Literature DB >> 29530488

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

Hui-Ting Hsu1, En-Kuei Tang2, Ming-Ting Wu3, Carol C Wu4, Chia-Hao Liang5, Chi-Shen Chen6, Guang-Yuan Mar6, Ruay-Sheng Lai6, Jo-Ching Wang3, Chuan-Ling Wu3, Yi-Luan Huang3, Fu-Zong Wu7.   

Abstract

OBJECTIVES: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Screening; diagnosis; low-dose CT (LDCT); lung adenocarcinoma; sensitivity and specificity

Mesh:

Year:  2018        PMID: 29530488     DOI: 10.1016/j.acra.2018.01.012

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  15 in total

1.  From low-dose to no-dose: thin-section magnetic resonance imaging for evaluation of pulmonary nodules.

Authors:  Tommaso D'Angelo; Thomas J Vogl; Julian L Wichmann
Journal:  J Thorac Dis       Date:  2018-04       Impact factor: 2.895

2.  The impact of patients' preferences on the decision of low-dose computed tomography lung cancer screening.

Authors:  Fu-Zong Wu; Pei-Lun Kuo; Carol C Wu; Ming-Ting Wu
Journal:  Transl Lung Cancer Res       Date:  2018-09

Review 3.  Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study.

Authors:  David S Gierada; William C Black; Caroline Chiles; Paul F Pinsky; David F Yankelevitz
Journal:  Radiol Imaging Cancer       Date:  2020-03-27

Review 4.  Landscape on CT screening for lung cancer in Asia.

Authors:  Natthaya Triphuridet; Claudia Henschke
Journal:  Lung Cancer (Auckl)       Date:  2019-09-30

5.  Differences in lung cancer characteristics and mortality rate between screened and non-screened cohorts.

Authors:  Fu-Zong Wu; Pei-Lun Kuo; Yi-Luan Huang; En-Kuei Tang; Chi-Shen Chen; Ming-Ting Wu; Yun-Pei Lin
Journal:  Sci Rep       Date:  2019-12-18       Impact factor: 4.379

6.  Association of cancer screening and residing in a coal-polluted East Asian region with overall survival of lung cancer patients: a retrospective cohort study.

Authors:  Runxiang Yang; Ming He; Dongmei Wang; Rongrong Ye; Lu Li; Rouyu Deng; Mohsin Shah; Sai-Ching Jim Yeung
Journal:  Sci Rep       Date:  2020-10-15       Impact factor: 4.379

7.  A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules.

Authors:  Yun-Ju Wu; Yung-Chi Liu; Chien-Yang Liao; En-Kuei Tang; Fu-Zong Wu
Journal:  Sci Rep       Date:  2021-01-18       Impact factor: 4.379

8.  Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening.

Authors:  Hong Lu; Jongphil Kim; Jin Qi; Qian Li; Ying Liu; Matthew B Schabath; Zhaoxiang Ye; Robert J Gillies; Yoganand Balagurunathan
Journal:  Cancer Manag Res       Date:  2020-11-27       Impact factor: 3.989

9.  Qualitative and quantitative imaging features of pulmonary subsolid nodules: differentiating invasive adenocarcinoma from minimally invasive adenocarcinoma and preinvasive lesions.

Authors:  Linlin Qi; Wenwen Lu; Lin Yang; Wei Tang; Shijun Zhao; Yao Huang; Ning Wu; Jianwei Wang
Journal:  J Thorac Dis       Date:  2019-11       Impact factor: 2.895

10.  Artificial neural networks improve LDCT lung cancer screening: a comparative validation study.

Authors:  Yin-Chen Hsu; Yuan-Hsiung Tsai; Hsu-Huei Weng; Li-Sheng Hsu; Ying-Huang Tsai; Yu-Ching Lin; Ming-Szu Hung; Yu-Hung Fang; Chien-Wei Chen
Journal:  BMC Cancer       Date:  2020-10-22       Impact factor: 4.430

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