scholarly journals Key Points of Clinical and CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV) Imported Pneumonia Based On 21 Cases Analysis

2020 ◽  
Author(s):  
Z.F. Xu ◽  
W.X. Wu ◽  
Y.B. Jin ◽  
A.Z. Pan
Keyword(s):  
Clinical Manifestations ◽  
Ct Imaging ◽  
Chest Ct ◽  
Imaging Features ◽  
Shortness Of Breath ◽  
Multiple Lesions ◽  
Reticular Pattern ◽  
Severe Group ◽  
Novel Coronavirus ◽  
Ct Features

AbstractBackground and ObjectiveWHO Director-General declared that the 2019-nCoV outbreak constitutes a Public Health Emergency of International Concern,and the outbreak is still on-going.Chest CT had been a key component of the diagnostic workup for patients with suspected infection. In this retrospective study, we attempt to summarize and analyze the chest CT features of 2019-nCov infections, and to identify the typical features to improved the diagnostic accuracy of new coronavirus pneumonia (NCP).MethodsChest CT scans and Clinical data of 21 patients confirmed NCP in our hospital were enrolled.These patients were divided into mild and sever group according to clinical manifestations described by the 6th clinical practice guideline of NCP in China. Main clinical and chest CT features were analyzed and identify.ResultsFever (85.7%) and cough (80.9%) were the two main symptoms of NCP patients.More significantly higher incidence (85.7%) of shortness of breath in the severe cases. Multiple lesions in both lungs and with incidence of GGO(100%),vascular enlargement (76.5%) and cobblestone/reticular pattern(70.6%) were the major feature.The incidence of consolidation, mixed pattern and vascular enlargement features were up to 100% in the severe group, significantly higher than that of patients in mild group. In addition, the incidence of air-bronchogram, dilated bronchi with thickened wall and fibrosis in the severe group was significantly higher than that in the mild group.ConclusionsFever and cough are the typical clinical features of NCP patients, and chest CT mainly manifested as multiple lesions in both lungs, often accompanied by GGO, vascular enlargement and cobblestone/reticular pattern.Changes in these main CT features can indicate development of the diseaseSummary2019 novel Coronavirus (2019-nCov) had typical clinical manifestations (fever and cough), and presented with characteristic chest CT imaging features (multiple lesions in both lungs, often accompanied by GGO, vascular enlargement and cobblestone/reticular pattern), which are helpful to the radiologist in the early detection and diagnosis of this emerging global health emergency. In addition, changes in these main CT features can indicate development of the disease.HighlightsFever (85.7%) and cough (80.9%) were the two main symptoms of NCP patients.The incidence of shortness of breath was 85.7% in the severe cases, significantly higher than 21.4% in the mild cases.Multiple lesions in both lungs and with incidence of GGO (100%), vascular enlargement (76.5%) and cobblestone/reticular pattern (70.6%) were the major features of NCP patients. 85.7% of cases in serve group displayed 4-5 lobes were involved simultaneously.Changes in these main CT imaging features can indicate development of the disease. About 19.1% of patients (4 of 21) presented with a normal CT.

scholarly journals Clinical Characteristics and CT Manifestations of 143 Patients With 2019 Novel Coronavirus Disease (COVID-19) in Taizhou City, Zhejiang, China

2020 ◽  
Author(s):  
Yani Kuang ◽  
Susu He ◽  
Shuangxiang Lin ◽  
Rui Zhu ◽  
Rongzhen Zhou ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Protein A ◽  
Clinical Manifestations ◽  
Imaging Features ◽  
First Case ◽  
Severe Group ◽  
Laboratory Examinations ◽  
The Difference ◽  
Severity Of The Disease ◽  
Novel Coronavirus

Abstract Background: In December 2019, the first case of pneumonia associated with the SARS-CoV-2 was found in Wuhan and rapidly spread throughout China, so data are needed on the affected patients. The purpose of our study was to find the clinical manifestations and CT features of COVID-19.Methods: All patients with COVID-19 in Taizhou city were retrospectively included and divided into non-severe group and severe group according to the severity of the disease. The clinical manifestations, laboratory examinations and imaging features of COVID-19 patients were analyzed, and the differences between the two groups were compared.Results: A total of 143 laboratory-confirmed cases were included in the study, including 110 non-severe patients and 33 severe patients. The median age of patients was 47 (range 4–86 years). Fever (73.4%) and cough (63.6%) were the most common initial clinical symptoms. Between two groups of cases, the results of aspartate transaminase, creatine kinase and lactate dehydrogenase, serum albumin, CR, glomerular filtration rate, amyloid protein A, fibrinogen, calcitonin level and oxygen partial pressure, IL – 10, absolute value of CD3, CD4, CD8 were different, and the difference was statistically significant (P < 0.05). Therefore, these quantitative indicators can be used to help assess the severity. On admission, the CT showed that the lesions were mostly distributed in the periphery of the lung or subpleural (135 cases (98%)), and most of lesions presented as patchy (81%), mixed density (63%) shadow. Consolidation (68% vs 41%), bronchial inflation signs (59% vs 41%), and bronchiectasis (71% vs 39%) were more common in the severe group.Conclusions: Most of the cases of COVID-19 in Taizhou have mild symptoms and no death. In addition to clinical symptoms, some laboratory tests (such as absolute values of CD4 and CD8) and CT findings can be used to assess the severity of the disease.

scholarly journals CT Findings in a Novel Coronavirus Disease (COVID-19) Pneumonia at Initial Presentation

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Chao Xiang ◽  
Ji Lu ◽  
Jun Zhou ◽  
Li Guan ◽  
Cheng Yang ◽  
...  
Keyword(s):  
Left Lung ◽  
Lower Lobe ◽  
Ground Glass Opacity ◽  
Initial Presentation ◽  
Ground Glass ◽  
Imaging Features ◽  
Reticular Pattern ◽  
Novel Coronavirus ◽  
Age Range ◽  
Ct Features

Background. COVID-19 first broke out in China and spread rapidly over the world. Objectives. To describe the CT features of COVID-19 pneumonia and to share our experience at initial diagnoses. Patients and Methods. Data from 53 patients (31 men, 22 women; mean age, 53 years; age range, 16-83 years) with confirmed COVID-19 pneumonia were collected. Their complete clinical data was reviewed, and their CT features were recorded and analyzed. Results. The average time between onset of illness and the initial CT scan was six days (range, 1-42 days). A total of 399 segments were involved and distributed bilaterally (left lung: 186 segments [46.6%], right lung: 213 segments [53.4%]) and peripherally (38 [71.7%] patients). Multiple lobes (45 [84.9%]) and bilateral lower lobes (left lower lobe: 104 [26.1%], right lower lobe: 107 [26.8%], and total: 211 [52.9%]) were the most commonly involved. Ground-glass opacity with consolidation (24 [45.3%]) and pure ground-glass opacity (28 [52.8%]) were the main findings. The other findings were crazy-paving (14 [26.4%]), bronchiectasis (12 [22.6%]), atelectasis (7 [13.2%]), parenchymal bands (6 [11.3%]), air bronchogram (6 [11.3%]), interlobular thickening (5 [9.4%]), reticular pattern (1 [1.9%]), and pleural effusion (1 [1.9%]). Conclusions. Most COVID-19 pneumonia patients had abnormalities on chest CT images at initial presentation. Imaging features combined with patient’s exposure history and onset symptoms could facilitate the identification of the suspected patient for further examinations.

scholarly journals Clinical Characteristics and CT Manifestations of 143 Patients With 2019 Novel Coronavirus Disease (COVID-19) in Taizhou City, Zhejiang, China

2020 ◽  
Author(s):  
Yani Kuang ◽  
Susu He ◽  
Shuangxiang Lin ◽  
Rui Zhu ◽  
Rongzhen Zhou ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Protein A ◽  
Clinical Manifestations ◽  
Imaging Features ◽  
First Case ◽  
Severe Group ◽  
Laboratory Examinations ◽  
The Difference ◽  
Severity Of The Disease ◽  
Novel Coronavirus

Abstract Background In December 2019, the first case of pneumonia associated with the SARS-CoV-2 was found in Wuhan and rapidly spread throughout China, so data are needed on the affected patients. The purpose of our study was to find the clinical manifestations and CT features of COVID-19.Methods All patients with COVID-19 in Taizhou city were retrospectively included and divided into non-severe group and severe group according to the severity of the disease. The clinical manifestations, laboratory examinations and imaging features of COVID-19 patients were analyzed, and the differences between the two groups were compared.Results A total of 143 laboratory-confirmed cases were included in the study, including 110 non-severe patients and 33 severe patients. The median age of patients was 47 (range 4–86 years). Fever (73.4%) and cough (63.6%) were the most common initial clinical symptoms. Between two groups of cases, the results of aspartate transaminase, creatine kinase and lactate dehydrogenase, serum albumin, CPR, glomerular filtration rate, amyloid protein A, fibrinogen, calcitonin level and oxygen partial pressure, red protein, IL – 10, absolute value of CD3, CD4, CD8 were different, and the difference was statistically significant (P < 0.05). On admission, the CT showed that the lesions were mostly distributed in the external lung or under the pleura (135 cases (98%)), and most of lesions presented as patchy (81%), heterogeneous (73%) and mixed density (63%) shadow. Consolidation (68% vs 41%), bronchial inflation signs (59% vs 41%), and bronchiectasis (71% vs 39%) were more common in the severe group.Conclusions Most of the cases of COVID-19 in Taizhou have mild symptoms and no death. In addition to clinical symptoms, some laboratory tests (such as absolute values of CD4 and CD8) and CT findings can be used to assess the severity of the disease.

CT Imaging Features of Patients Infected with 2019 Novel Coronavirus

2021 ◽  
Author(s):  
Tianhong Yao ◽  
Huirong Lin ◽  
Jingsong Mao ◽  
Shuaidong Huo ◽  
Gang Liu
Keyword(s):  
Ct Imaging ◽  
Chest Ct ◽  
Imaging Features ◽  
Ct Diagnosis ◽  
Clinical Value ◽  
Computed Tomographic ◽  
Coronavirus Infection ◽  
Novel Coronavirus ◽  
Reference Document ◽  
Pulmonary Ct

Novel coronavirus pneumonia is an acute, infectious pneumonia caused by a novel coronavirus infection. Computed tomographic (CT) imaging is one of the main methods to screen and diagnose patients with this disease. Here, the importance and clinical value of chest CT examination in the diagnosis of COVID-19 is expounded, and the pulmonary CT findings of COVID-19 patients in different stages are briefly summarized, thus providing a reference document for the CT diagnosis of COVID-19 patients.

scholarly journals A retrospective study of the initial chest CT imaging findings in 50 COVID-19 patients stratified by gender and age

2020 ◽  
Vol 28 (5) ◽  
pp. 875-884
Author(s):  
Qianbiao Gu ◽  
Xin Ouyang ◽  
An Xie ◽  
Xianzheng Tan ◽  
Jianbin Liu ◽  
...  
Keyword(s):  
Clinical Manifestations ◽  
Disease Diagnosis ◽  
Ct Images ◽  
Ct Imaging ◽  
Chest Ct ◽  
Elderly Group ◽  
Imaging Features ◽  
Imaging Findings ◽  
Gender And Age ◽  
Honeycomb Pattern

OBJECTIVE: To retrospectively analyze and stratify the initial clinical features and chest CT imaging findings of patients with COVID-19 by gender and age. METHODS: Data of 50 COVID-19 patients were collected in two hospitals. The clinical manifestations, laboratory examination and chest CT imaging features were analyzed, and a stratification analysis was performed according to gender and age [younger group: <50 years old, elderly group ≥50 years old]. RESULTS: Most patients had a history of epidemic exposure within 2 weeks (96%). The main clinical complaints are fever (54%) and cough (46%). In chest CT images, ground-glass opacity (GGO) is the most common feature (37/38, 97%) in abnormal CT findings, with the remaining 12 patients (12/50, 24%) presenting normal CT images. Other concomitant abnormalities include dilatation of vessels in lesion (76%), interlobular thickening (47%), adjacent pleural thickening (37%), focal consolidation (26%), nodules (16%) and honeycomb pattern (13%). The lesions were distributed in the periphery (50%) or mixed (50%). Subgroup analysis showed that there was no difference in the gender distribution of all the clinical and imaging features. Laboratory findings, interlobular thickening, honeycomb pattern and nodules demonstrated remarkable difference between younger group and elderly group. The average CT score for pulmonary involvement degree was 5.0±4.7. Correlation analysis revealed that CT score was significantly correlated with age, body temperature and days from illness onset (p < 0.05). CONCLUSIONS: COVID-19 has various clinical and imaging appearances. However, it has certain characteristics that can be stratified. CT plays an important role in disease diagnosis and early intervention.

scholarly journals Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaohua Ban ◽  
Xinping Shen ◽  
Huijun Hu ◽  
Rong Zhang ◽  
Chuanmiao Xie ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Roc Curve ◽  
Multinomial Logistic Regression ◽  
Univariate Analysis ◽  
Ct Imaging ◽  
Squamous Cell Carcinomas ◽  
Curve Analysis ◽  
Imaging Features ◽  
Roc Curve Analysis ◽  
Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

scholarly journals Clinical and radiological imaging as prognostic predictors in COVID-19 patients

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Maha Ibrahim Metwally ◽  
Mohammad Abd Alkhalik Basha ◽  
Mohamed M. A. Zaitoun ◽  
Housseini Mohamed Abdalla ◽  
Hanaa Abu Elazayem Nofal ◽  
...  
Keyword(s):  
Oxygen Saturation ◽  
Old Age ◽  
Fatal Outcome ◽  
Age Groups ◽  
Lower Lobe ◽  
Chest Ct ◽  
Imaging Features ◽  
Age Group ◽  
Significant Relation ◽  
Ct Features

Abstract Background Since the announcement of COVID-19 as a pandemic infection, several studies have been performed to discuss the clinical picture, laboratory finding, and imaging features of this disease. The aim of this study is to demarcate the imaging features of novel coronavirus infected pneumonia (NCIP) in different age groups and outline the relation between radiological aspect, including CT severity, and clinical aspect, including age, oxygen saturation, and fatal outcome. We implemented a prospective observational study enrolled 299 laboratory-confirmed COVID-19 patients (169 males and 130 females; age range = 2–91 years; mean age = 38.4 ± 17.2). All patients were submitted to chest CT with multi-planar reconstruction. The imaging features of NCIP in different age groups were described. The relations between CT severity and age, oxygen saturation, and fatal outcome were evaluated. Results The most predominant CT features were bilateral (75.4%), posterior (66.3%), pleural-based (93.5%), lower lobe involvement (89.8%), and ground-glass opacity (94.7%). ROC curve analysis revealed that the optimal cutoff age that was highly exposed to moderate and severe stages of NCIP was 38 years old (AUC = 0.77, p < 0.001). NCIP was noted in 42.6% below 40-year-old age group compared to 84% above 40-year-old age group. The CT severity was significantly related to age and fatal outcome (p < 0.001). Anterior, centrilobular, hilar, apical, and middle lobe involvements had a significant relation to below 90% oxygen saturation. A significant negative correlation was found between CT severity and oxygen saturation (r = − 0.49, p < 0.001). Crazy-paving pattern, anterior aspect, hilar, centrilobular involvement, and moderate and severe stages had a statistically significant relation to higher mortality. Conclusion The current study confirmed the value of CT as a prognostic predictor in NCIP through demonstration of the strong relation between CT severity and age, oxygen saturation, and the fatal outcome. In the era of COVID-19 pandemic, this study is considered to be an extension to other studies discussing chest CT features of COVID-19 in different age groups with demarcation of the relation of chest CT severity to different pattern and distribution of NCIP, age, oxygen saturation, and mortality rate.

scholarly journals Quantitative CT imaging features for COVID-19 evaluation: The ability to differentiate COVID-19 from non- COVID-19 (highly suspected) pneumonia patients during the epidemic period

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0256194
Author(s):  
Shengkun Peng ◽  
Lingai Pan ◽  
Yang Guo ◽  
Bo Gong ◽  
Xiaobo Huang ◽  
...  
Keyword(s):  
Volume Ratio ◽  
Ct Imaging ◽  
Lesion Volume ◽  
Component Ratio ◽  
Imaging Features ◽  
Quantitative Ct ◽  
Epidemic Period ◽  
Significant Difference ◽  
Sensitivity Specificity ◽  
Ct Features

Objectives COVID-19 and Non-Covid-19 (NC) Pneumonia encountered high CT imaging overlaps during pandemic. The study aims to evaluate the effectiveness of image-based quantitative CT features in discriminating COVID-19 from NC Pneumonia. Materials and methods 145 patients with highly suspected COVID-19 were retrospectively enrolled from four centers in Sichuan Province during January 23 to March 23, 2020. 88 cases were confirmed as COVID-19, and 57 patients were NC. The dataset was randomly divided by 3:2 into training and testing sets. The quantitative CT radiomics features were extracted and screened sequentially by correlation analysis, Mann-Whitney U test, the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and backward stepwise LR with minimum AIC methods. The selected features were used to construct the LR model for differentiating COVID-19 from NC. Meanwhile, the differentiation performance of traditional quantitative CT features such as lesion volume ratio, ground glass opacity (GGO) or consolidation volume ratio were also considered and compared with Radiomics-based method. The receiver operating characteristic curve (ROC) analysis were conducted to evaluate the predicting performance. Results Compared with traditional CT quantitative features, radiomics features performed best with the highest Area Under Curve (AUC), sensitivity, specificity and accuracy in the training (0.994, 0.942, 1.0 and 0.965) and testing sets (0.977, 0.944, 0.870, 0.915) (Delong test, P < 0.001). Among CT volume-ratio based models using lesion or GGO component ratio, the model combining CT lesion score and component ratio performed better than others, with the AUC, sensitivity, specificity and accuracy of 0.84, 0.692, 0.853, 0.756 in the training set and 0.779, 0.667, 0.826, 0.729 in the testing set. The significant difference of the most selected wavelet transformed radiomics features between COVID-19 and NC might well reflect the CT signs. Conclusions The differentiation between COVID-19 and NC could be well improved by using radiomics features, compared with traditional CT quantitative values.

scholarly journals Clinicopathological and imaging features of pulmonary alveolar microlithiasis in a dog – a case report

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Ana Canadas Sousa ◽  
Joana C. Santos ◽  
Clara Landolt ◽  
Catarina Gomes ◽  
Patrícia Dias-Pereira ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Case Report ◽  
Ground Glass Opacity ◽  
Imaging Features ◽  
Ct Guided ◽  
Pulmonary Alveolar Microlithiasis ◽  
Reticular Pattern ◽  
Pulmonary Parenchyma ◽  
Alveolar Microlithiasis ◽  
Ct Features

Abstract Background The aetiology of pulmonary alveolar microlithiasis (PAM) in animals is still unknown. In humans, this pulmonary disorder is a rare autosomal recessive disorder triggered by a mutation in the gene SLC34A2, which causes deposition and aggregation of calcium and phosphate in the pulmonary parenchyma with formation of microliths. Although histopathological examination is required for a definite diagnosis, in humans, imaging modalities such as computed tomography can demonstrate typical patterns of the disease. This is the first description of the computed tomographic (CT) features of a histologically confirmed PAM in dogs. Case presentation The following report describes a case of a 7-year-old female Boxer dog evaluated for paroxysmal loss of muscle tone and consciousness with excitement. The main differential diagnoses considered were syncope, seizures, and narcolepsy-cataplexy. The results of the complete blood count, serum biochemistry panel, urinalysis, arterial blood pressure, echocardiography, abdominal ultrasound, Holter monitoring, and ECG were all within normal limits. Additional exams included thoracic radiographs, head and thorax CT, bronchoalveolar lavage (BAL), and CT-guided cytology. Thoracic radiographs revealed micronodular calcifications in the lungs, with sandstorm appearance. Computed tomography of the thorax showed the presence of numerous mineralized high-density agglomerates of multiple sizes throughout the pulmonary parenchyma, a reticular pattern with ground glass opacity and intense mineralized fibrosis of the pleural lining. Head CT was unremarkable. BAL and CT-guided cytology were inconclusive, but imaging features strongly suggest the diagnosis of PAM, which was histologically confirmed after necropsy. Conclusions This case report contributes to the clinicopathological and imaging characterization of pulmonary alveolar microlithiasis in dogs. In this species, the diagnosis of PAM should be considered when CT features evidence a reticular pattern with ground glass opacity and the presence of an elevated number and size of calcifications.

scholarly journals Early chest computed tomography to diagnose COVID-19 from suspected patients: A multicenter retrospective study

2020 ◽  
Author(s):  
Congliang Miao ◽  
Mengdi Jin ◽  
Li Miao ◽  
Xinying Yang ◽  
Peng Huang ◽  
...  
Keyword(s):  
Ground Glass Opacity ◽  
High Specificity ◽  
Diagnostic Value ◽  
Chest Ct ◽  
Imaging Features ◽  
Rt Pcr ◽  
Polymerase Chain ◽  
Low Sensitivity ◽  
Chest Ct Scan ◽  
Ct Features

AbstractObjectiveThe purpose of this study is to distinguish the imaging features of COVID-19 with other chest infectious diseases and evaluate diagnostic value of chest CT for suspected patients.MethodsAdult suspected patients aged>18 years within 14 days who underwent chest CT scan and reverse-transcription polymerase-chain-reaction (RT-PCR) tests were enrolled. The enrolled patients were confirmed and grouped according to results of RT-PCR tests. The data of basic demographics, single chest CT features, and combined chest CT features were analyzed for confirmed and non-confirmed groups.ResultsA total of 130 patients were enrolled with 54 cases positive and 76 cases negative. The typical CT imaging features of positive group were ground glass opacity (GGO), crazy-paving pattern and air bronchogram. The lesions were mostly distributed bilaterally, close to the lower lungs or the pleura. When features combined, GGO with bilateral pulmonary distribution and GGO with pleural distribution were more common, of which were 31 cases (57.4%) and 30 cases (55.6%) respectively. The combinations were almost presented statistically significant (P<0.05) except for the combination of GGO with consolidation. Most combinations presented relatively low sensitivity but extremely high specificity. The average specificity of these combinations is around 90%.ConclusionsThe combinations of GGO could be useful in the identification and differential diagnosis of COVID-19, which alerts clinicians to isolate patients for treatment promptly and repeat RT-PCR tests until incubation ends.

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