The study found that activating the MAR algorithm had no significant impact on reducing metal artifacts across any of the evaluated dental materials, regardless of tooth type, position, or angle. Conclusion: The MAR algorithm, as tested, does not significantly reduce metal artifacts caused by dental materials like amalgam, metal posts, RFM crowns, or gutta-percha in CBCT images. In this context, clinical application of these algorithm does not provide justifiable added benefits.