Literature DB >> 33044173

Evaluation of disease severity with quantitative chest CT in COVID-19 patients.

Furkan Ufuk1, Mahmut Demirci1, Erhan Uğurlu2, Nazlı Çetin2, Nilüfer Yiğit2, Tuğba Sarı3.   

Abstract

PURPOSE: We aimed to assess the severity of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) using quantitative (QCT) and semiquantitative (SCT) assessments and compare with the clinical findings.
METHODS: Two observers independently examined the CT images of COVID-19 patients, and the SCT severity score was calculated. The SCT score was calculated as the sum of values ranging from 0 to 4, according to the volumetric rate of involvement for each lung lobe. In quantitative assessment, total lung volume (TLV) was automatically calculated from CT density values between -200 and -950 HU. Besides, healthy lung volume (HLV) was calculated from voxels between -800 and -950 HU. The QCT score was calculated with the following formula: (TLV - HLV / TLV) ×100. All patients were clinically divided into four groups: mild, common, severe, and critical. Interobserver agreement for SCT assessment was investigated using the Cohen's Kappa statistics (κ). Pearson's correlation coefficient was used for the relationship between continuous data. The diagnostic accuracy of SCT and QCT in the differentiation of clinically limited (mild, common) and extensive (severe, critical) disease was investigated using ROC analysis.
RESULTS: Seventy-six patients with a diagnosis of COVID-19 were included. There was good agreement between the two observers in the SCT evaluation of pulmonary disease severity (κ = 0.796; 95% CI, 0.751-0.841). A significant correlation was found between QCT and SCT scores (p < 0.001, r = 0.661). Both QCT and SCT scores showed a significant correlation with clinical severity score (p < 0.001, r = 0.620 and p = 0.004, r = 0.529, respectively). The ROC analysis revealed the AUC of QCT and SCT for differentiation of limited and extensive disease as 0.873 (95% CI, 0.774-0.972) and 0.816 (95% CI, 0.673-0.959), respectively.
CONCLUSION: The QCT assessment is an objective method in the evaluation of COVID-19 severity and is more successful than semiquantitative CT assessment to discriminate extensive from limited disease.

Entities:  

Mesh:

Year:  2021        PMID: 33044173      PMCID: PMC7963378          DOI: 10.5152/dir.2020.20281

Source DB:  PubMed          Journal:  Diagn Interv Radiol        ISSN: 1305-3825            Impact factor:   2.630


  18 in total

1.  Fleischner Society: glossary of terms for thoracic imaging.

Authors:  David M Hansell; Alexander A Bankier; Heber MacMahon; Theresa C McLoud; Nestor L Müller; Jacques Remy
Journal:  Radiology       Date:  2008-01-14       Impact factor: 11.105

2.  Coronavirus Disease 2019 (COVID-19): Role of Chest CT in Diagnosis and Management.

Authors:  Yan Li; Liming Xia
Journal:  AJR Am J Roentgenol       Date:  2020-03-04       Impact factor: 3.959

3.  Quantitative computed tomography assessment for systemic sclerosis-related interstitial lung disease: comparison of different methods.

Authors:  Furkan Ufuk; Mahmut Demirci; Goksel Altinisik
Journal:  Eur Radiol       Date:  2020-03-19       Impact factor: 5.315

4.  Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection.

Authors:  Adam Bernheim; Xueyan Mei; Mingqian Huang; Yang Yang; Zahi A Fayad; Ning Zhang; Kaiyue Diao; Bin Lin; Xiqi Zhu; Kunwei Li; Shaolin Li; Hong Shan; Adam Jacobi; Michael Chung
Journal:  Radiology       Date:  2020-02-20       Impact factor: 11.105

5.  Initial clinical features of suspected coronavirus disease 2019 in two emergency departments outside of Hubei, China.

Authors:  Wanbo Zhu; Kai Xie; Hui Lu; Lei Xu; Shusheng Zhou; Shiyuan Fang
Journal:  J Med Virol       Date:  2020-03-24       Impact factor: 20.693

6.  Interrater reliability: the kappa statistic.

Authors:  Mary L McHugh
Journal:  Biochem Med (Zagreb)       Date:  2012       Impact factor: 2.313

7.  Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT.

Authors:  Harrison X Bai; Ben Hsieh; Zeng Xiong; Kasey Halsey; Ji Whae Choi; Thi My Linh Tran; Ian Pan; Lin-Bo Shi; Dong-Cui Wang; Ji Mei; Xiao-Long Jiang; Qiu-Hua Zeng; Thomas K Egglin; Ping-Feng Hu; Saurabh Agarwal; Fang-Fang Xie; Sha Li; Terrance Healey; Michael K Atalay; Wei-Hua Liao
Journal:  Radiology       Date:  2020-03-10       Impact factor: 11.105

8.  A Novel Coronavirus from Patients with Pneumonia in China, 2019.

Authors:  Na Zhu; Dingyu Zhang; Wenling Wang; Xingwang Li; Bo Yang; Jingdong Song; Xiang Zhao; Baoying Huang; Weifeng Shi; Roujian Lu; Peihua Niu; Faxian Zhan; Xuejun Ma; Dayan Wang; Wenbo Xu; Guizhen Wu; George F Gao; Wenjie Tan
Journal:  N Engl J Med       Date:  2020-01-24       Impact factor: 91.245

9.  Chest CT Features of COVID-19 in Rome, Italy.

Authors:  Damiano Caruso; Marta Zerunian; Michela Polici; Francesco Pucciarelli; Tiziano Polidori; Carlotta Rucci; Gisella Guido; Benedetta Bracci; Chiara De Dominicis; Andrea Laghi
Journal:  Radiology       Date:  2020-04-03       Impact factor: 11.105

10.  CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19).

Authors:  Kunwei Li; Yijie Fang; Wenjuan Li; Cunxue Pan; Peixin Qin; Yinghua Zhong; Xueguo Liu; Mingqian Huang; Yuting Liao; Shaolin Li
Journal:  Eur Radiol       Date:  2020-03-25       Impact factor: 5.315

View more
  4 in total

1.  Lung perfusion changes in COVID-19 pneumonia: a dual energy computerized tomography study.

Authors:  Sonay Aydin; Mecit Kantarci; Erdal Karavas; Edhem Unver; Seven Yalcin; Fahri Aydin
Journal:  Br J Radiol       Date:  2021-09-01       Impact factor: 3.629

2.  New grading system for post-COVID-19 pulmonary fibrosis based on computed tomography findings.

Authors:  Ozlem Demircioglu; Derya Kocakaya; Canan Cimsit; Nuri Cagatay Cimsit
Journal:  Medicine (Baltimore)       Date:  2022-09-02       Impact factor: 1.817

Review 3.  Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence.

Authors:  Maria Elena Laino; Angela Ammirabile; Ludovica Lofino; Dara Joseph Lundon; Arturo Chiti; Marco Francone; Victor Savevski
Journal:  Emerg Radiol       Date:  2022-01-20

4.  New challenges for management of COVID-19 patients: Analysis of MDCT based "Automated pneumonia analysis program".

Authors:  Rahime Sezer; Dorina Esendagli; Cigdem Erol; Koray Hekimoglu
Journal:  Eur J Radiol Open       Date:  2021-07-20
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.