ISSN 1004-4140
CN 11-3017/P
LIU R, WU T T, GOU S B, et al. Clinical Application Potentials of Ground Glass Opacities in Different Stages of Coronavirus Disease 2019[J]. CT Theory and Applications, 2023, 32(3): 339-346. DOI: 10.15953/j.ctta.2023.046. (in Chinese).
Citation: LIU R, WU T T, GOU S B, et al. Clinical Application Potentials of Ground Glass Opacities in Different Stages of Coronavirus Disease 2019[J]. CT Theory and Applications, 2023, 32(3): 339-346. DOI: 10.15953/j.ctta.2023.046. (in Chinese).

Clinical Application Potentials of Ground Glass Opacities in Different Stages of Coronavirus Disease 2019

More Information
  • Received Date: March 10, 2023
  • Revised Date: April 01, 2023
  • Accepted Date: April 02, 2023
  • Available Online: April 23, 2023
  • Published Date: May 30, 2023
  • Objective: To analyze and compare the characteristics of ground glass opacities at different stages of coronavirus disease 2019 (COVID-19) on chest computed tomography (CT) images and to discuss its contribution to staging diagnoses and disease management for patients with COVID-19. Methods: Chest CT scans of 66 indigenous and 64 imported cases were collected from patients with COVID-19 in the Inner Mongolia region. Characteristics and the companion signs of ground glass opacities in the early and recovery stages of COVID-19 were analyzed and compared. Results: Of the 66 indigenous COVID-19 cases, 77.3% (51 cases) presented ground glass opacities in the early stage of the disease, while 63.7% (42 cases) had ground glass opacities in the recovery period. Notably, significantly different characteristics and companion signs of ground glass opacities were observed between the early and recovery stages. The average CT value of early-stage ground glass opacities (−329.14±143.66) HU was significantly higher than that of ground glass opacities (−616.71±89.82) HU in the recovery period. Compared with ground glass opacities in the recovery period, most early-stage ground glass opacities displayed clear edges (43 cases, 84.31% vs. 5 cases, 11.90%) and are often accompanied by paving stone signs (32 cases, 62.75% vs. 8 cases, 19.05%); thickened blood vessels (33 cases, 64.71% vs. 4 cases, 9.52%), and bronchial inflation symptoms (19 cases, 37.25% vs. 4 cases, 9.52%). The recovery period is more accompanied by irregular linear shadow than in the early stage (35 cases, 83.33% vs. 8 cases, 15.69%). There was no significant difference in the companion signs of interlobular septal thickening between the two stages (7 cases in the early stage, 13.72% vs. 2 cases in the recovery period, 4.76%). The results of the imported type are consistent with those of the indigenous type. Compared with ground glass opacities in the recovery period, most early-stage ground glass opacities displayed clear edges, while in the recovery group, the density of ground glass opacities was lower and accompanied more by irregular linear shadow. Both local and imported cases of COVID-19 showed more inflammatory consolidation and striation in the advanced stage than in the early stage. Conclusion: Compared with the ground glass opacities in the early stage, the ground glass opacities in the recovery period presented a lower density, unclear edges, and fewer signs of paving stone sign, thickened blood vessels, and bronchial inflation signs, but were more often accompanied by irregular linear shadows which are of great clinical application value for determining the course of COVID-19 and disease management.
  • [1]
    FANG Y C, ZHANG H Q, XIE J C, et al. Sensitivity of chest CT for COVID-19: Comparison to RT-PCR[J]. Radiology, 2020, (2): 200432−7.
    [2]
    中华医学会放射学分会传染病学组, 中国医师协会放射医师分会感染影像专委会, 中国研究型医院学会感染与炎症放射专委会, 等. 新型冠状病毒感染的肺炎影像学诊断指南(2020第二版)[J]. 首都医科大学学报, 2020,41(2): 168−173. doi: 10.3969/j.issn.1006-7795.2020.02.004
    [3]
    CHUNG M, BERNHEIM A, MEI X, et al. CT imaging features of 2019 novel Coronavirus (2019-nCoV)[J]. Radiology, 2020, 295: 202−207. doi: 10.1148/radiol.2020200230
    [4]
    国家卫生健康委员会. 《新型冠状病毒感染的肺炎诊疗方案试行(第七版)》[EB/OL]. [2020-03-03]. http://www.nhc.gov.cn/yzygj/s7653p/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml
    [5]
    Fleischner Society: Glossary of terms for thoracic imaging[J]. Radiology 2008, 246: 703.
    [6]
    贺文, 马大庆, 冯捷, 等. 肺磨玻璃密度高分辨率CT的诊断和鉴别诊断意义[J]. 中华放射学杂志, 2001,35(1): 52−55. doi: 10.3760/j.issn:1005-1201.2001.01.016

    HE W, MA D Q, FENG J, et al. The diagnostic value of grand glass opacity on HRCT of the lung[J]. Chinese Journal of Radiology, 2001, 35(1): 52−55. (in Chinese). doi: 10.3760/j.issn:1005-1201.2001.01.016
    [7]
    GUAN C S, LV Z B, LI J J, et al. CT appearances, patterns of progression, and follow-up of COVID-19: Evaluation on thin-section CT[J]. Insights into Imaging, 2021, 12: 73. doi: 10.1186/s13244-021-01019-0
    [8]
    BERNHEIM A, MEI X, HUANG M, et al. Chest CT findings in coronavirus disease-19 (COVID-19): Relationship to duration of infection[J]. Radiology, 2020, (2): 200463−8.
    [9]
    李小虎, 王海涛, 朱娟, 等. 输入性新型冠状病毒肺炎治愈患者肺内病变的影像学动态观察[J]. 中华放射学杂志, 2020,54(5): 435−439. doi: 10.3760/cma.j.cn112149-20200218-00189

    LI X H, WANG H T, ZHU J, et al. Imaging dynamic observation of cured COVID‑19 patients with imported coronavirus pneumonia[J]. Chinese Journal of Radiology, 2020, 54(5): 435−439. (in Chinese). doi: 10.3760/cma.j.cn112149-20200218-00189
    [10]
    HUANG C, WANG Y, LI X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China[J]. Lancet, 2020, (20): 30183−5.
    [11]
    刘茜, 王荣帅, 屈国强, 等. 新型冠状病毒肺炎死亡尸体系统解剖大体观察报告[J]. 法医学杂志, 2020,36(1): 21−23. doi: 10.12116/j.issn.1004-5619.2020.01.005
    [12]
    NG M Y, LEE E Y P, YANNG J, et al. Imaging profile of the COVID-19 infection: Radiologic findings and literature review[J]. Radiology, 2020, 2(1): 1−9.
    [13]
    车宏伟, 张晓琴, 柴军, 等. 新型冠状病毒肺炎临床表现及CT影像学分析[J]. CT理论与应用研究, 2021,30(4): 525−532. DOI: 10.15953/j.1004-4140.2021.30.04.14.

    CHE H W, ZHANG X Q, CHAI J, et al. Clinical manifestations and CT imaging analysis of corona virus disease 2019[J]. CT Theory and Applications, 2021, 30(4): 525−532. DOI: 10.15953/j.1004-4140.2021.30.04.14. (in Chinese).
    [14]
    PAN F, YE T, SUN P, et al. Time course of lung changes at chest CT during recovery from corona virus disease 2019 (COVID-19)[J]. Radiology, 2020, 295(3): 715−721. doi: 10.1148/radiol.2020200370
    [15]
    KANNE J P. Chest CT findings in 2019 novel coronavirus (2019-nCoV) infections from Wuhan, China: Key points for the radiologist[J]. Radiology, 2020, 295(1): 16−17. doi: 10.1148/radiol.2020200241
    [16]
    SHI H, HAN X, ZHENG C. Evolution of CT manifestations in a patient recovered from 2019 novel coronavirus (2019-nCoV) pneumonia in Wuhan, China[J]. Radiology, 2020, 295(1): 20. doi: 10.1148/radiol.2020200269
    [17]
    YU M, LIU Y, XU D, et al. Prediction of the development of pulmonary fibrosis using serial thin-section CT and clinical features in patients discharged after treatment for COVID-19 pneumonia[J]. Korean Journal of Radiology, 2020, 21(6): 746−755. doi: 10.3348/kjr.2020.0215
    [18]
    李秀梅, 刘伟, 常然, 等. 新型冠状病毒肺炎影像演变规律及肺纤维化危险因素[J]. 中国医学影像学杂志, 2022,30(1): 29−34. doi: 10.3969/j.issn.1005-5185.2022.01.006

    LI X M, LIU W, CHANG R, et al. Patterns of pulmonary image evolution and the risk factors of pulmonary fibrosis in patients with COVID-19[J]. Chinese Journal of Medical Imaging, 2022, 30(1): 29−34. (in Chinese). doi: 10.3969/j.issn.1005-5185.2022.01.006
  • Related Articles

    [1]YOU Long-ting, SONG Jian-guo, YU Hui-zhen, WANG Yue-lei. Analysis of the Influence Factors on the Time-Frequency Spectrum Obtained by Synchrosqueezing Wavelet Transform based on Reconstruction of Analytic Signal[J]. CT Theory and Applications, 2017, 26(3): 267-278. DOI: 10.15953/j.1004-4140.2017.26.03.02
    [2]ZHANG Xue-song, ZHAO Bo-shan. Cupping Artifacts Calibration in CT Image Based on Radon Transform[J]. CT Theory and Applications, 2016, 25(5): 539-546. DOI: 10.15953/j.1004-4140.2016.25.05.05
    [3]LIU Hai-yan, TIAN Gang, SHI Zhan-jie. The Comparison of Time-frequency Analysis Methods and Their Applications[J]. CT Theory and Applications, 2015, 24(2): 199-208. DOI: 10.15953/j.1004-4140.2015.24.02.06
    [4]FAN Hua, ZHAO Guo-chun, HAN Yan-jie, LIU Ming-jun, LI Xiao-qin, SUN Yong-jun. Image Fusion in Combination of the Improved IHS Transform and Wavelet Transform[J]. CT Theory and Applications, 2014, 23(5): 761-770.
    [5]FENG Xia, SHI Chao, DING Wen-bo, FENG Yan, HAO Zhen-ping. The Complication of Spectral Analysis Based on Fourier Transform in the Tire X-ray Detection[J]. CT Theory and Applications, 2014, 23(3): 453-458.
    [6]ZHANG Xi-le, HUANG Jing, LIU Nan, LU Li-jun, MA Jian-hua, CHEN Wu-fan. Wavelet-Transform Based Low-Dose CT Projection Filtering[J]. CT Theory and Applications, 2011, 20(2): 163-171.
    [7]DONG Fang, HU Liang, LI Bo-lin, LI Ming, CHEN Hao, WANG Yuan, ZHANG Cheng-xin, XU Zhou. Contour Data Denoise Based on Inter-Scale Correlations of Contourlet Transform[J]. CT Theory and Applications, 2008, 17(4): 62-66.
    [8]SUN Cun-jie, ZHANG Hong. The Study on Methods of CT Image Enhancement[J]. CT Theory and Applications, 2005, 14(4): 17-20.
    [9]HAN Yu-sheng, LU Wei, LIU Han, LI Cong-li. Enhancement processing on Security Inspection Image Based on Db Wavelet Transform and median Filtering[J]. CT Theory and Applications, 2005, 14(1): 7-10.
    [10]ZHONG Shi-hang. Examining Quality of Retaining Wall Made of Mortar and Stones by Means of Comparing Spectrum of Elastic Reflection Wave Frequncy[J]. CT Theory and Applications, 2002, 11(1): 1-5.
  • Cited by

    Periodical cited type(1)

    1. 张明霞,李玲,高兰,王玉华,孙莹,孙磊,霍萌,张春燕,王仁贵. 不同预后的抗MDA5抗体阳性IIMs患者肺部HRCT定量指标与临床研究. CT理论与应用研究. 2024(03): 351-358 . 本站查看

    Other cited types(0)

Catalog

    Article views (285) PDF downloads (20) Cited by(1)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return