Chest multidetector computed tomography imaging of COVID-19 pneumonia patients with hematologic malignancies
Adel El-Badrawy1, Nada Elbadrawy2
1Radiology Department, Faculty of Medicine, Mansoura University, Mansoura, 2Faculty of Oral and Dental Medicine, Delta University for Science and Technology, Gamasa, Dakahlya, Egypt
Correspondence to: Adel El-Badrawy, M.D.
Professor of Radiology, Radiology Department, Mansoura Faculty of Medicine, Mansoura University, 1 Omar Ben Abdel-Aziz from Gehan Street, Mansoura, Egypt
E-mail: adelelbadrawy@hotmail.com
Published online: August 3, 2022.
© The Korean Journal of Hematology. All rights reserved.

Abstract
Background: Data on the association between coronavirus disease 2019 (COVID-19) and the epidemiology and outcomes of hematological malignancies are limited. Hence, the present study aimed to assess the imaging findings using chest multidetector computed tomography (MDCT) in patients with hematologic malignancies who developed COVID-19 pneumonia.
Methods: This retrospective study included two groups, the first group consisted of COVID-19 infected patients with hematologic malignancies (100 patients), while the second group consisted of COVID-19 infected patients without hematologic malignancies or other comorbidities (100 patients). The hematological malignancies included in this study were non-Hodgkin’s lymphoma (40 patients), acute myeloid leukemia (25 patients), chronic lymphocytic leukemia (15 patients), multiple myeloma (10 patients), Hodgkin’s lymphoma (8 patients), and myelodysplastic syndrome (2 patients). Chest multidetector CT imaging was performed in all patients to assess for ground-glass opacity, consolidation, pleural effusion, and airway abnormalities.
Results: More than one CT finding was reported in each patient. No significant difference was observed in the ground-glass opacities (P=0.0594), nodule formation (P=0.2278), or airway thickening/dilatation (P=0.0566) between the two groups; meanwhile, a significant difference was observed in the degree of consolidation, the number of lobes affected, and pleural effusion (P=0.0001) as well as in the total lung severity (P=0.0001); minimal, mild, and severe affection rates; and (P=0.0047) moderate affection rates.
Conclusion: Early and reliable diagnosis of lung disease in COVID-19-infected patients may be achieved through multidetector CT imaging. Patients with hematological malignancies are more likely to have severe COVID-19 pneumonia, and radiologists should recognize the CT characteristics of this infection.
Keywords: Multi-detector computed tomography, COVID-19, Pneumonia, Hematologic malignancies


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