CBCT Artifact Evaluation in a Single Device: Insights and Limitations

Objective: To classify the types of artifacts in cone-beam computed tomography (CBCT) and to evaluate them according to age and gender. Methods: CBCT images of 1500 patients (766 males and 734 females) aged 5-92 (mean age: 40.89 ± 18.82 years) were retrospectively evaluated and the patients were cat...

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Bibliographic Details
Published inClinical and experimental health sciences (Online) Vol. 14; no. 2; pp. 349 - 356
Main Authors Yalçın, Eda Didem, Aslan Öztürk, Elif Meltem
Format Journal Article
LanguageEnglish
Published 01.06.2024
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Summary:Objective: To classify the types of artifacts in cone-beam computed tomography (CBCT) and to evaluate them according to age and gender. Methods: CBCT images of 1500 patients (766 males and 734 females) aged 5-92 (mean age: 40.89 ± 18.82 years) were retrospectively evaluated and the patients were categorized into 4 age groups: under 20 years old, 20-39 ages, 40-59 and over 60 years old. The types of artifacts encountered in CBCT images were classified. The relationship between the artifact types with age and gender were investigated. Chi-square test was applied to analyze the relationships between variables and distribution of parameters. Results: Of the cases, 284 (18.9%) were under the age of 20, 389 (25.9%) were between the ages of 20-39, 554 (36.9%) were between the ages of 40-59 and 273 (18.2%) were over the age of 60. Moire artifact was observed at the highest rate (100%), while motion artifact was determined at the lowest rate (19.5%), and no ring artifact was detected in the analyzed images. Metallic artifact, metallic artifact removal, streak artifact and presence of dark bands were found to be statistically significant in females (p = .002, p = .001, p = .002 and p = .002, respectively). There was no statistically significant correlation between cupping artifact, metallic artifact, metallic artifact removal, streak artifact, dark band and noise, and stitched artifact (p > .05). Conclusion: Both device and patient-based artifacts in CBCT images should be known, as well as the ways to prevent them.
ISSN:2459-1459
2459-1459
DOI:10.33808/clinexphealthsci.1291106