CT Imaging Features of Patients Infected with 2019 Novel Coronavirus

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.

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

10.1101/2020.03.03.20030775 ◽

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.

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Dynamic Chest CT Evaluation in Three Cases of 2019 Novel Coronavirus Pneumonia

Archives of Iranian Medicine ◽

10.34172/aim.2020.11 ◽

2020 ◽

Vol 23 (4) ◽

pp. 277-280 ◽

Cited By ~ 4

Author(s):

Xing Chen ◽

Shuying Liu ◽

Chunyi Zhang ◽

Guimei Pu ◽

Jian Sun ◽

...

Keyword(s):

Ct Scan ◽

Chest Ct ◽

Ground Glass ◽

Imaging Findings ◽

Recent Outbreak ◽

Multiple Regions ◽

Ct Evaluation ◽

Characteristic Features ◽

Novel Coronavirus ◽

Pulmonary Ct

A recent outbreak of pneumonia in Wuhan, China, was caused by the 2019 novel coronavirus (2019-nCoV). There have been some reports of imaging findings regarding the disease’s characteristic features. Here, we report three cases of coronavirus disease 2019 (COVID-19) with dynamic pulmonary CT evaluation. The CT scan showed multiple regions of ground-glass opacities and patchy consolidation in COVID-19 patients and the CT scan was useful in tracking the progression or regression of COVID-19.

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The characteristics and clinical value of chest CT images of novel coronavirus pneumonia

Clinical Radiology ◽

10.1016/j.crad.2020.03.002 ◽

2020 ◽

Vol 75 (5) ◽

pp. 335-340 ◽

Cited By ~ 24

Author(s):

X. Zhao ◽

B. Liu ◽

Y. Yu ◽

X. Wang ◽

Y. Du ◽

...

Keyword(s):

Ct Images ◽

Chest Ct ◽

Clinical Value ◽

Novel Coronavirus

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Clinical and computed tomographic imaging features of novel coronavirus pneumonia caused by SARS-CoV-2

Journal of Infection ◽

10.1016/j.jinf.2020.02.017 ◽

2020 ◽

Vol 80 (4) ◽

pp. 394-400 ◽

Cited By ~ 176

Author(s):

Yu-Huan Xu ◽

Jing-Hui Dong ◽

Wei-Min An ◽

Xiao-Yan Lv ◽

Xiao-Ping Yin ◽

...

Keyword(s):

Tomographic Imaging ◽

Imaging Features ◽

Computed Tomographic ◽

Novel Coronavirus ◽

Computed Tomographic Imaging

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A false alarm of COVID-19 pneumonia in lung cancer: a case report of anti-PD-1 related pneumonitis and literature review

10.21203/rs.3.rs-41095/v1 ◽

2020 ◽

Author(s):

Ying Dai ◽

Sha Liu ◽

Zhiyan Zhao ◽

...

Keyword(s):

Lung Cancer ◽

Clinical Symptoms ◽

Close Contact ◽

Ct Imaging ◽

Chest Ct ◽

Radiographic Feature ◽

Rt Pcr ◽

Lung Lobe ◽

History Of ◽

Novel Coronavirus

Abstract Background: The fatal toxicity of anti-PD-1/PD-L1 agents is pneumonitis. The diagnosis consists of the history of immunotherapy, clinical symptoms and presentation of computed tomography (CT) imaging. The typical CT findings include ground-glass opacities. Based on the similar radiographic feature with 2019 Novel Coronavirus (COVID-19) pneumonia, clinicians are cautious to evaluate diagnosis especially in COVID-19 epidemic areas. Case presentation: Herein we report a 67-year-old male patient with advanced non-small cell lung cancer developed pneumonitis post Sintilimab injection. The dyspnea appeared at the 15th day of close contact with his son who returned from Wuhan, but not accompanied with fever. The chest CT indicated peripherally subpleural lattice opacities at the inferior right lung lobe and bilateral thoracic infusion. The real-time reverse-transcription polymerase-chain-reaction (RT-PCR) from double swab samples within 72 hours remained negative. The patient was thereafter treated with prednisolone and antibiotics for over two weeks. Thereafter the chest CT demonstrated the former lesion almost absorbed, in line with prominently falling CRP level. The anti-PD-1 related pneumonitis with bacterial infection was diagnosed finally based on the clinical evidence and good response to the prednisolone and antibiotics. Conclusion: Both ani-PD-1 related pneumonitis and COVID-19 pneumonia harbor the common clinical symptom and the varied features of CT imaging. Differential diagnosis was based on the epidemiological and immunotherapy histories, RT-PCR tests. The response to glucocorticoid can indirectly help the diagnosis.

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Multi-task Deep Learning Based CT Imaging Analysis For COVID-19: Classification and Segmentation

10.1101/2020.04.16.20064709 ◽

2020 ◽

Cited By ~ 5

Author(s):

A. Amyar ◽

R. Modzelewski ◽

S. Ruan

Keyword(s):

Deep Learning ◽

Ct Images ◽

Ct Imaging ◽

Chest Ct ◽

The Novel ◽

Imaging Analysis ◽

Proposed Model ◽

Fast Spreading ◽

Novel Coronavirus ◽

Deep Learning Model

ABSTRACTThe fast spreading of the novel coronavirus COVID-19 has aroused worldwide interest and concern, and caused more than one million and a half confirmed cases to date. To combat this spread, medical imaging such as computed tomography (CT) images can be used for diagnostic. An automatic detection tools is necessary for helping screening COVID-19 pneumonia using chest CT imaging. In this work, we propose a multitask deep learning model to jointly identify COVID-19 patient and segment COVID-19 lesion from chest CT images. Our motivation is to leverage useful information contained in multiple related tasks to help improve both segmentation and classification performances. Our architecture is composed by an encoder and two decoders for reconstruction and segmentation, and a multi-layer perceptron for classification. The proposed model is evaluated and compared with other image segmentation and classification techniques using a dataset of 1044 patients including 449 patients with COVID-19, 100 normal ones, 98 with lung cancer and 397 of different kinds of pathology. The obtained results show very encouraging performance of our method with a dice coefficient higher than 0.78 for the segmentation and an area under the ROC curve higher than 93% for the classification.

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CT Imaging Features During Disease Progression of 2019 Novel Coronavirus (COVID-19) Pneumonia

Iranian Journal of Radiology ◽

10.5812/iranjradiol.102925 ◽

2020 ◽

Vol 17 (4) ◽

Author(s):

Nan Yu ◽

Yong Yu ◽

Shubo Cai ◽

Cong Shen ◽

Youmin Guo

Keyword(s):

Disease Progression ◽

Symptom Onset ◽

Early Stage ◽

Ground Glass Opacity ◽

Ct Imaging ◽

Imaging Features ◽

Imaging Characteristics ◽

Novel Coronavirus ◽

Stage 1

Objectives: To describe the characteristics of computed tomography (CT) in patients with 2019 novel coronavirus (COVID-19) pneumonia and their changes during disease progression. Patients and Methods: A total of 96 chest CT scans of 61 pneumonia patients associated with COVID-19 were reviewed to identify CT features associated with the time of symptom onset and the evolution of disease. Results: The initial CTs of 61 patients were obtained during 1 to 11 days after the onset. The main CT pattern of initial CT obtained during 1 - 3 days after the symptom onset was single (7/23, 35%) or multiple ground-glass opacity (GGO, 8/23, 35%). At 4 - 7 days after the symptom onset, the main imaging features were crazy paving GGO mixed with partial consolidation pattern (15/32, 47%). At 8 - 11 days after the symptom onset, the CT images showed consolidation pattern (3/6, 50%). A total of 35 follow up CTs were collected. The mean interval time between each follow up CT was 3 ± 2 days. The CT patterns also changed with the evolution of the disease: the features of GGO manifested at the early stage (1 - 3d). The crazy paving GGO pattern, consolidation pattern and mixed with partial consolidation pattern were found 4 to 14 days after the onset. In the absorption stage (15 - 24d), both density and extent of lesions were reduced. Conclusion: The CT imaging features are associated with the time of symptom onset and evolution of disease. Understanding the imaging characteristics of each stage is very helpful for understanding the development of disease.

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