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CT imaging features of 4121 patients with COVID-19: A meta-analysis
Abstract
Objective
We systematically reviewed the CT imaging features of COVID‐19 in order to provide reference for clinical practice.
Methods
Our article comprehensively searched PubMed, FMRS, EMbase, CNKI,WanFang databases and VIP databases to collect literatures about the CT imaging features of COVID‐19 from 1 January 2020 to 16 March 2020. Three reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, and then, this meta‐analysis was performed by using Stata12.0 software.
Results
34 retrospective studies involving a total of 4 121 COVID‐19 patients were included. The results of meta‐analysis showed that most patients presented bilateral lung involvement (73.8%, 95%CI: 65.9%‐81.1%) or multilobar involvement (67.3%,95%CI: 54.8%‐78.7 %) and just a little patients showed normal CT findings (8.4%). We found that the most common changes in lesion density was ground‐glass opacities (68.1%,95%CI: 56.9%‐78.2%). Other changes in density included air bronchogram sign(44.7%), crazy‐paving pattern (35.6%) and consolidation (32.0%). Patchy (40.3%), spider web sign (39.5%), cord‐like (36.8%) and nodular (20.5%) were common lesion shapes in COVID‐19 patients. Pleural thickening (27.1%) was found in some patients. Lymphadenopathy(5.4%) and pleural effusion (5.3%) were rare.
Conclusion
The lung lesions of patients with COVID‐19 were mostly bilateral lungs or multilobar involved. The most common chest CT findings were patchy and ground‐glass opacities. Some patients had air bronchogram, spider web sign and cord‐like. Lymphadenopathy and pleural effusion were rare.
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... Ground glass opacity has been depicted pictorially in [ Figures 1-3]. [11][12][13][14] ...
... Reverse batwing sign can be seen pictorially in Figure 9. [34] Pulmonary target sign The sign has been described as a central high attenuation focus surrounded by one or more dense complete or incomplete ring-like consolidation, forming one or more circles on chest CT in patients with COVID-19 pneumonia. [35] The Bao et al. [11] 83.31 Zhu et al. [12] 68.1 Ng et al. [13] 86 Guan et al. [14] 100 GGOs: Ground-glass opacities pathophysiology of this sign is that it is a manifestation of organizing pneumonia (OP). [36,37] The pulmonary target sign usually coexists with other typical OP features including the reverse halo or halo sign. ...
... Spider web sign is a common sign of COVID-19 pneumonia which represents subpleural, triangular residual opacity of resolving GGO with web-like thickening of the interlobular septa and thickened retraction adjacent pleura. [12,13] Spider web sign was reported from 39 to 45% of patients in various studies. Spider web sign has been shown in Figure 14. ...
... Particularly, the GGO was reported to be 77.2% [29], 83.3% [30], 78.0% [31], 68.1% [32], 68.0% [33], 71.7% [34], 79.0% [35], and 71.5% [36] in different meta-analyses. ...
... The consolidation pattern resulted similarly to the meta-analysis of Zhou et al. who reported a value of prevalence of consolidation pattern of 18% [33]. Instead, the other principal meta-analyses considered described a major prevalence between 33 and 44% [29][30][31][32][33][34][35][36]. ...
... This difference in the consolidation pattern might be due to the establishment of a "prevalent pattern," thanks to the segmentation. While the principal meta-analyses were often considered a "mixed-pattern" or coexistence of patterns [29][30][31][32][33][34]36], in this study the segmentation allowed a better pneumonia classification with the pattern mutual exclusion. ...
The National Health Systems have been severely stressed out by the COVID-19 pandemic because 14% of patients require hospitalization and oxygen support, and 5% require admission to an Intensive Care Unit (ICU). Relationship between COVID-19 prognosis and the extent of alterations on chest CT obtained by both visual and software-based quantification that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one has been proven. While commercial applications for automatic medical image computing and visualization are expensive and limited in their spread, the open-source systems are characterized by not enough standardization and time-consuming troubles. We analyzed chest CT exams on 246 patients suspected of COVID-19 performed in the Emergency Department CT room. The lung parenchyma segmentation was obtained by a threshold-based method using the open-source 3D Slicer software and software tools called “Segment Editor” and “Segment Quantification.” For the three main characteristics analyzed on lungs affected by COVID-19 pneumonia, a specifical densitometry value range was defined: from − 950 to − 700 HU for well-aerated parenchyma; from − 700 to − 250 HU for interstitial lung disease; from − 250 to 250 HU for parenchymal consolidation. For the well-aerated parenchyma and the interstitial alterations, the procedure was semi-automatic with low time consumption, whereas consolidations’ analysis needed manual interventions by the operator. After the chest CT, 13% of the sample was admitted to intensive care, while 34% of them to the sub-intensive care. In patients moved to intensive care, the parenchyma analysis reported a higher crazy paving presentation. The quantitative analysis of the alterations affecting the lung parenchyma of patients with COVID-19 pneumonia can be performed by threshold method segmentation on 3D Slicer. The segmentation could have an important role in the quantification in different COVID-19 pneumonia presentations, allowing to help the clinician in the correct management of patients.
... More recently, Rapid Diagnostic Test (RPT) was used for detecting the corona virus antigens with artificial antibodies. They show sensitivity between 34-80% and take less than 30 min [4] . But cases inadequate antigen traces in the nasal samples can go undetected on RPT. ...
... All rights reserved. jects involving 4121 COVID-19 patients, CT scans for 91.4% of them had presented with bilateral lung involvement that is suggestive of COVID-19 [4] . Guan et al. observed abnormal CT findings of Ground Glass Opacity (GGO) and bilateral patchy shadowing in 86.2% COVID-19 cases [5] . ...
... with severe symptoms), interlobular septal thickening, air bronchogram are likely to occur [3] . Crazy paving patterns, reverse 'halo' signs are also reported as CT features for COVID-19 detection [4] . AI-based analysis can help localize regions on chest CT that can potentially be a COVID-19 infection. ...
Accurate detection of COVID-19 is one of the challenging research topics in today's healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for COVID-19 localization from medical imaging modality like chest CT scan tremendously augment clinical care assistance. In this research, a Contour-aware Attention Decoder CNN has been proposed to precisely segment COVID-19 infected tissues in a very effective way. It introduces a novel attention scheme to extract boundary, shape cues from CT contours and leverage these features in refining the infected areas. For every decoded pixel, the attention module harvests contextual information in its spatial neighborhood from the contour feature maps. As a result of incorporating such rich structural details into decoding via dense attention, the CNN is able to capture even intricate morphological details. The decoder is also augmented with a Cross Context Attention Fusion Upsampling to robustly reconstruct deep semantic features back to high-resolution segmentation map. It employs a novel pixel-precise attention model that draws relevant encoder features to aid in effective upsampling. The proposed CNN was evaluated on 3D scans from MosMedData and Jun Ma benchmarked datasets. It achieved state-of-the-art performance with a high dice similarity coefficient of 85.43% and a recall of 88.10%.
... In our present study, we focused on investigating the disagreement of typical chest CT characteristics between Regarding bilateral or unilateral lung involvement, we discovered several intriguing results. The pooled incidence rates of bilateral lung involvement in all patients were 78% and indicated that COVID-19 infection most commonly affected bilateral lungs, which was consistent with the results of 78.2% by Bao et al. (63) and 73.8% by Zhu et al. (64). For subgroup analyses, we found that the incidence rates of unilateral lung involvement for patients in mainland China were significantly higher than those outside (15 vs. 7%) and the incidence rates of bilateral lung involvement were significantly low (75 vs. 84%). ...
... We also demonstrated that all CT features and corresponding pooled incidence rates were in accordance with previous meta-analyses (63,64); however, large gaps in the incidence rates of CT features between patients from within and outside mainland China were striking and all differences reached statistical significance. These results that CT patterns of patients with COVID-19 from within mainland China may not reflect those outside mainland China should be interpreted with caution, and the evidence provided to elucidate why features differ between those from within and outside mainland China is indirect and even anecdotal. ...
Background
Chest computerized tomography (CT) plays an important role in detecting patients with suspected coronavirus disease 2019 (COVID-19), however, there are no systematic summaries on whether the chest CT findings of patients within mainland China are applicable to those found in patients outside.
Methods
Relevant studies were retrieved comprehensively by searching PubMed, Embase, and Cochrane Library databases before 15 April 2022. Quality assessment of diagnostic accuracy studies (QUADAS) was used to evaluate the quality of the included studies, which were divided into two groups according to whether they were in mainland China or outside. Data on diagnostic performance, unilateral or bilateral lung involvement, and typical chest CT imaging appearances were extracted, and then, meta-analyses were performed with R software to compare the CT features of COVID-19 pneumonia between patients from within and outside mainland China.
Results
Of the 8,258 studies screened, 19 studies with 3,400 patients in mainland China and 14 studies with 554 outside mainland China were included. Overall, the risk of quality assessment and publication bias was low. The diagnostic value of chest CT is similar between patients from within and outside mainland China (93, 91%). The pooled incidence of unilateral lung involvement (15, 7%), the crazy-paving sign (31, 21%), mixed ground-glass opacities (GGO) and consolidations (51, 35%), air bronchogram (44, 25%), vascular engorgement (59, 33%), bronchial wall thickening (19, 12%), and septal thickening (39, 26%) in patients from mainland China were significantly higher than those from outside; however, the incidence rates of bilateral lung involvement (75, 84%), GGO (78, 87%), consolidations (45, 58%), nodules (12, 17%), and pleural effusion (9, 15%) were significantly lower.
Conclusion
Considering that the chest CT features of patients in mainland China may not reflect those of the patients abroad, radiologists and clinicians should be familiar with various CT presentations suggestive of COVID-19 in different regions.
... Consequently, an alternative modality such as CT imaging for detection and diagnosis may prove to be very valuable for treatment purposes and more importantly, limiting and controlling the spread of COVID-19. Chest CT imaging has the potential to both detect infection and determine its severity according to a series of studies [5]. This alternative method of detection is especially useful in the case of an ambiguous or false-negative RT-PCR result and help validate true-positive results, demonstrated by a study that found 5 of 167 patients with positive chest CT and negative RT-PCR results test positive for COVID-19 days later [6]. ...
... This study also categorized the lesions by shape, where patchy was the most common, followed by spider web sign, cord-like, and nodular, seen in this patient. Other radiological signs that accompanied these lesions were pleural thickening, followed by more rare signs of lymphadenopathy and pleural effusion [5]. ...
Diagnosis of COVID-19 is an increasingly challenging task during a pandemic where symptoms are beguiling due to a wide array of symptomatology. Radiologic diagnosis plays a vital role not only in diagnosis but in early assessment and triage of suspected patients with COVID-19 pneumonia. Typically, bilateral ground-glass opacities are considered high-risk and pathognomonic findings for diagnosis. However, COVID-19 is notorious for varying radiologic presentation as well. We describe a case of cannonball appearance of COVID-19 pneumonia which has not been described previously in the literature and is a novel finding.
... The use of chest CT imaging as a potential tool to infer COVID-19 has been demonstrated by several clinical studies. The main factors that favor the use of chest CT modality in COVID-19 diagnosis are the high sensitivity and low miss rate [59][60][61][62][63][64]. CT has registered 97% sensitivity in a study with 1014 patients in Wuhan, China [59]. ...
... The predominant patterns observed in these studies include Ground-Glass Opacities, consolidation, and septal thickening. CT scans with bilateral lung involvement are also indicative of COVID-19, which is reflected in a study conducted on 34 subjects [61]. Other common CT manifestations are bilateral patchy shadowing, which was observed in 86.2% of confirmed cases in the experiment by Guan et al. [62]. ...
Background and objective
In recent years, Artificial Intelligence has had an evident impact on the way research addresses challenges in different domains. It has proven to be a huge asset, especially in the medical field, allowing for time-efficient and reliable solutions. This research aims to spotlight the impact of deep learning and machine learning models in the detection of COVID-19 from medical images. This is achieved by conducting a review of the state-of-the-art approaches proposed by the recent works in this field.
Methods
The main focus of this study is the recent developments of classification and segmentation approaches to image-based COVID-19 detection. The study reviews 140 research papers published in different academic research databases. These papers have been screened and filtered based on specified criteria, to acquire insights prudent to image-based COVID-19 detection.
Results
The methods discussed in this review include different types of imaging modality, predominantly X-rays and CT scans. These modalities are used for classification and segmentation tasks as well. This review seeks to categorize and discuss the different deep learning and machine learning architectures employed for these tasks, based on the imaging modality utilized. It also hints at other possible deep learning and machine learning architectures that can be proposed for better results towards COVID-19 detection. Along with that, a detailed overview of the emerging trends and breakthroughs in Artificial Intelligence-based COVID-19 detection has been discussed as well.
Conclusion
This work concludes by stipulating the technical and non-technical challenges faced by researchers and illustrates the advantages of image-based COVID-19 detection with Artificial Intelligence techniques.
... Many observational studies, systematic reviews, and meta-analyses have been published regarding radiologic abnormalities in COVID- 19. Table 2 summarizes previously published meta-analyses with a relatively large patient population that reported the prevalence of pleural and nonpulmonary parenchymal abnormalities (17,(20)(21)(22)(23). Figure 2 represents pleural changes associated with progressive disease. ...
... Earlier studies estimated the incidence to be approximately 1% (70). Several large meta-analyses that evaluated radiologic presentations of COVID-19 did not report any case of pneumothorax (20)(21)(22) with COVID-19 (79). For critically ill patients, the incidence increased to 2% (80). ...
Objective: This narrative review aims to provide a detailed overview of pleural abnormalities in patients with coronavirus disease 19 or COVID-19.
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is a novel beta coronavirus responsible for COVID-19. Although pulmonary parenchymal and vascular changes associated with COVID-19 are well established, pleural space abnormalities have not been the primary focus of investigations.
Methods: Narrative overview of the medical literature regarding pleural space abnormalities in COVID-19. The appropriate manuscripts were identified by searching electronic medical databases and by hand searching the bibliography of the identified papers. Pleural abnormalities on transverse and ultrasound imaging are discussed. The incidence, clinical features, pathophysiology, and fluid characteristics of pleural
effusion are reviewed. Studies reporting pneumothorax and pneumomediastinum are examined to evaluate for pathogenesis and prognosis. A brief comparative analysis of pleural abnormalities among patients with COVID-19, severe acute respiratory syndrome (SARS), and Middle Eastern respiratory syndrome (MERS) has been provided.
Conclusions: Radiologic pleural abnormalities are common in COVID-19, but the incidence of pleural effusion appears to be low. Pneumothorax is rare and does not independently predispose the patient to worse outcomes. SARS-CoV-2 infects the pleural space; however, whether the pleural fluid can propagate the
infection is unclear.
... The most typical manifestation of chest CT was ground-glass opacities (68.1%). (84) In another article Rami M. Elshazli et al. studied the diagnosis and prognosis of 6320 patients. The results of the cohorts showed that patients with high IL-6, CRP, D-dimer and neutrophils had a higher probability of mortality. ...
The SARS-CoV-2 virus is the main cause of the pandemic viral pneumonia known as COVID-19. Some studies suggest that, in this disease, lymphopenia is the most common sign of infection, as well as increased CRP and IL-6 caused by a cytokine storm directed at the lungs. Therefore, the hypothesis of the study is to make a systematic revision of scientific studies linked to the immunological phenomenon known as COVID-19. Objectives: The main aim is to study the cytokine storm of COVID-19, as well as to determine the role of IL-6 and T-lymphocytes.Methods: A search strategy was made through the PICOS questions, based on the PRISMA method. The MeSH terms were looked up on PubMed, Google Scholar and SciELO (2019-2021). The level of quality was sought according to the ranking of Scimago institutions, and the H index of the journals was assessed. Results: 43 articles were included, and clinic, diagnosis, treatment, and pathogenesis were compared. A decrease in TCD4 / CD8 lymphocytes was shown in patients with severe disease, as well as an increase in IL-6 and CRP.Conclusions: The immunological phenomenon known as COVID-19 is characterized by lymphopenia and an increase in IL-6 amongst critically ill patients. Monitoring those parameters could help to understand the progression of the COVID-19 disease.
... CT images of the lungs of patients with COVID-19 show patchy or ground glass shadows [14]. As the disease progresses, the severity of the lung lesions may become more significant, and pulmonary fibrosis may develop, with a white coloration of both lungs detected by CT lung examination [15,16]. Therefore, it is crucial to display information about the lungs of COVID-19 cases through CT. ...
The coronavirus disease 2019 (COVID-19) rapidly spread around the world, and resulted in a global pandemic. Applying artificial intelligence to COVID-19 research can produce very exciting results. However, most research has focused on applying AI techniques in the study of COVID-19, but has ignored the security and reliability of AI systems. In this paper, we explore adversarial attacks on a deep learning system based on COVID-19 CT images with the aim of helping to address this problem. Firstly, we built a deep learning system that could identify COVID-19 CT images and non-COVID-19 CT images with an average accuracy of 76.27%. Secondly, we attacked the pretrained model with an adversarial attack algorithm, i.e., FGSM, to cause the COVID-19 deep learning system to misclassify the CT images, and the classification accuracy of non-COVID-19 CT images dropped from 80% to 0%. Finally, in response to this attack, we proposed how a more secure and reliable deep learning model based on COVID-19 medical images could be built. This research is based on a COVID-19 CT image recognition system, which studies the security of a COVID-19 CT image-based deep learning system. We hope to draw more researchers’ attention to the security and reliability of medical deep learning systems.
... The morphological pattern in the lungs observed on a CT scan is associated with the progression and severity of COVID-19 infection. Ground-glass opacities (GGOs), air bronchogram, consolidation, crazy paving pattern, and interlobular septal thickening with bilateral and multilobe involvement are the most common radiological features associated with COVID-19 observed in chest CT scans (10)(11)(12)(13). The CT-Severity Score (CTSS) is used to determine the severity of lung involvement depending on the percentage of lung parenchyma affected. ...
Background:
The COVID-19 pandemic has claimed numerous lives in the last three years. With new variants emerging every now and then, the world is still battling with the management of COVID-19.
Purpose:
To utilize a deep learning model for the automatic detection of severity scores from chest CT scans of COVID-19 patients and compare its diagnostic performance with experienced human readers.
Methods:
A deep learning model capable of identifying consolidations and ground-glass opacities from the chest CT images of COVID-19 patients was used to provide CT severity scores on a 25-point scale for definitive pathogen diagnosis. The model was tested on a dataset of 469 confirmed COVID-19 cases from a tertiary care hospital. The quantitative diagnostic performance of the model was compared with three experienced human readers.
Results:
The test dataset consisted of 469 CT scans from 292 male (average age: 52.30) and 177 female (average age: 53.47) patients. The standalone model had an MAE of 3.192, which was lower than the average radiologists' MAE of 3.471. The model achieved a precision of 0.69 [0.65, 0.74] and an F1 score of 0.67 [0.62, 0.71], which was significantly superior to the average reader precision of 0.68 [0.65, 0.71] and F1 score of 0.65 [0.63, 0.67]. The model demonstrated a sensitivity of 0.69 [95% CI: 0.65, 0.73] and specificity of 0.83 [95% CI: 0.81, 0.85], which was comparable to the performance of the three human readers, who had an average sensitivity of 0.71 [95% CI: 0.69, 0.73] and specificity of 0.84 [95% CI: 0.83, 0.85].
Conclusion:
The AI model provided explainable results and performed at par with human readers in calculating CT severity scores from the chest CT scans of patients affected with COVID-19. The model had a lower MAE than that of the radiologists, indicating that the CTSS calculated by the AI was very close in absolute value to the CTSS determined by the reference standard.
... the frequency of lymphadenopathy was found to be 3.38% in the general COVID-19 disease group [10]. In the study of Zhu, et al. the rate of lymphadenopathy among 4100 COVID-19 patients was found to be 5.4% [11]. In a study conducted on ...
Mediastinal lymphadenopathy is rare in Coronavirus Disease-2019 (COVID-19) patients with mild clinical course. The frequency of lymphadenopathy increases in COVID-19 patients who develop Acute Respiratory Distress Syndrome (ARDS). In a 38-year-old male patient, mediastinal lymphadenopathy and asymptomatic pulmonary embolism were detected during the third week of COVID-19 infection at home. Sarcoidosis was diagnosed with a finding of non-caseating granulomas. Even if it is asymptomatic, pulmonary embolism should be considered, especially in COVID-19 patients with high C - Reactive Protein (CRP) and D-dimer levels. If mediastinal lymphadenopathy is detected in mild COVID-19 cases, systemic diseases should be investigated. In severe COVID-19 cases, if lymphadenopathy continues despite a COVID-19 recovery, further investigation is required.
... The coronavirus disease 2019 (COV-ID-19), caused by a novel corona virus named SARS-CoV-2, has emerged as a global pandemic (1,2). Infected patients typically present with fever and respiratory symptoms in addition to showing interstitial inflammation upon computed tomography (CT) scanning (3,4). The associated pneumonia tends to progress with a remarkable speed, leading to diffuse alveolar damage or acute respiratory distress syndrome via hyperinflammation. ...
... [9] The early stage of COVID-19 is characterized by dilatation of capillaries and engorgement of vessels, mild fluid exudates in the alveoli, and interstitial edema, resulting in single or multiple patchy ground-glass opacities which are mostly peripheral, basal and subpleural. [21,22] Next is the advanced stage in which the lesions increase in density and size, forming a mixed pattern of GGO and consolidation with or without air bronchograms. The cause of this appearance is said to be the exudation into the alveolar space and the lung interstitium. ...
... La lésion radiologique la plus fréquente est celle dite ≪ en verre dépoli≫ (plus de 68% des cas) se matérialisant par des zones floues et grises. C'est ce qu'on appelle l'opacification du verre dépoli (GGO) ou la superposition d'une consolidation sur de nombreux GGO [1][2][3][4]. ...
CITATIONS 0 READS 24 7 authors, including: Some of the authors of this publication are also working on these related projects: Compression View project Hardware architectures of reconfigurable neural networks using NoC View project Hanene Abdelali University of Monastir 1 PUBLICATION 0 CITATIONS SEE PROFILE Résumé Dans cet article, nous rapportons la mise en place d'une chaîne complète d'évaluation automatique du degré des lésions Covid-19. Elle comporte (i) la préparation de la base de données privée, (ii) le prétraitement des images, (iii) la segmentation automatique basée sur U-NET et l'évaluation de ses résultats par les métriques usuelles, (iv) la reconstruction 3D et enfin (v) la quantification volumique des lésions covid-19 en utilisant des images scan comme entrée. Pour la validation, l'approche est appliquée sur notre propre base de données privée crééeà cet effet. Les résultats obtenus sont très encourageants. L'évaluation de la segmentation pour le poumon par les métriques DICE, IOU, Précision, Recall, et Accuracy ont permis d'obtenir : 0.81, 0.90, 0.93, 0.82 et 0.92 respectivement. De même pour les lésions ces valeurs sont : 0.89, 0.93, 0.93, 0.81 et 0.93 respectivement. Mots clés : Deep Learning. Segmentation. U-Net. Reconstruction 3D. Calcul volumique. Taux d'infection. Abstract In this article, we report the implementation of a complete chain for the automatic evaluation of the degree of Covid-19 lesions. It includes (i) the preparation of the private database, (ii) the preprocessing of the images, (iii) the automatic segmentation based on U-NET and the evaluation of its results by the usual metrics, (iv) the reconstruction 3D and finally (v) volumetric quantification of covid-19 lesions using scan images as input. For validation, the approach is applied on our own private database that we have created for this purpose. The results obtained are very encouraging. The evaluation of the segmentation for the lung by the metrics DICE, IOU, Precision, Recall, and Accuracy made it possible to obtain: 0.81, 0.90, 0.93, 0.82 and 0.92 respectively. Similarly for lesions these values are: 0.89, 0.93, 0.93, 0.81 and 0.93 respectively.
... La lésion radiologique la plus fréquente est celle dite ≪ en verre dépoli≫ (plus de 68% des cas) se matérialisant par des zones floues et grises. C'est ce qu'on appelle l'opacification du verre dépoli (GGO) ou la superposition d'une consolidation sur de nombreux GGO [1][2][3][4]. ...
Dans cet article, nous rapportons la mise en place d'une chaîne complète d'évaluation automatique du degré des lésions Covid-19. Elle comporte (i) la préparation de la base de données privée, (ii) le prétraitement des images, (iii) la segmentation automatique basée sur U-NET et l'évaluation de ses résultats par les métriques usuelles, (iv) la reconstruction 3D et enfin (v) la quantification volumique des lésions covid-19 en utilisant des images scan comme entrée. Pour la validation, l'approche est appliquée sur notre propre base de données privée crééeà cet effet. Les résultats obtenus sont très encourageants. L'évaluation de la segmentation pour le poumon par les métriques DICE, IOU, Précision, Recall, et Accuracy ont permis d'obtenir : 0.81, 0.90, 0.93, 0.82 et 0.92 respectivement. De même pour les lésions ces valeurs sont : 0.89, 0.93, 0.93, 0.81 et 0.93 respectivement. Mots clés : Deep Learning. Segmentation. U-Net. Reconstruction 3D. Calcul volumique. Taux d'infection. Abstract In this article, we report the implementation of a complete chain for the automatic evaluation of the degree of Covid-19 lesions. It includes (i) the preparation of the private database, (ii) the preprocessing of the images, (iii) the automatic segmentation based on U-NET and the evaluation of its results by the usual metrics, (iv) the reconstruction 3D and finally (v) volumetric quantification of covid-19 lesions using scan images as input. For validation, the approach is applied on our own private database that we have created for this purpose. The results obtained are very encouraging. The evaluation of the segmentation for the lung by the metrics DICE, IOU, Precision, Recall, and Accuracy made it possible to obtain: 0.81, 0.90, 0.93, 0.82 and 0.92 respectively. Similarly for lesions these values are: 0.89, 0.93, 0.93, 0.81 and 0.93 respectively.
... CT has played a central role in the diagnosis of COVID-19 for the presence of lung parenchymal abnormalities as signs of interstitial pneumonia, mainly bilateral GGOs with a subpleural distribution [15,16]. In our analysis, we focused on the %PAL, representing ground-glass opacities and %CL representing overall lung impairment, considering the high frequency of these opacities and their persistence after the acute phase that can correlate with altered respiratory function [17,18]. ...
(1) Background: Quantitative CT analysis (QCT) has demonstrated promising results in the prognosis prediction of patients affected by COVID-19. We implemented QCT not only at diagnosis but also at short-term follow-up, pairing it with a clinical examination in search of a correlation between residual respiratory symptoms and abnormal QCT results. (2) Methods: In this prospective monocentric trial performed during the “first wave” of the Italian pandemic, i.e., from March to May 2020, we aimed to test the relationship between %deltaCL (variation of %CL-compromised lung volume) and variations of symptoms-dyspnea, cough and chest pain-at follow-up clinical assessment after hospitalization. (3) Results: 282 patients (95 females, 34%) with a median age of 60 years (IQR, 51–69) were included. We reported a correlation between changing lung abnormalities measured by QCT, and residual symptoms at short-term follow up after COVID-19 pneumonia. Independently from age, a low percentage of surviving patients (1–4%) may present residual respiratory symptoms at approximately two months after discharge. QCT was able to quantify the extent of residual lung damage underlying such symptoms, as the reduction of both %PAL (poorly aerated lung) and %CL volumes was correlated to their disappearance. (4) Conclusions QCT may be used as an objective metric for the measurement of COVID-19 sequelae.
... 6,7 Among the CT features of COVID-19 pneumonia, mediastinal lymphadenopathy is rare and has a prevalence of 3-5% according to systematic meta-analyses. 8, 9 However, in one study conducted in France, mediastinal lymphadenopathy was observed in 66% of COVID-19 patients admitted to the intensive care unit (ICU). 10 Similarly, other studies have reported that mediastinal lymphadenopathy was significantly more frequent in critically ill patients and those who died during hospitalization. ...
Background:
We analyzed the differences between clinical characteristics and computed tomography (CT) findings in patients with coronavirus disease 2019 (COVID-19) to establish potential relationships with mediastinal lymphadenopathy and clinical outcomes.
Methods:
We compared the clinical characteristics and CT findings of COVID-19 patients from a nationwide multicenter cohort who were grouped based on the presence or absence of mediastinal lymphadenopathy. Differences between clinical characteristics and CT findings in these groups were analyzed. Univariate and multivariate analyses were performed to determine the impact of mediastinal lymphadenopathy on clinical outcomes.
Results:
Of the 344 patients included in this study, 53 (15.4%) presented with mediastinal lymphadenopathy. The rate of diffuse alveolar damage pattern pneumonia and the visual CT scores were significantly higher in patients with mediastinal lymphadenopathy than in those without (P < 0.05). A positive correlation between the number of enlarged mediastinal lymph nodes and visual CT scores was noted in patients with mediastinal lymphadenopathy (Spearman's ρ = 0.334, P < 0.001). Multivariate analysis showed that mediastinal lymphadenopathy was independently associated with a higher risk of intensive care unit (ICU) admission (odds ratio, 95% confidence interval; 3.25, 1.06-9.95) but was not significantly associated with an increased risk of in-hospital death in patients with COVID-19.
Conclusion:
COVID-19 patients with mediastinal lymphadenopathy had a larger extent of pneumonia than those without. Multivariate analysis adjusted for clinical characteristics and CT findings revealed that the presence of mediastinal lymphadenopathy was significantly associated with ICU admission.
... Ground glass opacities (GGO), crazy-paving pattern (GGO with superimposed septal thickening), and consolidation are the most common chest CT findings in COVID-19 pneumonia (Fig. 1) [6]. These findings are usually bilateral and multilobar, mostly distributed in the subpleural/peripheral and posterior regions of the lungs [7], but occasionally they can show a bronchovascular distribution or a combination of both. ...
Infection with SARS-CoV-2 has dominated discussion and caused global healthcare and economic crisis over the past 18 months. Coronavirus disease 19 (COVID-19) causes mild-to-moderate symptoms in most individuals. However, rapid deterioration to severe disease with or without acute respiratory distress syndrome (ARDS) can occur within 1-2 weeks from the onset of symptoms in a proportion of patients. Early identification by risk stratifying such patients who are at risk of severe complications of COVID-19 is of great clinical importance. Computed tomography (CT) is widely available and offers the potential for fast triage, robust, rapid, and minimally invasive diagnosis: Ground glass opacities (GGO), crazy-paving pattern (GGO with superimposed septal thickening), and consolidation are the most common chest CT findings in COVID pneumonia. There is growing interest in the prognostic value of baseline chest CT since an early risk stratification of patients with COVID-19 would allow for better resource allocation and could help improve outcomes. Recent studies have demonstrated the utility of baseline chest CT to predict intensive care unit (ICU) admission in patients with COVID-19. Furthermore, developments and progress integrating artificial intelligence (AI) with computer-aided design (CAD) software for diagnostic imaging allow for objective, unbiased, and rapid assessment of CT images.
... Typical initial or follow-up chest CT imaging findings in adults with COVID-19 pneumonia have recently been reported [8, 9,21]. The most common typical findings in COVID-19 pneumonia are described as multifocal peripherally located GGO appearance accompanied by thickening of the interlobular septa, prominent vascular structures, and halo and reverse halo signs [5,19,[21][22][23]. In a study including a small number of patients (47 adults and 14 pediatric patients), ...
... Of the 47 included studies, only 13 were SRs, [10,15,18,20,22,23,26,29,[38][39][40]43,52] while 34 were meta-analyses. [9,[11][12][13][14]16,17,19,21,24,25,27,28,[30][31][32][33][34][35][36][37]41,42,[44][45][46][47][48][49][50][51][53][54][55] A total of 17 studies were published by Chinese authors, 8 by Italian authors, and 4 by American authors. Nearly half of the SRs/meta-analyses were performed by <5 authors (n = 20, 42.6%), which was comparable between SRs only (n = 6, 46.2%) and meta-analysis (n = 14, 41.2%); nevertheless, Chinese-based studies (n = 11, 64.7%) were commonly performed by 6 to 10 authors compared with nonChinese-based studies (n = 7, 23.3%). ...
During the coronavirus disease 2019 (COVID-19) pandemic, convenient accessibility and rapid publication of studies related to the ongoing pandemic prompted shorter preparation time for studies. Whether the methodological quality and reporting characteristics of published systematic reviews (SRs)/meta-analyses are affected during the specific pandemic condition is yet to be clarified. This study aimed to evaluate the epidemiology, methodological quality, and reporting characteristics of published SRs/meta-analyses related to COVID-19.The Ovid Medline, Ovid Embase, Cochrane Library, and Web of Science electronic databases were searched to identify published SRs/meta-analyses related to the COVID-19 pandemic. Study screening, data extraction, and methodology quality assessment were performed independently by 2 authors. The methodology quality of included SRs/meta-analyses was evaluated using revised version of a measurement tool to assess SRs, and the reporting characteristics were assessed based on the preferred reporting items for SRs and meta-analyses guidelines.A total of 47 SRs/meta-analyses were included with a low to critically low methodological quality. The median number of days from the date of literature retrieval to the date that the study was first available online was 21 days; due to the limited time, only 7 studies had study protocols, and the studies focused on a wide range of COVID-19 topics. The rate of compliance to the preferred reporting items for SRs and meta-analyses checklists of reporting characteristics ranged from 14.9% to 100%. The rate of compliance to the items of protocol and registration, detailed search strategy, and assessment of publication bias was less than 50%.SRs/meta-analyses on COVID-19 were poorly conducted and reported, and thus, need to be substantially improved.
... El derrame pleural es el acumulo de líquido en el espacio pleural entre las capas visceral y parietal, que puede clasificarse como trasudado o exudado, la prueba de oro para su diagnóstico es la (7) radiografía de tórax . A pesar de que el derrame pleural no es un hallazgo común en pacientes con infección por SARS-CoV- (8,9) 2, algunos estudios reportan su presencia . Recientes estudios manifiestan mayor incidencia de derrame pleural asociados con la neumonía por coronavirus en pacientes críticamente enfermos o con casos graves en comparación (10,11,12) con casos simples o con síntomas leves . ...
Objetivos:
El presente trabajo tuvo como propósito describir las características físicas, citológicas y bioquímicas, así como clasificar los líquidos pleurales de pacientes con COVID-19 como exudados o trasudados.
Materiales y Métodos:
Se realizó un estudio observacional, transversal descriptivo. Se recopiló datos del examen citoquímico de muestras de líquido pleural procesadas entre los meses de abril a setiembre del 2020, en el laboratorio del Centro de Emergencias de Lima Metropolitana (CELIM).
Resultados:
Durante el periodo de estudio un total de 81 muestras de líquido pleural de pacientes con COVID-19 fueron evaluadas, de estos, 26 cumplieron con nuestros criterios de elegibilidad. Catorce líquidos (54%), tuvieron un color rojo y 18 (69%) tuvieron un aspecto turbio. Los líquidos pleurales exudativos fueron la mayoría (n = 17), las proteínas totales presentaron una media de 3.3 gr/dl (DE: 1.5), LDH una mediana de 544 U/L (RIC: 262-2016), el recuento leucocitario tuvo una mediana de 610 leucocitos/ul (RIC: 180-968) y el recuento diferencial de polimorfonucleares una mediana 29% (RIC: 15-60). En cuanto a las características clínicas, del total de exudados el 41% correspondían a neoplasias y el 23% a neumonías. Mientras que, del total de trasudados (n=9), 45% provenían de pacientes con neoplasias.
Conclusiones:
En nuestro estudio observamos que la mayoría de las muestras de líquido pleural de pacientes con COVID-19 fueron clasificadas como exudados. Estas presentaron un bajo porcentaje diferencial leucocitario de polimorfonucleares. Los valores de los parámetros bioquímicos tales como proteínas totales y LDH se relacionaron adecuadamente con la clasificación de exudados.
... Furthermore, according to the results of the reviewed articles, the extent of lung involvement varied in the studies, indicating the severity of the disease (9,(11)(12)(13)(14)(15)(16)(17)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36). Pan et al. (30) reported the highest severity of lung abnormalities in chest CT about ten days after the primary inception of symptoms for recovered COVID-19 patients (without intensive respiratory distress during the disease period). ...
Context: The early detection of COVID-19 is of paramount importance for the disease treatment and control. As real-time reverse-transcription polymerase chain reaction indicates a low sensitivity, the computed tomography of patients' chest can play an effective role in the diagnosis of COVID-19, particularly for patients with false-negative RT-PCR tests. It is also effective in monitoring the clinical trends and assessing the severity of the disease. Objectives: Accordingly, this study aimed to review the different manifestations of the COVID-19 infections in High-Resolution Computed Tomography images of patients' chests and analyze the distribution of the disease in the lungs. The results can contribute to providing a comprehensive and concise reference on the appearance of various types of involvement and lung lesions and the extent of these lesions in the COVID-19 patients. Data Sources: We systematically searched four major indexing databases (namely PubMed, Science Direct, Google Scholar, and Cochrane Central) for articles published by May 2021 using the following keywords: High-Resolution Computed Tomography (HRCT), COVID-19, and Manifestations. Results: Overall, 29 studies addressing the role of HRCT in detecting and evaluating the manifestations of the COVID-19 infection in patients' lungs as Ground Glass Opacification (GGO), Consolidation, Irregular Solid Nodules, Fibrous Stripes, Crazy Paving Pattern, Air Bronchogram Sign, etc. were reviewed. Conclusions: GGO was the most common finding, as reported in 96.6% of the reviewed articles, followed by Consolidations (65.5%) and Irregular Solid Nodules (55.2%). Most patients revealed the disease process as a bilateral distribution in the peripheral areas of the lung.
... Chest computed tomography (CT) imaging plays a key role in the early diagnosis of COVID-19. [2][3][4][5] Previous studies [6][7][8][9][10] and a recent meta-analysis [11] indicated that ground-glass opacity (GGO) is the most common radiologic finding on chest CT in patients with COVID-19, but this finding is non-specific because it is found in other infectious and inflammatory conditions, which limits its clinical application. [12] practice, clinicians and radiologists are eager to understand the diagnostic accuracy of GGO in patients with COVID-19, which remains unproven. ...
... Thus, in the highly suspected group (Table 2), there were no patients with pleural fluid. Although cancer patients are not included, according to a meta-analysis of 4,121 patients, pleural effusion (5.3%) was reported as the rarest CTT imaging feature of COVID-19 (16). ...
Objective
There are many clinical conditions, such as lung cancer, that need to be followed up and treated during a pandemic. Providing health care for patients who are immune-suppressive requires extra care.
Method
Among 108 lung cancer patients who had been hospitalized during the COVID-19 pandemic, 18 with respiratory symptoms were evaluated retrospectively.
Results
The patients’ median age was 64±9.4 with a male predominance (male n=16, female n=2). Thirteen had non-small cell lung cancer (NSCLC), and 5 had small cell lung cancer (SCLC). Nine (50%) patients were receiving chemotherapy. The most common symptom was shortness of breath (n=14, 77.8%), followed by fever (n=10, 55.6%). The findings confirmed on computed thorax tomography (CTT) were as follows: consolidation (n=8, 44.4%), ground glass opacities (n=8, 44.4%) and thoracic tumour/mediastinal-hilar lymphadenopathy (n=3, 16.7%). Hypoxia was seen in 11 patients (61.1.%), twelve patients had an elevated LDH (median=302±197) and lymphopenia (median=1055±648), and 5 (27.7%) were highly suspected of having contracted COVID-19. None of their nasopharyngeal swaps was positive. Two of these 5 patients received COVID-19 specific treatment even though they thrice had negative reverse transcription polymerase chain reaction (RT-PCR) results. The two patients responded well to both clinical and radiological treatment. For one case with SCLC receiving immunotherapy, methylprednisolone was initiated for radiation pneumonitis after excluding COVID-19.
Conclusion
In line with a country’s health policies and the adequacy of its health system, the necessity of a multidisciplinary approach in the management and treatment of complications in patients with lung cancer has become even more important during the COVID-19 pandemic.
... COVID-19 and MERS-COV are both from the same type of β-coronavirus with the same clinical and radiologic symptoms and disease stages in both adults and children. [11,46,47] The fatality rate for COVID-19 is less than MERS. Some scholars argue the answer to this issue is within the number of studies and its populations. ...
COVID‑19 is a respiratory infection brought about by SARS‑COV‑2. Most of the
patients contaminated by this pathogen are afflicted by respiratory syndrome with multiple stages
ranging from mild upper respiratory involvement to severe dyspnea and acute respiratory distress
syndrome cases. Keeping in mind the high sensitivity of computed tomography (CT) scan in
detecting abnormalities, it became the number one modality in COVID‑19 diagnosis. A wide
diversity of CT features can be found in COVID‑19 cases, which can be observed before the onset
of clinical signs. The review article is aimed to highlight recent discrepancies in CT‑scan and chest
X‑ray (CXR) characteristics between COVID‑19 and Middle East Respiratory Syndrome (MERS).
Methods: This review study was performed in the literature from the beginning of COVID‑19 until
the middle of April 2021. For this reason, all relevant works through scientific citation websites such
as Google Scholar, PubMed, and Web of Science have been investigated in the mentioned period.
Results: COVID‑19 was more reproductive than MERS, while MERS was significantly higher in
terms of mortality rate (COVID‑19: 2.3% and MERS: 34.4%). Signs of ground‑glass opacity (GGO),
peripheral consolidation, and GGO accompanying with consolidation are the same signs CXR in
both MERS and COVID‑19. Indeed, fever, cough, headache, and sore throat are the most symptoms
in all studied patients. Conclusion: Both COVID‑19 and MERS have the same imaging signs.
The most similar chest CT findings are GGO, peripheral consolidation, and GGO superimposed
by consolidation in both studied diseases, and no statistical differences were seen among the mean
number of chest CT‑scans in MERS and COVID‑19 cases.
... There is rarely pleural effusion and lymphadenopathy. 15,16 In view of the complexity of clinical and imaging manifestations, thin-layer CT of the chest is recommended scanning combined with previous image data and dynamic observation of laboratory examination results for identification. ...
A pandemic of coronavirus diseases 2019 (COVID-19) outbreak is a major public health emergency that has spread in the fastest speed, and caused the most extensive infection world widely. Transbronchial biopsy (TBB) and computed tomography guided percutaneous needle biopsy (CTPNB) is the most common and significant method for the diagnosis of lung cancer. During the COVID-19 pandemic, the indications of TBB and CTPNB must be managed strictly. Therefore, it is extremely indispensable to perform meticulous and individualized management for lung cancer patients to protect the patients from COVID-19.
... or lesions in multiple lung lobes (67.3%; 95% CI: 54.8%-78.7%). [48] Compared to adults, the current study found that the detection rate of abnormal CT findings in children was only 63.2% (95% CI: 55.8%-70.6%), which is similar to the study of the European Society of Paediatric Radiology Cardiothoracic Imaging Taskforce (64%). ...
Background:
There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes.
Objectives:
To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice.
Data sources:
We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu.
Methods:
Reports on chest CT imaging features of children with COVID-19 from January 1, 2020 to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software.
Results:
Thirty-seven articles (1747 children) were included in this study. The heterogeneity of meta-analysis results ranged from 0% to 90.5%. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8%-70.6%), with a rate of 61.0% (95% CI: 50.8%-71.2%) in China and 67.8% (95% CI: 57.1%-78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7%-48.3%), multiple lung lobe lesions was 65.1% (95% CI: 55.1%-67.9%), and bilateral lung lesions was 61.5% (95% CI: 58.8%-72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported 3 cases of white lung, another reported 2 cases of pneumothorax, and another 1 case of bullae.
Conclusions:
The lung CT results of children with COVID-19 are usually normal or slightly atypical. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool.
... A recent meta-analysis of CT imaging of COVID-19 patients showed 91.6% of patients showed abnormal pattern in chest imaging manifestations and patchy or GGO were the most common findings in the acute phase (Zhu et al., 2020). Two studies including some critical COVID-19 patients, showed that a prevalence of the chest CT abnormalities ranging from 80.7% to 53.91% at the 3-and 6-month follow-ups (Gonzalez et al., 2021;Huang et al., 2021). ...
Objective
: To evaluate the long-term consequences of survivors with COVID-19 one year after recovery, and to identify the risk factors associated with abnormal patterns in chest imaging manifestations, or impaired lung function.
Methods
: COVID-19 patients were recruited and prospectively followed up with symptoms, HRQoL (health-related quality of life), psychological questionnaires, 6MWT (6-minute walking test), chest CT, PFTs and blood tests. Multivariable logistic regression models were used to evaluate the association between the clinical characteristics and the chest CT abnormalities or the pulmonary function.
Results
: Ninety-four patients with COVID-19 were recruited between January 16 and February 6, 2021. Muscle fatigue and insomnia were the most common symptoms. Chest CT scan were abnormal in 71.28% of participants. Results of multivariable regression showed an increase odd in age. Ten patients had impairment of DLCO (diffusing capacity of the lung for carbon monoxide). Urea nitrogen concentration on admission was significantly associated with impaired DLCO. The level of IgG and the neutralizing activity were significantly lower compared with those at the early phase.
Conclusions
: One year after hospitalization for COVID-19, a cohort of survivors were mainly troubled with muscle fatigue and insomnia. Pulmonary structural abnormalities and pulmonary diffusion capacities were highly prevalent in surviving COVID-19 patients. It is necessary to intervene main target population for long-term recovery.
... A detailed epidemiological history can provide an important reference to identify high-risk patients [6,7]. Chest computed tomography (CT) is recommended as a valuable and fast tool to assist clinical diagnosis [8][9][10]. Although it was not a COVID-19 validation criterion, compared to the reverse-transcription polymerase chain reaction (RT-PCR), the high sensitivity and timeliness of chest CT make it an invaluable tool for early detection and diagnosis [11]. ...
Introduction:
Public life in China is gradually returning to normal with strong measures in coronavirus 2019 (COVID-19) control. Because of the long-term effects of COVID-19, medical institutions had to make timely adjustments to control policies and priorities to balance between COVID-19 prevention and daily medical services.
Methodology:
The framework for infection prevention and control in the inpatient department was effectively organized at both hospital and department levels. A series of prevention and control strategies was implemented under this leadership: application of rigorous risk assessment and triage before admission through a query list; classifying patients into three risk levels and providing corresponding medical treatment and emergency handling; establishing new ward visiting criteria for visitors; designing procedures for PPE and stockpile management; executing specialized disinfection and medical waste policies.
Results:
Till June 2020, the bed occupancy had recovered from 20.0% to 88.1%. In total, 13045 patients were received in our hospital, of which 54 and 127 patients were identified as high-risk and medium-risk, respectively, and 2 patients in the high-risk group were eventually laboratory-confirmed with COVID-19. No hospital-acquired infection of COVID-19 has been observed since the emergency appeared.
Conclusions:
The strategies ensured early detection and targeted prevention of COVID-19 following the COVID-19 pandemic, which improved the recovery of medical services after the pandemic.
... Están descriptos casos de AAF positivos asociados a infección por SARS-CoV-2 14 que podría ser un diagnóstico diferencial, sin embargo, la paciente presentaba antecedentes de 3 abortos, no tuvo fiebre y la disnea se asoció a derrame pleural (poco frecuente en COVID-19) 15 y lesiones nodulares compatibles con progresión neoplásica. También sería posible plantear lupus eritematoso sistémico asociado al SAF en este caso. ...
... In more severe conditions, crazy paving and fragmented consolidation may also occur [16]. Ground-glass appearance seen mainly on chest CT is estimated due to alveolar edema, exudation, and secondary bleeding resulting from inflammation [22]. The most common abnormalities on the CT-scan of 20 children with COVID-19 were subpleural lesions (100% patients), unilateral pulmonary lesions (30%) or bilateral (50%), GGO (60%), and halo sign (50%) [23]. ...
Background: SARS-CoV-2 causes respiratory tract infections that can sometimes become severe, and the virus was first identified in Wuhan city, China, in late 2019. The term COVID-19 is used for clinical diseases caused by SARS-CoV-2. The number of cases and literature related to the radiological picture of COVID-19-induced pneumonia, its findings, and contribution to diagnosis, correlation with RT-PCR, and its differences with adults is still limited to pediatric patients. Methods: We performed literature searches of the latest articles with PubMed, Google Scholar, and Cochrane Library databases published from 2016 to 2020 (5-year span). Two reviewers searched all articles independently (W and I., with more than five years of experience in radiology, respectively). Results: A total of 35 papers was identified and screened for eligibility from medical databases. There were 24 papers and included in this review. In the population of children, manifestations in radiology are less noticeable. The diagnosis of COVID-19 should prioritize the usage of CXR. Radiology in COVID-19-induced pneumonia may differ between the population of children and adults. Patchy lesions are the most commonly found images on chest x-rays, while bilateral ground-glass opacities (GGO) are the most often features in CT scans. Peribronchial distribution and peribronchial cuffing were more commonly seen in pediatric patients but less frequently found in adults. Conclusion: The characteristics of radiological features in pediatric patients with COVID-19 infection are patchy lesions, peribronchial distribution, and peribronchial cuffing.
... In our study, GGO which was described as patchy, bilateral, subpleural, and peripheral was the most common findings in chest CT. Our findings were following other studies like those conducted by Bao et al [17], Zhu et al [18], Guan et al [19], Ng et al [10], Shi et al [20], Pan et al [21], Song et al [1], Duan and Qin [22], Guan et al [23] and Bernheim et al [24], which also reported GGO as the most common chest CT imaging findings in patients diagnosed with Covid-19. Contrary to our findings, Wu et al [25] and Zhang et al [26] studies, did not report GGO as the most common finding. ...
Background: The novel coronavirus disease (COVID-19) is usually under diagnosed in resource-constrained countries as Africa. Although Real-time-reverse-transcription polymerase chain reaction (RT-PCR) testing is considered to be the gold standard tool to diagnose or screen for COVID-19, chest imaging is a valuable tool to support the diagnosis of COVID-19 pneumonia. Therefore, Radiologists usually play an important role in the diagnosis of COVID-19 pneumonia, especially in resource-constrained environments. This study aimed to evaluate the patterns of chest CT findings in covid-19 pneumonia and to emphasize its diagnostic value in coronavirus disease. Materials and Method: This study was a retrospective cross-sectional study conducted in a reputable diagnostic center in Port Harcourt and comprised of 13 chest CT images diagnosed of Covid-19 pneumonia that met the inclusion criteria set for this study. All the chest CT examinations were performed by registered radiographers on a 64-slice CT scanner (GE Optima CT660, GE medical systems). Results: Chest CT findings in patients with confirmed covid-19 infection was evaluated and the results revealed that 13 (100%) had GGO. Out of 13 patients with GGO, bilateral distribution of the opacities was found in 11(84.62%), followed by peripheral opacities 9(69%) and the least 2 (15.38%) was unilateral distribution. Conclusion: The commonest chest CT appearance of covid-19 pneumonia is bilateral GGO with a predilection for the lower lobes of the lungs. Radiologists and clinicians should take cognizance of imaging appearances and diagnostic capabilities of Chest CT in covid-19 pneumonia, especially in the context of the current pandemic.
... This study collected clinical characteristics, laboratory results, severity of disease, and mortality of Contrary to previous studies, our study illustrated that the prevalence of mediastinal lymphadenopathy in COVID-19 disease was 17.4%, which is more common than mentioned in previous researches, 3.38 and 5.4% (14,26). ...
Background and Objectives: There are conflicting studies on the prevalence of mediastinal lymphadenopathy (LAP) and its relationship to the prognosis of COVID-19 disease. The prevalence varied from 3.4 to 66 percent and more prevalent in patients who died. This study aimed to investigate the mediastinal lymphadenopathy and the disease progression in COVID-19 patients.
Materials and Methods: In this case-control study, 195 COVID-19 patients were divided into two groups, with the mediastinal lymphadenopathy and without it. In these groups, demographic characteristics, underlying diseases, laboratory results, and outcomes were compared.
Results: The median age in the LAP group was higher than the opposite group (62 vs. 58.5; p= 0.037). SpO2 (85% vs. 90%; P
... Ground glass opacities (GGO), crazy paving pattern and consolidations are the most common chest CT findings in patients with COVID-19 pneumonia [8,9]. The distribution of these CT findings is usually bilateral and multilobar with a predominant involvement of subpleural/peripheral and posterior regions of the lungs [8,10]. ...
Purpose:
The aim of this study is to define the role of an "Automated Multi Detector Computed Tomography (MDCT) Pneumonia Analysis Program'' as an early outcome predictor for COVID-19 pneumonia in hospitalized patients.
Materials and methods:
A total of 96 patients who had RT-PCR proven COVID-19 pneumonia diagnosed by non-contrast enhanced chest MDCT and hospitalized were enrolled in this retrospective study. An automated CT pneumonia analysis program was used for each patient to see the extent of disease. Patients were divided into two clinical subgroups upon their clinical status as good and bad clinical course. Total opacity scores (TOS), intensive care unit (ICU) entry, and mortality rates were measured for each clinical subgroups and also laboratory values were used to compare each subgroup.
Results:
Left lower lobe was the mostly effected side with a percentage of 78.12 % and followed up by right lower lobe with 73.95 %. TOS, ICU entry, and mortality rates were higher in bad clinical course subgroup. TOS values were also higher in patients older than 60 years and in patients with comorbidities including, Hypertension (HT), Diabetes Mellitus (DM), Chronic Obstructive Pulmonary Disease (COPD), Chronic Heart Failure (CHF) and malignancy.
Conclusion:
Automated MDCT analysis programs for pneumonia are fast and an objective way to define the disease extent in COVID-19 pneumonia and it is highly correlated with the disease severity and clinical outcome thus providing physicians with valuable knowledge from the time of diagnosis.
... However, the studies mentioned either lack quantitation or were not normalized to the quality of the sample preparation. The involvement of the mediastinal lymph nodes in the pathological process could be indirectly evidenced by computed tomography (CT) studies since mediastinal lymphadenopathy was detected in 6% of all hospitalized patients [20][21][22] and 66% of patients with severe COVID-19 [23]. Intrathoracic lymph node enlargement was also detected during the autopsy of patients who died from COVID-19 [17,18]. ...
Lymphopenia is a frequent hematological manifestation, associated with a severe course of COVID-19, with an insufficiently understood pathogenesis. We present molecular genetic immunohistochemical, and electron microscopic data on SARS-CoV-2 dissemination and viral load (VL) in lungs, mediastinum lymph nodes, and the spleen of 36 patients who died from COVID-19. Lymphopenia <1 × 109/L was observed in 23 of 36 (63.8%) patients. In 12 of 36 cases (33%) SARS-CoV-2 was found in lung tissues only with a median VL of 239 copies (range 18–1952) SARS-CoV-2 cDNA per 100 copies of ABL1. Histomorphological changes corresponding to bronchopneumonia and the proliferative phase of DAD were observed in these cases. SARS-CoV-2 dissemination into the lungs, lymph nodes, and spleen was detected in 23 of 36 patients (58.4%) and was associated with the exudative phase of DAD in most of these cases. The median VL in the lungs was 12,116 copies (range 810–250281), lymph nodes—832 copies (range 96–11586), and spleen—71.5 copies (range 0–2899). SARS-CoV-2 in all cases belonged to the 19A strain. A immunohistochemical study revealed SARS-CoV-2 proteins in pneumocytes, alveolar macrophages, and bronchiolar epithelial cells in lung tissue, sinus histiocytes of lymph nodes, as well as cells of the Billroth pulp cords and spleen capsule. SARS-CoV-2 particles were detected by transmission electron microscopy in the cytoplasm of the endothelial cell, macrophages, and lymphocytes. The infection of lymphocytes with SARS-CoV-2 that we discovered for the first time may indicate a possible link between lymphopenia and SARS-CoV-2-mediated cytotoxic effect.
... The standard norm for COVID-19 detection is RT-PCR of viral nucleic acid, although, current reports have acknowledged the relevance of chest CT scans analysis in COVID-19 patients with false negative RT-PCR findings, especially, when there is a clinical suspicion of infection [13][14][15]. Chest CT features, as bilateral involvement, subpleural or peripherally distributed GGO, consolidation, reticulation, crazy paving pattern, air bronchogram signs, intralobular septal thickening, pulmonary vascular enlargement [16][17][18][19][20][21][22][23][24][25], are considered to be characteristic manifestations of COVID-19 infection [26] and with a high sensitivity [4,27] may let suspect this infection both in symptomatic and in some cases asymptomatic patients [28]. However, some lately published meta-analyses, evaluating accuracy of CT scans detecting COVID-19 pulmonary involvement, points out a risk of a low specificity and false-positive findings also [27,29]. ...
Background: the 2019 coronavirus disease pandemic (COVID-19) has spread at an astonishing speed across the world, causing major morbidity and mortality. Computed tomography (CT) examination plays an important role in crisis areas in the diagnosis of COVID-19. COVID-19 Reporting and Data System (CO-RADS) has a five-point scale of suspicion for COVID-19 pneumonia in chest CT picture which standardizes the evaluation scheme and simplifies reporting. Aim: to summarise and present the role of COVID-19 Reporting and Data System in computed tomography of bilateral pneumonia diagnostic. Materials and methods: recently published studies were reviewed to evaluate COVID-19 Reporting and Data System scale as effective tool to detect COVID-19 pneumonia on chest CT scans. Databases from the subscription list of Lithuanian University of Health Sciences were selected: Medline (PubMed), SpringerLink and ScienceDirect. Results: chest CT features, as bilateral involvement, subpleural or peripherally distributed GGO, consolidation, reticulation, crazy paving pattern, air bronchogram signs, intralobular septal thickening, pulmonary vascular enlargement, are considered to be characteristic manifestations of COVID-19 infection. Studies show that Dutch Radiological Society presented CO-RADS scale sensitivity and specificity may vary from 61-88% and 66,4-98%, respectively. Conclusion: chest CT scan has a high sensitivity for COVID-19 diagnosis and could reduce false negative results obtained from RT-PCR tests. Furthermore, a standardized reporting system could increase clarification, minimize reporting variability and help radiologists recognize the results they observe, especially, for less experienced specialists.
... In many previous studies, this method was also used to diagnose the lung damage resulted from viral pneumonia, such as lung fibrosis [4,9,14,22,23]. Thin-section CT scans from all the patients showed that evidence of fibrosis was found in almost half of patients that was consistent with the findings of some previous studies in COVID-19 patients [9,14,24]. We found that pulmonary fibrosis developed in COVID-19 patients could be reversed in a part of the population. ...
Background
Thousands of Coronavirus Disease 2019 (COVID-19) patients have been discharged from hospitals Persistent follow-up studies are required to evaluate the prevalence of post-COVID-19 fibrosis.
Methods
This study involves 462 laboratory-confirmed patients with COVID-19 who were admitted to Shenzhen Third People’s Hospital from January 11, 2020 to April 26, 2020. A total of 457 patients underwent thin-section chest CT scans during the hospitalization or after discharge to identify the pulmonary lesion. A total of 287 patients were followed up from 90 to 150 days after the onset of the disease, and lung function tests were conducted about three months after the onset. The risk factors affecting the persistence of pulmonary fibrosis were identified through regression analysis and the prediction model of the persistence of pulmonary fibrosis was established.
Results
Parenchymal bands, irregular interfaces, reticulation and traction bronchiectasis were the most common CT features in all COVID-19 patients. During the 0–30, 31–60, 61–90, 91–120 and > 120 days after onset, 86.87%, 74.40%, 79.56%, 68.12% and 62.03% patients developed with pulmonary fibrosis and 4.53%, 19.61%, 18.02%, 38.30% and 48.98% patients reversed pulmonary fibrosis, respectively. It was observed that Age, BMI, Fever, and Highest PCT were predictive factors for sustaining fibrosis even after 90 days from onset. A predictive model of the persistence with pulmonary fibrosis was developed based-on the Logistic Regression method with an accuracy, PPV, NPV, Sensitivity and Specificity of the model of 76%, 71%, 79%, 67%, and 82%, respectively. More than half of the COVID-19 patients revealed abnormal conditions in lung function after 90 days from onset, and the ratio of abnormal lung function did not differ on a statistically significant level between the fibrotic and non-fibrotic groups.
Conclusions
Persistent pulmonary fibrosis was more likely to develop in patients with older age, higher BMI, severe/critical condition, fever, a longer viral clearance time, pre-existing disease and delayed hospitalization. Fibrosis developed in COVID-19 patients could be reversed in about a third of the patients after 120 days from onset. The pulmonary function of less than half of COVID-19 patients could turn to normal condition after three months from onset. An effective prediction model with an average area under the curve (AUC) of 0.84 was established to predict the persistence of pulmonary fibrosis in COVID-19 patients for early diagnosis.
The playing activity of a football player, taking place in conditions of high-intensity loads, cannot but cause corresponding changes in the work of his organs and systems. The fatigue that arises and progresses during the competition affects the effectiveness of technical and tactical actions of the player. Significant expansion of technical and tactical actions with maximum use of playing space, universalization of players necessitates increasing the requirements for special endurance of football players during competitions. Therefore, it seems legitimate to characterize the new trends that have emerged in football and are directly related to the impact of speed-power endurance on the effectiveness of technical and tactical skills of players.
This chapter reviews the current guidelines on when to perform thoracic imaging in COVID‐19; technical considerations to minimize the risk for transmission while imaging; the appearance of COVID‐19 in the thorax on various imaging modalities, including chest radiography, thoracic computed tomography, lung ultrasound, positron emission tomography/computed tomography and thoracic magnetic resonance imaging; and current guidelines for reporting of the pulmonary findings in COVID‐19.
Spatial resolution in existing chest x-ray (CXR)-based scoring systems for coronavirus disease 2019 (COVID-19) pneumonia is low, and should be increased for better representation of anatomy, and severity of lung involvement. An existing CXR-based system, the Brixia score, was modified to increase the spatial resolution, creating the MBrixia score. The MBrixia score is the sum, of a rule-based quantification of CXR severity on a scale of 0 to 3 in 12 anatomical zones in the lungs. The MBrixia score was applied to CXR images from COVID-19 patients at a single tertiary hospital in the period May 4th–June 5th, 2020. The relationship between MBrixia score, and level of respiratory support at the time of performed CXR imaging was investigated. 37 hospitalized COVID-19 patients with 290 CXRs were identified, 22 (59.5%) were admitted to the intensive care unit and 10 (27%) died during follow-up. In a Poisson regression using all 290 MBrixia scored CXRs, a higher MBrixia score was associated with a higher level of respiratory support at the time of performed CXR. The MBrixia score could potentially be valuable as a quantitative surrogate measurement of COVID-19 pneumonia severity, and future studies should investigate the score’s validity and capabilities of predicting clinical outcomes.
Long-lasting coronavirus disease 2019 (COVID-19) symptoms beyond 12 weeks, the so-called 'long COVID' have been increasingly reported worldwide. Long COVID can be manifested in various forms, and there is an increasing demand for proper assessment and management. However, it is challenging when trying to determine the best-practice standards of care based on the current evidence because there is no internationally agreed clinical definition or clear treatment pathway. Therefore, the present guidelines have been drafted to provide advice on diagnosis and management based on the latest updated available evidence and the consensus of expert opinion. So far, no standard test and drug treatment can be strongly recommended for patients with long COVID because of a lack of evidence. The present guidelines provide advice based on 12 key questions, including appropriate interventions for long COVID that can be used in clinical practice. Continuous careful observation and studies related to long COVID are needed for the long-term impact of COVID-19 and proper management for long COVID to be determined.
Artificial intelligence (AI) methods for the automatic detection and quantification of COVID-19 lesions in chest computed tomography (CT) might play an important role in the monitoring and management of the disease. We organized an international challenge and competition for the development and comparison of AI algorithms for this task, which we supported with public data and state-of-the-art benchmark methods. Board Certified Radiologists annotated 295 public images from two sources (A and B) for algorithms training (n=199, source A), validation (n=50, source A) and testing (n=23, source A; n=23, source B). There were 1,096 registered teams of which 225 and 98 completed the validation and testing phases, respectively. The challenge showed that AI models could be rapidly designed by diverse teams with the potential to measure disease or facilitate timely and patient-specific interventions. This paper provides an overview and the major outcomes of the COVID-19 Lung CT Lesion Segmentation Challenge - 2020.
In recent days, various types of LDHs are used for biomedical functions. Due to the unique structure of LDH, it has a vast area of application. In different biomedical sectors, the application of unimolecular LDHs and various LDH-based nanohybrid materials is increasing day by day. LDH nanoparticles are significant reservoirs and carriers in different biomedical sectors such as cardiovascular drugs, anti-inflammatory drugs, cancer therapeutic agents, vitamins, antioxidants, DNAs, RNAs, antibodies and some proteins. However, the LDH-DRUG nanohybrids have absorptive capacity which can received by the mediated endocytosis process. Furthermore, in recent times LDH materials are noticed because of their uses in vaccine therapy. In bioimaging systems, LDHs are plays an important role to deliver highly sensitive contrasting agents to various targeted cells of the human body. Moreover, in biosensing applications such as several enzymatic and non-enzymatic LDH-based biosensors have been explored toward the detection of different bioactive molecules. Most of the research has been focused on the detection of glucose, dopamine and H2O2. This review encapsulates the topical advancements of LDHs and LDH-based nanoarchitectures in drug delivery, gene therapy, bioimaging and biosensing applications. Also, this review works includes all the proposed synthesis routes.
Our daily experience in a COVID hospital has allowed us to learn about this disease in many of its changing and unusual aspects. Some of these uncommon manifestations, however, appeared more frequently than others, giving shape to a multifaceted COVID-19 disease. This pictorial review has the aim to describe the radiological aspects of atypical presentations and of some complications of COVID-19 disease in adults and children and provide a simple guide for radiologists to become familiar with the multiform aspects of this disease.
Objectives
Diagnostic challenges during the corona virus disease (COVID-19) pandemic forced the radiology regulating body to adopt the use of CT Chest as a triage and diagnostic tool, which was subsequently abandoned. The Royal Wolverhampton hospital followed both protocols. Here, we investigate the evidence behind this decision within the context of surgical admissions during the COVID-19 peak in our hospital.
Methods
Retrospective data collection and analysis of all surgical admissions between the 1st of March to the 31st of May. Data were collected from the radiology and electronic portal looking into patients undergoing CT chest to diagnose the presence of COVID-19 as well as swab results.
Results
Seventy-eight patients fulfilled our inclusion criteria. The scan either confirmed the presence or absence (4, 63 patients) of COVID-19 but was sometimes inconclusive (11 patients). Comparing these to the results of the swabs; CT showed sensitivity 42.86%, Specificity 97.92%, and accuracy 90.91%. In the inconclusive CT report group, chances of having a positive swab result were 45%: None of the scan results changed any of the surgical planning. Lymphocyte count in the context of surgical presentation did not have any statistical significance to predict the presence of COVID-19 (P = .7). Cost implications on our cohort of patients for adding the chest CT is estimated to be around £31 000.
Conclusion
CT Thorax during the pandemic was a good negative predictor but had limited diagnostic value and did not change patient management. Newer, faster techniques of PCR swabs and antibody testing would be a better and cheaper alternative.
Abstract
SARS-CoV-2 infection is characterized by its high contagiousness and unusual potential lethality. Microscopically, diffuse alveolar damage is the main histologic lung injury dominated by alveolar destruction. At the early stage, the authors note non-specific lesions similar to lesions of diffuse alveolar damage. In particular, the alveoli dilated and filled with exudative fibromyxoid material, the thickening of the interalveolar partitions by edema and an essentially mononuclear inflammatory infiltrate with eosinophilic hyaline membranes covering the alveoli. Viral inclusions are not generally found, and at an advanced stage, the installation of pulmonary fibrosis is noted. The place of non-invasive and/or invasive ventilation is undetermined in hypoxemic respiratory failure secondary to SARS-Cov-2 pneumonia, whereas in the most severe cases of COVID-19, the use of oxygenation by extracorporeal membrane is immediate. The cytokine storm in the lungs prompted clinicians to administer immunomodulators, the results of which was a reduction in hospital mortality.
SARS-CoV-2 epidemics has resulted in an unprecedented global health crisis causing a high number of deaths with pneumonia being the most common manifestation. Chest CT is the best imaging modality to identify pulmonary involvement, but unfortunately there are no pathognomonic features for COVID-19 pneumonia, since many other infectious and non-infectious diseases may cause similar alterations. The adoption of artificial intelligence in biomedical imaging has the potential to revolutionize the identification, management, and the patient’s outcome. If adequately validated, it could be used as a support with predictive and prognostic purposes in symptomatic patients but also as a screening test in asymptomatic patients in COVID-19 epidemics. Some studies have already shown the potential adoption of artificial intelligence for detection of COVID-19 infection, or even to differentiate from community-acquired pneumonia, but at present artificial intelligence cannot routinely applied for COVID-19 due to several limitations. This book chapter will first revise the basics of radiomics with a short practical and easy guide for radiologists; then, the main radiological findings of COVID-19 pneumonia will be presented with the most relevant information that are assessed to evaluate extent of the disease; finally, the main current literature on potential clinical application of radiomics and artificial intelligence for COVID-19 will be presented together with limitations and perspectives.
Since the beginning of 2020, coronavirus disease 2019 (COVID-19) has spread throughout China. This study explains the findings from lung computed tomography images of some patients with COVID-19 treated in this medical institution and discusses the difference between COVID-19 and other lung diseases.
Background:
Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients.
Methods:
We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death.
Results:
The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission.
Conclusions:
During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.).
Background
The pneumonia caused by the 2019 novel coronavirus (SARS-CoV-2, also called 2019-nCoV) recently break out in Wuhan, China, and was named as COVID-19. With the spread of the disease, similar cases have also been confirmed in other regions of China. We aimed to report the imaging and clinical characteristics of these patients infected with SARS-CoV-2 in Guangzhou, China.Methods
All patients with laboratory-identified SARS-CoV-2 infection by real-time polymerase chain reaction (PCR) were collected between January 23, 2020, and February 4, 2020, in a designated hospital (Guangzhou Eighth People’s Hospital). This analysis included 90 patients (39 men and 51 women; median age, 50 years (age range, 18–86 years). All the included SARS-CoV-2-infected patients underwent non-contrast enhanced chest computed tomography (CT). We analyzed the clinical characteristics of the patients, as well as the distribution characteristics, pattern, morphology, and accompanying manifestations of lung lesions. In addition, after 1–6 days (mean 3.5 days), follow-up chest CT images were evaluated to assess radiological evolution.FindingsThe majority of infected patients had a history of exposure in Wuhan or to infected patients and mostly presented with fever and cough. More than half of the patients presented bilateral, multifocal lung lesions, with peripheral distribution, and 53 (59%) patients had more than two lobes involved. Of all included patients, COVID-19 pneumonia presented with ground glass opacities in 65 (72%), consolidation in 12 (13%), crazy paving pattern in 11 (12%), interlobular thickening in 33 (37%), adjacent pleura thickening in 50 (56%), and linear opacities combined in 55 (61%). Pleural effusion, pericardial effusion, and lymphadenopathy were uncommon findings. In addition, baseline chest CT did not show any abnormalities in 21 patients (23%), but 3 patients presented bilateral ground glass opacities on the second CT after 3–4 days.ConclusionSARS-CoV-2 infection can be confirmed based on the patient’s history, clinical manifestations, imaging characteristics, and laboratory tests. Chest CT examination plays an important role in the initial diagnosis of the novel coronavirus pneumonia. Multiple patchy ground glass opacities in bilateral multiple lobular with periphery distribution are typical chest CT imaging features of the COVID-19 pneumonia.
Objective:
To analyze the dynamic changes of chest CT images of patients with corona virus disease-19 (COVID-19).
Methods:
Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed.
Results:
The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare, the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%).
Conclusions:
The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.
Background:
A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients.
Methods:
All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not.
Findings:
By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0-58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0-13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα.
Interpretation:
The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies.
Funding:
Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
Background
The ongoing outbreak of the recently emerged novel coronavirus (2019-nCoV) poses a challenge for public health laboratories as virus isolates are unavailable while there is growing evidence that the outbreak is more widespread than initially thought, and international spread through travellers does already occur.AimWe aimed to develop and deploy robust diagnostic methodology for use in public health laboratory settings without having virus material available.Methods
Here we present a validated diagnostic workflow for 2019-nCoV, its design relying on close genetic relatedness of 2019-nCoV with SARS coronavirus, making use of synthetic nucleic acid technology.ResultsThe workflow reliably detects 2019-nCoV, and further discriminates 2019-nCoV from SARS-CoV. Through coordination between academic and public laboratories, we confirmed assay exclusivity based on 297 original clinical specimens containing a full spectrum of human respiratory viruses. Control material is made available through European Virus Archive - Global (EVAg), a European Union infrastructure project.Conclusion
The present study demonstrates the enormous response capacity achieved through coordination of academic and public laboratories in national and European research networks.
Background:
Clostridium difficile causes toxin-mediated nosocomial diarrhea and community-acquired infections; no preventive vaccine is licensed. In this phase 2 study, we explored safety, tolerability, and immunogenicity in older US adults of an investigational bivalent C. difficile vaccine that contains equal dosages of genetically and chemically detoxified toxins A and B.
Methods:
Conducted from July 2015 through March 2017, 855 healthy adults aged 65-85 years from 15 US centers were randomized 3:3:1 to receive vaccine (100 or 200 μg) or placebo at 0, 1, and 6 months (month regimen) or 1, 8, and 30 days (day regimen). Serum toxin A- and B-specific neutralizing antibodies were measured. Participant-reported local reactions (LRs) and systemic events (SEs), adverse events (AEs), serious AEs, newly diagnosed chronic medical conditions, and immediate AEs were recorded.
Results:
The 200-μg dose level elicited higher immune responses than the 100-µg dose level across regimens. Compared with the day regimen, the month regimen induced stronger and more persistent immune responses that remained elevated 12 months after dose 3. Responses peaked at month 7 (month regimen) and day 37 (day regimen). LRs (primarily injection site pain) were more frequent in vaccine recipients than controls; SE frequency was similar across groups. More related AEs were reported in the day regimen group than the month regimen group.
Conclusions:
The C. difficile vaccine was safe, well tolerated, and immunogenic in healthy US adults aged 65-85 years. Immune responses were particularly robust in the 200-μg month regimen group. These results support continued vaccine development.
Clinical trials registration:
NCT02561195.
Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers.
Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention.
We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods.
From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed.
The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
An unexplained pneumonia outbreak at the end of 2019 was found to be associated with a novel coronavirus (SARS-CoV-2). The virus is the seventh known coronavirus that can infect humans. In a short period of time, this coronavirus infection has spread to many regions of the world, causing the concern of countries around the world. At present, related research on SARS-CoV-2 is still in its infancy. This article summarizes the findings of the latest research related to SARS-CoV-2 to provide reference for subsequent research and prevention. © 2020, Editorial Board of Journal of Xi'an Jiaotong University (Medical Sciences). All right reserved.
Objective:
To analyze the dynamic changes of chest CT images of patients with coronavirus disease 2019 (COVID-19).
Methods:
Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed.
Results:
The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare,the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%).
Conclusions:
The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.
Objective: To improve the imaging diagnosis of novel coronavirus disease 2019 (COVID-19) by comparing the chest CT imaging characteristics between COVID-19 and bacterial pneumonia. Methods: CT data of 42 COVID-19 cases from January 16 to February 18, 2020 were retrospectively analyzed, and we also compared with the CT data of 36 cases of bacterial pneumonia collected from November 27, 2017 to February 6, 2020. Results: The incidence of bilateral lobes involvement in COVID-19 group was 73.8%, which was significantly higher than that in bacterial pneumonia group (vs 41.7%, P<0.01). The incidences of ground glass shadow (95.2%), mesh shadow (31.0%), and pavement sign (26.2%) were significantly higher than those of bacterial pneumonia (77.8%, 8.3% and 0, respectively, all P<0.05). The incidences of consolidation (35.7%), and central lobular nodule or tree-bud signs (9.5%) were lower than those of bacterial pneumonia (66.7% and 47.2%, respectively, both P<0.05). Conclusion: In COVID-19 patients, more CT signs such as ground glass shadow, mesh shadow and paved appearance were found than in bacterial pneumonia ones, whereas the consolidation shadow, central lobular nodules and tree-bud signs were less common. © 2020, Editorial Board of Medical Journal of Wuhan University. All right reserved.
Objective: To analyze the CT imaging findings of coronavirus disease 2019 (COVID-19) in Wuhan, China, in order to recognize its imaging diagnosis. Methods: The clinical data and chest CT imaging of 30 COVID-19 patients confirmed by nucleic acid assay for 2019-nCoV (SARS-CoV-2) were retrospectively analyzed. The CT findings of severe cases were compared with those of non-severe cases. Results: Most of the pneumonia lesions were located in bilateral lungs (70%). The main CT features were ground-glass shadow (100%) and consolidation (63%). There were more male patients (60%), and severe cases were more prone to pulmonary consolidation (P<0.05). Conclusion: There are characteristics CT images in COVID-19 cases, and thinner CT scan is necessary for the diagnosis. © 2020, Editorial Board of Medical Journal of Wuhan University. All right reserved.
Objective:
To evaluated the effectiveness and safety of Chinese herbal medicines (CHMs) for coronary heart disease (CHD) complicated with anxiety.
Methods:
Randomized controlled clinical trials (RCTs) with parallel-groups were included after searching through electric-databases from inception to May, 2017. Meta-analysis was undertaken with RevMan 5.3 software.
Results:
Twenty-three RCTs enrolling 1654 patients were included in this systematic review. The combination therapy (CHMs combined with anxiolytic) appeared to be superior to anxiolytic in terms of reducing the score of Zung Self-rating Anxiety scale (SAS) (mean Difference (MD), －12.25; 95% confidence interval (CI), －14.01 to －10.48, eliminating method; MD, －3.92; 95% CI, －5.48 to －2.35, tranquilizing method), improving the total effect rate (relative risk (RR), 1.26; 95% CI, 1.08 to 1.46, eliminating method) and reducing the TCM symptoms scores (MD, －2.24; 95% CI, －4.25 to －0.23, tranquilizing method) with a lower incidence of adverse events (RR, 0.46; 95% CI, 0.25 to 0.85, tonifying method). CHMs demonstrated benefits in lowering the score of Hamilton Anxiety Rating scale (MD, －6.77; 95% CI, －8.16 to －5.37, tonifying method),lowering the score of SAS (MD, －10.1; 95% CI, －13.73 to －6.30, tonifying method) and reducing the TCM symptoms scores (MD, －2.18; 95% CI, －3.12 to －1.24, tranquilizing method).
Conclusion:
We got a low evidence that CHMs,which had less side effects, showed potentially benefits to patients with CHD complicated with anxiety. While the results should be interpreted with caution. Trails with higher quality are required to verify the effectiveness and safety of CHMs for CHD complicated with anxiety.
Objective: To investigate the clinical characteristics of medical staff with novel coronavirus pneumonia(NCP). Methods: 30 patients infected with novel coronavirus referred to jianghan university hospital between January 11, 2020 and January 3, 2020 were studied. The data reviewed included those of clinical manifestations, laboratory investigation and Radiographic features. Results: The patients consisted of 10 men and 20 women, including 22 doctors and 8 nurses,aged 21~59 years(mean 35±8 years).They were divided to 26 common type and 4 severe cases, all of whom had close(within 1m) contact with patients infected of novel coronavirus pneumonia. The average contact times were 12 (7,16) and the average cumulative contact time was 2 (1.5,2.7) h.Clinical symptoms of these patients were fever in 23 patients (76.67%) , headache in 16 petients (53.33%) , fatigue or myalgia in 21patients (70%) , nausea, vomiting or diarrhea in 9 petients (30%) , cough in 25 petients (83.33%) , and dyspnea in 14 petients (46.67%) .Routine blood test revealed WBC<4.0×10(9)/L in 8 petients (26.67%) , (4-10) ×10(9)/L in 22 petients (73.33%) , and WBC>4.0×10(9)/L in 4 petients (13.33%) during the disease.Lymphocyte count<1.0×10(9)/L occurred in 12 petients (40%),abnormal liver function in 7 petients (23.33%) ,myocardial damage in 5 petients(16.67%), elevated D-dimer (>0.5mg/l) in 5 patients (16.67%). Compared with normal patients, the average exposure times, cumulative exposure time, BMI, Fever time, white blood cell count, liver enzyme, LDH, myoenzyme and D-dimer were significantly increased in severe patients, while the lymphocyte count and albumin levels in peripheral blood were significantly decreased.Chest CT mainly showed patchy shadows and interstitial changes.According to imaging examination, 11 patients (36.67%) showed Unilateral pneumonia and 19 patients (63.33%) showed bilateral pneumonia,4 patients (13.33%) showed bilateral multiple mottling and ground-glass opacity.Compared with the patients infected in the protected period, the proportion of severe infection and bilateral pneumonia were both increased in the patients infected in unprotected period. Conclusion: Medical staffs are at higher risk of infection.Infection rates are associated with contact time, the amount of suction virus. Severe patients had BMI increased, heating time prolonged, white blood cell count, lymphocyte count, D-dimer and albumin level significantly changed and were prone to be complicated with liver damage and myocardial damage.Strict protection measures is important to prevent infection for medical workers.
Background
Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described.
Methods
In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death.
Findings
191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/L (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days.
Interpretation
The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/L could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Funding
Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
Objectives:
In late December, 2019, an outbreak of coronavirus disease (COVID-19) in Wuhan, China was caused by a novel coronavirus, newly named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to quantify severity of COVID-19 infection on High-Resolution CT and to determine its relationship with clinical parameters.
Materials and methods:
From Jan 11, 2020, to Feb 5, 2020, the clinical, laboratory and HRCT features of 42 patients (26-75 years, 25 males) with COVID-19 were analyzed. The initial and follow-up CT obtained a mean of 4.5 days and 11.6 days from the illness onset were retrospectively assessed for the severity and progression of pneumonia. Correlations among clinical parameters, initial CT features and progression of opacifications were evaluated with Spearman correlation and linear regression analysis.
Results:
Thirty-five (83%) patients exhibited a progressive process according to CT features during the early stage from onset. Follow-up CT findings showed progressive opacifications, consolidation, interstitial thickening, fibrous strips and air bronchograms, compared to initial CT (all p<0.05). Before regular treatments, there was a moderate correlation between the days from onset and sum score of opacifications (R=0.68, p<0.01). The C-reactive protein, erythrocyte sedimentation rate and lactate dehydrogenase showed significantly positive correlation with the severity of pneumonia assessed on initial CT (R range 0.36-0.75, p<0.05). The highest temperature and the severity of opacifications assessed on initial CT were significantly related to the progression of opacifications on follow-up CT (p=0.001-0.04).
Conclusions:
Patients with the COVID-19 infection usually presented with typical ground-grass opacities and other CT features, which showed significant correlations with some clinical and laboratory measurements. Follow-up CT images often demonstrated progressions during the early stage from illness onset.
OBJECTIVE. The purpose of this study was to investigate 62 subjects in Wuhan, China, with laboratory-confirmed coronavirus disease (COVID-19) pneumonia and describe the CT features of this epidemic disease. MATERIALS AND METHODS. A retrospective study of 62 consecutive patients with laboratory-confirmed COVID-19 pneumonia was performed. CT images and clinical data were reviewed. Two thoracic radiologists evaluated the distribution and CT signs of the lesions and also scored the extent of involvement of the CT signs. The Mann-Whitney U test was used to compare lesion distribution and CT scores. The chi-square test was used to compare the CT signs of early-phase versus advanced-phase COVID-19 pneumonia. RESULTS. A total of 62 patients (39 men and 23 women; mean [± SD] age, 52.8 ± 12.2 years; range, 30-77 years) with COVID-19 pneumonia were evaluated. Twenty-four of 30 patients who underwent routine blood tests (80.0%) had a decreased lymphocyte count. Of 27 patients who had their erythrocyte sedimentation rate and high-sensitivity C-reactive protein level assessed, 18 (66.7%) had an increased erythrocyte sedimentation rate, and all 27 (100.0%) had an elevated high-sensitivity C-reactive protein level. Multiple lesions were seen on the initial CT scan of 52 of 62 patients (83.9%). Forty-eight of 62 patients (77.4%) had predominantly peripheral distribution of lesions. The mean CT score for the upper zone (3.0 ± 3.4) was significantly lower than that for the middle (4.5 ± 3.8) and lower (4.5 ± 3.7) zones (p = 0.022 and p = 0.020, respectively), and there was no significant difference in the mean CT score of the middle and lower zones (p = 1.00). The mean CT score for the anterior area (4.4 ± 4.1) was significantly lower than that for the posterior area (7.7 ± 6.3) (p = 0.003). CT findings for the patients were as follows: 25 patients (40.3%) had ground-glass opacities (GGO), 21 (33.9%), consolidation; 39 (62.9%), GGO plus a reticular pattern; 34 (54.8%), vacuolar sign; 28 (45.2%), microvascular dilation sign; 35 (56.5%), fibrotic streaks; 21 (33.9%), a subpleural line; and 33 (53.2%), a subpleural transparent line. With regard to bronchial changes seen on CT, 45 patients (72.6%) had air bronchogram, and 11 (17.7%) had bronchus distortion. In terms of pleural changes, CT showed that 30 patients (48.4%) had pleural thickening, 35 (56.5%) had pleural retraction sign, and six (9.7%) had pleural effusion. Compared with early-phase disease (≤ 7 days after the onset of symptoms), advanced-phase disease (8-14 days after the onset of symptoms) was characterized by significantly increased frequencies of GGO plus a reticular pattern, vacuolar sign, fibrotic streaks, a subpleural line, a subpleural transparent line, air bronchogram, bronchus distortion, and pleural effusion; however, GGO significantly decreased in advanced-phase disease. CONCLUSION. CT examination of patients with COVID-19 pneumonia showed a mixed and diverse pattern with both lung parenchyma and the interstitium involved. Identification of GGO and a single lesion on the initial CT scan suggested early-phase disease. CT signs of aggravation and repair coexisted in advanced-phase disease. Lesions presented with a characteristic multifocal distribution in the middle and lower lung regions and in the posterior lung area. A decreased lymphocyte count and an increased high-sensitivity C-reactive protein level were the most common laboratory findings.
OBJECTIVE. The objective of our study was to determine the misdiagnosis rate of radiologists for coronavirus disease 2019 (COVID-19) and evaluate the performance of chest CT in the diagnosis and management of COVID-19. The CT features of COVID-19 are reported and compared with the CT features of other viruses to familiarize radiologists with possible CT patterns. MATERIALS AND METHODS. This study included the first 51 patients with a diagnosis of COVID-19 infection confirmed by nucleic acid testing (23 women and 28 men; age range, 26-83 years) and two patients with adenovirus (one woman and one man; ages, 58 and 66 years). We reviewed the clinical information, CT images, and corresponding image reports of these 53 patients. The CT images included images from 99 chest CT examinations, including initial and follow-up CT studies. We compared the image reports of the initial CT study with the laboratory test results and identified CT patterns suggestive of viral infection. RESULTS. COVID-19 was misdiagnosed as a common infection at the initial CT study in two inpatients with underlying disease and COVID-19. Viral pneumonia was correctly diagnosed at the initial CT study in the remaining 49 patients with COVID-19 and two patients with adenovirus. These patients were isolated and obtained treatment. Ground-glass opacities (GGOs) and consolidation with or without vascular enlargement, interlobular septal thickening, and air bronchogram sign are common CT features of COVID-19. The The "reversed halo" sign and pulmonary nodules with a halo sign are uncommon CT features. The CT findings of COVID-19 overlap with the CT findings of adenovirus infection. There are differences as well as similarities in the CT features of COVID-19 compared with those of the severe acute respiratory syndrome. CONCLUSION. We found that chest CT had a low rate of missed diagnosis of COVID-19 (3.9%, 2/51) and may be useful as a standard method for the rapid diagnosis of COVID-19 to optimize the management of patients. However, CT is still limited for identifying specific viruses and distinguishing between viruses.
Objective: To investigate the imaging findings of 2019 novel coronavirus pneumonia (COVID-19). Methods: From January 20 to February 5, 2020, a total of 130 patients diagnosed with COVID-19 from seven hospitals in China were collected. The imaging data were reviewed and analyzed in detail. Results: (1) Distribution: the lesion detected in the lung unilaterally in 14 cases (10.7%) and bilaterally in 116 cases (89.3%). According to the distribution in the lobes of the lung, all cases could be classified into subpleural distribution (102 cases, 78.4%), centrilobular distribution (99 cases, 76.1%) and diffused distribution (8 cases, 6.1%). (2) Number of lesions: single lesion 9 cases (6.9%); multiple lesions 113 cases (86.9%), diffuse lesions 8 cases (6.1%). (3) Imaging density: 70 cases (53.8%) of ground-glass opacity (GGO), 60 cases (46.2%) of GGO + consolidation. (4) Accompanying signs: 100 cases (76.9%) with vascular thickening, 98 cases (75.3%) with "pleural parallel sign" ; "intralobular septal thickening" in 100 cases (76.9%); "halo sign" in 13 cases (10%); "reversed-halo sign" in 6 cases (4.6%); pleural effusion in 3 cases (2.3 %), and pneumatocele in 2 cases (1.5%); no case with pulmonary cavity. Among 35 patients that underwent follow-up CT, 21 patients (60%) improved while 14 (40%) exacerbated. Conclusions: COVID-19 imaging characteristic mainly has subpleural, centrilobular and diffused distribution. The first two distributions can overlap or progress to diffused distribution. In the later period, it was mainly manifested as organizing pneumonia and fibrosis. The most valuable characteristic is the pleural parallel sign.
OBJECTIVE. The increasing number of cases of confirmed coronavirus disease (COVID-19) in China is striking. The purpose of this study was to investigate the relation between chest CT findings and the clinical conditions of COVID-19 pneumonia. MATERIALS AND METHODS. Data on 101 cases of COVID-19 pneumonia were retrospectively collected from four institutions in Hunan, China. Basic clinical characteristics and detailed imaging features were evaluated and compared between two groups on the basis of clinical status: nonemergency (mild or common disease) and emergency (severe or fatal disease). RESULTS. Patients 21-50 years old accounted for most (70.2%) of the cohort, and five (5.0%) patients had disease associated with a family outbreak. Most patients (78.2%) had fever as the onset symptom. Most patients with COVID-19 pneumonia had typical imaging features, such as ground-glass opacities (GGO) (87 [86.1%]) or mixed GGO and consolidation (65 [64.4%]), vascular enlargement in the lesion (72 [71.3%]), and traction bronchiectasis (53 [52.5%]). Lesions present on CT images were more likely to have a peripheral distribution (88 [87.1%]) and bilateral involvement (83 [82.2%]) and be lower lung predominant (55 [54.5%]) and multifocal (55 [54.5%]). Patients in the emergency group were older than those in the non-emergency group. Architectural distortion, traction bronchiectasis, and CT involvement score aided in evaluation of the severity and extent of the disease. CONCLUSION. Patients with confirmed COVID-19 pneumonia have typical imaging features that can be helpful in early screening of highly suspected cases and in evaluation of the severity and extent of disease. Most patients with COVID-19 pneumonia have GGO or mixed GGO and consolidation and vascular enlargement in the lesion. Lesions are more likely to have peripheral distribution and bilateral involvement and be lower lung predominant and multifocal. CT involvement score can help in evaluation of the severity and extent of the disease.
Objective:
To investigate the clinical and CT features associated with severe and critical Corona Virus Disease 2019 (COVID-19) pneumonia.
Materials and methods:
Eighty-three patients with COVID-19 pneumonia including 25 severe/critical cases and 58 ordinary cases were enrolled. The chest CT images and clinical data of them were reviewed and compared. The risk factors associated with disease severity were analyzed.
Results:
Compared with the ordinary patients, the severe/critical patients had older ages, higher incidence of comorbidities, cough, expectoration, chest pain and dyspnea. The incidences of consolidation, linear opacities, crazy-paving pattern and bronchial wall thickening in severe/critical patients were significantly higher than those of the ordinary patients. Besides, severe/critical patients showed higher incidences of lymph node enlargement, pericardial effusion and pleural effusion than the ordinary patients. The CT scores of severe/critical patients were significantly higher than those of the ordinary patients (P < 0.001). Receiver operating characteristic (ROC) curve showed that the sensitivity and specificity of CT Score were 80.0% and 82.8% respectively for the discrimination of the two types. The clinical factors of age > 50 years old, comorbidities, dyspnea, chest pain, cough, expectoration, decreased lymphocytes and increased inflammation indicators were risk factors for severe/critical COVID-19 pneumonia. CT findings of consolidation, linear opacities, crazy-paving pattern, bronchial wall thickening, high CT scores and extrapulmonary lesions were features of severe/critical COVID-19 pneumonia.
Conclusions:
There are significant differences in clinical symptoms, laboratory examinations and CT manifestations between the ordinary patients and the severe/critical patients. Many factors are related to the severity of the disease, which can help clinicians to judge the severity of the patient and evaluate the prognosis.
Background:
We aimed to report the clinical characteristics of imported coronavirus disease-19 (COVID-19) in Jiangsu Province.
Methods:
We retrospectively investigated the clinical, imaging, and laboratory characteristics of confirmed cases of COVID-19 with WHO interim guidance in three Grade ⅢA hospitals of Jiangsu from Jan 22 to Feb 14, 2020. Real time RT-PCR was used to detect the new coronavirus in respiratory samples.
Results:
Of the 80 patients infected with COVID-19, 41 patients were female, with a median age of 46.1 years. Except for 3 severe patients, the rest of the 77 patients exhibited mild or moderate symptoms. 9 patients were unconfirmed until a third-time nucleic acid test. 38 cases had a history of chronic diseases. The main clinical manifestations of the patients were fever and cough, which accounted for 63 cases (78.75%) and 51 cases (-63.75%) respectively. Only 3 patients (3.75%) showed liver dysfunction. Imaging examination showed that 55 patients (-68.75%) showed abnormal, 25 cases (31.25%) had no abnormal density shadow in the parenchyma of both lungs. Up to now, 21 cases were discharged from the hospital, and no patient died. The average length of stay for discharged patients was 8 days.
Conclusions:
Compared with the cases in Wuhan, the cases in Jiangsu exhibited mild or moderate symptoms and no obvious gender susceptivity. The proportion of patients having liver dysfunction and abnormal CT imaging was relatively lower than that of Wuhan. Notably, infected patients may be falsely excluded based on two consecutively negative respiratory pathogenic nucleic acid test results.
Background
Little is known about COVID-19 outside Hubei. The aim of this paper was to describe the clinical characteristics and imaging manifestations of hospitalized patients with confirmed COVID-19 infection in Wenzhou, Zhejiang, China.
Methods
In this retrospective cohort study, 149 RT-PCR confirmed positive patients were consecutively enrolled from January 17th to February 10th, 2020 in three tertiary hospitals of Wenzhou. Outcomes were followed up until Feb 15th, 2020.
Findings
A total of 85 patients had Hubei travel/residence history, while another 49 had contact with people from Hubei and 15 had no traceable exposure history to Hubei. Fever, cough and expectoration were the most common symptoms, 14 patients had decreased oxygen saturation, 33 had leukopenia, 53 had lymphopenia, and 82 had elevated C reactive protein. On chest computed tomography, lung segments 6 and 10 were mostly involved. A total of 287 segments presented ground glass opacity, 637 presented mixed opacity and 170 presented consolidation. Lesions were more localized in the peripheral lung with a patchy form. No significant difference was found between patients with or without Hubei exposure history. Seventeen patients had normal CT on admission of these, 12 had negative findings even10 days later.
Interpretation
Most patients presented with a mild infection in our study. The imaging pattern of multifocal peripheral ground glass or mixed opacity with predominance in the lower lung is highly suspicious of COVID-19 in the first week of disease onset. Nevetheless, some patients can present with a normal chest finding despite testing positive for COVID-19. Funding: We did not receive any fundings.
Background:
A cluster of patients with coronavirus disease 2019 (COVID-19) pneumonia caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were successively reported in Wuhan, China. We aimed to describe the CT findings across different timepoints throughout the disease course.
Methods:
Patients with COVID-19 pneumonia (confirmed by next-generation sequencing or RT-PCR) who were admitted to one of two hospitals in Wuhan and who underwent serial chest CT scans were retrospectively enrolled. Patients were grouped on the basis of the interval between symptom onset and the first CT scan: group 1 (subclinical patients; scans done before symptom onset), group 2 (scans done ≤1 week after symptom onset), group 3 (>1 week to 2 weeks), and group 4 (>2 weeks to 3 weeks). Imaging features and their distribution were analysed and compared across the four groups.
Findings:
81 patients admitted to hospital between Dec 20, 2019, and Jan 23, 2020, were retrospectively enrolled. The cohort included 42 (52%) men and 39 (48%) women, and the mean age was 49·5 years (SD 11·0). The mean number of involved lung segments was 10·5 (SD 6·4) overall, 2·8 (3·3) in group 1, 11·1 (5·4) in group 2, 13·0 (5·7) in group 3, and 12·1 (5·9) in group 4. The predominant pattern of abnormality observed was bilateral (64 [79%] patients), peripheral (44 [54%]), ill-defined (66 [81%]), and ground-glass opacification (53 [65%]), mainly involving the right lower lobes (225 [27%] of 849 affected segments). In group 1 (n=15), the predominant pattern was unilateral (nine [60%]) and multifocal (eight [53%]) ground-glass opacities (14 [93%]). Lesions quickly evolved to bilateral (19 [90%]), diffuse (11 [52%]) ground-glass opacity predominance (17 [81%]) in group 2 (n=21). Thereafter, the prevalence of ground-glass opacities continued to decrease (17 [57%] of 30 patients in group 3, and five [33%] of 15 in group 4), and consolidation and mixed patterns became more frequent (12 [40%] in group 3, eight [53%] in group 4).
Interpretation:
COVID-19 pneumonia manifests with chest CT imaging abnormalities, even in asymptomatic patients, with rapid evolution from focal unilateral to diffuse bilateral ground-glass opacities that progressed to or co-existed with consolidations within 1-3 weeks. Combining assessment of imaging features with clinical and laboratory findings could facilitate early diagnosis of COVID-19 pneumonia.
Funding:
None.
Purpose:
To investigate the clinical and imaging characteristics of computed tomography (CT) in novel coronavirus pneumonia (NCP) caused by SARS-CoV-2.
Materials and methods:
A retrospective analysis was performed on the imaging findings of patients confirmed with COVID-19 pneumonia who had chest CT scanning and treatment after disease onset. The clinical and imaging data were analyzed.
Results:
Fifty patients were enrolled, including mild type in nine, common in 28, severe in 10 and critically severe in the rest three. Mild patients (29 years) were significantly (P<0.03) younger than either common (44.5 years) or severe (54.7) and critically severe (65.7 years) patients, and common patients were also significantly (P<0.03) younger than severe and critically severe patients. Mild patients had low to moderate fever (<39.1°C), 49 (98%) patients had normal or slightly reduced leukocyte count, 14 (28%) had decreased counts of lymphocytes, and 26 (52%) patients had increased C-reactive protein. Nine mild patients were negative in CT imaging. For all the other types of NCP, the lesion was in the right upper lobe in 30 cases, right middle lobe in 22, right lower lobe in 39, left upper lobe in 33 and left lower lobe in 36. The lesion was primarily located in the peripheral area under the pleura with possible extension towards the pulmonary hilum. Symmetrical lesions were seen in 26 cases and asymmetrical in 15. The density of lesion was mostly uneven with ground glass opacity as the primary presentation accompanied by partial consolidation and fibrosis.
Conclusion:
CT imaging presentations of NCP are mostly patchy ground glass opacities in the peripheral areas under the pleura with partial consolidation which will be absorbed with formation of fibrotic stripes if improved. CT scanning provides important bases for early diagnosis and treatment of NCP.
Objectives:
To investigate the chest computed tomography (CT) findings in patients with confirmed corona virus disease 2019 (COVID-19) and to evaluate its relationship with clinical features.
Materials and methods:
Study sample consisted of 80 patients diagnosed as COVID-19 from January to February 2020. The chest CT images and clinical data were reviewed and the relationship between them was analyzed.
Results:
Totally 80 patients diagnosed with COVID-19 were included. With regards to the clinical manifestations, 58/80 (73%) of patients had cough, 61/80 (76%) of patients had high temperature levels. The most frequent CT abnormalities observed were ground glass opacity (GGO) (73/80 cases, 91%), consolidation (50/80 cases, 63%) and interlobular septal thickening (47/80, 59%). Most of the lesions were multiple, with an average of 12±6 lung segments involved. The most common involved lung segments were the dorsal segment of the right lower lobe (69/80, 86%), the posterior basal segment of the right lower lobe (68/80, 85%), the lateral basal segment of the right lower lobe (64/80, 80%), the dorsal segment of the left lower lobe (61/80, 76%) and the posterior basal segment of the left lower lobe (65/80, 81%). The average pulmonary inflammation index (PII) value was (34%±20%) for all the patients. Correlation analysis showed that the PII value was significantly correlated with the values of lymphocyte count, monocyte count, C-reactive protein, procalcitonin, days from illness onset and body temperature (p<0.05).
Conclusion:
The common chest CT findings of COVID-19 are multiple GGO, consolidation and interlobular septal thickening in both lungs, which are mostly distributed under the pleura. There are significant correlations between the degree of pulmonary inflammation and the main clinical symptoms and laboratory results. CT plays an important role in the diagnosis and evaluation of this emerging global health emergency.
The purpose of this case report is to describe the imaging and associated clinical features of an asymptomatic novel coronavirus pneumonia (COVID-19) patient outside Wuhan, China. The principle findings are that in this patient with laboratory-confirmed COVID-19, CT findings preceded symptoms and included bilateral pleural effusions, previously not reported in association with COVID-19. The role of this case report is promotion of potential recognition amongst radiologists of this new disease, which has been declared a global health emergency by the World Health Organization (WHO).
In this retrospective study, chest CTs of 121 symptomatic patients infected with coronavirus disease-19 (COVID-19) from four centers in China from January 18, 2020 to February 2, 2020 were reviewed for common CT findings in relationship to the time between symptom onset and the initial CT scan (i.e. early, 0-2 days (36 patients), intermediate 3-5 days (33 patients), late 6-12 days (25 patients)). The hallmarks of COVID-19 infection on imaging were bilateral and peripheral ground-glass and consolidative pulmonary opacities. Notably, 20/36 (56%) of early patients had a normal CT. With a longer time after the onset of symptoms, CT findings were more frequent, including consolidation, bilateral and peripheral disease, greater total lung involvement, linear opacities, "crazy-paving" pattern and the "reverse halo" sign. Bilateral lung involvement was observed in 10/36 early patients (28%), 25/33 intermediate patients (76%), and 22/25 late patients (88%).