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      Lung involvement in patients with coronavirus disease-19 (COVID-19): a retrospective study based on quantitative CT findings

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          Abstract

          Purpose

          To explore lung involvement in patients with coronavirus disease-19 (COVID-19) using quantitative computed tomography (QCT).

          Methods

          A total of 52 patients with COVID-19 who were admitted to three hospitals in China from January 23, 2020 to February 1, 2020 were retrospectively analyzed using QCT. The accuracy of QCT segmentation was assessed. The relationship between the time from symptom onset to initial CT and QCT parameters acquired on the initial CT were explored.

          Results

          First, the ability of QCT to detect and segment lesions was investigated and it was unveiled that results of segmentation of the majority of cases (42/52) were satisfactory and for 8 out of 52 patients, the images depicted lesions with miss-segmentation; besides, 2 out of 52 cases had negative finding on chest CT achieved by both radiologists and QCT. QCT-related parameters showed to have a relationship with the time from symptom onset to initial CT. In the early-stage (0–3 days), the percentage of lung involvement was 4%, with a mean density of − 462 ± 99 HU. The peak density of lesions appeared at the range of − 500 to − 700 HU on density histogram. In the intermediate-stage (4–6 days), the mean percentage of lung involvement noticeably increased compared with that in early stage (7%, p < 0.05). In late stage (7–14 days), the percentage of lung involvement decreased to 5%. The mean density of lesions was the highest (− 430 ± 80), and heterogeneity density distribution showed a dual-peak on density histogram.

          Conclusion

          COVID-19 can be promptly detected by QCT. In addition, the QCT-related parameters can highly facilitate assessment of pulmonary involvement.

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          Most cited references13

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary 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 WHO and 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.
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            A Novel Coronavirus from Patients with Pneumonia in China, 2019

            Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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              Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

              In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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                Author and article information

                Contributors
                cjr.guoyoumin@vip.163.com
                Journal
                Chin J Acad Radiol
                Chin J Acad Radiol
                Chinese Journal of Academic Radiology
                Springer Singapore (Singapore )
                2520-8985
                2520-8993
                11 May 2020
                : 1-6
                Affiliations
                [1 ]GRID grid.449637.b, ISNI 0000 0004 0646 966X, Department of Radiology, , Affiliated Hospital of Shaanxi University of Chinese Medicine, ; Xian Yang, China
                [2 ]GRID grid.43169.39, ISNI 0000 0001 0599 1243, Department of Radiology, , Affiliated Hospital of Xi’an Jiaotong University, ; Xi’an, China
                [3 ]GRID grid.43169.39, ISNI 0000 0001 0599 1243, Department of Radiology, , Number 9 Affiliated Hospital of Xi’an Jiaotong University, ; Xi’an, China
                [4 ]Department of Radiology, Xi’an Chest hospital, Xi’an, China
                [5 ]GRID grid.43169.39, ISNI 0000 0001 0599 1243, Department of Radiology, , Affiliated Hospital of Xi’an Jiaotong University, ; Yanta west road 277#, Xi’an, China
                Article
                34
                10.1007/s42058-020-00034-2
                7211979
                32395696
                485ecaf8-57dc-4922-9932-46965e252eef
                © Springer Nature Singapore Pte Ltd. 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 16 March 2020
                : 16 April 2020
                : 26 April 2020
                Funding
                Funded by: Subject innovation Team of Shaanxi University of Chinese medicine
                Award ID: 2019-QN09
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100007128, Natural Science Foundation of Shaanxi Province;
                Award ID: 2019JM-361
                Award Recipient :
                Categories
                Original Article

                lung,computed tomography,covid-19
                lung, computed tomography, covid-19

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