Chest CT versus RT-PCR for the detection of COVID-19: systematic review and meta-analysis of comparative studies.
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ABSTRACT: Objectives
To compare the performance of chest computed tomography (CT) scan versus reverse transcription polymerase chain reaction (RT-PCR) as the reference standard in the initial diagnostic assessment of coronavirus disease 2019 (COVID-19) patients.Design
A systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A search of electronic information was conducted using the following databases: MEDLINE, EMBASE, EMCARE, CINAHL and the Cochrane Central Register of Controlled Trials.Setting
Studies that compared the diagnostic performance within the same patient cohort of chest CT scan versus RT-PCR in COVID-19 suspected patients.Participants
Thirteen non-randomised studies enrolling 4092 patients were identified.Main outcome measures
Sensitivity, specificity and accuracy were primary outcome measures. Secondary outcomes included other test performance characteristics and discrepant findings between both investigations.Results
Chest CT had a median sensitivity, specificity and accuracy of 0.91 (range 0.82-0.98), 0.775 (0.25-1.00) and 0.87 (0.68-0.99), respectively, with RT-PCR as the reference. Importantly, early small, China-based studies tended to favour chest CT versus later larger, non-China studies.Conclusions
A relatively high false positive rate can be expected with chest CT. It is possible it may still be useful to provide circumstantial evidence, however, in some patients with a suspicious clinical presentation of COVID-19 and negative initial Severe Acute Respiratory Syndrome Coronavirus 2 RT-PCR tests, but more evidence is required in this context. In acute cardiorespiratory presentations, negative CT scan and RT-PCR tests is likely to be reassuring.
SUBMITTER: Karam M
PROVIDER: S-EPMC8127597 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Nowadays 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.
| S-EPMC7769992 | biostudies-literature
Project description:BackgroundOur hospital is a designated institution for COVID-19 patients in Chengdu, China. This study aimed to analyze the clinical and chest CT features of 15 COVID-19 patients with positive reverse transcription-polymerase chain reaction (RT-PCR) retest results after discharge. Patients who met the current standards of discharge could still carry the SARS-CoV-2 virus.MethodsClinical manifestations, laboratory data, and chest CT images were retrospectively reviewed and analyzed.ResultsThe most common symptoms at Covid-19COVID-19 initial onset were fever (12/15, 80%) and cough (11/15, 73.3%). Most of the patients had a normal white blood cells (12/15, 80%), neutrophils (12/15, 80%), and lymphocytes count (13/15, 86.7%); some patients had increased C-reactive protein (CRP) (5/15, 33.3%), and increased lactate dehydrogenase (LDH) (4/15, 26.7%) during first admission. Five patients (33.3%) had a cough before their first discharge. The average interval from the first discharge to re-admission was 17 days (range, 9–30 days). At re-admission, two (13.3%) patients presented with cough, and one (6.6%) had chest pain with anxiety. At re-admission, all patients had normal clinical results except five (33.3%) patients had increased CRP compared with first discharging, two (13.3%) patients had increased neutrophils count, and one (6.6%) had increased CRP. The majority of patients had normal procalcitonin. Ground glass opacities (GGOs) and reticulation in the peripheral and subpleural areas were the most common CT manifestations, and six patients (40%) showed a transformation from reticulation to GGOs when re-admitted.ConclusionsThere may be no specific clinical characteristics to predict the re-detectability of the virus. A regular medical observation and a bi-monthly follow-up is recommended.
| S-EPMC7276372 | biostudies-literature
Project description:BackgroundMany studies have described lung lesion computed tomography (CT) features of coronavirus disease 2019 (COVID-19) patients at the early and progressive stages. In this study, we aim to evaluate lung lesion CT radiological features along with quantitative analysis for the COVID-19 patients ready for discharge.MethodsFrom February 10 to March 10, 2020, 125 COVID-19 patients (age: 16–67 years, 63 males) ready for discharge, with two consecutive negative reverse transcription-polymerase chain reaction (RT-PCR) and no clinical symptoms for more than 3 days, were included. The pre-discharge CT was performed on all patients 1–3 days after the second negative RT-PCR test, and the follow-up CTs were performed on 44 patients 2–13 days later. The imaging features and quantitative analysis were evaluated on both the pre-discharge and the follow-up CTs, by both radiologists and an artificial intelligence (AI) software.ResultsOn the pre-discharge CT, the most common CT findings included ground-glass opacity (GGO) (99/125, 79.2%) with bilateral mixed distribution, and fibrosis (56/125, 44.8%) with bilateral subpleural distribution. Enlarged mediastinal lymph nodes were also commonly observed (45/125, 36.0%). AI enabled quantitative analysis showed the right lower lobe was mostly involved, and lesions most commonly had CT value of –570 to –470 HU consistent with GGO. Follow-up CT showed GGO decrease in size and density (40/40, 100%) and fibrosis reduction (17/26, 65.4%). Compared with the pre-discharge CT results, quantitative analysis shows the lung lesion volume regressed significantly at follow-up.ConclusionsFor COVID-19 patients ready for discharge, GGO and fibrosis are the main CT features and they further regress at follow-up.
| S-EPMC7276361 | biostudies-literature
Project description:Background Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19. Materials and Methods This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more. Results Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days ± 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days ± 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative. Conclusion Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ????? ????? ??? ????? ?? ?????? ?? ????? ????? ???.
| S-EPMC7233399 | biostudies-literature
Project description:OBJECTIVE:To determine the yield of preoperative screening for COVID-19 with chest CT and RT-PCR in patients without COVID-19 symptoms. SUMMARY OF BACKGROUND DATA:Many centers are currently screening surgical patients for COVID-19 using either chest CT, RT-PCR or both, due to the risk for worsened surgical outcomes and nosocomial spread. The optimal design and yield of such a strategy are currently unknown. METHODS:This multicenter study included consecutive adult patients without COVID-19 symptoms who underwent preoperative screening using chest CT and RT-PCR before elective or emergency surgery under general anesthesia. RESULTS:A total of 2093 patients without COVID-19 symptoms were included in 14 participating centers; 1224 were screened by CT and RT-PCR and 869 by chest CT only. The positive yield of screening using a combination of chest CT and RT-PCR was 1.5% [95% confidence interval (CI): 0.8-2.1]. Individual yields were 0.7% (95% CI: 0.2-1.1) for chest CT and 1.1% (95% CI: 0.6-1.7) for RT-PCR; the incremental yield of chest CT was 0.4%. In relation to COVID-19 community prevalence, up to ?6% positive RT-PCR was found for a daily hospital admission rate >1.5 per 100,000 inhabitants, and around 1.0% for lower prevalence. CONCLUSIONS:One in every 100 patients without COVID-19 symptoms tested positive for SARS-CoV-2 with RT-PCR; this yield increased in conjunction with community prevalence. The added value of chest CT was limited. Preoperative screening allowed us to take adequate precautions for SARS-CoV-2 positive patients in a surgical population, whereas negative patients needed only routine procedures.
| S-EPMC7668335 | biostudies-literature
Project description:BackgroundCharacteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated.PurposeWe aim to test whether chest CT manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system.MethodsWe conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI System, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney U test as appropriate.ResultsThe main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment.ConclusionWe documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.
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Project description:PurposePatients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic.Methods and materialsChest CT images were proposed during radiation therapy CT simulation. Images were reviewed by an expert radiologist according to the COVID-19 Reporting and Data System classification. Nasal swabs with RT-PCR assay were initially proposed in cases of suspicious imaging or clinical context and were eventually integrated into the systematic screening. A dedicated radiation therapy workflow was proposed for COVID-19 patients to limit the risk of contamination.ResultsFrom March 18, 2020 to May 1, 2020, 480 patients were screened by chest CT, and 313 patients had both chest CT and RT-PCR (65%). The cumulative incidence of COVID-19 was 5.4% (95% confidence interval [CI], 3.6-7.8; 26 of 480 patients). Diagnosis of COVID-19 was made before radiation therapy for 22 patients (84.6%) and during RT for 4 patients (15.3%). Chest CT directly aided the diagnosis of 7 cases in which the initial RT-PCR was negative or not feasible, out of a total of 480 patients (1.5%) and 517 chest CT acquisitions. Four patients with COVID-19 at the time of the chest CT screening had a false negative CT. Sensitivity and specificity of chest CT screening in patients with both RT-PCR and chest CT testing were estimated at 0.82 (95% CI, 0.60-0.95) and 0.98 (95% CI, 0.96-0.99), respectively. Adaptation of the radiation therapy treatment was made for all patients, with 7 postponed treatments (median: 5 days; interquartile range, 1.5-14.8).ConclusionsThe benefit of systematic use of chest CT screening during CT simulation for patients undergoing radiation therapy during the COVID-19 pandemic seemed limited.
| S-EPMC7887448 | biostudies-literature
Project description:This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus disease (COVID-19). The novelty of this work is in the introduction of optimized InceptionResNetV2 for COVID-19 (CO-IRv2) method. A part of the CO-IRv2 scheme is derived from the concepts of InceptionNet and ResNet with hyperparameter tuning, while the remaining part is a new architecture consisting of a global average pooling layer, batch normalization, dense layers, and dropout layers. The proposed CO-IRv2 is applied to a new dataset of 2481 computed tomography (CT) images formed by collecting two independent datasets. Data resizing and normalization are performed, and the evaluation is run up to 25 epochs. Various performance metrics, including precision, recall, accuracy, F1-score, area under the receiver operating characteristics (AUC) curve are used as performance metrics. The effectiveness of three optimizers known as Adam, Nadam and RMSProp are evaluated in classifying suspected COVID-19 patients and normal people. Results show that for CO-IRv2 and for CT images, the obtained accuracies of Adam, Nadam and RMSProp optimizers are 94.97%, 96.18% and 96.18%, respectively. Furthermore, it is shown here that for the case of CT images, CO-IRv2 with Nadam optimizer has better performance than existing DL algorithms in the diagnosis of COVID-19 patients. Finally, CO-IRv2 is applied to an X-ray dataset of 1662 images resulting in a classification accuracy of 99.40%.
| S-EPMC8553063 | biostudies-literature
Project description:ObjectiveAimed to summarize the characteristics of chest CT imaging in Chinese hospitalized patients with Coronavirus Disease 2019 (COVID-19) to provide reliable evidence for further guiding clinical routine.MethodsPubMed, Embase and Web of Science databases were searched to identify relevant articles involving the features of chest CT imaging in Chinese patients with COVID-19. All data were analyzed utilizing R i386 4.0.0 software. Random-effects models were employed to calculate pooled mean differences.Results19 retrospective studies (1332 cases) were included. The results demonstrated that the combined proportion of ground-glass opacities (GGO) was 0.79 (95% CI 0.68, 0.89), consolidation was 0.34 (95% CI 0.23, 0.47); mixed GGO and consolidation was 0.46 (95% CI 0.37; 0.56); air bronchogram sign was 0.41 (95% CI 0.26; 0.55); crazy paving pattern was 0.32 (95% CI 0.17, 0.47); interlobular septal thickening was 0.55 (95% CI 0.42, 0.67); reticulation was 0.30 (95% CI 0.12, 0.48); bronchial wall thickening was 0.24 (95% CI 0.11, 0.40); vascular enlargement was 0.74 (95% CI 0.64, 0.86); subpleural linear opacity was 0.28 (95% CI 0.12, 0.48); intrathoracic lymph node enlargement was 0.03 (95% CI 0.00, 0.07); pleural effusions was 0.03 (95% CI 0.02, 0.06). The distribution in lung: the combined proportion of central was 0.05 (95% CI 0.01, 0.11); peripheral was 0.74 (95% CI 0.62, 0.84); peripheral involving central was 0.38 (95% CI 0.19, 0.75); diffuse was 0.19 (95% CI 0.06, 0.32); unifocal involvement was 0.09 (95% CI 0.05, 0.14); multifocal involvement was 0.57 (95% CI 0.48, 0.68); unilateral was 0.16 (95% CI 0.10, 0.23); bilateral was 0.83 (95% CI 0.78, 0.89); The combined proportion of lobes involved (> 2) was 0.70 (95% CI 0.61, 0.78); lobes involved (≦ 2) was 0.35 (95% CI 0.26, 0.44).ConclusionGGO, vascular enlargement, interlobular septal thickening more frequently occurred in patients with COVID-19, which distribution features were peripheral, bilateral, involved lobes > 2. Therefore, based on chest CT features of COVID-19 mentioned, it might be a promising means for identifying COVID-19.
| S-EPMC7576554 | biostudies-literature
Project description:Background COVID-19 was discovered in February in China. Due to the high prevalence of the disease, early detection and rapid isolation of patients are the vital points for controlling the outbreak. The purpose of this study was to determine the correct location of chest CT scan in the diagnosis of COVID-19. Main text The current study is a systematic review and meta-analysis. 2959 papers were found in all national and international databases. The study has been reported based on the PRISMA checklist. All analyses were done by CMA Ver. 2 software. The statistical analysis results show that the GGO observation level in the available shape was 46% in CT scan results, and the consolidation observation level in the general form was 33% in CT scan results. Pleural effusion was 7%, and linear opacity observation level was 24% in CT scan results in the general form. The CT scan test sensitivity level was gained 94.7%, and PCR test sensitivity level was achieved as 94.8%. This level was 89% in the early stage. Conclusion The chest CT has about 24% higher diagnostic sensitivity than the PCR test, in the early stage. GGO revealed a declining process and also indicates that GGO is an early symptom of the disease in CT scan. Linear opacity is the reason behind the initial dyspnea in coronavirus suffering patients referring to the medical centers. The extra-pulmonary lesions increase in the last stage of the disease that makes the patient’s worse. Supplementary Information The online version contains supplementary material available at 10.1186/s43055-021-00457-6.
| S-EPMC7992511 | biostudies-literature