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Effectiveness and Feasibility of Complementary Lung-RADS Version 1.1 in Risk Stratification for pGGN in LDCT Lung Cancer Screening in a Chinese Population

Authors Meng Q, Ren P, Gao P, Dou X, Chen X, Guo L, Song Y

Received 25 September 2019

Accepted for publication 30 December 2019

Published 9 January 2020 Volume 2020:12 Pages 189—198

DOI https://doi.org/10.2147/CMAR.S232269

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Dr Eileen O'Reilly


Qingcheng Meng,1,* Pengfei Ren,2,* Pengrui Gao,1 Xinmin Dou,1 Xuejun Chen,1 Lanwei Guo,3 Yongping Song4

1Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 2Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 3Department of Cancer Prevention Office, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 4Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yongping Song
Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, People’s Republic of China
Tel/Fax +86 371 65587016
Email songyongping001@126.com

Purpose: To evaluate the effectiveness of using a modified lung imaging reporting and data system (Lung-RADS) for risk stratification of pure ground-glass nodules (pGGNs) in low-dose computed tomography (LDCT) for lung cancer (LC) screenings in China.
Patients and Methods: Eight subjects with nine pGGNs originating from a Cancer Screening Program were enrolled as training set and 32 asymptomatic subjects with 35 pGGNs were selected as validation set from November 2013 to October 2018. The complementary Lung-RADS categories were set based on the GGN-vessel relationship (GVR). The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed.
Results: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. The combined incidence of invasive adenocarcinoma in type III and IV was more than that of benign and preinvasive diseases (30% vs 75%, P=0.013). Type II GVR between two benign (66.7%), seven preinvasive (53.8%), and six invasive (21.4%) GGN cases was statistically significant (χ2=5.415, P=0.019). GGN pathological groups and GVR had a significant correlation (r=0.584, P=0.00). Compared to Lung-RADS 1.1, complementary Lung-RADS 1.1 had better performance in the training set, with its sensitivity increased from 33.3% to 88.9%, accuracy increased from 44.4% to 88.9%, false-negative proportion (FNP) decreased from 66.7% to 11.1%, and the sensitivity to predict malignant nodules increased from 13.8% to 93.1%, accuracy increased from 28.6% to 80.0%, and FNP decreased from 86.2% to 6.9% in validation set. The detection rate of preinvasive disease and adenocarcinoma was increased from 12.5% to 90.6% and that of missed diagnosis decreased from 87.5% to 9.4% in the validation set, P=0.004.
Conclusion: Complementary Lung-RADS 1.1 is superior to Lung-RADS 1.1 and would be beneficial for LC screening of LDCT in China.

Keywords: low-dose computed tomography, lung neoplasms, lung-RADS, mass screening, ground-glass nodules

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