The value of chest CT as a COVID-19 screening tool in children.
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ABSTRACT:
SUBMITTER: Merkus PJFM
PROVIDER: S-EPMC7236836 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Publications
The value of chest CT as a COVID-19 screening tool in children.
Merkus Peter J F M PJFM Klein Willemijn M WM
The European respiratory journal 20200625 6
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Project description:Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and early screening is one of the key factors for COVID-19 control and treatment. Here, we developed and validated chest CT-based imaging biomarkers for COVID-19 patient screening from two independent hospitals with 419 patients. We identified the vasculature-like signals from CT images and found that, compared to healthy and community acquired pneumonia (CAP) patients, COVID-19 patients display a significantly higher abundance of these signals. Furthermore, unsupervised feature learning led to the discovery of clinical-relevant imaging biomarkers from the vasculature-like signals for accurate and sensitive COVID-19 screening that have been double-blindly validated in an independent hospital (sensitivity: 0.941, specificity: 0.920, AUC: 0.971, accuracy 0.931, F1 score: 0.929). Our findings could open a new avenue to assist screening of COVID-19 patients.
| S-EPMC9533142 | biostudies-literature
Project description:Aim: Pulmonary disease burden and biomarkers are possible predictors of outcomes in patients with COVID-19 and provide complementary information. In this study, the prognostic value of adding quantitative chest computed tomography (CT) to a multiple biomarker approach was evaluated among 148 hospitalized patients with confirmed COVID-19. Materials & methods: Patients admitted between March and July 2020 who were submitted to chest CT and biomarker measurement (troponin I, D-dimer and C-reactive protein) were retrospectively analyzed. Biomarker and tomographic data were compared and associated with death and intensive care unit admission. Results: The number of elevated biomarkers was significantly associated with greater opacification percentages, lower lung volumes and higher death and intensive care unit admission rates. Total lung volume <3.0 l provided further stratification for mortality when combined with biomarker evaluation. Conclusion: Adding automated CT data to a multiple biomarker approach may provide a simple strategy for enhancing risk stratification of patients with COVID-19.
| S-EPMC8855956 | biostudies-literature
Project description:Background The standard for diagnosis of SARS-CoV-2 virus is reverse transcription polymerase chain reaction (RT-PCR) test, but chest CT may play a complimentary role in the early detection of COVID-19 pneumonia. Purpose To investigate CT features of patients with COVID-19 in Rome, Italy, and to compare the accuracy of CT with RT-PCR. Methods In this prospective study from March 4, 2020, until March 19, 2020, consecutive patients with suspected COVID-19 infection and respiratory symptoms were enrolled. Exclusion criteria were: chest CT with contrast medium performed for vascular indications, patients who refused chest CT or hospitalization, and severe CT motion artifact. All patients underwent RT-PCR and chest CT. Diagnostic performance of CT was calculated using RT-PCR as reference. Chest CT features were calculated in a subgroup of RT-PCR-positive and CT-positive patients. CT features of hospitalized patients and patient in home isolation were compared by using Pearson chi squared test. Results Our study population comprised 158 consecutive study participants (83 male and 75 female, mean age 57 y ±17). Fever was observed in 97/158 (61%), cough in 88/158 (56%), dyspnea in 52/158 (33%), lymphocytopenia in 95/158 (60%), increased C-reactive protein level in 139/158 (88%), and elevated lactate dehydrogenase in 128/158 (81%) study participants. Sensitivity, specificity, and accuracy of CT were 97% (60/62)[95% IC, 88-99%], 56% (54/96)[95% IC,45-66%] and 72% (114/158)[95% IC 64-78%], respectively. In the subgroup of RT-PCR-positive and CT-positive patients, ground-glass opacities (GGO) were present in 58/58 (100%), multilobe and posterior involvement were both present in 54/58 (93%), bilateral pneumonia in 53/58 (91%), and subsegmental vessel enlargement (> 3 mm) in 52/58 (89%) of study participants. Conclusion The typical pattern of COVID-19 pneumonia in Rome, Italy, was peripherally ground-glass opacities with multilobe and posterior involvement, bilateral distribution, and subsegmental vessel enlargement (> 3 mm). Chest CT sensitivity was high (97%) but with lower specificity (56%).
| S-EPMC7194020 | biostudies-literature
Project description:Since December 2019, the novel coronavirus disease (COVID-19) has spread rapidly throughout China. This article reviews the chest CT features of COVID-19 and analyzes the role of chest CT in this health emergency.
| S-EPMC7162628 | biostudies-literature
Project description:Computed tomography (CT) of the chest is one of the main diagnositic tools for coronavirus disease 2019 (COVID-19) infection. To document the chest CT findings in patients with confirmed COVID-19 and their association with the clinical severity, we searched related literatures through PubMed, MEDLINE, Embase, Web of Science (inception to May 4, 2020) and reviewed reference lists of previous systematic reviews. A total of 31 case reports (3768 patients) on CT findings of COVID-19 were included. The most common comorbid conditions were hypertension (18.4%) and diabetes mellitus (8.3%). The most common symptom was fever (78.7%), followed by cough (60.2%). It took an average of 5.6 days from symptom onset to admission. The most common chest CT finding was vascular enlargement (84.8%), followed by ground-glass opacity (GGO) (60.1%), air-bronchogram (47.8%), and consolidation (41.4%). Most lung lesions were located in the lung periphery (72.2%) and involved bilateral lung (76%). Most patients showed normal range of laboratory findings such as white blood cell count (96.4%) and lymphocyte (87.2%). Compared to previous published meta-analyses, our study is the first to summarize the different radiologic characteristics of chest CT in a total of 3768 COVID-19 patients by compiling case series studies. A comprehensive diagnostic approach should be adopted for patients with known COVID-19, suspected cases, and for exposed individuals.
| S-EPMC8436104 | biostudies-literature
Project description:INTRODUCTION:COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. MATERIALS AND METHODS:From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p?<?0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis. RESULTS:Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66?±?16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63?±?15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55?±?0.26L vs 0.43?±?0.23L, p?=?0.0005) and fibrotic alterations (0.05?±?0.03 L vs 0.04?±?0.03 L, p?<?0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p?<?0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p?<?0.001), respectively. CONCLUSIONS:Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.
| S-EPMC7548413 | biostudies-literature
Project description: Not available
| S-EPMC7267478 | biostudies-literature
Project description:PurposeTo compare the diagnostic performance and inter-observer agreement of five different CT chest severity scoring systems for COVID-19 to find the most precise one with the least interpretation time.Methods and materialsThis retrospective study included 85 patients (54 male and 31 female) with PCR-confirmed COVID-19. They underwent CT to assess the severity of pulmonary involvement. Three readers were asked to assess the pulmonary abnormalities and score the severity using five different systems, including chest CT severity score (CT-SS), chest CT score, total severity score (TSS), modified total severity score (m-TSS), and 3-level chest CT severity score. Time consumption on reporting of each system was calculated.ResultsTwo hundred fifty-five observations were reported for each system. There was a statistically significant inter-observer agreement in assessing qualitative lung involvement using the m-TSS and the other four quantitative systems. The ROC curves revealed excellent and very good diagnostic accuracy for all systems when cutoff values for detection severe cases were > 22, > 17, > 12, and > 26 for CT-SS, chest CT score, TSS, and 3-level CT severity score. The AUC was very good (0.86), excellent (0.90), very good (0.89), and very good (0.86), respectively. Chest CT score showed the highest specificity (95.2%) in discrimination of severe cases. Time consumption on reporting was significantly different (< 0.001): CT-SS > 3L-CT-SS > chest CT score > TSS.ConclusionAll chest CT severity scoring systems in this study demonstrated excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. CT-SS and TSS had the highest specificity and least time for interpretation.Key points• All chest CT severity scoring systems discussed in this study revealed excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. • Chest CT scoring system and TSS had the highest specificity. • Both TSS and m-TSS consumed the least time compared to the other three scoring systems.
| S-EPMC8760133 | biostudies-literature
Project description:PURPOSE:To assess the prognostic value of pneumonia severity score (PSS), pectoralis muscle area (PMA), and index (PMI) on chest computed tomography (CT) in adult coronavirus disease 2019 (COVID-19) patients. METHOD:The chest CT images of COVID-19 patients were evaluated for the PSS as the ratio of the volume of involved lung parenchyma to the total lung volume. The cross-sectional areas of the pectoralis muscles (PMA, cm2) were also measured automatically on axial CT images, and PMI was calculated as the following formula: PMI?=?PMA / patient's height square (m2). The relationship between clinical variables, PSS, PMA, sex-specific PMI values, and patient outcomes (intubation, prolonged hospital stay, and death) were investigated using multivariable logistic regression analysis. All patients were followed for more than a month. RESULTS:One-hundred thirty patients (76 males, 58.46 %) were included in the study. Fifteen patients (11.54 %) were intubated, 24 patients (18.46 %) had prolonged hospital stay, and eight patients (6.15 %) died during follow-up. Patients with comorbidity had a higher mean of PSS (6.3 + 4.5 vs 3.9 + 3.8; p?=?0.001). After adjusting the confounders, PSS was an independent predictor of intubation (adjusted Odds Ratio [OR]: 1.73, 95 % CI 1.31-2.28, p?<?0.001), prolonged hospital stay (OR: 1.20, 95 % CI 1.09-1.33, p?<?0.001), and death (OR: 2.13, 95 % CI 1.1-4.13, p?=?0.026. PMI value was a predictor of prolonged hospital stay (OR: 0.83, 95 % CI 0.72-0.96, p?=?0.038) and death (OR: 0.53, 95 % CI 0.29-0.96, p?=?0.036). Incrementally increasing PMA value was a predictor of prolonged hospital stay (OR: 0.93, 95 % CI 0.89-0.98, p?=?0.01) and intubation (OR: 0.98, 95 % CI 0.96-1, p?=?0.036). CONCLUSION:PSS, PMA, and PMI values have prognostic value in adult COVID-19 patients and can be easily assessed on chest CT images.
| S-EPMC7480333 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) is caused by a coronavirus family member known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The main laboratory test to confirm the quick diagnosis of COVID-19 infection is reverse transcription-polymerase chain reaction (RT-PCR) based on nasal or throat swab sampling. A small percentage of false-negative RT-PCR results have been reported. The RT-PCR test has a sensitivity of 50-72%, which could be attributed to a low viral load in test specimens or laboratory errors. In contrast, chest CT has shown 56-98% of sensitivity in diagnosing COVID-19 at initial presentation and has been suggested to be useful in correcting false negatives from RT-PCR. Chest X-rays and CT scans have been proposed to predict COVID-19 disease severity by displaying the score of lung involvement and thus providing information about the diagnosis and prognosis of COVID-19 infection. As a result, the current study provides a comprehensive overview of the utility of the severity score index using X-rays and CT scans in diagnosing patients with COVID-19 when compared to RT-PCR.
| S-EPMC9877460 | biostudies-literature