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CT Dental Artifact: Comparison of an Iterative Metal Artifact Reduction Technique with Weighted Filtered Back-Projection

BACKGROUND: Dental hardware produces streak artifacts on computed tomography (CT) images reconstructed with the standard weighted filtered back projection (wFBP) method. PURPOSE: To perform a preliminary evaluation of an iterative metal artifact reduction (IMAR) technique to assess its ability to im...

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Detalles Bibliográficos
Autores principales: Diehn, Felix E, Michalak, Gregory J, DeLone, David R, Kotsenas, Amy L, Lindell, E Paul, Campeau, Norbert G, Halaweish, Ahmed F, McCollough, Cynthia H, Fletcher, Joel G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5714095/
https://www.ncbi.nlm.nih.gov/pubmed/29225924
http://dx.doi.org/10.1177/2058460117743279
Descripción
Sumario:BACKGROUND: Dental hardware produces streak artifacts on computed tomography (CT) images reconstructed with the standard weighted filtered back projection (wFBP) method. PURPOSE: To perform a preliminary evaluation of an iterative metal artifact reduction (IMAR) technique to assess its ability to improve anatomic visualization over wFBP in patients with dental amalgam or other hardware. MATERIAL AND METHODS: CT images from patients with dental hardware were reconstructed using wFBP and IMAR software and soft-tissue or bone window/level settings. The anatomy most affected by metal artifacts was identified. Two neuroradiologists determined subjective and objective imaging features, including overall metal artifact score (1 = severe artifacts, 5 = no artifacts), soft-tissue visualization score of the most-compromised structure, and artifact length along the skin surface. CT numbers were used to quantify artifact severity. RESULTS: Twenty-four patients were included. IMAR improved overall metal artifact score in 18/24 cases (median =2 ± 0.9 vs. 1 ± 0.6, P < 0.001). Mean CT number in the most-affected anatomical structure significantly improved with IMAR (94.6 vs. 219 HU, P = 0.002) and length of affected skin surface decreased (40.4 mm vs. 118.7 mm, P < 0.001). However, osseous/dental artifactual defects were found in 22/24 cases with IMAR vs. 11/24 with wFBP. CONCLUSION: IMAR software reduced metal artifact both subjectively and objectively and improved visualization of adjacent soft tissues. However, it produced a higher rate of artifactual defects in the teeth and bones than wFBP. Our findings support the use of IMAR as a valuable complement to, but not a replacement for, standard wFBP image reconstruction.