Original Article

Split Viewer

Blood Res 2022; 57(3):

Published online September 30, 2022

https://doi.org/10.5045/br.2022.2022085

© The Korean Society of Hematology

Chest multidetector computed tomography imaging of COVID-19 pneumonia patients with hematologic malignancies

Adel El-Badrawy1, Nada Elbadrawy2

1Department of Radiology, 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.
Department of Radiology, Faculty of Medicine, Mansoura University, 1 Omar Ben Abdel-Aziz from Gehan Street, Mansoura 35516, Egypt
E-mail: adelelbadrawy@hotmail.com

Received: April 19, 2022; Revised: July 10, 2022; Accepted: July 18, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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

Article

Original Article

Blood Res 2022; 57(3): 216-222

Published online September 30, 2022 https://doi.org/10.5045/br.2022.2022085

Copyright © The Korean Society of Hematology.

Chest multidetector computed tomography imaging of COVID-19 pneumonia patients with hematologic malignancies

Adel El-Badrawy1, Nada Elbadrawy2

1Department of Radiology, 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.
Department of Radiology, Faculty of Medicine, Mansoura University, 1 Omar Ben Abdel-Aziz from Gehan Street, Mansoura 35516, Egypt
E-mail: adelelbadrawy@hotmail.com

Received: April 19, 2022; Revised: July 10, 2022; Accepted: July 18, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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

Fig 1.

Figure 1.63-year-old male patient with coronavirus disease (COVID-19) and history of chronic lymphocytic leukemia. Multidetector CT scan of the chest (A) showed bilateral pleural effusions (asterisks) and malignant lymphadenopathy in the superior mediastinum (arrows); (B) bilateral ground-glass opacities (asterisks); (C) bronchial dilatation (arrow), bilateral ground-glass opa-cities (asterisks), and right pneum-onic consolidation (right triangles); and (D) bilateral ground-glass opa-cities (asterisks), bronchial dilatation (arrows), and interlobular septal thickening.
Blood Research 2022; 57: 216-222https://doi.org/10.5045/br.2022.2022085

Fig 2.

Figure 2.36-year-old woman with coronavirus disease (COVID-19) and history of non-Hodgkin lym-phoma. Multidetector CT scan of the chest (A, B) showed multiple bilateral axillary and superior med-iastinal looking malignant lymphad-enopathy (arrows) and (C, D) ground-glass opacities (asterisks), interlobular septal thick-ening, and bronchial dilatation (arrow). Follow- up MDCT scan of the chest after 11 days (E, F) showed improvement in ground-glass opacities (asterisks).
Blood Research 2022; 57: 216-222https://doi.org/10.5045/br.2022.2022085

Fig 3.

Figure 3.55-year-old man with coronavirus disease (COVID-19) and history of acute myeloid leukemia. Multidetector CT scan of the chest (A, B) showed ground- glass opacities (arrows) and nodules (triangles). Follow-up MDCT scan of the chest after 10 days (C, D) showed increased ground-glass opacities (arrows) with newly developed mild left pleural effusion (asterisk).
Blood Research 2022; 57: 216-222https://doi.org/10.5045/br.2022.2022085

Fig 4.

Figure 4.45-year-old woman with coronavirus disease (COVID-19) and history of multiple myeloma. Multidetector CT scan of the chest (A) showed dilated cardiac chamber, pericardial (arrow), and pleural effusions (asterisks) and (B, C) bronchial dilatation (triangle) and ground-glass opacities (arrows). Follow-up MDCT scan of the chest after 8 days (D) showed progression of pericardial effusion (arrow) and pleural effusion (asterisks) and (E, F) Ground-glass opacities (arrows) and a newly developed consolidation (oval).
Blood Research 2022; 57: 216-222https://doi.org/10.5045/br.2022.2022085

Table 1 . Baseline demographic findings of 100 patients with hematologic malignancies..

Hematologic malignanciesAge (yr), range (mean)Sex
MaleFemaleTotal
Non-Hodgkin lymphoma25–58 (40.83)261440
Acute myeloid leukemia43–67 (48.44)16925
Chronic lymphocytic leukemia44–75 (50.2)9615
Multiple myeloma41–55 (47.6)4610
Hodgkin lymphoma27–45 (33.25)538
Myelodysplastic syndrome61–67 (64)2-2
Total25–75 (44.67)6238100

Table 2 . Clinical presentation of COVID-19 pneumonia in 100 patients with hematologic malignancies and 100 patients from the control group..

Study group (N=100)Control group (N=100)P
Fever91/10089/1000.637
Cough83/10045/100<0.001
Dyspnea74/10029/100<0.001
Fatigue48/10039/1000.200
Myalgia67/10062/1000.460
Sore throat23/10034/1000.085
Chest pain16/10014/1000.692
Sputum production17/1007/1000.030
Headache28/10026/1000.750
Anosmia56/10051/1000.478
Nausea18/10014/1000.440
Diarrhea12/1006/1000.138
Abdominal pain14/1009/1000.269
Anorexia15/10012/1000.535
Blenching6/1002/1000.149

Table 3 . Chest MDCT findings of COVID-19 pneumonia in 100 patients with hematologic malignancies and 100 patients from the control group..

Study group (N=100)Control group (N=100)P
Ground-glass opacity100/10095/1000.0594
Consolidation80/10027/1000.0001
Nodule18/10011/1000.2278
N of lobes450/500395/5000.0001
Interlobar septal thickening32/10024/1000.2702
Pleural effusion50/1007/1000.0001
Lymphadenopathy16/1005/1000.0192
Airway thickening/dilatation70/10056/1000.0566
Central and/or peripheral
Central10/1005/1000.2828
Peripheral30/10058/1000.0001
Central and peripheral60/10037/1000.0018
Total lung severity
Minimal3/10030/1000.0001
Mild7/10030/1000.0001
Moderate45/10025/1000.0047
Severe45/10015/1000.0001

Table 4 . Incidence of lobar involvement of COVID-19 pneumonia in 100 patients with hematologic malignancies and 100 patients from the control group..

N of patientsTotal N of lobes involved
Study groupControl groupPa)Study groupControl groupPa)
1 lobe0 (0%)2 (2%)0.4980 (0.0%)2 (0.5%)0.4364
2 lobes1 (1%)3 (3%)0.6212 (0.4%)6 (1.5%)0.2096
3 lobes7 (7%)22 (22%)0.00321 (4.7%)66 (16.7%)<0.001
4 lobes33 (33%)44 (44%)0.110132 (29.3%)176 (44.6%)<0.001
5 lobes59 (59%)29 (29%)<0.001295 (65.6%)145 (36.7%)<0.001

a)P-values were calculated using a chi-square test except the values in the first two rows, which were calculated using Fisher’s exact test..


Blood Res
Volume 59 2024

Stats or Metrics

Share this article on

  • line

Related articles in BR

Blood Research

pISSN 2287-979X
eISSN 2288-0011
qr-code Download