Literature DB >> 33664342

Quantitative and semi-quantitative CT assessments of lung lesion burden in COVID-19 pneumonia.

Xiaojun Guan1, Liding Yao1, Yanbin Tan1, Zhujing Shen1, Hanpeng Zheng2, Haisheng Zhou2, Yuantong Gao3, Yongchou Li3, Wenbin Ji4, Huangqi Zhang4, Jun Wang5, Minming Zhang6, Xiaojun Xu7.   

Abstract

This study aimed to clarify and provide clinical evidence for which computed tomography (CT) assessment method can more appropriately reflect lung lesion burden of the COVID-19 pneumonia. A total of 244 COVID-19 patients were recruited from three local hospitals. All the patients were assigned to mild, common and severe types. Semi-quantitative assessment methods, e.g., lobar-, segmental-based CT scores and opacity-weighted score, and quantitative assessment method, i.e., lesion volume quantification, were applied to quantify the lung lesions. All four assessment methods had high inter-rater agreements. At the group level, the lesion load in severe type patients was consistently observed to be significantly higher than that in common type in the applications of four assessment methods (all the p < 0.001). In discriminating severe from common patients at the individual level, results for lobe-based, segment-based and opacity-weighted assessments had high true positives while the quantitative lesion volume had high true negatives. In conclusion, both semi-quantitative and quantitative methods have excellent repeatability in measuring inflammatory lesions, and can well distinguish between common type and severe type patients. Lobe-based CT score is fast, readily clinically available, and has a high sensitivity in identifying severe type patients. It is suggested to be a prioritized method for assessing the burden of lung lesions in COVID-19 patients.

Entities:  

Year:  2021        PMID: 33664342      PMCID: PMC7933172          DOI: 10.1038/s41598-021-84561-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  25 in total

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9.  CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients.

Authors:  Fengjun Liu; Qi Zhang; Chao Huang; Chunzi Shi; Lin Wang; Nannan Shi; Cong Fang; Fei Shan; Xue Mei; Jing Shi; Fengxiang Song; Zhongcheng Yang; Zezhen Ding; Xiaoming Su; Hongzhou Lu; Tongyu Zhu; Zhiyong Zhang; Lei Shi; Yuxin Shi
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10.  Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study.

Authors:  Tao Chen; Di Wu; Huilong Chen; Weiming Yan; Danlei Yang; Guang Chen; Ke Ma; Dong Xu; Haijing Yu; Hongwu Wang; Tao Wang; Wei Guo; Jia Chen; Chen Ding; Xiaoping Zhang; Jiaquan Huang; Meifang Han; Shusheng Li; Xiaoping Luo; Jianping Zhao; Qin Ning
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  5 in total

1.  Predictors for COVID-19 Complete Remission with HRCT Pattern Evolution: A Monocentric, Prospective Study.

Authors:  Diana Manolescu; Bogdan Timar; Felix Bratosin; Ovidiu Rosca; Cosmin Citu; Cristian Oancea
Journal:  Diagnostics (Basel)       Date:  2022-06-05

2.  Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

Authors:  David Bermejo-Peláez; Raúl San José Estépar; María Fernández-Velilla; Carmelo Palacios Miras; Guillermo Gallardo Madueño; Mariana Benegas; Carolina Gotera Rivera; Sandra Cuerpo; Miguel Luengo-Oroz; Jacobo Sellarés; Marcelo Sánchez; Gorka Bastarrika; German Peces Barba; Luis M Seijo; María J Ledesma-Carbayo
Journal:  Sci Rep       Date:  2022-06-07       Impact factor: 4.996

Review 3.  Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review.

Authors:  Jingjing Chen; Yixiao Li; Lingling Guo; Xiaokang Zhou; Yihan Zhu; Qingfeng He; Haijun Han; Qilong Feng
Journal:  Neural Comput Appl       Date:  2022-09-19       Impact factor: 5.102

4.  Time to hospitalisation, CT pulmonary involvement and in-hospital death in COVID-19 patients in an Emergency Medicine Unit.

Authors:  Luca Marino; Marianna Suppa; Antonello Rosa; Adriana Servello; Alessandro Coppola; Mariangela Palladino; Anna Maria Mazzocchitti; Emanuela Bresciani; Luigi Petramala; Giuliano Bertazzoni; Daniele Pastori
Journal:  Int J Clin Pract       Date:  2021-06-16       Impact factor: 3.149

5.  Respiratory Outcomes After 6 Months of Hospital Discharge in Patients Affected by COVID-19: A Prospective Cohort.

Authors:  Gabriele da Silveira Prestes; Carla Sasso Simon; Roger Walz; Cristiane Ritter; Felipe Dal-Pizzol
Journal:  Front Med (Lausanne)       Date:  2022-03-07
  5 in total

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