Korean Journal of Radiology

  • 제18권2호
  • /
  • Pages.402-407
  • /
  • 2017
  • /
  • 1229-6929(pISSN)
  • /
  • 2005-8330(eISSN)
대한영상의학회 (The Korean Society of Radiology)
권호 표지
DOI QR코드

DOI QR Code

Are Lung Imaging Reporting and Data System Categories Clear to Radiologists? A Survey of the Korean Society of Thoracic Radiology Members on Ten Difficult-to-Classify Scenarios

  • Han, Dae Hee (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Goo, Jin Mo (Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Chong, Semin (Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine) ;
  • Ahn, Myeong Im (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
  • 투고 : 2016.06.26
  • 심사 : 2016.09.20
  • 발행 : 2017.04.01
⟨ 이전 논문 다음 논문 ⟩

초록

Objective: To evaluate possible variability in chest radiologists' interpretations of the Lung Imaging Reporting and Data System (Lung-RADS) on difficult-to-classify scenarios. Materials and Methods: Ten scenarios of difficult-to-classify imaginary lung nodules were prepared as an online survey that targeted Korean Society of Thoracic Radiology members. In each question, a description was provided of the size, consistency, and interval change (new or growing) of a lung nodule observed using annual repeat computed tomography, and the respondent was instructed to choose one answer from five choices: category 2, 3, 4A, or 4B, or "un-categorizable." Consensus answers were established by members of the Korean Imaging Study Group for Lung Cancer. Results: Of the 420 answers from 42 respondents (excluding multiple submissions), 310 (73.8%) agreed with the consensus answers; eleven (26.2%) respondents agreed with the consensus answers to six or fewer questions. Assigning the imaginary nodules to categories higher than the consensus answer was more frequent (16.0%) than assigning them to lower categories (5.5%), and the agreement rate was below 50% for two scenarios. Conclusion: When given difficult-to-classify scenarios, chest radiologists showed large variability in their interpretations of the Lung-RADS categories, with high frequencies of disagreement in some specific scenarios.

키워드

과제정보

연구 과제 주관 기관 : Ministry for Health and Welfare

참고문헌

  1. National Lung Screening Trial Research Team, Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409 https://doi.org/10.1056/NEJMoa1102873
  2. Jaklitsch MT, Jacobson FL, Austin JH, Field JK, Jett JR, Keshavjee S, et al. The American Association for Thoracic Surgery guidelines for lung cancer screening using low-dose computed tomography scans for lung cancer survivors and other high-risk groups. J Thorac Cardiovasc Surg 2012;144:33-38 https://doi.org/10.1016/j.jtcvs.2012.05.060
  3. Detterbeck FC, Mazzone PJ, Naidich DP, Bach PB. Screening for lung cancer: diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143(5 Suppl):e78S-e92S https://doi.org/10.1378/chest.12-2350
  4. Canadian Task Force on Preventive Health Care, Lewin G, Morissette K, Dickinson J, Bell N, Bacchus M, et al. Recommendations on screening for lung cancer. CMAJ 2016;188:425-432 https://doi.org/10.1503/cmaj.151421
  5. Wood DE. National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines for Lung Cancer Screening. Thorac Surg Clin 2015;25:185-197 https://doi.org/10.1016/j.thorsurg.2014.12.003
  6. de Koning HJ, Meza R, Plevritis SK, ten Haaf K, Munshi VN, Jeon J, et al. Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive Services Task Force. Ann Intern Med 2014;160:311-320 https://doi.org/10.7326/M13-2316
  7. Decision Memo for Screening for Lung Cancer with Low Dose Computed Tomography (LDCT) (CAG-00439N). Web site. https://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=274. Accessed June 3, 2016
  8. Lung CT Screening Reporting and Data System (Lung-RADSTM). Web site. https://www.acr.org/Quality-Safety/Resources/LungRADS. Accessed June 3, 2016
  9. Pinsky PF, Gierada DS, Black W, Munden R, Nath H, Aberle D, et al. Performance of Lung-RADS in the National Lung Screening Trial: a retrospective assessment. Ann Intern Med 2015;162:485-491 https://doi.org/10.7326/M14-2086
  10. McKee BJ, Regis SM, McKee AB, Flacke S, Wald C. Performance of ACR Lung-RADS in a clinical CT lung screening program. J Am Coll Radiol 2015;12:273-276 https://doi.org/10.1016/j.jacr.2014.08.004
  11. Grimshaw JM, Hutchinson A. Clinical practice guidelines--do they enhance value for money in health care? Br Med Bull 1995;51:927-940 https://doi.org/10.1093/oxfordjournals.bmb.a073006

피인용 문헌

  1. A Survey of Institutions with Sixteen Detector-Rows or More CT Scanners for the Introduction of National Lung Cancer Screening Program Using Low-Dose Chest CT vol.77, pp.6, 2017, https://doi.org/10.3348/jksr.2017.77.6.404
  2. Screening for Lung Cancer: Lexicon for Communicating With Health Care Providers vol.210, pp.3, 2017, https://doi.org/10.2214/ajr.17.18865
  3. Radiological Report of Pilot Study for the Korean Lung Cancer Screening (K-LUCAS) Project: Feasibility of Implementing Lung Imaging Reporting and Data System vol.19, pp.4, 2018, https://doi.org/10.3348/kjr.2018.19.4.803
  4. Appropriate Timing for Follow-Up CT Imaging for Stable Lung CT Screening Reporting and Data System Category 3 Lesions Identified at Baseline Low-Dose CT vol.211, pp.6, 2017, https://doi.org/10.2214/ajr.18.20216
  5. National Lung Cancer Screening in Korea: Introduction and Imaging Quality Control vol.80, pp.5, 2017, https://doi.org/10.3348/jksr.2019.80.5.826
  6. Clinical Significance of Lung-RADS Category 3 Lesions in the National Lung Screening Trial vol.16, pp.7, 2017, https://doi.org/10.1016/j.jtho.2021.02.025