1001
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Lee HJ, Moon JW, Woo JY, Kim YN. Clinical and Radiologic Findings of COVID-19 Pneumonia: South Korean Experience From Three Cases. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2020; 81:583-590. [PMID: 36238634 PMCID: PMC9431928 DOI: 10.3348/jksr.2020.81.3.583] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 03/31/2020] [Accepted: 04/12/2020] [Indexed: 01/15/2023]
Abstract
Coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. Several articles have so far reported on radiological findings of COVID-19 pneumonia. Herein, we present three cases of COVID-19 pneumonia in South Korea, and provide clinical information as well as chest radiograph and chest CT findings.
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Affiliation(s)
- Hyung Ju Lee
- Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Jung Won Moon
- Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Ji Young Woo
- Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Yoo Na Kim
- Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
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1002
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Yoo SJ, Goo JM, Yoon SH. Role of Chest Radiographs and CT Scans and the Application of Artificial Intelligence in Coronavirus Disease 2019. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2020; 81:1334-1347. [PMID: 36237723 PMCID: PMC9431829 DOI: 10.3348/jksr.2020.0138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/02/2020] [Accepted: 09/15/2020] [Indexed: 01/08/2023]
Abstract
코로나바이러스감염증-19 (coronavirus disease 2019; 이하 COVID-19)는 전 세계적 대유행 질환으로 인류 보건을 위협하고 있다. 흉부 CT 및 흉부X선사진은 COVID-19의 표준 진단검사인 역전사 중합효소 연쇄반응에 더하여 COVID-19 진단 및 중증도 평가에서 중요한 역할을 하고 있다. 본 종설에서는 흉부 CT 및 흉부X선사진의 COVID-19 폐렴에 대한 현재 역할에 대하여 살펴보고 인공지능을 적용한 대표적 초기 연구들과 저자들의 경험을 소개함으로써 향후 활용가치에 대해 살펴보고자 한다.
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Affiliation(s)
- Seung-Jin Yoo
- Department of Radiology, Hanyang University Medical Center, Hanyang University College of Medicine, Seoul, Korea
| | - Jin Mo Goo
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
| | - Soon Ho Yoon
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea
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1003
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Zhang H, Liu X, Yu P, Cheng M, Wang W, Sun Y, Zeng B, Fan B. Dynamic CT assessment of disease change and prognosis of patients with moderate COVID-19 pneumonia. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2020; 28:851-861. [PMID: 32741802 PMCID: PMC7592657 DOI: 10.3233/xst-200711] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 06/25/2020] [Accepted: 07/04/2020] [Indexed: 05/17/2023]
Abstract
OBJECTIVES To assess prognosis or dynamic change from initial diagnosis until recovery of the patients with moderate coronavirus disease (COVID-19) pneumonia using chest CT images. MATERIALS AND METHODS In this retrospective study, 33 patients (18 men, 15 women; median age, 49.0 years) with confirmed with moderate COVID-19 pneumonia in a multicenter hospital were included. The patients underwent at least four chest non-contrast-enhanced computed tomography (CT) scans at approximately 5-day intervals. We analyzed the clinical and CT characteristics of the patients. Moreover, the total CT score and the sum of lung involvement were determined for every CT scan. RESULTS The most widespread presenting symptoms were fever (32/33, 97.0%) and cough (17/33, 51.5%), which were often accompanied by decreased lymphocyte count (15/33, 45.5%) and increased C-reactive protein levels (18/33, 54.6%). Bilateral, multifocal ground glass opacities (32/33, 97.0%), consolidation (25/33, 75.8%), vascular thickening (23/33, 69.7%), and bronchial wall thickening (21/33, 63.6%) with peripheral distribution were the most frequent CT findings during moderate COVID-19 pneumonia. In patients recovering from moderate COVID-19 pneumonia, four stages (stages 1-4) of evolution were identified on chest CT with average CT scores of 3.4±2.3, 6.0±4.4, 5.6±3.8, and 4.9±3.2, respectively, from the onset of symptoms. For most patients, the peak of average total CT score increased for approximately 8 days after the onset of symptoms, after which it decreased gradually. The mean CT score of all patients was 4.7 at the time of discharge. CONCLUSION The moderate COVID-19 pneumonia CT score increased rapidly in a short period of time initially, followed by a slow decline over a relatively long time. The peak of the course occurred in stage 2. Complete recovery of patients with moderate COVID-19 pneumonia with high mean CT score at the time of discharge requires longer time.
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Affiliation(s)
- Hua Zhang
- Department of Radiology, the Third Affiliated Hospital of Nanchang University (also known as the First Hospital of Nanchang), Jiangxi, China
| | - Xiaohong Liu
- Department of Radiology, JiangXi PingXiang people’s hospital, Jiangxi, China
| | - Peng Yu
- Department of Radiology, JiangXi JinXian people’s hospital, Jiangxi, China
| | - Mingyuan Cheng
- Department of Radiology, the Third Affiliated Hospital of Nanchang University (also known as the First Hospital of Nanchang), Jiangxi, China
| | - Weiting Wang
- Department of Radiology, Jiangxi provincial chest hospital, Jiangxi, China
| | | | - Bingliang Zeng
- Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi, China
| | - Bing Fan
- Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi, China
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1004
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Lei P, Huang Z, Liu G, Wang P, Song W, Mao J, Shen G, Zhou S, Qian W, Jiao J. Clinical and computed tomographic (CT) images characteristics in the patients with COVID-19 infection: What should radiologists need to know? JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2020; 28:369-381. [PMID: 32280076 PMCID: PMC7369068 DOI: 10.3233/xst-200670] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 03/05/2020] [Accepted: 03/09/2020] [Indexed: 05/15/2023]
Abstract
OBJECTIVE To evaluate the clinical and computed tomographic (CT) features in the patients with COVID-19 pneumonia confirmed by the real-time reverse transcriptase polymerase chain reaction (rRT-PCR) amplification of the viral DNA from a sputum sample. MATERIAL AND METHODS Clinical information and CT findings of a total of 14 patients with COVID-19 infection (age range, 12-83 years; females 6) were analyzed retrospectively. The clinical information includes the history of exposure, laboratory results, and the symptoms (such as fever, cough, headache, etc.); CT findings of chest include the extension and distribution of lesion, the ground-glass opacity (GGO), consolidation, bronchovascular enlarged, irregular linear appearances, pleural effusion, and lymphadenopathy. RESULTS Eight patients had the exposure history for recent travel to Wuhan of Hubei province (8/14, 57%), 6 had the exposure to patients with COVID-19 infection. Significant statistical differences were observed in lymphocyte percentage decreased and C-reactive protein elevated (p = 0.015). Seven patients had fever, 7 had cough, 2 had headache, 3 had fatigue, 1 had body soreness, 3 had diarrhea, and 2 had no obvious symptoms. In chest CT examination, 10 patients were positive (10/14, 71.43%). Among these patients, 9 had lesions involving both lungs (9/10, 90%), 8 had lesions involving 4 to 5 lobes (8/10, 80%). Most of lesions were distributed peripherally and the most significant lesions were observed in the right lower lobe in 9 patients (9/10, 90%). Nodules were observed in 5 patients (5/10, 50%); GGO, consolidation, and bronchovascular enlarged were shown in 9 patients (9/10, 90%); irregular linear appearances were revealed in 7 patients (7/10, 70%); and pleural effusions were exhibited in 2 patients (2/10, 20%). Last, no patients showed lymphadenopathy. CONCLUSION There were some typical CT features for diagnosis of COVID-19 pneumonia. The radiologists should know these CT findings and clinical information, which could help for accurate analysis in the patients with 2019 novel coronavirus infection.
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Affiliation(s)
- Pinggui Lei
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Zhaoshu Huang
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Guoli Liu
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Pingxian Wang
- Department of Medical Insurance, the Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Wen Song
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Jujiang Mao
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Guiquan Shen
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Shi Zhou
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
| | - Wei Qian
- Department of Electrical and Computer Engineering, College of Engineering, University of Texas, El Paso, TX, USA
| | - Jun Jiao
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University. Guiyang, China
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1005
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Jin KN, Yoon SH, Park CH, Beck KS, Do KH, Yong HS. KSR/KSTR Guidelines for the Use of Diagnostic Imaging for COVID-19. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2020; 81:577-582. [PMID: 36238630 PMCID: PMC9431921 DOI: 10.3348/jksr.2020.81.3.577] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 04/15/2020] [Accepted: 04/15/2020] [Indexed: 11/15/2022]
Abstract
The Korean Society of Radiology and the Korean Society of Thoracic Radiology have prepared recommendations for the use of diagnostic imaging for COVID-19 in various clinical scenarios. We have tried to grasp the situation in the real world, aggregated opinions from the chest radiologists, and reviewed available references, in order to suggest the most reasonable recommendations possible at this moment. As circumstances change and new evidences emerge, the recommendations should immediately be modified accordingly.
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Affiliation(s)
| | - Kwang Nam Jin
- Department of Radiology, SMG-SNU Boramae Medical Center, Seoul, Korea
| | - Soon Ho Yoon
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Chul Hwan Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Kyongmin Sarah Beck
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kyung-Hyun Do
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hwan Seok Yong
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
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1006
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Chidambaram V, Tun NL, Haque WZ, Majella MG, Sivakumar RK, Kumar A, Hsu ATW, Ishak IA, Nur AA, Ayeh SK, Salia EL, Zil-E-Ali A, Saeed MA, Sarena APB, Seth B, Ahmadzada M, Haque EF, Neupane P, Wang KH, Pu TM, Ali SMH, Arshad MA, Wang L, Baksh S, Karakousis PC, Galiatsatos P. Factors associated with disease severity and mortality among patients with COVID-19: A systematic review and meta-analysis. PLoS One 2020; 15:e0241541. [PMID: 33206661 PMCID: PMC7673562 DOI: 10.1371/journal.pone.0241541] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 10/17/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID-19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19. METHODS We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently. RESULTS Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45, 95%CI 1.23-1.71), dyspnea (RR 2.55, 95%CI 1.88-2.46), diabetes (RR 1.59, 95%CI 1.41-1.78), hypertension (RR 1.90, 95%CI 1.69-2.15). Congestive heart failure (OR 4.76, 95%CI 1.34-16.97), hilar lymphadenopathy (OR 8.34, 95%CI 2.57-27.08), bilateral lung involvement (OR 4.86, 95%CI 3.19-7.39) and reticular pattern (OR 5.54, 95%CI 1.24-24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality. CONCLUSION Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.
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Affiliation(s)
- Vignesh Chidambaram
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Nyan Lynn Tun
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Waqas Z. Haque
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Marie Gilbert Majella
- Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Ranjith Kumar Sivakumar
- Department of Anaesthesia and Intensive Care, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Amudha Kumar
- Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
| | - Angela Ting-Wei Hsu
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Izza A. Ishak
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Aqsha A. Nur
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Samuel K. Ayeh
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Emmanuella L. Salia
- Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Ahsan Zil-E-Ali
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Muhammad A. Saeed
- Johns Hopkins University, Baltimore, Maryland, United States of America
| | | | - Bhavna Seth
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | | | - Eman F. Haque
- Southern Methodist University, Dallas, Texas, United States of America
| | - Pranita Neupane
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Kuang-Heng Wang
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Tzu-Miao Pu
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | | | | | - Lin Wang
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Sheriza Baksh
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Petros C. Karakousis
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Panagis Galiatsatos
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
- * E-mail:
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1007
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Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks. Eur J Clin Microbiol Infect Dis 2020; 39. [PMID: 32337662 PMCID: PMC7183816 DOI: 10.1007/s10096-020-03901-z 10.1007/s10096-020-03901-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more trustworthy, useful, and rapid technique to classify and evaluate COVID-19, specifically in the epidemic region. Almost all hospitals have CT imaging machines; therefore, the chest CT images can be utilized for early classification of COVID-19 patients. However, the chest CT-based COVID-19 classification involves a radiology expert and considerable time, which is valuable when COVID-19 infection is growing at rapid rate. Therefore, an automated analysis of chest CT images is desirable to save the medical professionals' precious time. In this paper, a convolutional neural networks (CNN) is used to classify the COVID-19-infected patients as infected (+ve) or not (-ve). Additionally, the initial parameters of CNN are tuned using multi-objective differential evolution (MODE). Extensive experiments are performed by considering the proposed and the competitive machine learning techniques on the chest CT images. Extensive analysis shows that the proposed model can classify the chest CT images at a good accuracy rate.
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1008
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Lakbar I, Luque-Paz D, Mege JL, Einav S, Leone M. COVID-19 gender susceptibility and outcomes: A systematic review. PLoS One 2020. [PMID: 33141872 DOI: 10.1371/journal.pone.0241] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Epidemiological differences between men and women have been reported with regards to sepsis, influenza and severe coronavirus infections including SARS-CoV and MERS-CoV. AIM To systematically review the literature relating to men versus women on SARS-CoV-2 in order to seek differences in disease characteristics (e.g. infectivity, severity) and outcomes (e.g. mortality). METHODS We searched 3 electronic databases up or observational studies reporting differences between men and women in the SARS-CoV-2 disease characteristics stated. We identified and included 47 studies, reporting data for 21,454 patients mainly from China. RESULTS The unadjusted mortality rates of men were higher than those of women, with a mortality OR 0.51 [0.42, 0.61] (p<0.001) for women. The proportion of men presenting with severe disease and admitted to the intensive care unit (ICU) was also higher than that of women (OR 0.75 [0.60-0.93] p<0.001 and OR 0.45 [0.40-0.52] p<0.001 respectively). Adjusted analyses could not be conducted due to lack of data. CONCLUSION COVID-19 may be associated with worse outcomes in males than in females. However, until more detailed data are provided in further studies enabling adjusted analysis, this remains an unproven assumption.
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Affiliation(s)
- Ines Lakbar
- Department of Anesthesiology and Intensive Care Unit, Nord Hospital, Assistance Publique Hôpitaux Universitaire de Marseille, Aix Marseille University, Marseille, France
- MEPHI, IHU Méditerranée Infection, Aix Marseille Université, Marseille, France
- Department of Anesthesiology and Intensive Care Unit, Toulouse, France
| | - David Luque-Paz
- Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, Rennes, France
- University of Rennes, Inserm, BRM (Bacterial Regulatory RNAs and Medicine), UMR 1230, Rennes, France
| | - Jean-Louis Mege
- MEPHI, IHU Méditerranée Infection, Aix Marseille Université, Marseille, France
| | - Sharon Einav
- Intensive Care Unit of the Shaare Zedek Medical Centre and Hebrew University Faculty of Medicine, Jerusalem, Israel
| | - Marc Leone
- Department of Anesthesiology and Intensive Care Unit, Nord Hospital, Assistance Publique Hôpitaux Universitaire de Marseille, Aix Marseille University, Marseille, France
- MEPHI, IHU Méditerranée Infection, Aix Marseille Université, Marseille, France
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