|Year : 2022 | Volume
| Issue : 1 | Page : 9-16
Significance of chest computed tomography scan findings at time of diagnosis in patients with COVID-19 pneumonia
Rajaa Suhail Najim1, Ahmed Diaa Abdulwahab2, Dina Nasih Tawfeeq3
1 Department of Basic Science, College of Dentistry, Tikrit University, Tikrit, Saladin, Iraq
2 Department of Radiology, Rizgary Teaching Hospital, Erbil, Iraq
3 Department of Radiology, College of Medicine, Tikrit University, Tikrit, Saladin, Iraq
|Date of Submission||28-Aug-2021|
|Date of Decision||29-Aug-2021|
|Date of Acceptance||21-Sep-2021|
|Date of Web Publication||24-Jan-2022|
Dr. Dina Nasih Tawfeeq
Department of Radiology, College of Medicine, Tikrit university, Tikrit-34001, Salahadin
Source of Support: None, Conflict of Interest: None
Background and objectives: Many published reports demonstrated the cardinal hallmark of COVID-19 infection, such as bilateral ground glass opacities (GGO) with or without consolidation in posterior and peripheral lungs fields. Various CT algorithms including CT scoring system were used to assess quantitively and qualitatively the severity of COVID-19 pneumonia. The aim of this study was to summarize the significance of certain radiological features in evaluating Covid-19 pneumonia severity in Iraqi patients. Materials and methods: This was a cross sectional study conducted in Erbil tertiary hospitals in Iraq from June 2020, until August 2020. Review of chest CT scan for 132 patients was done and the main chest CT manifestations of patients with COVID-19 infection was reported. Then, CT scoring system was implicated in a quantitative comparison with radiological findings observed in chest CT examinations of patients having different disease severity at time of diagnosis. Results: The mean age of study sample was 51.08 ±14.2 years. The typical CT findings were consistent with mainly GGOs (78.8%) followed by consolidation. Atypical CT patterns according to previous reports were also observed including tree in bud, crazy paving, bronchiectasis, round organizing pneumonia, pulmonary nodules, mediastinal lymphadenopathy, cavitation and pleural thickening. Lung involvement was significantly more in the lower lobes than upper lobes. CT severity score was significantly higher in the lower lobes as well. Chest CT severity score (CT-SS) was significantly higher in cases with most common pathological lung changes (p < 0.001) except for tree in bud, crazy paving and cavitation. Conclusion: CT-SS is an essential examination tool in the diagnosis, disease severity evaluation and lobar extension of COVID-19 infection. High CT-SS are significantly associated with certain chest CT findings like GGOs, consolidation, bronchiectasis and interlobular septa thickening which reflects the seriousness of such CT findings in COVID-19 at time of diagnosis.
Keywords: Computed tomography, computed tomography severity score, COVID-19 pneumonia, ground-glass opacity
|How to cite this article:|
Najim RS, Abdulwahab AD, Tawfeeq DN. Significance of chest computed tomography scan findings at time of diagnosis in patients with COVID-19 pneumonia. Indian J Med Spec 2022;13:9-16
|How to cite this URL:|
Najim RS, Abdulwahab AD, Tawfeeq DN. Significance of chest computed tomography scan findings at time of diagnosis in patients with COVID-19 pneumonia. Indian J Med Spec [serial online] 2022 [cited 2022 Dec 9];13:9-16. Available from: http://www.ijms.in/text.asp?2022/13/1/9/336424
| Introduction|| |
Computed tomography (CT) scan seems to have an essential role in diagnosis of COVID-19 and disease staging, especially it is now widely available and can be done rapidly.
The radiology literature has reported the characteristic CT findings of COVID-19 pneumonia, which most commonly include bilateral, multifocal, peripheral, often-rounded ground-glass opacities that are predominantly located in the lower lobes and posterior segments which may be accompanied by consolidation.,,,, In a global pandemic, recognition of these CT findings with deep learning algorithms may prove insightful to the seriousness of certain imaging features in assessing the severity of disease. Chest CT severity score (CT-SS) is a CT-based algorithm of pulmonary involvement in COVID-19 pneumonia with its importance in assessing disease severity and might be beneficial to speed up diagnostic workflow in symptomatic cases. Initially, Pan et al. proposed CT scoring criteria that took into account lobe involvement but gave no consideration to changes in CT features. Another study conducted by Huang concluded that timely diagnosis is one of the key factors to provide a better prognosis for patients with COVID-19 by considering both lobe involvement and changes in CT findings. Therefore, we implicated CT-SS in quantitative comparison with positive CT findings that might validate the significance of certain chest CT findings during disease severity evaluation.
The objectives of this study were to investigate the imaging features of emerging COVID-19 pneumonia on chest CT examinations performed on a population sample from Iraq, to provide a comprehensive radiological literature review on ongoing radiological data from our local area, and to investigate the seriousness of some of radiological manifestations in disease severity evaluation at time of diagnosis.
| Materials and Methods|| |
This cross-sectional study was approved by the ethical committee of our local institutional review board, and written informed and oral consent was obtained from all study participants. In case of inability of the patients to provide informed consent, it was received from the relatives or the admitting physicians who requested the CT examination. Consecutive patients admitted at the emergency departments of Erbil tertiary hospitals were enrolled from June 2020 to August 2020.
Inclusion criteria were (a) fever and respiratory symptoms, such as cough, and dyspnea; (b) mild respiratory symptoms and close contact with a person with confirmed COVID-19 infection; and (c) a previously positive specific blood test result and positive naso- and oropharyngeal swabs.
Exclusion criteria were (a) patients with already existing chronic lung diseases and heart-related chest problems; (b) contrast material-enhanced chest CT performed for a vascular indication (i.e., pulmonary embolism, aortic dissection, and coronary syndrome); (c) severe motion artifact on chest CT; and (d) Patients with negative reverse transcription–polymerase chain reaction results.
All chest CT examinations were performed with patients in the supine position during end-inspiration without contrast medium injection. Chest CT was performed on a 16-slice CT scanner (Philips Mx8000 IDT CT Scanner) dedicated only to patients with COVID-19 infection. The following technical parameters were used: tube voltage, 120 kV; tube current modulation, 100–250 mAs; spiral pitch factor, 0.98; and collimation width, 0.625. Reconstructions were made at a slice thickness of 1.25 mm. Two radiologists in consensus with 10 and 5 years of experience evaluated the images defining patients as having positive CT findings when a diagnosis of viral pneumonia was reported
The following CT features were also recorded: (a) ground-glass opacities (GGOs), (b) GGO pattern, (c) consolidation, (d) subpleural bands and architectural distortion, (e) number of lobes involved, (f) distribution, (g) fibrotic bands, (h) pulmonary nodules, (i) bronchiectasis, (j) interlobular septal thickening, (k) bronchovascular thickening, (l) pleural thickening, (m) round pneumonia, (n) crazy-paving pattern, (o) tree in bud pattern, (p) presence of cavitation and lymphadenopathy (defined as a lymph node with a short axis of 10 mm or more), (q) halo sign or atoll sign, and (r) pneumothorax.
All CT findings were described according to the Fleischner's Society recommendations, and defined as follows: GGO (appears as hazy increased opacity in the lung, with the preservation of bronchial and vascular margins), consolidation (appears as a homogeneous increase in pulmonary parenchymal attenuation that obscures the margins of vessels and airway walls), a crazy-paving pattern (appears as thickened interlobular septa and intralobular lines superimposed on a background of GGO), and CT halo sign (appears as GGO surrounding a nodule or mass)., Atoll sign is referred as the reversed halo sign, is a focal rounded GGO area surrounded by a complete or incomplete circular consolidation. Tree in bud (appears as multiple areas of centrilobular nodules with a linear branching pattern),, Interlobular Septal thickening (appears as Interlobular septa are the 10–20 mm long linear or sheet-like structures that form the lobular borders, which are more or less perpendicular to the peripheral pleura) [Figure 1].
|Figure 1: Axial unenhanced computed tomography images of the chest in two different patients presented with atypical COVID-19 pneumonia computed tomography manifestation. (a) A 7-year-old man admitted to the hospital. Chest computed tomography showed focal lower lobe tree in bud pattern; and (b) chest computed tomography of a 65-year-old man showed lymphadenopathy (short axis >10 mm) in the right lower paratracheal and preaortic stations and pleural thickening|
Click here to view
A semiquantitative scoring system called CT-SS, was applied to estimate the extent of pulmonary involvement in COVID-19 pneumonia according to previous studies., Each of the 5 lobes was calculated visually considering the extent of anatomic involvement and scored from 0 to 5, as follows: 0, no involvement; 1, <5% involvement; 2, 5%–25% involvement; 3, 26%–50% involvement; 4, 51%–75% involvement; and 5, >75% involvement. Then, the global CT score was calculated from the sum of each individual lobar score, yielding a value ranging from 0 to 25.
The Statistical Package for Social Sciences SPSS software (version 22) was used for data analysis. Descriptive data analysis included calculation of frequencies, percentages, means, and standard deviations (SDs). Differences between means of continuous variables were measured using Student's t-test and one-way ANOVA. P < 0.05 was considered statistically significant.
| Results|| |
Out of 150 patients, 18 cases were excluded from the study because they had one of the exclusion criteria. The study sample comprises 132 patients, ranging from 18 to 86 years, with a mean age of 51.08 ± 14.2 years.
The demographic characteristics of all patients with COVID-19 are summarized in [Table 1]. The most common age group (37.9%) was 56 and older. Sixty-five patients (49.2%) were female and 67 patients (50.8%) were male.
The radiological findings as shown in [Table 2] revealed that GGO was the most frequent pattern either diffuse (46.2%) or rounded opacities (32.6%), followed by consolidation which was seen without or with GGO reaching about 30% [Figure 2]. Nearly half of the patients had fibrotic bands and/or interlobular septal thickening. Most patients had bilateral and peripheral lung involvement (90.9% and 89%, respectively). A simultaneous involvement of two or more lobes was observed in 117 patients (88.6%). Subpleural fibrous bands [Figure 3]a and architectural distortion was the least common pattern seen in less than 10% of cases.
|Table 2: The frequency of computed tomography scan characteristics and patterns in COVID-19 patients (n=132)|
Click here to view
|Figure 2: (a) Axial unenhanced computed tomography scan in two different patients with unknown exposure history who presented with positive polymerase chain reaction test. Chest computed tomography of a 39-year-old male shows diffuse bilateral confluent and predominantly linear ground-glass opacities with a pronounced peripheral distribution. (b) Chest computed tomography images of a 58-year-old man show upper and lower lobe ground-glass opacities with pulmonary consolidation with air bronchogram in the apical segment of the right lower lobe|
Click here to view
|Figure 3: (a) Axial and reconstructed coronal unenhanced computed tomography scan in a 39-year-old male with peripheral and predominantly lower subpleural fibrous bands in both lungs, with bilateral traction bronchiectasis (b) Reconstrued coronal unenhanced CT scan of the same patient with the traction bronchiectasis in both lower lobes|
Click here to view
The distribution of lung abnormalities was recorded as predominantly subpleural or peripheral (involving mainly the peripheral one-third of the lung) (85.6%), central (involving mainly the two inner-thirds of the lung) (11.4%), or diffuse (continuous involvement without respect to lung segments) (3%).
Regarding other patterns, diffuse GGO with interstitial thickening giving the crazy-paving appearance was also observed in 24 patients (18.2%). Bronchovascular thickening was seen in 48 cases (21.2%), while bronchiectasis was less frequent manifestation in 28 patients (21.2%) [Figure 3]b. Tree in bud was the least seen pattern observed in less than 10%. Pulmonary nodules were also seen ranging from random, peripheral to the centrilobular distribution, the random distribution was more common at 32.6%. Interestingly round pneumonia was observed in about 13% of the cases. Less frequent findings such as pleural thickening and lymphadenopathy were almost of the same percentage of less than 25% and pneumothorax was seen in one case only.
Other related CT features such as CT halo sign and atoll sign were also observed in 9 cases (6.8%) and 5 cases (3.8%), respectively [Figure 4].
|Figure 4: Computed tomography images of ground glass opacity. A 44- year woman presented with fever and dyspnea. (a) Scan shows bilateral ground-glass opacities with rounded morphology in both upper and lower lobes, as well as inter- and intralobular septal thickening (crazy paving pattern). (b) Scan shows Lower lobe focal rounded GGO area surrounded by incomplete circular consolidation (atoll sign)|
Click here to view
Pathological lung involvement was most frequent in the lower lobes: right lower lobe (RLL) in 123 patients (93.2%) and left lower lobe (LLL) in 119 patients (90%). The mean CT scores were estimated as follows: 1.23 ± 1.02 for the right upper lobe (RUL), 0.98 ± 1.0 for the middle lobe (ML), 3.9 ± 1.3 for the RLL, 1.27 ± 1.06 for the left upper lobe (LUL), and 1.9 ± 1.37 for the LLL [Table 3]. The mean global CT score was 7.28 ± 4.91.
|Table 3: The estimated mean values of computed tomography score in COVID-19 patients (n=132)|
Click here to view
In terms of CT score, comparisons have been made between lobes for each lung. Regarding the right lung, the mean CT score was significantly higher in RLL than in ML (P < 0.0001) and RUL (P < 0.0001); no significant difference was found between RUL and ML (P = 080). Concerning the left lung, the mean CT score was significantly higher in LLL than in LUL (P < 0.0001). However, by comparing RLL and LLL, no statistically significant difference was observed between them (P = 0.958) [Table 3].
The total means of CT score were compared among clinical CT features and categories, as shown in [Table 4]. In general, the estimated values of CT score were higher in positive groups (cases that showed pathological CT manifestations) than negative groups. A significant difference was observed when almost all positive categories were compared with negative ones, except crazy paving, tree in bud appearances, and cavitation. CT score was significantly high in the GGO including the diffuse and round morphology (mean ± SD: 7.96 ± 4.93) (P < 0.0001). CT score was also significantly high in cases with consolidation (9.50 ± 5.56) (P < 0.0001). The mean CT score was significantly associated with bronchiectasis and pleural thickening (mean ± SD: 11.53 ± 5.80 and mean ± SD: 11.38 ± 5.29, respectively) (P < 0.0001).
|Table 4: The main computed tomography patterns and features in coronavirus disease 2019-infected patients with their related computed tomography score|
Click here to view
On the other hand, there was no statistical relationship between the total mean CT-SS and tree in bud, crazy paving, cavitation, and subpleural bands with architectural distortion.
| Discussion|| |
There are extensive studies on Covid 19-pneumonia in the literatures, dealing with different aspect of the disease.,,,, It is agreed that even when a patient is clinically consistent with Covid infection, we still have to study comprehensively the significant radiological manifestations that might be beneficial to speed-up diagnostic workflow in Covid cases. According to the literature, the typical findings of chest CT images of individuals with COVID-19 are multifocal bilateral patchy GGOs or consolidation with reticular or interlobular septal thickening, and mostly in the peripheral fields of the lungs.,,,,, Similarly, the main characteristics of COVID-19 pneumonia, as observed in this study, is the presence of bilateral peripheral diffuse areas of GGOs and patchy consolidation (78.8%), with interlobular septal thickenings (50.8%) in the lower lobes.
Consolidative opacities were observed in nearly one-third of our COVID population sample (32.6%). In the literature, consolidative patches were observed as well but with varying frequencies and different descriptive terms. For example, in two large studies on COVID-19 patients,,,,, consolidations were described as “patchy shadows” as one of the most frequent manifestations. Chung et al. reported that 29% of cases with COVID-19 pneumonia had areas of consolidation with or without GGOs which was nearly consistent with our results. Whereas, another study by Pan et al. revealed that consolidative opacities were seen in <20% of COVID-19 patients in their evaluation. In the same report, the authors also mentioned that approximately 70% of patients had multilobar involvement which are less than our results reaching 90%.
The chest CT scan findings could manifest different features in COVID-19 patients at different times depending on the disease severity., A recent study demonstrated the primary CT finding in the advanced stages (8–14 days) is GGOs with consolidation accompanied by repairing CT signs, including the appearance of subpleural line, distortion of the bronchus, and fibrotic strips. Since this is cross-sectional study and chest CT findings vary with time and disease severity, our patients demonstrated variable spectra of severity of lung involvement; accordingly, subpleural bands or lines with architectural distortion were noticed in nearly 7% of our COVID-19 cases.
Pulmonary fibrosis or fibrotic bands were to some extent common in our population sample reaching 54.4%. Pulmonary fibrosis usually is seen as irregular interfaces, parenchymal bands, and fibrotic changes during the follow-up of COVID-19 patients. It has been found that nearly half of COVID-19 patients have irregular fibrotic bands on initial CT and subsequently on follow-up these fibrotic changes may rise up to 90%.,,
Previous reports did describe typical and atypical chest CT patterns.,, Some studies reported that pleural effusion, pericardial effusion, lymphadenopathy, cavitation, CT halo sign, and pneumothorax were less common or rare.,,, Other studies reported that solid pulmonary nodules, cavitation, pleural effusions, and mediastinal/hilar lymph node enlargement were also not typically observed in cases of COVID-19 infection.
Regarding pulmonary nodules, generally in our study, more than half of cases had subcentimeter ground-glass pulmonary nodules distributed randomly between the outer and inner parts of pulmonary lobes. This result disagrees with some reports that stated that pulmonary nodules are infrequently seen with COVID-19 pneumonia, reaching about 10%., Some studies explained pulmonary nodule observation to be associated with disease severity.,
Interestingly, mediastinal lymphadenopathy was observed in 24% of patients. This was almost half the proportion (59%) reported in a study on COVID-19 features in Italy by Caruso et al. Whereas, this proportion of patients exhibited that mediastinal lymphadenopathy was higher than that in the report published by Pan et al.
In a study conducted by Jin et al. found that nearly 7% of COVID patients had another atypical finding such as bronchial wall thickening and pleural effusions. In comparison, our study showed that one-third of COVID patients had bronchovascular thickening and <25% had pleural thickening rather than pleural effusion.
In our study, less frequent CT manifestation of COVID-19 was round pneumonia (12.9%), crazy paving (18.2%), tree in bud (6.8%), and cavitation (14.4%). These various CT findings are not in agreement with the previous reports that showed different proportions., In fact, Franco et al. reported higher frequency of round opacity and crazy-paving pattern reaching 25% and no cavitation was observed in COVID-19 pneumonia patients.
CT halo sign and atoll sign is atypical and uncommon finding of COVID 19 pneumonia,, Our result was in agreement with reports conducted by Li et al. who suggested that some CT patterns like CT halo sign can be found within the spectrum of radiologic presentations of COVID-19 pneumonia. Classically, the CT halo sign has been described in hemorrhagic nodules, but viral infections are known differential causes for it.
In terms of radiological finding significance, in the present study, we used the CT scoring criteria proposed by Pan et al. that considers both lobe involvement and compare it with CT features, in an attempt to more comprehensively evaluate COVID-19 pneumonia on sequential chest CT examination and its association with certain pathological lung pattern. The semi-quantitative CT score could help to stratify the anatomic lung damage and lobar extent of disease in patients with COVID-19 pneumonia.,
According to the findings of the present study, by comparing lung lobes, the lower lobes were more significantly involved than the upper lobes on both sides. The mean CT score comparison between lobes for each lung showed a significant difference between RLL and RUL, RLL and RML, and LLL and LUL (P < 0.001). This result was in agreement with a study conducted by Francone et al. who found that calculated CT score based on the extent of lobar involvement showed that pathological involvement was most common in the lower lobes., In general, In the early stage of COVID-19, lung changes were mainly seen in the lower lobes on CT images. Later, during progression of the disease, lobe involvement and changes in CT findings can be in two or more major areas.
Chest CT is crucial in the early diagnosis of COVID-19 pneumonia because most symptomatic patients have characteristic CT findings. High CT score was significantly related to the presence of GGOs, consolidation, bronchiectasis, and pleural thickening, indicating that patients with more pathological imaging features are of higher CT score (P < 0.001). A recent study conducted by Li et al. found that CT scores were significantly high in severe critical group of COVID-19 patients than the less severely affected patient. The authors suggested that the GGO, consolidation, subpleural bands, architectural distortion named “spider web sign,” and crazy-paving pattern in patients with COVID-19 pneumonia were frequent pattern in patients with severe manifestation. In fact, consolidation was significantly more frequent in critical patients of COVID-19 pneumonia than less critically affected patients, which indicates that the alveoli are completely filled by inflammatory exudation., CT findings of consolidation, linear opacities, crazy-paving pattern, bronchial wall thickening, high CT scores, and extrapulmonary lesions may be features of severe COVID-19 pneumonia. Despite this agreement, our results showed no statistical relationship between the high values of total mean CT score and the crazy paving or the high values of total mean CT score and subpleural bands with architectural distortion (P = 0.296 and P = 0.544, respectively). Some reports mentioned that the median CT score, consolidation, and extensive distribution in patients having extensive CT manifestation (mortality group) was significantly higher compared to survival group (P < 0.05), suggesting that a more severe clinical course for these abnormalities can be pathologically correlated with diffuse alveolar damage.
| Conclusion|| |
In this study, we found that CT findings of GGO consolidation, linear opacities, crazy-paving pattern, and bronchiectasis in Iraq do come along with published literature about COVID-19 pneumonia. CT-SS plays an important role in the diagnosis, disease severity evaluation, and lobar extension of this disease. The observation of certain pathological findings such as GGOs and consolidation on chest CT is associated with high CT-SS, which can reflect the seriousness of these findings during COVID-19 pneumonia severity evaluation.
Several limitations should be addressed. In our setting, clinical and laboratory data were limited because of the urgency of the situation. Patient outcomes were not available at the time of this communication.
We highly appreciate many members of the frontline medical and nursing staff who demonstrated selfless and heroic devotion to duty in the face of this outbreak.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Carotti M, Salaffi F, Sarzi-Puttini P, Agostini A, Borgheresi A, Minorati D, et al.
Chest CT features of coronavirus disease 2019 (COVID-19) pneumonia: Key points for radiologists. Radiol Med 2020;125:636-46.
Ng MY, Lee EY, Yang J, Yang F, Li X, Wang H, et al.
Imaging profile of the COVID-19 infection: Radiologic findings and literature review. Radiol Cardiothorac Imaging 2020;2:e200034.
Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al.
Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology 2020;295:715-21.
Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, et al.
CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology 2020;295:202-7.
Pan Y, Guan H, Zhou S, Wang Y, Li Q, Zhu T, et al.
Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): A study of 63 patients in Wuhan, China. Eur Radiol 2020;30:3306-9.
Bai HX, Hsieh B, Xiong Z, Halsey K, Choi JW, Tran TM, et al.
Performance of radiologists in differentiating COVID-19 from non-COVID-19 viral pneumonia at chest CT. Radiology 2020;296:E46-54.
Francone M, Iafrate F, Masci GM, Coco S, Cilia F, Manganaro L, et al.
Chest CT score in COVID-19 patients: Correlation with disease severity and short-term prognosis. Eur Radiol 2020;30:6808-17.
Huang G, Gong T, Wang G, Wang J, Guo X, Cai E, et al.
Timely diagnosis and treatment shortens the time to resolution of coronavirus disease (COVID-19) pneumonia and lowers the highest and last CT scores from sequential chest CT. AJR Am J Roentgenol 2020;215:367-73.
Wormanns D, Hamer OW. Glossary of terms for thoracic imaging-German version of the Fleischner Society Recommendations. Rofo 2015;187:638-61.
Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J. Fleischner Society: Glossary of terms for thoracic imaging. Radiology 2008;246:697-722.
Zuo H. Contribution of CT features in the diagnosis of COVID-19. Can Respir J 2020;2020:9-10.
Eisenhuber E. The tree-in-bud sign. Radiology 2002;222:771-2.
Bagci U, Yao J, Wu A, Caban J, Palmore TN, Suffredini AF, et al.
Automatic detection and quantification of tree-in-bud (TIB) opacities from CT scans. IEEE Trans Biomed Eng 2012;59:1620-32.
Chang YC, Yu CJ, Chang SC, Galvin JR, Liu HM, Hsiao CH, et al.
Pulmonary sequelae in convalescent patients after severe acute respiratory syndrome: Evaluation with thin-section CT. Radiology 2005;236:1067-75.
Lei J, Li J, Li X, Qi X. CT imaging of the 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology 2020;295:18.
Fang Y, Zhang H, Xu Y, Xie J, Pang P, Ji W. CT manifestations of two cases of 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology 2020;295:208-9.
Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al.
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.
Xu X, Yu C, Qu J, Zhang L, Jiang S, Huang D, et al
. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Korean J Radiol 2020;47:1275-80.
Zhou S, Wang Y, Zhu T, Xia L. CT features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China. AJR Am J Roentgenol 2020;214:1287-94.
Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al
. Radiological Society of North America expert consensus document on reporting chest CT findings related to COVID-19: Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA. Radiol Cardiothorac Imaging 2020;2:e200152.
Xia T, Li J, Gao J, Xu X. Small solitary ground-glass nodule on CT as an initial manifestation of coronavirus disease 2019 (COVID-19) pneumonia. Korean J Radiol 2020;21:545-9.
Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, et al.
Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: A descriptive study. Lancet Infect Dis 2020;20:425-34.
Yu M, Liu Y, Xu D, Zhang R, Lan L, Xu H. Prediction of the development of pulmonary fibrosis using serial thin-section CT and clinical features in patients discharged after treatment for COVID-19 pneumonia. Korean J Radiol 2020;21:746-55.
Ward PA, Hunninghake GW. Lung inflammation and fibrosis. Am J Respir Crit Care Med 1998;157:S123-9.
Wei J, Yang H, Lei P, Fan B, Qiu Y, Zeng B, et al.
Analysis of thin-section CT in patients with coronavirus disease (COVID-19) after hospital discharge. J Xray Sci Technol 2020;28:383-9.
Caruso D, Polidori T, Guido G, Nicolai M, Bracci B, Cremona A, et al
. Typical and atypical COVID-19 computed tomography findings. World J Clin Cases 2020;8:3177.
Kong W, Agarwal PP. Chest imaging appearance of COVID-19 infection. Radiol Cardiothorac Imaging 2020;2:e200028.
Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, Fan YP, et al.
A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version). Mil Med Res 2020;7:4.
Li X, Zeng X, Liu B, Yu Y. COVID-19 infection presenting with CT halo sign. Radiol Cardiothorac Imaging 2020;2:e200026.
Caruso D, Zerunian M, Polici M, Pucciarelli F, Polidori T, Rucci C, et al.
Chest CT features of COVID-19 in Rome, Italy. Radiology 2020;296:E79-85.
Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): A pictorial review. Eur Radiol 2020;30:4381-9.
Zhao W, Zhong Z, Xie X, Yu Q, Liu J. Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: A multicenter study. AJR Am J Roentgenol 2020;214:1072.
Lu Z, Cao Y, Qin Q, Pan LZ. Clinical features and chest CT manifestations of coronavirus disease 2019 (COVID-19) in a single-center study in Shanghai, China. AJR Am J Roentgenol 2020;10:1.
Wang J, Xu Z, Wang J, Feng R, An Y, Ao W, et al.
CT characteristics of patients infected with 2019 novel coronavirus: Association with clinical type. Clin Radiol 2020;75:408-14.
Shaghaghi S, Daskareh M, Irannejad M, Shaghaghi M, Kamel IR. Target-shaped combined halo and reversed-halo sign, an atypical chest CT finding in COVID-19. Clin Imaging 2021;69:72-4.
Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19): A systematic review of imaging findings in 919 patients. AJR Am J Roentgenol 2020;215:87-93.
Li K, Fang Y, Li W, Pan C, Qin P, Zhong Y, et al.
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). Eur Radiol 2020;30:4407-16.
Pinto PS. The CT halo sign. Radiology 2004;230:109-10.
Koo HJ, Lim S, Choe J, Choi SH, Sung H, Do KH. Radiographic and CT features of viral pneumonia. Radiographics 2018;38:719-39.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]