Diagnostic performance of CT and its key signs for COVID-19: A systematic review and meta-analysis

AbstractPurposeTo evaluate the diagnostic value of chest CT in 2019 novel coronavirus disease (COVID-19), using the reverse transcription polymerase chain reaction (RT-PCR) as a reference standard. At the same time, the imaging features of CT in confirmed COVID-19 patients would be summarized.MethodsA comprehensive literature search of 5 electronic databases was performed. The pooled sensitivity, specificity, positive predictive value, and negative predictive value were calculated using the random-effects model and the summary receiver operating characteristic (SROC) curve. We also conducted a meta-analysis to estimate the pooled incidence of the chest CT imaging findings and the 95% confidence interval (95%CI). Meta-regression analysis was used to explore the source of heterogeneity.ResultsOverall, 25 articles comprising 4,857 patients were included. The pooled sensitivity of CT was 93% (95% CI, 89-96%) and specificity was 44% (95% CI, 27-62%). The area under the SROC curve was 0.94 (95% CI, 0.91-0.96). For the RT-PCR assay, the pooled sensitivity of the initial test and the missed diagnosis rate after the second-round test were 76% (95% CI: 59-89%; I2=96%) and 26% (95% CI: 14-39%; I2=45%), respectively. According to the subgroup analysis, the diagnostic sensitivity of CT in Hubei was higher than that in other regions. Besides, the most common patterns on CT imaging finding was ground glass opacities (GGO) 58% (95% CI: 49-70%), followed by air bronchogram 51% (95% CI: 31-70%). Lesions were inclined to distribute in peripheral 64% (95% CI: 49-78%), and the incidence of bilateral lung involvement was 69% (95% CI: 58-79%).ConclusionsThere were still several cases of missed diagnosis after multiple RT-PCR examinations. In high-prevalence areas, CT could be recommended as an auxiliary screening method for RT-PCR.Key pointsTaking RT-PCR as the reference standard, the pooled sensitivity of CT was 93% (95% CI, 89-96%) and the specificity was 44% (95% CI, 27-62%). The area under the SROC curve was 0.94 (95% CI, 0.91-0.96).For the RT-PCR assay, the pooled sensitivity of the initial test and the missed diagnosis rate after the second-round test were 76% (95% CI: 59-89%) and 26% (95% CI: 14-39%), respectively.GGO was the key sign of the CT imaging, with an incidence of 58% (95% CI: 49-70%) in patients with SARS-CoV-2 infection. Pneumonia lesions were inclined to distribute in peripheral 64% (95% CI: 49-78%) and bilateral 69% (95% CI: 58-79%) lung lobes.

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A meta-analysis of accuracy and sensitivity of chest CT and RT-PCR in COVID-19 diagnosis

Scientific Reports ◽

10.1038/s41598-020-80061-2 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Fatemeh Khatami ◽

Mohammad Saatchi ◽

Seyed Saeed Tamehri Zadeh ◽

Zahra Sadat Aghamir ◽

Alireza Namazi Shabestari ◽

...

Keyword(s):

Polymerase Chain Reaction ◽

Reverse Transcriptase ◽

Ct Scan ◽

Predictive Value ◽

Meta Analysis ◽

Chest Ct ◽

Rt Pcr ◽

Chain Reaction ◽

Polymerase Chain ◽

Chest Ct Scan

AbstractNowadays there is an ongoing acute respiratory outbreak caused by the novel highly contagious coronavirus (COVID-19). The diagnostic protocol is based on quantitative reverse-transcription polymerase chain reaction (RT-PCR) and chests CT scan, with uncertain accuracy. This meta-analysis study determines the diagnostic value of an initial chest CT scan in patients with COVID-19 infection in comparison with RT-PCR. Three main databases; PubMed (MEDLINE), Scopus, and EMBASE were systematically searched for all published literature from January 1st, 2019, to the 21st May 2020 with the keywords "COVID19 virus", "2019 novel coronavirus", "Wuhan coronavirus", "2019-nCoV", "X-Ray Computed Tomography", "Polymerase Chain Reaction", "Reverse Transcriptase PCR", and "PCR Reverse Transcriptase". All relevant case-series, cross-sectional, and cohort studies were selected. Data extraction and analysis were performed using STATA v.14.0SE (College Station, TX, USA) and RevMan 5. Among 1022 articles, 60 studies were eligible for totalizing 5744 patients. The overall sensitivity, specificity, positive predictive value, and negative predictive value of chest CT scan compared to RT-PCR were 87% (95% CI 85–90%), 46% (95% CI 29–63%), 69% (95% CI 56–72%), and 89% (95% CI 82–96%), respectively. It is important to rely on the repeated RT-PCR three times to give 99% accuracy, especially in negative samples. Regarding the overall diagnostic sensitivity of 87% for chest CT, the RT-PCR testing is essential and should be repeated to escape misdiagnosis.

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The role of CT imaging for management of COVID-19 in epidemic area: early experience from a University Hospital

Insights into Imaging ◽

10.1186/s13244-020-00957-5 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Vikram rao Bollineni ◽

Koenraad Hans Nieboer ◽

Seema Döring ◽

Nico Buls ◽

Johan de Mey

Keyword(s):

Ct Scan ◽

Predictive Value ◽

Ct Imaging ◽

Chest Ct ◽

University Hospital ◽

Rt Pcr ◽

Ct Findings ◽

Epidemic Area ◽

Chest Ct Scan ◽

Pcr Test

Abstract Background To evaluate the clinical value of the chest CT scan compared to the reference standard real-time polymerase chain reaction (RT-PCR) in COVID-19 patients. Methods From March 29th to April 15th of 2020, a total of 240 patients with respiratory distress underwent both a low-dose chest CT scan and RT-PCR tests. The performance of chest CT in diagnosing COVID-19 was assessed with reference to the RT-PCR result. Two board-certified radiologists (mean 24 years of experience chest CT), blinded for the RT-PCR result, reviewed all scans and decided positive or negative chest CT findings by consensus. Results Out of 240 patients, 60% (144/240) had positive RT-PCR results and 89% (213/240) had a positive chest CT scans. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of chest CT in suggesting COVID-19 were 100% (95% CI: 97–100%, 144/240), 28% (95% CI: 19–38%, 27/240), 68% (95% CI: 65–70%) and 100%, respectively. The diagnostic accuracy of the chest CT suggesting COVID-19 was 71% (95% CI: 65–77%). Thirty-three patients with positive chest CT scan and negative RT-PCR test at baseline underwent repeat RT-PCR assay. In this subgroup, 21.2% (7/33) cases became RT-PCR positive. Conclusion Chest CT imaging has high sensitivity and high NPV for diagnosing COVID-19 and can be considered as an alternative primary screening tool for COVID-19 in epidemic areas. In addition, a negative RT-PCR test, but positive CT findings can still be suggestive of COVID-19 infection.

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The exact place of PCR and chest CT in screening, staging, and diagnosis of Covid-19: A meta-analysis

10.21203/rs.3.rs-32961/v1 ◽

2020 ◽

Author(s):

Fatemeh Khatami ◽

Mohammad Saatchi ◽

Seyed Saeed Tamehri Zadeh ◽

Zahra Sadat Aghamir ◽

Alireza Namazi Shabestari ◽

...

Keyword(s):

Polymerase Chain Reaction ◽

Reverse Transcriptase ◽

Ct Scan ◽

Predictive Value ◽

Meta Analysis ◽

Chest Ct ◽

Rt Pcr ◽

Chain Reaction ◽

Polymerase Chain ◽

Chest Ct Scan

Abstract Introduction: Nowadays there is an ongoing acute respiratory outbreak causing by the novel highly contagious coronavirus (nCoV). There are two diagnostic protocol based on chest CT scan and quantitative reverse-transcription polymerase chain reaction (RT-PCR) which their diagnostic accuracy is under the debate. We designed this meta-analysis study to determine the diagnostic value of initial chest CT scan in patients with nCoV infection in comparison with RT- PCR.Search strategy and statistical analysis: Three main databases the PubMed (MEDLINE), Scopus, and EMBASE was systematically searched for all published literatures from January 1st, 2019, to the 27th march 2020 with key grouping of “COVID19 virus”, “2019 novel coronavirus”, “Wuhan coronavirus”, “2019-nCoV”, “X-Ray Computed Tomography”, “Polymerase Chain Reaction”, “Reverse Transcriptase PCR”, and “PCR Reverse Transcriptase”. All relevant case- series, cross-sectional, and cohort studies were selected. Data extraction was done in Excel 2007 (Microsoft Corporation, Redmond, CA) and their analysis was performed using STATA v.14.0SE (College Station, TX, USA) and RevMan 5.Result: From first recruited 668 articles we end up to the final 47 studies, which comprised a total sample size of 4238 patients. In compare to RT-PCR, the overall sensitivity, specificity, positive predictive value, and negative predictive value of chest CT scan were 86% (95% CI: 83% -90%), 43 % (95% CI: 26% -60%), 67% (95% CI: 57% -78%), and 84% (95% CI: 74% -95%) respectively. However the RT-PCR should be repeated for three times in order to give the 99% accuracy especially in negative samples.Conclusion: According to the acceptable sensitivity of chest CT scan, it can be employed complement to RT-PCR to diagnosis patients who are clinically suspicious for nCoV.

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COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest CT Images

Frontiers in Medicine ◽

10.3389/fmed.2020.608525 ◽

2020 ◽

Vol 7 ◽

Author(s):

Hayden Gunraj ◽

Linda Wang ◽

Alexander Wong

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Network Architecture ◽

Ct Images ◽

Ct Imaging ◽

Chest Ct ◽

Deep Convolutional Neural Network ◽

Screening Tools ◽

Screening Methods ◽

Rt Pcr

The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease, there is a pressing need for rapid and effective screening tools to identify patients infected with COVID-19, and to this end CT imaging has been proposed as one of the key screening methods which may be used as a complement to RT-PCR testing, particularly in situations where patients undergo routine CT scans for non-COVID-19 related reasons, patients have worsening respiratory status or developing complications that require expedited care, or patients are suspected to be COVID-19-positive but have negative RT-PCR test results. Early studies on CT-based screening have reported abnormalities in chest CT images which are characteristic of COVID-19 infection, but these abnormalities may be difficult to distinguish from abnormalities caused by other lung conditions. Motivated by this, in this study we introduce COVIDNet-CT, a deep convolutional neural network architecture that is tailored for detection of COVID-19 cases from chest CT images via a machine-driven design exploration approach. Additionally, we introduce COVIDx-CT, a benchmark CT image dataset derived from CT imaging data collected by the China National Center for Bioinformation comprising 104,009 images across 1,489 patient cases. Furthermore, in the interest of reliability and transparency, we leverage an explainability-driven performance validation strategy to investigate the decision-making behavior of COVIDNet-CT, and in doing so ensure that COVIDNet-CT makes predictions based on relevant indicators in CT images. Both COVIDNet-CT and the COVIDx-CT dataset are available to the general public in an open-source and open access manner as part of the COVID-Net initiative. While COVIDNet-CT is not yet a production-ready screening solution, we hope that releasing the model and dataset will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon them.

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Structured reporting of chest CT provides high sensitivity and specificity for early diagnosis of COVID-19 in a clinical routine setting

British Journal of Radiology ◽

10.1259/bjr.20200574 ◽

2021 ◽

Vol 94 (1117) ◽

pp. 20200574

Author(s):

Alexander Gross ◽

Georg Heine ◽

Martin Schwarz ◽

Dorina Thiemig ◽

Sven Gläser ◽

...

Keyword(s):

Early Diagnosis ◽

Predictive Value ◽

High Sensitivity ◽

Pulmonary Involvement ◽

Chest Ct ◽

Structured Reporting ◽

Rt Pcr ◽

Clinical Routine ◽

Dominant Feature ◽

Routine Clinical Setting

Objectives: Although chest CT has been widely used in patients with COVID-19, its role for early diagnosis of COVID-19 is unclear. We report the diagnostic performance of chest CT using structured reporting in a routine clinical setting during the early phase of the epidemic in Germany. Methods: Patients with clinical suspicion of COVID-19 and moderate-to-severe symptoms were included in this retrospective study. CTs were performed and reported before RT-PCR results (reference standard) became available. A structured reporting system was used that concluded in a recently described five-grade score (“CO-RADS”), indicating the level of suspicion for pulmonary involvement of COVID-19 from 1 = very low to 5 = very high. Structured reporting was performed by three Radiologists in consensus. Results: In 96 consecutive patients (50 male, mean age 64), RT-PCR was positive in 20 (21%) cases. CT features significantly more common in RT-PCR-positive patients were ground-glass opacities as dominant feature, crazy paving, hazy margins of opacities, and multifocal bilateral distribution (p < 0.05). Using a cut-off point between CO-RADS 3 and 4, sensitivity was 90%, specificity 91%, positive predictive value 72%, negative predictive value 97%, and accuracy 91%. ROC analysis showed an AUC of 0.938. Conclusions: Structured reporting of chest CT with a five-grade scale provided accurate diagnosis of COVID-19. Its use was feasible and helpful in clinical routine. Advances in knowledge: Chest CT with structured reporting may be a provisional diagnostic alternative to RT-PCR testing for early diagnosis of COVID-19, especially when RT-PCR results are delayed or test capacities are limited.

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Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis

Diagnostics ◽

10.3390/diagnostics10121023 ◽

2020 ◽

Vol 10 (12) ◽

pp. 1023

Author(s):

Temitope Emmanuel Komolafe ◽

John Agbo ◽

Ebenezer Obaloluwa Olaniyi ◽

Kayode Komolafe ◽

Xiaodong Yang

Keyword(s):

Computed Tomography ◽

Meta Analysis ◽

Age Groups ◽

Disease Prevalence ◽

Chest Ct ◽

Imaging Features ◽

Rt Pcr ◽

Chest Computed Tomography ◽

Pooled Prevalence ◽

History Of

Background: The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients’ biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Objectives: To perform a meta-analysis to evaluate the diagnostic performance of chest CT, common CT morphological abnormalities, disease prevalence, biodata information, and gender prevalence of patients. Methods: Studies were identified by searching PubMed and Science Direct libraries from 1 January 2020 to 30 April 2020. Pooled CT positive rate of COVID-19 and RT-PCR, CT-imaging features, history of exposure, and biodata information were estimated using the quality effect (QE) model. Results: Out of 36 studies included, the sensitivity was 89% (95% CI: 80–96%) and 98% (95% CI: 90–100%) for chest CT and reverse transcription-polymerase chain reaction (RT-PCR), respectively. The pooled prevalence across lesion distribution were 72% (95% CI: 62–80%), 92% (95% CI: 84–97%) for lung lobe, 88% (95% CI: 81–93%) for patients with history of exposure, and 91% (95% CI: 85–96%) for patients with all categories of symptoms. Seventy-six percent (95% CI: 67–83%) had age distribution across four age groups, while the pooled prevalence was higher in the male with 54% (95% CI: 50–57%) and 46% (95% CI: 43–50%) in the female. Conclusions: The sensitivity of RT-PCR was higher than chest CT, and disease prevalence appears relatively higher in the elderly and males than children and females, respectively.

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Diagnostic Accuracy of Rapid Antigen Detection Tests for Respiratory Syncytial Virus Infection: Systematic Review and Meta-analysis

Journal of Clinical Microbiology ◽

10.1128/jcm.01816-15 ◽

2015 ◽

Vol 53 (12) ◽

pp. 3738-3749 ◽

Cited By ~ 87

Author(s):

Caroline Chartrand ◽

Nicolas Tremblay ◽

Christian Renaud ◽

Jesse Papenburg

Keyword(s):

Systematic Review ◽

Respiratory Syncytial Virus ◽

Diagnostic Accuracy ◽

Sensitivity And Specificity ◽

Meta Analysis ◽

Reference Standard ◽

Rt Pcr ◽

Test Sensitivity ◽

Subgroup Analyses ◽

Syncytial Virus

Respiratory syncytial virus (RSV) rapid antigen detection tests (RADT) are extensively used in clinical laboratories. We performed a systematic review and meta-analysis to evaluate the accuracy of RADTs for diagnosis of RSV infection and to determine factors associated with accuracy estimates. We searched EMBASE and PubMed for diagnostic-accuracy studies of commercialized RSV RADTs. Studies reporting sensitivity and specificity data compared to a reference standard (reverse transcriptase PCR [RT-PCR], immunofluorescence, or viral culture) were considered. Two reviewers independently extracted data on study characteristics, diagnostic-accuracy estimates, and study quality. Accuracy estimates were pooled using bivariate random-effects regression models. Heterogeneity was investigated with prespecified subgroup analyses. Seventy-one articles met inclusion criteria. Overall, RSV RADT pooled sensitivity and specificity were 80% (95% confidence interval [CI], 76% to 83%) and 97% (95% CI, 96% to 98%), respectively. Positive- and negative-likelihood ratios were 25.5 (95% CI, 18.3 to 35.5) and 0.21 (95% CI, 0.18 to 0.24), respectively. Sensitivity was higher in children (81% [95% CI, 78%, 84%]) than in adults (29% [95% CI, 11% to 48%]). Because of this disparity, further subgroup analyses were restricted to pediatric data (63 studies). Test sensitivity was poorest using RT-PCR as a reference standard and highest using immunofluorescence (74% versus 88%;P< 0.001). Industry-sponsored studies reported significantly higher sensitivity (87% versus 78%;P= 0.01). Our results suggest that the poor sensitivity of RSV RADTs in adults may preclude their use in this population. Furthermore, industry-sponsored studies and those that did not use RT-PCR as a reference standard likely overestimated test sensitivity.

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Sequential battery of COVID-19 testing to maximize negative predictive value before surgeries

Revista do Colégio Brasileiro de Cirurgiões ◽

10.1590/0100-6991e-20202634 ◽

2020 ◽

Vol 47 ◽

Author(s):

NEERAJ SINHA ◽

GALIT BALAYLA

Keyword(s):

Immune Response ◽

Negative Predictive Value ◽

Predictive Value ◽

Chest Ct ◽

Viral Dynamics ◽

Rt Pcr ◽

Testing Methods ◽

Course Of Illness ◽

Epidemiologic Survey ◽

Novel Virus

ABSTRACT SARS-CoV-2 is a novel virus which has proven to be highly contagious. Specific viral dynamics and immune response to the virus are yet to be fully defined and determining the sensitivity and specificity of the available testing methods is still a work in progress. This study examines the published information on the testing methods, and finds that yield of COVID-19 tests changes with specimen types and with time through course of illness. We propose a sequential battery of testing consisting of an epidemiologic survey, RT-PCR tests, serologic tests and chest CT on surgical candidates which may increase the negative predictive value, and facilitate surgical procedures.

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Application of artificial intelligence image-assisted diagnosis system in chest CT examination of COVID-19

10.21203/rs.3.rs-31153/v1 ◽

2020 ◽

Author(s):

Mengqi Zhang ◽

Yangyang Wang ◽

Qianyun Ding ◽

Haiwen Li ◽

Fu Dai ◽

...

Keyword(s):

Artificial Intelligence ◽

Ct Scan ◽

Predictive Value ◽

False Positive ◽

Chest Ct ◽

True Positive ◽

Diagnosis System ◽

Ct Examination ◽

Missed Diagnosis ◽

Assisted Diagnosis

Abstract Purpose The purpose of this study is to evaluate the application efficiency of artificial intelligence (AI) image-assisted diagnosis system in chest CT examination of corona virus disease 2019 (COVID-19). Methods A total of 33 cases of COVID-19 patients who underwent chest CT in Hefei Binhu Hospital between January 2020 and March 2020 were retrospectively included. All patients were tested positive for novel coronavirus nucleic acid by fluorescent reverse transcription-polymerasechain reaction (RT-PCR). The pneumonia screening function of the AI image-assisted diagnosis system was employed for the 103 chest CT examinations of the 33 cases. The diagnosis of four senior radiologists were used as the standard for synchronous under blind state. The sensitivity, specificity, misdiagnosis rate, missed diagnosis rate and other evaluation indexes of the COVID-19 performed by the AI image-assisted diagnosis system were analyzed, and an dynamic evaluation on the CT reexamination was conducted. Results Out of the 103 chest CT examinations, there were 88 cases of true positive, 1 case of false positive, 12 cases of true negative and 2 cases of false negative. The sensitivity was 97.78% (88/90); the specificity was 92.31% (12/13); the positive predictive value was 98.88% (88/89); the negative predictive value was 85.71% (12/14); the accuracy was 97.09% (100/103); the Youden index was 90.09%; the positive likelihood ratio was 12.711 and the negative likelihood ratio was 0.024. There were 790 identified lesions in these CT examinations in total, of which 569 were true positive and 221 were false positive. There were also 64 missed diagnosis markers. The detection rate of all lesions was 89.89% and the rate of false positives was 27.97%. In the last CT scan, the lesion size were smaller and the percentage of lesions in total lung volume along with the mean density of lesions was lower than that of the first CT scan. Conclusion The AI image-assisted diagnosis system has certain clinical application value in the early diagnosis and follow-up evaluation of chest CT examination of COVID-19.

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Impact of COVID-19 pre-test probability on positive predictive value of high cycle threshold SARS-CoV-2 real-time reverse transcription PCR test results

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2021.369 ◽

2021 ◽

pp. 1-18

Author(s):

Jonathan B. Gubbay ◽

Heather Rilkoff ◽

Heather L. Kristjanson ◽

Jessica D. Forbes ◽

Michelle Murti ◽

...

Keyword(s):

Positive Predictive Value ◽

Real Time ◽

Reverse Transcription ◽

Predictive Value ◽

Large Scale ◽

Rdrp Gene ◽

Nucleic Acid Detection ◽

Rt Pcr ◽

Pcr Assay ◽

Test Probability

Abstract Objectives Performance characteristics of SARS-CoV-2 nucleic acid detection assays are understudied within contexts of low pre-test probability, including screening asymptomatic persons without epidemiological links to confirmed cases, or asymptomatic surveillance testing. SARS-CoV-2 detection without symptoms may represent presymptomatic or asymptomatic infection, resolved infection with persistent RNA shedding, or a false positive test. This study assessed positive predictive value of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) assays by retesting positive specimens from five pre-test probability groups ranging from high to low with an alternate assay. Methods A total of 122 rRT-PCR positive specimens collected from unique patients between March and July 2020 were retested using a laboratory-developed nested RT-PCR assay targeting the RNA-dependent RNA polymerase (RdRp) gene followed by Sanger sequencing. Results Significantly fewer (15.6%) positive results in the lowest pre-test probability group (facilities with institution-wide screening having ≤ 3 positive asymptomatic cases) were reproduced with the nested RdRp gene RT-PCR assay than in each of the four groups with higher pre-test probability (individual group range 50·0% to 85·0%). Conclusions Large-scale SARS-CoV-2 screening testing initiatives among low pre-test probability populations should be evaluated thoroughly prior to implementation given the risk of false positives and consequent potential for harm at the individual and population level.

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