Korean J Radiol.  2017 Apr;18(2):402-407. 10.3348/kjr.2017.18.2.402.

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 DH
• Goo JM
• Chong S
• Ahn MI

• KMID: 2427953
• DOI: http://doi.org/10.3348/kjr.2017.18.2.402

Abstract

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.

Keyword

Questionnaires; Pulmonary nodule; Screening; Lung-RADS

MeSH Terms

Humans
Internet
Lung/diagnostic imaging
Lung Neoplasms/*diagnosis/diagnostic imaging/pathology
Middle Aged
Observer Variation
Radiologists/*psychology
Societies, Medical
Surveys and Questionnaires
*Tomography, X-Ray Computed

Figure

• 

  Fig. 1 Lung-RADS categories rearranged by Korean Imaging Study Group for Lung Cancer according to nodule type, size, and interval change. Solid (A), part-solid nodule (B), pure GGN (C), and special consideration (D). *Additional features: spiculation, GGN that doubles in size in 1 year, enlarged lymph nodes etc. GGN = ground-glass nodule, Lung-RADS = Lung Imaging Reporting and Data System

• 

  Fig. 2 Respondents' score distributions. Score = number of answers that agreed with consensus answers

• 

  Fig. 3 Number of answers that disagreed with consensus answers. Answers were distributed according to degree of over- or under-estimation of malignancy risk: “under” indicates underestimation of risk by two Lung-RADS categories; “over 1” indicates overestimation by one category. Lung-RADS = Lung Imaging Reporting and Data System

• 

  Fig. 4 Number of answers submitted for each question. White letters in graph indicate consensus answers.

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