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Review article

Radiological presentation of COVID-19 pneumonia

Aleksandra Đurić-Stefanović1,2
  • Center for Radiology and MR Imaging, University Clinical Center of Serbia, Belgrade Serbia
  • Faculty of Medicine, University of Belgrade, Serbia

ABSTRACT

Interstitial pneumonia is the main manifestation of the COVID-19 disease. The aim of this paper is to present the spectrum of typical radiological findings (CT - computed tomography, and radiographic) in COVID-19 pneumonia, the different CT examination techniques, the types and evolution of inflammatory lesions in the lungs, the criteria for assessing the probability of COVID-19 pneumonia in comparison to other types of interstitial pneumonia, and the scoring systems for determining the extent of COVID-19 pneumonia, based on CT findings and radiography. The standard CT examination protocol is a native CT examination of the chest, and, due to high sensitivity of low-dose CT protocols for detecting lung lesions, this imaging technique has become widely used in radiological practice during the COVID-19 pandemic. Bilateral, multiple, round or confluent zones of ground-glass density, predominantly localized subpleurally, peripherally and posteriorly, usually most extensive in the lower lobes, represent a typical CT presentation of COVID-19 pneumonia. Consolidations may develop at a later stage. A chest X-ray shows homogeneously reduced transparency in the lateral pulmonary fields, circular and irregular cloudlike shadows, and confluent patchy shadows, usually most extensive basally and laterally. RSNA and CO-RADS criteria are used to assess the probability of COVID-19 pneumonia, based on the criteria of a typical/atypical CT finding. Four stages of COVID-19 pneumonia have been defined, based on the dynamics of inflammatory lung lesion presentation: early, progressive, the phase of consolidation and the phase of organization. To assess the extent and severity of pneumonia, various scoring systems have been proposed, the most widely accepted one being the CT severity scoring system, based on visual semiquantitative assessment of the percentage of lung parenchyma inflammation lesions involvement of each of the five lobes, on a scale of 1 (<5%) to 5 (>75%), whereby the maximum score can be 25.


INTRODUCTION

The first studies related to clinical and radiological manifestations present in patients suffering from the infection caused by the new corona virus, which was subsequently officially named SARS-CoV-2, were published online on January 24, 2020, in the Lancet and New England Journal of Medicine [1],[2],[3]. According to the official data issued by the World Health organization, since December 2019, when the epidemic broke out in the city of Wuhan, in China, and very quickly spread all over the world, throughout the pandemic of the COVID-19 disease (Corona Virus Disease 2019), which was officially declared on March 11, 2020, until June 2021, cases of more than 174 million infected and over 3.7 million deceased persons have been confirmed.1 According to the official data issued by the Ministry of Health of the Republic of Serbia, since the first officially confirmed case of COVID-19 in Serbia, on March 6, 2020, until June 11, 2021, cases of 714,634 infected patients and 6,951 deceased patients have been confirmed.2

Interstitial pneumonia is the dominant manifestation of the COVID-19 disease, as is the case with its ‘predecessors’ from the same group of pathogens: SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) [1],[2]. The main symptoms of the COVID-19 infection are fever, faintness and coughing. The following may also be present: headache, pain in the muscles, a sore throat, loss of smell and taste, diarrhea, etc., while leukopenia with lymphopenia may be detected in the blood [1],[2]. Several days after the onset of disease, labored breathing may occur, i.e., the sensation of shortness of breath, which is a symptom indicating respiratory insufficiency caused by COVID-19 pneumonia [1],[2].

In most patients infected with the new corona virus, computed tomography (CT) is applied, in order to obtain an image of the changes occurring in the parenchyma of the lungs, which are characteristic of interstitial pneumonia of viral etiology, but, with certain features which characterize COVID-19 pneumonia [1],[2],[4],[5]. Bilateral, multiple, circular or confluent zones of ground-glass density, which are predominantly localized subpleurally/peripherally and posteriorly, with the largest zones located in the lower lobes, represent the typical presentation of COVID-19 pneumonia [1],[2],[3],[4],[5]. Consolidations may also develop at a later stage [1],[2],[3],[4],[5]. Although numerous studies have shown that computed tomography is more sensitive in detecting the COVID-19 infection than the PCR test [6],[7], and that, in a significant percentage of the patients, it also detects changes in the lungs even in asymptomatic patients [8], according to available clinical practice guidelines, routine application of CT imaging in all patients is not recommended [9].

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Figure 1. Radiographic presentation of COVID-19 pneumonia: homogeneously reduced transparency in lateral pulmonary fields (a); circular and irregular cloudlike shadows, bilaterally (b); confluent bilateral patchy shadows, basally, and veil-like shadows, laterally (c); extensive confluent bilateral patchy shadows, basally and laterally (d)

Chest radiography, although less sensitive than CT, especially in the early phase and in milder clinical forms of the disease, due to wide availability, simpler, shorter and safer application, as well as a lower exponential dose of radiation for the patient, remains widely applied in triage and follow-up of COVID-19 patients, and it is the method of choice in monitoring severely ill patients and patients with low mobility who are hospitalized in intensive care units [9]. X-ray images of the lungs may show the following: a pronounced reticular pattern (as the earliest radiological manifestation), homogenously decreased transparency in the lateral pulmonary fields (peripheral veil-like shadows) (Figure 1a), circular and irregular cloudlike shadows (Figure 1b), and confluent patchy shadows, usually most extensive basally and laterally [10],[11] (Figures 1c, 1d).

CT EXAMINATION TECHNIQUE

Since the onset of the epidemic in China, based on the previous experiences with the SARS and MERS epidemics, with the same practice being applied in the whole world, the standard protocol for the examination is the, so called, native-phase CT examination of the thorax, which entails a CT examination without intravenous application of iodine contrast material, for the purpose of faster, simpler and safer application, both for staff and patients [4],[12]. Due to the fact that several studies have demonstrated acceptably high sensitivity of lowdose CT protocols, this imaging technique has become widely applied in radiological practice during the COVID-19 pandemic, since low-dose technique reduces the exponential radiation dose to less than 1 mSv, as compared to 5 - 10 mSv, which is the level of the dose absorbed by a patient during a CT examination of the thorax [13]. In cases of clinical suspicion of pulmonary embolism, which occurs with significant frequency in COVID-19 pneumonia, CT examination with intravenous application of iodine contrast material is carried out, in keeping with the protocol for pulmoangiography [14].

TYPES OF LUNG LESIONS AND THEIR EVOLUTION

The types of lung lesions occurring in patients with mild or moderate clinical presentation, who have successfully recovered from COVID-19 pneumonia, as well as the evolution of these changes in the interval from symptom onset to recovery, were described in the studies by Pan et al., published online, on February 13, 2020 [4] and subsequently, in other numerous studies [5],[15],[16].

Table 1. The evolution of COVID-19 pneumonia, by stages, according to CT presentation in patients with mild or moderate clinical presentation and favorable clinical outcome [4]

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Figure 2. Typical CT presentation and evolution of COVID-19 pneumonia: bilateral, multiple subpleural and peripherally localized ground-glass opacities in the axial (a) and coronal section (b); the ‘paving-stone’ sign (c); consolidation in the pulmonary (d) and soft tissue ‘window’(e); organizing pneumonia (f)

Depending on the CT presentation of the lung changes and the dynamics of their presentation over time, COVID-19 pneumonia has been divided into four stages [4] (Table 1). The early stage (stage of interstitial pneumonitis) is characterized by lesions known as ground- glass opacities (GGO) (Figures 2a, 2b), which develop as the result of the release of inflammatory exudate into the interstitium [4],[16]. In the second, progressive stage, thickened intralobular septs are visible, which occur due to the inflammatory proliferation of interstitial elements, which increases density and visually appears as a fine web within the ground-glass opacities (‘crazy paving’, i.e., ‘paving stone’ sign) [4],[16] (Figure 2c). In the third, the stage of consolidation, which represents the peak stage of pneumonia, the density is increased to such an extent that blood vessels cannot be distinguished within the changes in the lungs [4],[16] (Figure 2d), the air bronchogram sign is visible, and consolidation is also present in the soft tissue ‘window’, in the form of fluid content in the pulmonary acini (Figure 2e). In the fourth stage, i.e., the stage of organizing pneumonia, linear and band-like changes in the lungs are dominant (thickened interlobular septs and fibroadhesions), with remaining consolidation (Figure 2f).

The peak distribution of inflammatory changes in the lungs is, on average, on day 10 from the onset of symptoms, and after day 14, gradual regression in their number and overall distribution can be registered [5] (Figures 3a, 3b). In patients with an unfavorable clinical course, the radiological finding worsens even after day 14, with the development of new confluent ground-glass density zones, further progressing into the clinical presentation of acute respiratory distress syndrome (ARDS), probably as the result of generalized pulmonary microvascular obstructive thrombo-inflammatory syndrome [5],[16]. In asymptomatic patients and patients with mild clinical presentation, CT monitoring shows only groundglass density opacities, and there is no consolidation [16]. Fibrous changes in the lungs, in the form of late sequelae, have been detected after a period of six months on follow-up CT examination, in approximately 35% of patients who were hospitalized due to COVID-19 pneumonia [17].

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Figure 3. Evolution of COVID-19 pneumonia in a 68-year-old female patient: a comparative presentation of CT findings on day 11 (‘peak’) (a), and day 29 of symptom onset (organizing pneumonia) (b)

ASSESSMENT OF THE PROBABILITY OF COVID-19 PNEUMONIA AS COMPARED TO OTHER CAUSES OF INTERSTITIAL PNEUMONIA

Bilateral, multifocal, round and confluent zones of ground-glass density (interstitial pneumonitis), and subsequently also consolidations, localized peripherally/subpleurally, with the most extensive ones located posteriorly in the lower lobes, are typically visualized on CT examination in COVID-19 pneumonia. The distribution of pleural changes may be lobular (round zones), subpleural (confluent zones), or diffuse [16].

Typically, in COVID-19 pneumonia, there are no excavations/cavitations and nodular lesions in the pulmonary parenchyma, nor are there enlarged mediastinal lymph nodes or pleural effusion [12],[18],[19]. For the assessment of the probability of COVID-19 pneumonia, based on the typical/atypical CT scan criteria, and for the purpose of more precise differential diagnosis in relation to interstitial pneumonia of other etiology, three systems of grading have been proposed: RSNA (Radiological Society of North America) [12], CO-RADS [18] and COVID-RADS [19], of which the first two have come into wide clinical use, without significant difference in diagnostic reliability [20] (Table 2).

Table 2. Probability of COVID-19 pneumonia, based on CT presentation: RSNA and CO-RADS criteria

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In the differential diagnosis of COVID-19 pneumonia, other types of interstitial pneumonia of various etiology are also a possibility, as they characteristically manifest with opacities of ground-glass density, as well. Among them are the following types of pneumonia: viral (type A influenza, adenovirus, hantavirus, respiratory syncytial virus, SARS, MERS), atypical bacterial pneumonia (mycoplasma, chlamydia), rare opportunistic fungal Pneumocystis jiroveci pneumonia, hypersensitive, eosinophilic and lipoid pneumonia, damage to the lungs caused by the use of some drugs and narcotics, etc. [21],[22]. Knowing the differences in the clinical presentation, the laboratory findings and the typical radiological presentation, characterized by predominantly subpleural and peripheral distribution of inflammatory changes in the lungs, is essential in establishing the right diagnosis.

SCORING SYSTEMS FOR ASSESSING THE EXTENT AND SEVERITY OF COVID-19 PNEUMONIA ON THE BASIS OF CT AND RADIOGRAPHIC FINDINGS

For the assessment of the extent and severity of pneumonia, based on CT and radiography findings, different scoring systems have been proposed by different authors [4],[23],[24],[25],[26]. The widely accepted CT Severity Scoring System, described in the above-mentioned study by Pan et al. [4], based on the previously applied scoring system for analyzing the scope of lung changes in ARDS, is founded on visual, semiquantitative assessment of the percentage of pulmonary parenchyma affected by inflammatory changes. Based on this scoring system, the extent of inflammation in each of the five lobes is assessed on a scale from 0 to 5, with 1 point signifying that less than 5% of the lung parenchyma in the lobe is affected by inflammation; 2 points show that between 5% and 25% of the parenchyma is involved; 3 points indicate between 26% and 49% of parenchyma affected by inflammation; 4 points signify between 50% and 75% of parenchyma involved; while 5 points indicate that more than 75% of the parenchyma in the lobe is inflamed. Thus, the total number of points, i.e., CT score, can range from 0 to 25 [4] (Figures 4a, 4b). A different group of Chinese authors has proposed a similar, but simpler scoring system, with the scale ranging from 0 to 4. It differs from the previous system in the fact that there is no category signifying less than 5% of parenchymal involvement, rather, 1 point signifies that up to 25% of the parenchyma of the lobe is affected; 2 points indicate between 26% and 50% of parenchyma involvement; 3 points signify that between 50% and 75% of parenchyma is affected; while 4 points indicate that more than 75% of the parenchyma in the lobe is inflamed [23]. By multiplying the number of points with five (total number of lung lobes), the overall score (possible range: 0 - 20) is obtained [23]. More complex scoring systems combine the assessment of the extent of parenchymal involvement, in the segments and the lobes, with the type of inflammatory changes, whereby consolidations carry double the number of points as compared to the ground-glass opacities. Therefore, by multiplying the number of points for each lung lobe and by adding these points up, higher values of the overall as well as the maximum score are obtained, as compared to the two previously described scoring systems [24],[25].

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Figure 4. Coronal (a) and sagittal (b) section of the CT examination of the same patient (axial section in Figure 3a): in all lobes >25% of parenchyma affected (3 points), therefore the total CT severity score estimated at 15/25

Different scoring systems are also being used for assessing the extent of pulmonary parenchyma affected on X-ray images [26]. The simplest system is the one where the percentage to which each lung is affected by inflammatory changes is assessed visually on a scale ranging from 1 to 4 (1:<25%; 2: 25-50%; 3: 26-75%; and 4: >75%), and the sum of points for each lung can range from 0 to 8 [26]. Italian authors from Brescia have published the CXR (Chest X-Ray) or Brixia scoring system, which analyzes, not only the presence of inflammatory changes, but also their dominant type [27]. According to this classification, both lungs are divided into three fields each (upper, middle and lower), which makes a total of 6 lung fields. Each field is analyzed for the presence of three types of inflammatory changes: interstitial opacities (1 point), mixed interstitial and consolidation lesions (2 points), and dominant presence of consolidations (3 points). Thereby, the overall score cane range from 0 to 18 points [27]. A similar, but simpler method is applied in the Chest Severity Score System, proposed by American authors, as it analyzes only the presence of inflammatory changes in each of the three fields of the lungs (upper, middle and lower), in both lungs. Therefore, the possible score range is between 0 and 6 [28].

For a more precise assessment of the percentage of the lung parenchyma affected by pneumonia, volumetric CT analysis, a quantitative method which exactly shows the volume of lung parenchyma affected by inflammatory changes, as well as the volume of unaffected parenchyma, may be applied. This method can be manual, semiautomatic or automatic, while numerous algorithms based on the application of artificial intelligence have also been tested and applied [29],[30]. It has been shown that the extent of lung parenchyma involvement, as seen on the CT scan, which exceeds 25% of the overall parenchyma volume, correlates most commonly with respiratory insufficiency, which requires oxygen therapy [31]. It has also been demonstrated that patients with more severe clinical presentation and a less favorable outcome, initially had multilobular and diffuse distribution of inflammatory lesions, with a higher average CT score, which continued to rapidly rise in the several following days, turning into ARDS [24],[32].

CONCLUSION

Computed tomography detects, with high sensitivity, inflammatory changes in patients with COVID-19. Bilateral, multiple, round or confluent zones of groundglass density, predominantly localized subpleurally, peripherally and posteriorly, usually most extensive in the lower lobes, represent a typical CT presentation of COVID-19 pneumonia.

Repeated low-dose CT scan examinations make it possible to monitor the dynamics of the evolution of pneumonia in the qualitative (stage) and quantitative (extent of the inflammation in the lungs) sense. Chest radiography, although less sensitive than CT, due to wide availability, simpler, shorter and safer application, as well as a lower exponential dose of radiation for the patient, remains widely applied in triage and follow-up of COVID-19 patients.

1 https://covid19.who.int

2 https://covid19.rs

  • Conflict of interest:
    None declared.

Informations

Volume 2 No 3

September 2021

Pages 266-277
  • Keywords:
    COVID-19 pneumonia, computed tomography, chest X-ray
  • Received:
    14 July 2021
  • Revised:
    14 August 2021
  • Accepted:
    23 August 2021
  • Online first:
    30 September 2021
  • DOI:
  • Cite this article:
    Đurić-Stefanović A. Radiological presentation of COVID-19 pneumonia. Serbian Journal of the Medical Chamber. 2021;2(3):266-77. doi: 10.5937/smclk2-32749
Corresponding author

Aleksandra Đurić-Stefanović, PhD
Center for Radiology and MR Imaging, University Clinical Center of Serbia
Department of Digestive Radiology, Hospital for Digestive Surgery (First Surgical Hospital)
6 Koste Todorovića Street, 11129 Beograd, Serbia
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


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1. 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(10223):497-506.[CROSSREF]

2. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514-23.[CROSSREF]

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13. Kang Z, Li X, Zhou S. Recommendation of low-dose CT in the detection and management of COVID-2019. Eur Radiol 2020; 30(8):4356-7.[CROSSREF]

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17. Han X, Fan Y, Alwalid O, Li N, Jia X, Yuan M, et al. Six-month follow-up chest CT findings after severe COVID-19 pneumonia. Radiology. 2021;299(1):E177-86.[CROSSREF]

18. Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stöger L, Beenen L, et al. COVID-19 standardized reporting working group of the Dutch Radiological Society. CO-RADS: A categorical CT assessment scheme for patients suspected of having COVID-19-Definition and evaluation. Radiology. 2020;296(2):E97-104.[CROSSREF]

19. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies. Eur Radiol. 2020;30(9):4930-42.[CROSSREF]

20. Abdel-Tawab M, Basha MAA, Mohamed IAI, Ibrahim HM, Zaitoun MMA, Elsayed SB, et al. Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia. Insights Imaging. 2021;12(1):55.[CROSSREF]

21. Guarnera A, Podda P, Santini E, Paolantonio P, Laghi A. Differential diagnoses of COVID-19 pneumonia: the current challenge for the radiologist- a pictorial essay. Insights Imaging. 2021;12(1):34.[CROSSREF]

22. Hani C, Trieu NH, Saab I, Dangeard S, Bennani S, Chassagnon G, et al. COVID-19 pneumonia: A review of typical CT findings and differential diagnosis. Diagn Interv Imaging. 2020;101(5):263-8.[CROSSREF]

23. 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(1):202-7.[CROSSREF]

24. Li Y, Yang Z, Ai T, Wu S, Xia L. Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19) Eur Radiol. 2020;30(11):6186-93.[CROSSREF]

25. Yang R, Li X, Liu H, Zhen Y, Zhang X, Xiong Q, et al. Chest CT severity score: An imaging tool for assessing severe COVID-19. Radiol Cardiothorac Imaging. 2020;2(2):e200047.[CROSSREF]

26. Wasilewski PG, Mruk B, Mazur S, Półtorak-Szymczak G, Sklinda K, Walecki J. COVID-19 severity scoring systems in radiological imaging - a review. Pol J Radiol. 2020;85:e361-8.[CROSREF]

27. Borghesi A, Maroldi R. COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression. Radiol Med. 2020;125(5):509-13.[CROSSREF]

28. Toussie D, Voutsinas N, Finkelstein M, Cedillo MA, Manna S, Maron SZ, et al. Clinical and chest radiography features determine patient outcomes in young and middle-aged adults with COVID-19. Radiology. 2020;297(1):E197-E206.[CROSSREF]

29. Lanza E, Muglia R, Bolengo I, Santonocito OG, Lisi C, Angelotti G, et al. Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation. Eur Radiol. 2020;30(12):6770-8.[CROSSREF]

30. NäppiJ, Uemura T, Watari C, Hironaka T, Kamiya T, Yoshida H. U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19. Sci Rep. 2021;11(1):9263.[CROSSREF]

31. Colombi D, Bodini FC, Petrini M, Maffi G, Morelli N, Milanese G, et al. Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia. Radiology. 2020;296(2):E86-96.[CROSSREF]

32. Pan F, Zheng C, Ye T, Li L, Liu D, Li L, et al. Different computed tomography patterns of  Coronavirus  Disease  2019  (COVID-19) between survivors and non-survivors. Sci Rep. 2020;10(1):11336.[CROSSREF]

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5. 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(1):87-93.[CROSSREF]

6. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing in Coronavirus Disease 2019 (COVID-19) in China: A report of 1014 cases. Radiology. 2020;296(2):E32-40.[CROSSREF]

7. Xie X, Zhong Z, Zhao W, Zheng C, Wang F, Liu J. Chest CT for typical 2019- nCoV  pneumonia: Relationship to negative RT-PCR Testing. Radiology. 2020;296(2):E41-5.[CROSSREF]

8. Inui S, Fujikawa A, Jitsu M, Kunishima N, Watanabe S, Suzuki Y, et al. Chest CT findings in cases from the cruise ship Diamond Princess with Coronavirus Disease (COVID-19). Radiol Cardiothorac Imaging. 2020;2(2):e200110.[CROSSREF]

9. Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, et al. The Role of chest imaging in patient management during the COVID-19 pandemic: A multinational consensus statement from the Fleischner Society. Radiology. 2020;296(1):172-80.[CROSSREF]

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11. Vespro V, Andrisani MC, Fusco S, Di Meglio L, Plensich G, Scarabelli A, et al. Chest X-ray findings in a large cohort of 1117 patients with SARS-CoV-2 infection: a multicenter study during COVID-19 outbreak in Italy. Intern Emerg Med. 2021;16(5):1173-81.[CROSSREF]

12. Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al. Radiological Society of North America Expert consensus statement on reporting chest CT findings related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA - Secondary Publication. J Thorac Imaging. 2020;35(4):219-27.[CROSSREF]

13. Kang Z, Li X, Zhou S. Recommendation of low-dose CT in the detection and management of COVID-2019. Eur Radiol 2020; 30(8):4356-7.[CROSSREF]

14. Léonard-Lorant I, Delabranche X, Séverac F, Helms J, Pauzet C, Collange O, et al. Acute pulmonary embolism in patients with COVID-19 at CT angiography and relationship to d-dimer levels. Radiology. 2020;296(3):E189-91.[CROSSREF]

15. Wang YC, Luo H, Liu S, Huang S, Zhou Z, Yu Q, et al. Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China. Eur Radiol. 2020;30(11):6194-203.[CROSSREF]

16. Wu J, Pan J, Teng D, Xu X, Feng J, Chen Y-C. Interpretation of CT signs of 2019 novel coronavirus (COVID-19) pneumonia. Eur Radiol. 2020;30(10):5455-62.[CROSSREF]

17. Han X, Fan Y, Alwalid O, Li N, Jia X, Yuan M, et al. Six-month follow-up chest CT findings after severe COVID-19 pneumonia. Radiology. 2021;299(1):E177-86.[CROSSREF]

18. Prokop M, van Everdingen W, van Rees Vellinga T, Quarles van Ufford H, Stöger L, Beenen L, et al. COVID-19 standardized reporting working group of the Dutch Radiological Society. CO-RADS: A categorical CT assessment scheme for patients suspected of having COVID-19-Definition and evaluation. Radiology. 2020;296(2):E97-104.[CROSSREF]

19. Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies. Eur Radiol. 2020;30(9):4930-42.[CROSSREF]

20. Abdel-Tawab M, Basha MAA, Mohamed IAI, Ibrahim HM, Zaitoun MMA, Elsayed SB, et al. Comparison of the CO-RADS and the RSNA chest CT classification system concerning sensitivity and reliability for the diagnosis of COVID-19 pneumonia. Insights Imaging. 2021;12(1):55.[CROSSREF]

21. Guarnera A, Podda P, Santini E, Paolantonio P, Laghi A. Differential diagnoses of COVID-19 pneumonia: the current challenge for the radiologist- a pictorial essay. Insights Imaging. 2021;12(1):34.[CROSSREF]

22. Hani C, Trieu NH, Saab I, Dangeard S, Bennani S, Chassagnon G, et al. COVID-19 pneumonia: A review of typical CT findings and differential diagnosis. Diagn Interv Imaging. 2020;101(5):263-8.[CROSSREF]

23. 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(1):202-7.[CROSSREF]

24. Li Y, Yang Z, Ai T, Wu S, Xia L. Association of “initial CT” findings with mortality in older patients with coronavirus disease 2019 (COVID-19) Eur Radiol. 2020;30(11):6186-93.[CROSSREF]

25. Yang R, Li X, Liu H, Zhen Y, Zhang X, Xiong Q, et al. Chest CT severity score: An imaging tool for assessing severe COVID-19. Radiol Cardiothorac Imaging. 2020;2(2):e200047.[CROSSREF]

26. Wasilewski PG, Mruk B, Mazur S, Półtorak-Szymczak G, Sklinda K, Walecki J. COVID-19 severity scoring systems in radiological imaging - a review. Pol J Radiol. 2020;85:e361-8.[CROSREF]

27. Borghesi A, Maroldi R. COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression. Radiol Med. 2020;125(5):509-13.[CROSSREF]

28. Toussie D, Voutsinas N, Finkelstein M, Cedillo MA, Manna S, Maron SZ, et al. Clinical and chest radiography features determine patient outcomes in young and middle-aged adults with COVID-19. Radiology. 2020;297(1):E197-E206.[CROSSREF]

29. Lanza E, Muglia R, Bolengo I, Santonocito OG, Lisi C, Angelotti G, et al. Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation. Eur Radiol. 2020;30(12):6770-8.[CROSSREF]

30. NäppiJ, Uemura T, Watari C, Hironaka T, Kamiya T, Yoshida H. U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19. Sci Rep. 2021;11(1):9263.[CROSSREF]

31. Colombi D, Bodini FC, Petrini M, Maffi G, Morelli N, Milanese G, et al. Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia. Radiology. 2020;296(2):E86-96.[CROSSREF]

32. Pan F, Zheng C, Ye T, Li L, Liu D, Li L, et al. Different computed tomography patterns of  Coronavirus  Disease  2019  (COVID-19) between survivors and non-survivors. Sci Rep. 2020;10(1):11336.[CROSSREF]


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