Iterative Metal Artifact Reduction in Head and Neck CT Facilitates Tumor Visualization of Oral and Oropharyngeal Cancer Obscured by Artifacts From Dental Hardware

Bayerl N, May M, Wuest W, Roth J, Kramer M, Hofmann C, Schmidt B, Uder M, Ellmann S (2023)

Publication Type: Journal article

Publication year: 2023

Journal

DOI: 10.1016/j.acra.2023.04.007

Abstract

Rationale and Objectives: The purpose of this study was to evaluate the diagnostic utility of iterative metal artifact reduction (iMAR) in computed tomography (CT)-imaging of oral and oropharyngeal cancers when obscured by dental hardware artifacts and to determine the most appropriate iMAR settings for this purpose. Materials and Methods: The study retrospectively enrolled 27 patients (8 female, 19 male; mean age 64 ± 12.7 years) with histologically confirmed oral or oropharyngeal cancer obscured by dental artifacts in contrast-enhanced CT. Raw CT data were reconstructed with ascending iMAR strengths (levels 1/2/3/4/5) and one reconstruction without iMAR (level 0). For subjective analysis, two blinded radiologists rated tumor visualization and artifact severity on a five-point Likert scale. For objective analysis, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) were determined. Results: iMAR reconstructions improved the subjective image quality of tumor edge and contrast, and the objective parameters of tumor SNR and CNR, reaching their optimum at iMAR levels 4 and 5 (P < .001). AI decreased with iMAR reconstructions reaching its minimum at iMAR level 5 (P < .001). Tumor detection rates increased 2.4-fold with iMAR 5, 2.1-fold with iMAR 4, and 1.9-fold with iMAR 3 compared to reconstructions without iMAR. Disadvantages such as algorithm-induced artifacts increased significantly with higher iMAR strengths (P < .05), reaching a maximum with iMAR 5. Conclusion: iMAR significantly improves CT imaging of oral and oropharyngeal cancers, as confirmed by both subjective and objective measures, with best results at highest iMAR strengths.

Authors with CRIS profile

Involved external institutions

Krankenhaus Martha-Maria Nürnberg Germany (DE) RNZ – Radiologisch-Nuklearmedizinisches Zentrum Germany (DE)

How to cite

APA:

Bayerl, N., May, M., Wuest, W., Roth, J., Kramer, M., Hofmann, C.,... Ellmann, S. (2023). Iterative Metal Artifact Reduction in Head and Neck CT Facilitates Tumor Visualization of Oral and Oropharyngeal Cancer Obscured by Artifacts From Dental Hardware. Academic Radiology. https://doi.org/10.1016/j.acra.2023.04.007

MLA:

Bayerl, Nadine, et al. "Iterative Metal Artifact Reduction in Head and Neck CT Facilitates Tumor Visualization of Oral and Oropharyngeal Cancer Obscured by Artifacts From Dental Hardware." Academic Radiology (2023).

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