Introduction: Chest X-ray (CXR) is one of the routinely used radiological examinations in COVID-19. However, the lesion detectability level of CXR is low. To date, to the best of our knowledge, the visualization quality of X-ray in COVID-19 has not been specifically evaluated in different lesions. Our study aims to determine the visualization quality of CXR in COVID-19 patients according to elementary lesions.
Material and Method: 52 COVID-positive patients (26 Males and 26 Females); 69,6346±15,14250 (32-89) years [mean±SD age (range)] were included in the study. 98 different elementary lesions of lung detected on CT were evaluated in six different groups (consolidation, indeterminate ground-glass opacity (IGGO), dense GGO (DGGO), reversed halo, parenchymal band and curvilinear band). Lesions were compared with CXR taken on the same day. The detectability rates of the lesions on CXR were evaluated.
Results: The mean sizes of CXR negative and CXR positive lesions for every group (consolidations, IGGO, DGGO, reversed halo sign, parenchymal band, curvilinear band) were respectively 1.36 cm -5.75 cm, 3.44 cm -5.50 cm, 2.25 cm -5.06 cm, 2.5cm -4.09 cm, N/A -3.14 cm and 1 cm -4.5 cm. According to Mann-Whitney U analysis, p values were found as (respectively in consolidations, IGGO, DGGO, reversed halo sign, and curvilinear band) 0.0001p, 0.145, 0.0001 p, 0.143 and 0.286. Given consolidation and DGGO groups, there was a statistically significant difference between non-visualized and visualized groups. According to ROC analysis, cut-off values were respectively 3 cm and 3.5 cm for consolidation and DGGO.
Conclusion: Our study showed that consolidations smaller than 3 cm and DGGO smaller than 3.5 cm are difficult to visualize with CXR. Although there is no definite cut-off value in other elementary lesions, the visualization ratio of parenchymal bands and curvilinear bants on chest X-rays is quite high. IGGOs may not be detected even at higher dimensions. Reversed halos less than 3 cm can rarely be detected on CXR.
Primary Language | English |
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Subjects | Health Care Administration |
Journal Section | Original Article |
Authors | |
Publication Date | July 20, 2022 |
Published in Issue | Year 2022 |
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