Pattern of chest computerized tomography scan findings in symptomatic RT-PCR positive Covid-19 patients at the Korle Bu Teaching Hospital, Ghana Klenam Dzefi-Tettey1, Emmanuel Kobina Mesi Edzie2, Philip Narteh Gorleku2, Edmund Kwakye Brakohiapa3, Franklin Acheampong4, Abdul Raman Asemah2, Henry Kusodzi2, Patience Sumbawiera Saaka1, Ewurama Andam Idun 5, Adu Tutu Amankwa6 1. Department of Radiology. Korle Bu Teaching Hospital. P.O. Box KB 77, Korle Bu, Accra. Ghana. 2. Department of Medical Imaging. School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, P.M.B University of Cape Coast, Cape Coast.Ghana. 3. Department of Radiology, University of Ghana Medical School. 4. Korle Bu Teaching Hospital. P.O. Box KB 77, Accra, Ghana. 5. Department of Radiology, 37 Military Hospital, Accra, Ghana. 6. Department of Radiology, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah. University of Science and Technology, Kumasi, Ghana. Abstract Background: Chest Computerized Tomography (CT) features of Corona Virus Disease 2019 (COVID-19) pneumonia are nonspecific, variable and sensitive in detecting early lung disease. Hence its usefulness in triaging in resource-limited regions. Objectives: To assess the pattern of chest CT scan findings of symptomatic COVID-19 patients confirmed by a positive RT- PCR in Ghana. Methods: This study retrospectively reviewed chest CT images of 145 symptomatic RT-PCR positive COVID-19 patients examined at the Radiology Department of the Korle Bu Teaching Hospital (KBTH) from 8th April to 30th November 2020. Chi-Squared test was used to determine associations among variables. Statistical significance was specified at p≤0.05. Results: Males represent 73(50.3%). The mean age was 54.15±18.09 years. The age range was 5 months-90 years. Consolidation 88(60.7%), ground glass opacities (GGO) 78(53.8%) and crazy paving 43(29.7%) were the most predominant features. These features were most frequent in the elderly (≥65years). Posterobasal, peripheral and multilobe disease were found bilaterally. The most common comorbidities were hypertension 72(49.7%) and diabetes mellitus 42(29.2%) which had significant association with lobar involvement above 50%. Conclusion: The most predominant Chest CT scan features of COVID-19 pneumonia were GGO, consolidation with air bron- chograms, crazy paving, and bilateral multilobe lung disease in peripheral and posterior basal distribution. Keywords: Computerized Tomography Scan; COVID-19 Pneumonia; Ghana. DOI: https://dx.doi.org/10.4314/ahs.v22i2.8 Cite as: Dzefi-Tettey K, Edzie EKM, Gorleku PN, Brakohiapa EK, Acheampong F, Asemah AR, Kusodzi H, Saaka PS, Idun EA, Amank- wa AT. Pattern of chest computerized tomography scan findings in symptomatic RT-PCR Positive Covid-19 Patients at the Korle Bu Teaching Hospital, Ghana. Afri Health Sci. 2022;22(2): 63-74. https://dx.doi.org/10.4314/ahs.v22i2.8 Introduction Corresponding author. Severe Acute Respiratory Syndrome Coronavirus 2 Klenam Dzefi-Tettey, (SARS-CoV-2) is a highly infectious virus which causes Department of Radiology. the Corona Virus Disease 2019 (COVID-19) pneumo- Korle Bu Teaching Hospital nia1. Since the outbreak of the disease in Wuhan, China Tel: +233244234399 in late December 2019, there has been 64,455,107 con- ORCID ID: https://orcid.org/0000-0002-6322-5341 firmed cases and 1,474,415 reported deaths distributed Email Address: k.dzefitettey@kbth.gov.gh across 220 countries and territories around the world African © 2022 Dzefi-Tettey K et al. Licensee African Health Sciences. This is an Open Access article distributed under the terms of the Creative commons Attribution License Health Sciences (https://creativecommons.org/licenses/BY/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. African Health Sciences, Vol 22 Issue 2, June, 2022 63 and two international conveyances as at November 30th, COVID-19 pneumonia13, 14. In chronic obstructive pul- 2020, 23: 16 GMT2. monary disease, bronchial wall thickening and lung em- Clinically, the disease can be asymptomatic or mild symp- physema may be visualized15. toms like low-level fever, fatigue, dry cough, nasal con- CT features of COVID-19 pneumonia are nonspecific gestion, a runny nose, diarrhea and slight weakness with and similar to those of other lung infections, and they or without pneumonia. Severe symptoms are dyspnea show variations depending on the stage of the disease and/or hypoxemia3. onset. Therefore, it is necessary that radiologists have knowledge of the varying imaging patterns of COVID-19 Currently, Reverse-Transcriptase-Polymerase-Chain-Re- and their changes during the course of the disease. We action (RT-PCR) is the standard test used in diagnosing present the pattern of chest CT scan findings of symp- COVID-19 and preferably over chest CT scan4, 5. Though tomatic COVID-19 patients confirmed by a positive RT- findings of viral pneumonia on chest CT scan are re- PCR test in Ghana. garded as evidence of clinical diagnosis of COVID-19 infection, the World Health Organization (WHO) does Methods not recommend chest CT scan findings without confir- Study design, setting and participants mation with RT-PCR4. Recent studies have shown that This single-center retrospective study was conducted on the RT-PCR is only 30–60% sensitive although it is highly an original cohort of 145 symptomatic RT-PCR positive specific and during the early course of the disease it is patients who had chest CT scans at the Radiology De- less sensitive than chest CT scan5. Early triaging between partment of the Korle Bu Teaching Hospital (KBTH) patients with and without the disease is very important in from 8th April to 30th November 2020. KBTH, located in the hospital setting6. Though chest CT scan has low spec- Accra, was established in 1923 and is currently the leading ificity, it is useful in the early detection and management referral center in Ghana and the third largest hospital in of COVID-19 pneumonia due to its high sensitivity7. In Africa16. The final population of 145 patients included addition to being sensitive in identifying early parenchy- in this study were selected consecutively with no exclu- mal lung lesions, chest CT imaging is also very useful in sions made. detecting disease progression and other differential diag- The information obtained for this study included; Age; nosis8. Being one of the most readily available imaging Sex; clinical data such as symptoms and duration of onset modalities used in radiological practice in Ghana, its role of symptoms (in days); a positive RT-PCR test result and in imaging of COVID-19 patients cannot be overempha- chest CT scan findings. Using the Ghana age structure sized9. standards, patients were grouped into one of these cat- egories: children (≤14 years), early working age (15-24), Ghana recorded its first two cases on the 12th of March, prime working age (25-54), mature working age (55-64) 2020, approximately a month after the first case was re- and the elderly (≥65 years). The duration of onset of corded in Africa10. The numbers have since increased symptoms was categorized into four stages: stage 1 (0-4 with over 51,667 confirmed cases and 323 deaths as at days), stage 2 (5-9 days), stage 3 (10-14 days) and stage 4 November 30th, 202011. Over this period, patients under (15-21 days). investigation for COVID-19 have been referred to the Radiology Department of the Korle Bu Teaching Hospi- Image acquisition tal (KBTH) for non-enhanced chest CT imaging studies All the non-enhanced chest CT images were acquired us- in order to characterize their lung disease. ing a 32-slice Canon Aquilion Start (model TSX-037A, To date, most cases reported CT findings which include Otawara, Tochigi 324-8550, Japan) Multi Detector CT ground-glass opacities, focal consolidations, reversed (MDCT) scanner. All scans were unenhanced with pa- halo sign, which are usually bilateral and multifocal, pe- tient in supine position and images acquired during ripheral in distribution, and predominance in the mid- end-inspiration. The parameters used were: tube voltage dle, lower, and posterior lung fields12. In some studies, 120 kV; tube current-exposure time, 300mAs; matrix 512 pulmonary hemorrhage, pulmonary edema, chronic ob- x 512, slice thickness and interval 1mm and 0.625mm re- structive pulmonary disease, bronchiolitis obliterans, and spectively. Images were subsequently reconstructed at the drug-induced lung disease showed similar CT features as workstation and transferred to the Picture Archiving and 64 African Health Sciences, Vol 22 Issue 2, June, 2022 Communication System (PACS), (IBM Waston Health are multifocal rounded GGO with consolidation in a pe- Global Headquarters 75 Binney St, Cambridge, MA ripheral distribution with scattered areas of (“crazy pav- 02141, USA). ing”) and (“reversed halo”) signs but no pleural effusion or pneumothorax. Indeterminate features are multifocal Image interpretation non-rounded GGO with consolidation, lacking peripheral The images were reviewed by three radiologists with distribution, and with a diffuse, perihilar, or unilateral dis- more than 10 years’experience in interpreting chest CT tribution. A typical features are multifocal (“tree-in-bud”) images. Where there were disagreements between re- opacities, isolated lobar or segmental consolidation, dis- ports, consensus was reached by discussion. Reporting crete small nodules, lung cavities, or smooth interlobular was done following the Radiological Society of North septal thickening with pleural effusion (edema)21. Nega- America (RSNA) Expert Consensus Statement on Re- tive features are normal chest CT scan findings. porting Chest CT Scan Findings of Patients related to COVID-19 pneumonia, endorsed by the Society of Tho- Statistical analysis racic Radiology, the American College of Radiology, and Statistical analysis was performed using the Statistical RSNA17. Package for the Social Sciences (SPSS Inc. Chicago, IL, version 21.0). Continuous variables were expressed as Ground glass opacity (GGO), crazy-paving pattern, and mean and standard deviation, whereas categorical vari- pulmonary consolidation are radiological terms used and ables were expressed as counts and percentages. Tables, based on the standard glossary for thoracic imaging by graphs and charts were constructed with Microsoft Excel the Fleischner Society18. 2010 (Microsoft Corp, Redmond, WA USA). Chi-Squared Lung features were described as the presence or absence test was used to determine the associations among vari- of GGO, “crazy paving”, consolidation, “reversed halo” ables. Statistical significance for this study was specified sign, cavitation, nodule and micronodule18-20. Opacity at p≤0.05. patterns were classified as predominantly ground glass, predominantly consolidation or predominantly nodular if Ethical considerations the percentage of the particular pattern was greater than The institutional review board of the KBTH approved 50%18, 19. Based on distribution, these opacities were fur- this study with administrative approval number KBTH- ther classified as peripheral, central or mixed (peripheral ADM/00154/2020. Strict anonymity and confidentiality and central), anterior or posterior and the lobes involved were ensured. noted. Pleural changes were defined by the presence or absence of pleural thickening or pleural effusions. Bron- Results chial changes were defined by the presence or otherwise One hundred and forty-five (145) RT-PCR confirmed of air bronchogram17, 20. Pneumothorax was also looked Covid-19 pneumonia patients were included in this study out for and documented. The degree of lobar involve- comprising 73(50.3%) males and 72(49.7%) females with ment with respect to the duration of onset of symptoms age range of 5 months to 90 years. Majority of the pa- was evaluated. Based on the RSNA Expert Consensus tients 61(42.1%) fell within the age category of 25-54 Statement on reportingnon-enhanced chest CT scan fea- years, followed by 49(33.8%) within the ≥ 65 years’ cate- tures for COVID-19 pneumonia, each non-enhanced gory with just a few 3(2.1%) in the ≤ 14-year group. The chest CT scan report was classified as: Typical appear- average age of patients was 54.15±18.09 years. Cough ance, Indeterminate appearance, Atypical appearance and (51.7%), Fever (42.8%), Dyspnea (40.7%) and myalgia Negative for COVID-19 pneumonia. Typical features (28.3%) were the most common clinical symptoms. Table 1 African Health Sciences, Vol 22 Issue 2, June, 2022 65 Table 1: Demographics and clinical symptoms of Patients with COVID-19 pneumonia. Table 1: Demographics and clinical symptoms of Patients with COVID-19 pneumonia. Item Count (%) Total Patients 145 SIteexm C ount (%) TMoatlael Patients 1743(55 0.3%) FSeemx ale 7 2(49.7%) AMgaele 7 3(50.3%) FMeimniamleu m 07.24(24 9(5.7 M%)o nth) MAgaex imum 9 0 years Mienainm (uSmD ) 504.4.215 ( 5( 1M8.o0n9t)h ) AMgaex iGmruomu p 9 0 years M≤1e4a n y (eSaDrs) 35 4(.21.51 %(1)8 .09) A15g-e2 4G ryoeuaprs 4 (2.8%) ≤251-45 4y e yaersa rs 63 1( 2(.412%.1)% ) 1555--2644 yyeeaarrss 42 8( 2(.189%.3)% ) 2≥5 6-55 4y e yaersa rs 6419 ((4323..81%)) S55y-m64p t oymeasr s 2 8 (19.3%) F≥ e6v5e ry ears 6492 ((3432..88%)) SCyomugpht oms 7 5 (51.7%) AFenvoesrm ia 6152 ((1420..38%)) CSpouutguhm Production 77 5( 4(5.81%.7)% ) ADnysopsnmeiaa 1595 ((1400..73%)) MSpyuatlugmia Production 74 1( 4(2.88%.3)% ) HDeyasdpancehae 959 ( 6(4.20%.7)% ) GMaysatlrgoiian testinal symptoms 441 ( 2(.288%.3)% ) HMeeaadna c Shey mptoms onset in Days (SD) 79 .7(68. 2(4%.5) 54) Gastrointestinal symptoms 4 (2.8%) Mean Symptoms onset in Days (SD) 7.78 (4.554) The elderly group (≥65years) recorded the highest fre- features across all age groups. Air bronchograms were quencies in almost all the lung CT features except for mi- the most common 82 (56.6%) bronchial features. Lesions cronodules. Normal or negative chest CT scan findings were distributed mostly in bilateral, peripheral and poste- were most frequent 18(69.2%) in the 25–54 year group. rior basal lobes with the elderly group (≥ 65 years) being Consolidation 88 (60.7%), GGO 78 (53.8%) and crazy significantly affected followed by the (25-54 year) group. paving 43 (29.7%) were the most dominant chest CT scan The other significant associations are presented in Table 2. 66 African Health Sciences, Vol 22 Issue 2, June, 2022 Table 2: Age Distribution of Chest CT scan features of Patients with Covid-19 pneumonia Item Count (%) P-Value ≤14 years 15-24 years 25-54 years 55-64 years ≥ 65 years Total Patients 3(2.1%) 4(2.8%) 61(42.1%) 28(19.3%) 49(33.8%) 145(100.0%) - Lung Features GGO 1(1.3%) 1(1.3%) 26(33.3%) 18(23.1%) 32(41.0%) 78 (53.8%) 0.064 Consolidation 1(1.1%) 3(3.4%) 31(35.2%) 18(20.5%) 35(39.8%) 88 (60.7%) 0.175 Crazy paving 0(0.0%) 1(2.3%) 9(20.9%) 9(20.9%) 24(55.8%) 43 (29.7%) 0.001* Micronodules 0(0.0%) 0(0.0%) 5(33.39%) 6(40.0%) 4(26.7%) 15 (10.3%) 0.282 Reversed halo 0(0.0%) 0(0.0%) 3(15.8%) 4(21.1%) 12(63.2%) 19 (13.1%) 0.025* Cavitation 0(0.0%) 0(0.0%) 4(44.4%) 1(11.1%) 4(44.4%) 9 (6.2%) 0.810 Septal thickening 0(0.0%) 2(5.1%) 10(25.6%) 6(15.4%) 21(53.8%) 39 (26.9%) 0.012* No lesion(Normal 1(3.8%) 0(0.0%) 18(69.2%) 4(15.4%) 3(11.5%) 26 (17.9%) 0.011* features) Pleural features Thickening 0(0.0%) 0(0.0%) 9(32.1%) 8(28.6%) 11(39.3%) 28 (19.3%) 0.234 Effusion 0(0.0%) 1(3.7%) 10(37.0%) 9(33.3%) 7(25.9%) 27 (18.6%) 0.276 Bronchial features Air bronchogram 2(2.4%) 2(2.4%) 29(35.4%) 14(17.1%) 35(42.7%) 82 (56.6%) 0.121 Bronchiectasis 0(0.0%) 0(0.0%) 4(40.0%) 2(20.0%) 4(40.0%) 10 (6.9%) 0.889 Lesion distribution Peripheral 1(1.1%) 2(2.2%) 29(31.2%) 20(21.5%) 41(44.1%) 93 (64.1%) 0.001* Central 0(0.0%) 0(0.0%) 7(33.3%) 3(14.3%) 11(52.4%) 21 (14.5%) 0.265 Mixed 1(3.3%) 0(0.0%) 8(26.7%) 8(26.7%) 13(43.3%) 30 (20.7%) 0.170 Anterior 0(0.0%) 0(0.0%) 13(39.4%) 7(21.2%) 13(39.4%) 33 (22.8%) 0.386 Posterior 2(1.9%) 2(1.9%) 32(31.1%) 23(22.3%) 44(42.7%) 103 (71.0%) <0.001* Apical 0(0.0%) 0(0.0%) 16(35.6%) 9(20.0%) 20(44.4%) 45 (31.0%) 0.092 Basal 2(1.8%) 4(3.6%) 38(34.2%) 24(21.6%) 43(38.7%) 111 (76.6%) 0.008* Lesion predominance GGO 1(1.3%) 1(1.3%) 26(33.3%) 18(23.1%) 32(41.0%) 78 (53.8%) 0.064 Consolidation 1(1.1%) 3(3.4%) 31(35.2%) 18(20.5%) 35(39.8%) 88 (60.7%) 0.175 Pneumothorax 0(0.0%) 0(0.0%) 1(50.0%) 1(50.0%) 0(0.0%) 2 (1.4%) 0.686 Lymphadenopat hy Mediastinal 0(0.0%) 0(0.0%) 2(66.7%) 1(33.3%) 0(0.0%) 3 (2.1%) 0.562 Hilar 0(0.0%) 0(0.0%) 1(50.0%) 1(50.0%) 0(0.0%) 2 (1.4%) 0.686 Lobar Involvement Right Upper Lobe 0(0.0%) 0(0.0%) 20(37.0%) 8(14.8%) 26(48.1%) 54(37.2%) 0.011* Right Middle 1(1.1%) 1(1.1%) 35(37.6%) 17(18.3%) 39(41.9%) 93(64.1%) 0.031* Lobe Right Lower Lobe 2(1.9%) 4(3.8%) 32(30.8%) 24(23.1%) 42(40.4%) 104(71.7%) <0.001* Left Upper Lobe 0(0.0%) 0(0.0%) 16(32.7%) 10(20.4%) 23(46.9%) 49(33.8%) 0.026* Left Lower Lobe 2(2.0%) 1(1.0%) 33(33.3%) 22(22.2%) 41(41.4%) 99(68.3%) 0.003* *Statistically significant African Health Sciences, Vol 22 Issue 2, June, 2022 67 Throughout the stages of COVID-19 pneumonia infec- (58 out of 87) with percentage lobar involvement more tion, bilateral multilobe lung disease with peripheral, pos- than 50%. Hypertension was the commonest comorbid- terior and basal distribution were the commonest find- ity 72(49.7%) followed by diabetes mellitus 42(29.0 %) ings. Table 3. and these were associated with percentage lobar involve- 37.9 % (33) of the COVID-19 pneumonia patients had ment significantly above 50%. In addition, patients with more than 75% lobar involvement which occurred during multiple comorbidities had percentage lobar involvement stage 2 (5-9) days and had the highest number of patients significantly above 50%. Table 4. Table 3: Lesion distribution with the extent of lobe involvement throughout the various stages of the COVID-19 pneumonia Lesion Distribution (Count) Stages of symptom Extent of Lobe Involvement Peripheral Central Mixed Anterior Posterior Apical Basal onset No Involvement 0 0 0 0 0 0 0 Single Lobe 0 0 0 0 0 0 1 0-4 Days Unilateral Multilobe 0 0 1 0 1 1 0 Bilateral Multilobe 15 2 5 5 18 8 18 No Involvement 0 0 0 0 0 0 0 Single Lobe 2 0 2 0 4 2 6 5-9 Days Unilateral Multilobe 1 1 1 2 1 1 2 Bilateral Multilobe 55 13 15 19 57 25 61 No Involvement 0 0 0 0 0 0 0 Single Lobe 1 0 0 0 1 0 1 10-14 Unilateral Days Multilobe 0 0 0 0 0 0 0 Bilateral Multilobe 11 3 4 5 13 6 13 No Involvement 0 0 0 0 0 0 1 15-21 Single Lobe 1 0 0 1 1 0 1 Days Unilateral Multilobe 0 0 0 0 0 0 0 Bilateral Multilobe 7 2 2 1 7 2 7 Note: Stages are groups based on time from initial onset of symptoms to time of chest CT scan defined by; stage 1 (0-4 days), stage 2 (5-9 days), stage 3 (10-14 days) and stage 4 (15-21 days). 68 African Health Sciences, Vol 22 Issue 2, June, 2022 Table 4: Presence of comorbidity, stages of symptoms onset and percentage lobar involvement among COVID-19 pneumonia patients. Item Count (%) P-Value Percentage Lobar Involvement 0% 1-25 % 26-50 % 51-75 % > 75% Total Age Group ≤14 years 1(33.3%) 0(0.0%) 1(33.3%) 1(33.3%) 0(0.0%) 3 (2.1%) 15-24 years 1(25.0%) 2(50.0%) 0(0.0%) 1(25.0%) 0(0.0%) 4 (2.8%) 25-54 years 15(24.6%) 8(13.1%) 3(4.9%) 16(26.2%) 19(31.1%) 61 (42.1%) 0.003* 55-64 years 4(14.3%) 0(0.0%) 8(28.6%) 9(32.1%) 7(25.0%) 28 (19.3%) ≥ 65 years 4(8.2%) 2(4.1%) 4(8.2%) 16(32.7%) 23(46.9%) 49 (33.8%) Stages of Symptoms onset 0-4 days 5(19.2%) 1(3.8%) 6(23.1%) 6(23.1%) 8(30.8%) 24 (17.9%) 5-9 days 13(14.9%) 9(10.3%) 7(8.0%) 25(28.7%) 33(37.9%) 87 (60.0%) 0.220 10-14 days 5(23.8%) 1(4.8%) 0(0.0%) 9(42.9%) 6(28.6%) 21 (14.5%) 15-21 days 2(18.2%) 1(9.1%) 3(27.3%) 3(27.3%) 2(18.2%) 11 (7.6%) Comorbidities Hypertension 6(8.3%) 1(1.4%) 6(8.3%) 28(38.9%) 31(43.1%) 72(49.7%) <0.001* Diabetes Mellitus 3(7.1%) 1(2.4%) 4(9.5%) 14(33.3%) 20(47.6%) 42(29.0%) 0.029* Acute/Chronic 6(22.2%) 2(7.4%) 4(14.8%) 3(11.1%) 12(44.4%) 27(18.6%) 0.151 Pulmonary Diseases Cardiovascular 4(26.7%) 1(6.7%) 2(13.3%) 6(40.0%) 2(13.3%) 15(10.3%) 0.398 Disorders Stroke 1(20.0%) 0(0.0%) 0(0.0%) 3(60.0%) 1(20.0%) 5(3.4%) 0.466 Chronic Renal 2(10.0%) 0(0.0%) 1(5.0%) 9(45.0%) 8(40.0%) 20(13.8%) 0.126 Failure Retroviral 0(0.0%) 1(25.0%) 0(0.0%) 3(75.0%) 0(0.0%) 4(2.8%) 0.093 Infection Malignancy 1(20.0%) 2(40.0%) 1(20.0%) 1(20.0%) 0(0.0%) 5(3.4%) 0.121 Others 0(0.0%) 0(0.0%) 1(14.3%) 5(71.4%) 1(14.3%) 7(4.8%) 0.094 Comorbidities Per Patient 0 12(36.4%) 6(18.2%) 4(12.1%) 3(9.1%) 8(24.2%) 33(22.8%) 1 6(12.5%) 4(8.3%) 6(12.5%) 18(37.5%) 14(29.2%) 48(33.1%) 0.009* 2 5(10.9%) 2(4.3%) 4(8.7%) 14(30.4%) 21(45.7%) 46(31.7%) >2 2(11.1%) 0(0.0%) 2(11.1%) 8(44.4%) 6(33.3%) 18(12.4%) *Statistically significant Others: 4 Deep Vein Thrombosis (DVT), 2 Systemic Lupus Erythematosis (SLE), 1 Bleeding hemorrhoids. In assessing the overall chest CT scan features for the chest CT scan features for PUI for COVID-19 pneumo- COVID-19 pneumonia patients based on the RSNA Ex- nia, we found that majority of the patients 80(55.20%) pert Consensus Statement on reporting non-enhanced out of 145 had typical features for Covid-19 pneumonia Figure 1. African Health Sciences, Vol 22 Issue 2, June, 2022 69 Figure 1: Classification of the chest CT scan features of COVID-19 pneumonia (Based on the RSNA Expert Consensus Statement on reporting non-enhanced chest CT scan features for PUI COVID-19 pneumonia). Figure 2: Axial and coronal reformatted unenhanced chest CT scan of a 63-year -old man with positive RT-PCR test and 7-days history of fever, cough and dyspnea showing consolidation with air bronchograms in bilateral posterior basal distribution; typical features of COVID-19 pneumonia. 70 African Health Sciences, Vol 22 Issue 2, June, 2022 Discussion basal segments of the right and lower lobes33. They did Chest CT imaging results of RT-PCR positive patients not however report the difference of lobe involvement with COVID-19 pneumonia have been reported. The and distribution with respect to age. Our study revealed most common symptoms were cough, fever, and dyspnea that certain lobes were more frequently involved in older which took an average of 7.78 (±4.554) days to manifest. patients (Table 2). This might give clues to radiologists to These symptoms are arguably the common presentation be very observant when reviewing the images of these among patients with COVID-19 pneumonia worldwide8, populations; however, more studies are needed. Most of 22-24. our findings were bilateral, peripheral, posterior and bas- al distribution of lung lesions on imaging. Other studies The CT imaging features from this study were GGO, have reported this finding31, 34. However, in contrast to consolidation, crazy paving pattern, air bronchogram our study, Chung et al reported only 33% of peripheral signs, and intralobular septal thickening. These lung fea- distribution27. tures were predominant in the elderly population (Table 2). Our result is consistent with a study in Rome, Italy, In evaluating the presence of the predominant CT ab- conducted by Damiano et al on 158 patients compris- normalities with time (between onset of symptoms and ing 83 males and 75 females. The cohort in their study chest CT imaging) in confirmed cases of COVID-19, we showed a higher frequency of pulmonary consolida- realized that abnormalities were more manifested in the tions (60.7% against 72.0%) and GGO (53.8% against group with onset of symptoms between 5 – 9 days and 100%)25. Zhu et al also reported only 47% of GGO in least in those between 10 – 14 days. Further, we found patients with COVID-19 from a population of 32 symp- that bilateral multi-lobar disease was more common tomatic patients26. Recently, Chung et al analyzed a small among those we evaluated between 5 – 9 days after onset population of 21 patients and found a very low frequen- of symptoms. Multi-lobar involvement after being at its cy of crazy paving pattern compared with our results (4 peak in the 5 - 9 days’ onset of symptoms group, appeared patients against 43 patients)27. There were no signs of to decline in patients with onset of symptoms of 10 days reticulation, calcification and tree-in-bud appearance in and beyond (Table 3). In a study by Pan et al. to investi- any of our patients and only a few of the patients had gate lung changes of COVID-19 pneumonia with time, bronchiectasis. The absence of these imaging features it was highlighted that the degree of lung involvement have also been demonstrated by other studies28-30. In increased with time reaching a peak between 9 – 13 days one study, they found that calcification, bronchiectasis, after onset of symptoms and steadily declined thereaf- cavitation, reticulation, reversed halo-sign, tree-in-bud ter35. However, the differences in the time period within appearance, and nodules were absent iall patients except which the maximum CT abnormalities were found, may one who had pleural effusion29. The authors argued that suggest several factors among which could be a probable these lung features normally develop and it may not be faster progression of lung disease in our study population possible to arrive at a conclusion through investigation of compared to the study earlier cited, an area which may early imaging and hence was considered as a late finding. need further investigation. They further added that invasive fungal infections like as- pergillosis, vasculitis and even tumor metastasis can have Comorbidities associated with COVID-19 have been reversed halo sign29. reported for some diseases such as hypertension, renal diseases, cardiovascular diseases, chronic respiratory dis- Our study also showed that, over all, the lobes more fre- eases, chronic kidney diseases, malignancies, and diabetes quently involved are the lower lobes. Song et al. in their mellitus36. We found hypertension and diabetes mellitus study also found lower lobe involvement in 90% of to be the most common comorbidities with a percent- COVID-19 pneumonia patients which is consistent with age lobar involvement above 50%. The number of these what we found, whilst Shi et al. also had similar finding comorbidities were significantly associated with the se- with peripheral and lower lobe involvement31, 32. In addi- verity of lobar involvement (Table 4). Huang and Wang tion, a study in China among 102 patients with COVID-19 et al also found hypertension to be the common type of revealed that the most involved sites were the posterior comorbidity associated with COVID-19 followed by di- African Health Sciences, Vol 22 Issue 2, June, 2022 71 abetes mellitus1, 12. This was also corroborated by a re- References cent study in Ghana37. Understanding the relationship 1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, between comorbidities and COVID-19 will not only im- Zhang L, Fan G, Xu J, Gu X, Cheng Z. Clinical features prove clinical decisions but will enable understanding of of patients infected with 2019 novel coronavirus in Wu- how to manage complications for the population at risk. han, China. The Lancet. 2020 Feb 15;395(10223):497-506. As part of our study, we classified each patient’s chest https://doi.org/10.1016/S0140-6736(20)30183-5 CT imaging findings as Typical, Atypical, Indeterminate 2. 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