Modified Lung-RADS Improves Performance of Screening LDCT in a Population with High Prevalence of Non-smoking-related Lung Cancer

We proposed a modification of the ACR Lung Imaging Reporting and Data System (Lung-RADS) to clarify the characteristics of subsolid nodules with categories 1-11, and to compare the diagnostic accuracy with Lung-RADS and National Lung Screening Trial criteria in an Asian population with high prevalen...

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Published inAcademic radiology Vol. 25; no. 10; p. 1240
Main Authors Hsu, Hui-Ting, Tang, En-Kuei, Wu, Ming-Ting, Wu, Carol C, Liang, Chia-Hao, Chen, Chi-Shen, Mar, Guang-Yuan, Lai, Ruay-Sheng, Wang, Jo-Ching, Wu, Chuan-Ling, Huang, Yi-Luan, Wu, Fu-Zong
Format Journal Article
LanguageEnglish
Published United States 01.10.2018
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ISSN1878-4046
DOI10.1016/j.acra.2018.01.012

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Abstract We proposed a modification of the ACR Lung Imaging Reporting and Data System (Lung-RADS) to clarify the characteristics of subsolid nodules with categories 1-11, and to compare the diagnostic accuracy with Lung-RADS and National Lung Screening Trial criteria in an Asian population with high prevalence of adenocarcinoma. We analyzed a retrospective cohort of 1978 consecutive healthy subjects (72.8% nonsmoker) who underwent low-dose computed tomography from August 2013 to October 2014 (1084 men, 894 women). Lung-RADS categories 2 and 3 were modified to include subcategories of 2A/2B/2C and 3A/3B/3C, respectively. Clinical information and nodule characteristics were recorded. Receiver operating characteristic curves were used to compare diagnostic accuracy at different cutoffs. Thirty-two subjects (30 nonsmokers) had pathology-proven adenocarcinoma spectrum lesions in the follow-up period (1.6 ± 0.5 years). Modified Lung-RADS, using modified Lung-RADS category 2C as cutoff, had an area under the curve (AUC) of 0.973 in predicting adenocarcinoma spectrum lesions (sensitivity of 100%, specificity of 89.3%), which was significantly higher than that of Lung-RADS (AUC = 0.815, P < .001) and National Lung Screening Trial (AUC = 0.906, P < .001). Furthermore, modified Lung-RADS showed an AUC of 0.992 in predicting invasive adenocarcinoma (sensitivity of 95%, specificity of 97.8%) when category 3B was used as cutoff. Modified Lung-RADS may substantially improve sensitivity while maintaining specificity for detection of adenocarcinoma spectrum lesions in an Asian population. Compared to Lung-RADS, it has enhanced ability to differentiate invasive from indolent adenocarcinoma by more refined subclassification of subsolid nodules using two cutoff values of category 2C and 3B. The effect of using modified Lung-RADS in clinical practice must be carefully studied in prospective large cohort studies.
AbstractList We proposed a modification of the ACR Lung Imaging Reporting and Data System (Lung-RADS) to clarify the characteristics of subsolid nodules with categories 1-11, and to compare the diagnostic accuracy with Lung-RADS and National Lung Screening Trial criteria in an Asian population with high prevalence of adenocarcinoma. We analyzed a retrospective cohort of 1978 consecutive healthy subjects (72.8% nonsmoker) who underwent low-dose computed tomography from August 2013 to October 2014 (1084 men, 894 women). Lung-RADS categories 2 and 3 were modified to include subcategories of 2A/2B/2C and 3A/3B/3C, respectively. Clinical information and nodule characteristics were recorded. Receiver operating characteristic curves were used to compare diagnostic accuracy at different cutoffs. Thirty-two subjects (30 nonsmokers) had pathology-proven adenocarcinoma spectrum lesions in the follow-up period (1.6 ± 0.5 years). Modified Lung-RADS, using modified Lung-RADS category 2C as cutoff, had an area under the curve (AUC) of 0.973 in predicting adenocarcinoma spectrum lesions (sensitivity of 100%, specificity of 89.3%), which was significantly higher than that of Lung-RADS (AUC = 0.815, P < .001) and National Lung Screening Trial (AUC = 0.906, P < .001). Furthermore, modified Lung-RADS showed an AUC of 0.992 in predicting invasive adenocarcinoma (sensitivity of 95%, specificity of 97.8%) when category 3B was used as cutoff. Modified Lung-RADS may substantially improve sensitivity while maintaining specificity for detection of adenocarcinoma spectrum lesions in an Asian population. Compared to Lung-RADS, it has enhanced ability to differentiate invasive from indolent adenocarcinoma by more refined subclassification of subsolid nodules using two cutoff values of category 2C and 3B. The effect of using modified Lung-RADS in clinical practice must be carefully studied in prospective large cohort studies.
Author Tang, En-Kuei
Liang, Chia-Hao
Mar, Guang-Yuan
Huang, Yi-Luan
Wu, Ming-Ting
Wu, Carol C
Wu, Chuan-Ling
Wu, Fu-Zong
Lai, Ruay-Sheng
Chen, Chi-Shen
Hsu, Hui-Ting
Wang, Jo-Ching
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  organization: Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
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  fullname: Chen, Chi-Shen
  organization: Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
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  fullname: Mar, Guang-Yuan
  organization: Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
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  surname: Lai
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  organization: Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
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  givenname: Jo-Ching
  surname: Wang
  fullname: Wang, Jo-Ching
  organization: Department of Radiology, Kaohsiung Veterans General Hospital, No. 386, Ta-Chung 1st Road, Kaohsiung, 81362, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan
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  givenname: Chuan-Ling
  surname: Wu
  fullname: Wu, Chuan-Ling
  organization: Department of Radiology, Kaohsiung Veterans General Hospital, No. 386, Ta-Chung 1st Road, Kaohsiung, 81362, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan
– sequence: 11
  givenname: Yi-Luan
  surname: Huang
  fullname: Huang, Yi-Luan
  organization: Department of Radiology, Kaohsiung Veterans General Hospital, No. 386, Ta-Chung 1st Road, Kaohsiung, 81362, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan
– sequence: 12
  givenname: Fu-Zong
  surname: Wu
  fullname: Wu, Fu-Zong
  email: cmvwu1029@gmail.com
  organization: Department of Radiology, Kaohsiung Veterans General Hospital, No. 386, Ta-Chung 1st Road, Kaohsiung, 81362, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan; School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. Electronic address: cmvwu1029@gmail.com
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ContentType Journal Article
Copyright Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
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Issue 10
Keywords Screening
diagnosis
low-dose CT (LDCT)
sensitivity and specificity
lung adenocarcinoma
Language English
License Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
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References 30017500 - Acad Radiol. 2018 Oct;25(10):1237-1239
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Snippet We proposed a modification of the ACR Lung Imaging Reporting and Data System (Lung-RADS) to clarify the characteristics of subsolid nodules with categories...
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StartPage 1240
SubjectTerms Adenocarcinoma - diagnostic imaging
Adenocarcinoma - epidemiology
Adenocarcinoma - pathology
Adult
Aged
Aged, 80 and over
Asian Continental Ancestry Group
Cohort Studies
Data Systems
Early Detection of Cancer
Female
Humans
Lung Neoplasms - diagnostic imaging
Lung Neoplasms - epidemiology
Lung Neoplasms - pathology
Male
Middle Aged
Prevalence
Radiology Information Systems
Retrospective Studies
Sensitivity and Specificity
Taiwan
Tomography, X-Ray Computed
Title Modified Lung-RADS Improves Performance of Screening LDCT in a Population with High Prevalence of Non-smoking-related Lung Cancer
URI https://www.ncbi.nlm.nih.gov/pubmed/29530488
Volume 25
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