key: cord-0883516-kaoxedk2
authors: Garg, Mandeep; Gupta, Pankaj; Maralakunte, Muniraju; Kumar-M, Praveen; Sinha, Anindita; Kang, Mandeep; Agarwala, Ritesh; Sandhu, Manavjit Singha
title: Diagnostic accuracy of CT and radiographic findings for novel coronavirus 2019 pneumonia: Systematic review and meta-analysis
date: 2020-11-11
journal: Clin Imaging
DOI: 10.1016/j.clinimag.2020.11.021
sha: a06c0dbef90339109254649dd620fbda0ad7ab6e
doc_id: 883516
cord_uid: kaoxedk2

PURPOSE: To evaluate pooled prevalence, sensitivity, and specificity of chest computed tomography (CT) and radiographic findings for novel coronavirus-2019 (COVID-19) pneumonia. METHODS: We performed systematic literature search in PubMed and Embase to identify articles reporting baseline imaging findings of COVID-19 pneumonia. The quality of the articles was assessed using NIH quality assessment tool for case series studies. The pooled prevalence, sensitivity, specificity, and diagnostic odds ratio of imaging findings were calculated. RESULTS: Fifty-six studies (6007 patients, age, 2.1–70 years, 2887 females, 5762 CT, 396 radiographs,) were included. The mean interval between onset of symptoms and CT acquisition was 1–8 days. On CT, the pooled prevalence of ground glass opacities (GGO), GGO plus consolidation, and consolidation only was 66.9% (95% CI 60.8–72.4%), 44.9% (38.7–51.3%), and 32.1 (23.6–41.9%) respectively. Pooled sensitivity and specificity of GGO on CT was 73% (71%–80%) and 61% (41%–78%), respectively. For GGO plus consolidation and consolidation only, the pooled sensitivities/ specificities were 58% (48%–68%)/ 58% (41%–73%) and 49% (20%–78%)/ 56% (30%–78%), respectively. The pooled prevalence of GGO and consolidation on chest radiograph was 38.7% (22.2%–58.3%) and 46.9% (29.7%–64.9%), respectively. The diagnostic accuracy of radiographic findings could not be assessed due to small number of studies. CONCLUSION: GGO on CT has the highest diagnostic performance for COVID-19 pneumonia, followed by GGO plus consolidation and consolidation only. However, the moderate to low sensitivity and specificity suggest that CT should not be used as the primary tool for diagnosis. Chest radiographic abnormalities are seen half of the patients.

World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a "public health emergency" at the end of January 2020 (1) . The disease is highly infectious, and the reported modes of spread are via aerosol and feco-oral route (2) .

The initial symptoms are indistinguishable from other viral diseases. Pneumonia is the most frequent presentation and manifests as fever, cough, dyspnea. Although most patients have mild disease with complete recovery, patients with advanced age and underlying co-morbidities have higher mortality (3) . There are no specific clinical or 93% according to the site and method of obtaining the specimen (5) . Bronchoalveolar lavage fluid specimen has the highest positivity rates followed by sputum, and nasal swabs (5) .

Imaging is invaluable in the assessment of the COVID-19 patients. Standard frontal chest radiographs reveal ground-glass opacities (GGO) or consolidation (4) . The most common CT finding is bilateral, peripheral GGO. Consolidation, combination of consolidation and GGO, and crazy paving pattern are the other commonly reported findings (6, 7) . The CT features of COVID-19 pneumonia depend on the duration of infection (8, 9) . CT may be normal in the early phase. The CT findings peak between 6 and 11 days and comprise mainly of GGO. Between 12 and 17 days, a mixed pattern of findings (GGO and consolidation) predominate. Majority of the patients have residual findings on CT at the time of discharge. Additionally, the CT findings may progress over time. In one study, worsening of GGO and progression to consolidation was reported in 85.7% of the patients (10) . CT involvement scores, architectural distortion, and traction bronchiectasis may aid in evaluation of disease severity (7) . Despite some reports of better diagnostic accuracy of chest CT compared with RT-PCR, the American College of Radiology (ACR) does not recommend the use of a CT chest for screening purposes (11) (12) (13) . CT scans can be efficiently utilized in a selected group of hospitalized COVID-19 patients to assess the extent, severity, and prognosis of the disease and to detect associated complications. The visual as well as quantitative maps of the affected lungs, may provide an objective assessment of the severity of involvement.

Most of the published systematic reviews on the imaging findings in COVID-19 comprise studies conducted in the early period of the disease outbreak (14) (15) (16) (17) . The J o u r n a l P r e -p r o o f Journal Pre-proof quantitative analyses were limited to pooled prevalence estimates. The present systemic review and meta-analysis is aimed to evaluate the pooled prevalence and the diagnostic accuracy of individual imaging findings on chest CT scans and radiographs in patients with COVID-19 pneumonia.

This meta-analysis complied with the Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines (18) .

Two reviewers searched Pubmed and Embase and screened the titles and abstracts independently. The disagreement regarding the inclusion of a potential article was resolved in consensus. There was no language restriction for the search. The search was limited to the articles reporting COVID-19 infection only. The initial search was completed on 2 nd April and again updated on 7 th April 2020. The detailed search strategy is shown in Table 1 . Studies were first screened by examining their titles and abstracts. Their references were also checked for other relevant publications. The full texts of potentially eligible studies were retrieved for review.

Review articles, case series (≤10), case reports, pictorial essays, letter to the editor (on already published papers), unpublished data, conference abstracts, and proceedings on the topic of interest were excluded.

The data was extracted on an excel sheet by two reviewers independently. The following details were obtained: type of study, country of origin, imaging modality (CT or chest radiograph); reference standard for diagnosis; patient demographic information Two reviewers assessed the methodologic and reporting quality of each study independently by using the NIH quality assessment tool for case series studies (19).

This tool comprised nine questions. The responses to each of these questions were "yes", "no" or others (cannot determine, CD; not reported, NR; or not applicable, NA).

The overall assessment was "good", "fair" or "poor".

readxl (20) (21) (22) (23) . The studies providing the number of patients with individual imaging findings and the total number of patients were summarized as pooled prevalence.

Studies reporting the sensitivity as well as specificity were used to extract TP, TN, FP, and FN for evaluating pooled sensitivity, specificity, and diagnostic odds ratio. The meta-analysis was done using the inverse variance method with logit transformation along with the Clopper-Pearson confidence interval for individual studies. The pooling of the diagnostic odds ratio was also computed by the inverse variance method. The Forest plots were constructed for pooled prevalence, sensitivity, specificity, and diagnostic odds ratio. For the pooled analysis, heterogeneity was quantified using the I 2 test statistic, including 95% CI. The I 2 statistic reports the percentage of total variation across studies that is due to heterogeneity rather than chance. A value of I 2 statistic greater than 50% implies heterogeneity. Wilson method was used for the calculation of CI for both pooled analysis as well as the summary results. A bivariate diagnostic random-effect model was used for computing the combined sensitivity and specificity.

For the computation of the bivariate model, a minimum of 4 studies was essential.

Hierarchical summary receiver operating plot (hsROC) with 95% predictive and calculated region was plotted, and area under the curve (AUC) was determined.

The study selection process is detailed in the flowchart (Figure 1) . The initial search Table 1 . There were four studies in the Chinese language. Most of the studies were from the Chinese population. Three studies were reported from the United States (n=3) and one study each from Japan (n=1) and Italy (n=1).

The results of the quality assessment are presented in Supplementary Table 2 . Most of the studies were rated as "fair" by both the reviewers. Figures 1 and 2) .

Findings of chest radiographs were reported by five studies comprising 396 patients.

The pooled prevalence of GGO and consolidation was 38.7% (22.2%-58.3%, I 2 83%) and 46.9% (29.7%-64.9%, I 2 84%), respectively (Supplementary Figure 3) . The diagnostic accuracy meta-analysis for radiographic abnormalities could not be conducted due to a limited number of studies.

Pooled sensitivities and specificities of GGO on CT were 73% (71%-80%, I 2 96%) and 61% (41%-78%, I 2 94%) respectively. For GGO plus consolidation and consolidation only, the pooled sensitivities/ specificities were 58% (48%-68%, I 2 31%)/ 58% (41%-73%, I 2 77%) and 49% (20%-78%, I 2 96%)/ 56% (30%-78%, I 2 91%), respectively. The pooled diagnostic odds ratio of GGO, GGO plus consolidation, and consolidation only (Figures 3-5) . Table 2 shows the results of the pooled prevalence J o u r n a l P r e -p r o o f Journal Pre-proof and diagnostic accuracy meta-analysis of CT findings. Table 3 shows the pooled prevalence of chest radiographic abnormalities.

We reported a systematic review and meta-analysis of chest CT and radiographic findings in 5993 patients with COVID-19 pneumonia. We included 56 studies that reported the chest imaging findings at baseline. Besides evaluating the prevalence of various findings in COVID-19 pneumonia, we also conducted diagnostic accuracy metaanalysis for certain studies where the required data was available. We found that GGOs, GGO plus consolidation, and consolidation only were the frequent imaging findings in that order. The diagnostic odds ratio of GGO was the highest (4.97, 95% CI: 2.36-10.35) with the AUC of 0.728. Additionally, we found that on chest radiograph, consolidation was more frequently reported than GGOs (46.9%, 95% CI: 29.7-64.9% vs.

38.78%, 95% CI: 22.2-58.3). Pooled prevalence of nodules, halo sign, crazy-paving, lymphadenopathy, and pleural effusion was also reported. Sensitivity, specificity, and diagnostic odds ratio could not be evaluated due to the paucity of studies specifically reporting these findings.

A few previous systematic reviews and meta-analyses have investigated the imaging findings in COVID-19 pneumonia (14) (15) (16) (17) . In the meta-analysis by the Cao Y et al., the clinical and imaging findings from 31 studies were reported. Bilateral pneumonia was the most common finding (14) . Among the specific imaging findings, GGOs was respectively. This study did not report other findings, and meta-analysis was not performed. In the meta-analysis by Xu B et al., data from 16 studies comprising 3186 patients was included (18) . The authors reported the overall diagnostic accuracy of CT J o u r n a l P r e -p r o o f Journal Pre-proof rather than the individual CT findings. The pooled sensitivity of CT was reported to be 92% while the pooled specificity was reported for only two studies (33% and 25%) (18) .

Our study is the one of the most updated and recent meta-analysis, including the studies published in English as well as non-English literature. We reported most of the findings recommended by the Radiological Society of North America in the context of COVID-19 pneumonia (75) . We purposely excluded the case reports and smaller case series (<10 subjects) to avoid misinterpretation of the data.

There were a few limitations to our study. First, we evaluated the findings of only the baseline CT scan and chest radiograph, and so could not assess the pattern of disease progression. However, the inclusion of a baseline CT scan matches well with the primary aim of our meta-analysis. Second, most of the studies were retrospective and included patients with varying degrees of disease severity. Thus, the results of our meta-analysis need to be reviewed carefully. Prospective and systematically conducted studies will strengthen our observations. However, considering the pandemic nature and global impact of this highly infectious viral disease, we believe that our results are timely and highly relevant despite these limitations. GGO: ground glass opacity; CI: confidence interval, DOR: diagnostic odds ratio, AUC: area under the curve, *-Diagnostic accuracy meta-analysis not performed due to limited number of studies reporting these findings Figure 1 : Flowchart of study inclusion. 

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