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Effects of Patient-Based Imaging Artifacts On CT Diagnosis of COVID-19 and Its Severity
Burcu Akman1, Ahmet Turan Kaya1
1Burcu Akman, MD, and Ahmet Turan Kaya, MD, are assistant professors for the Department of Radiology at Amasya University in Turkey.
Purpose:
To investigate the effects of patient-induced artifacts on the diagnostic performance of the COVID-19 Reporting and Data System (CO-RADS) and the computed tomography chest severity score (CT-SS).
Methods:
A single-center retrospective analysis of patients aged 18 years and older who were admitted to the authors' hospital with laboratory-confirmed COVID-19 and underwent chest CT between July and November 2021 was conducted. Patients' chest CT scans were examined by 3 radiologists for CT-SS and CO-RADS classifications. Patient-based artifacts, including metal artifacts, incomplete projection artifacts, motion artifacts, and insufficient inspiration, were identified by 3 readers who were unaware of each other. For statistical analysis, interreader agreement was investigated using Fleiss kappa () agreement analysis.
Results:
The study population included 549 patients with a median age of 66 years (IQR, 55-75 years), 321 (58.5%) of whom were men. According to the overall CO-RADS classification, the highest interreader agreement was in patients without CT artifacts ( = 0.924), while the lowest interreader agreement was in patients with motion artifacts ( = 0.613). For the CO-RADS 1 and 2 patient groups, insufficient inspiration decreased the interreader agreement most ( = 0.712 and = 0.250, respectively). For the CO-RADS 3, 4, and 5 patient groups, motion artifacts reduced the interreader agreement most ( = 0.464, = 0.453, and = 0.705, respectively). For total CT-SS, the highest kappa value was in patients without artifacts ( = 0.574), while the lowest kappa value was in patients with motion artifacts ( = 0.374).
Discussion:
The CT technologist can avoid patient-induced artifacts by placing patients carefully on the CT table, giving patients necessary instructions before CT acquisition, and selecting optimal scanning parameters. The authors are not aware of another study in the literature investigating the effects of patient-based artifacts on interreader agreement of CO-RADS classification and CT-SS for COVID-19.
Conclusion:
CT artifacts degrade image quality and might lead to interreader disagreement of CO-RADS classification and CT-SS for patients with COVID-19.
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