Objectives: To assess interobserver agreement in Lung CT Screening Reporting and Data System (Lung-RADS) categorisation in subsolid nodule-enriched low-dose screening CTs.
Methods: A retrospective review of low-dose screening CT reports from 2013 to 2017 using keyword searches for subsolid nodules identified 54 baseline CT scans. With an additional 108 negative screening CT scans, a total of 162 CT scans were categorised according to the Lung-RADS by two fellowship-trained thoracic radiologists in consensus. We randomly selected 20, 20, 10, and 10 scans from categories 1/2, 3, 4A, and 4B CT scans, respectively, to ensure balanced category representation. Five radiologists classified the 60 CT scans into Lung-RADS categories. The frequencies of concordance and minor and major discordance were calculated, with major discordance defined as at least 6 months of management discrepancy. We used Cohen's κ statistics to analyse reader agreement.
Results: An average of 60.3% (181 of 300) of all cases and 45.0% (90 of 200) of positive screens were correctly categorised. The minor and major discordance rates were 12.3% and 27.3% overall and 18.5% and 36.5% in positive screens, respectively. The concordance rate was significantly higher among experienced thoracic radiologists. Overall, the interobserver agreement was moderate (mean κ, 0.45; 95% confidence interval: 0.40-0.51). The proportion of part-solid risk-dominant nodules was significantly higher in cases with low rates of accurate categorisation.
Conclusion: This retrospective study observed variable accuracy and moderate interobserver agreement in radiologist categorisation of subsolid nodules in screening CTs. This inconsistency may affect management recommendations for lung cancer screening.
Key Points: • Diagnostic performance for Lung-RADS categorisation is variable among radiologists with fair to moderate interobserver agreement in subsolid nodule-enriched CT scans. • Experienced thoracic radiologists showed more accurate and consistent Lung-RADS categorisation than radiology residents. • The relative abundance of part-solid nodules was a potential factor related to increased disagreement in Lung-RADS categorisation.
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http://dx.doi.org/10.1007/s00330-021-07800-5 | DOI Listing |
Dent Res J (Isfahan)
December 2024
Department of Periodontology, Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
Background: Chronic apical periodontitis (AP) may influence the outcome of root canal treatment. Thus, it is important to diagnose AP using the best method available. This research was done to compare the diagnostic accuracy of parallel periapical radiography (PR) and different field of views (FOVs) of cone-beam computed tomography (CBCT).
View Article and Find Full Text PDFOpen Heart
January 2025
Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Background: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis imaging quantitative CT, AI-QCT).
Methods: The study included 208 patients with suspected coronary artery disease (CAD) undergoing CCTA in Perfusion Imaging and CT Coronary Angiography With Invasive Coronary Angiography-1.
J Clin Med
January 2025
Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, 38123 Trento, Italy.
The assessment of lymph node (LN) involvement with clinical imaging is a key factor in cancer staging. Node Reporting and Data System 1.0 (Node-RADS) was introduced in 2021 as a new system specifically tailored for classifying and reporting LNs on computed tomography (CT) and magnetic resonance imaging scans.
View Article and Find Full Text PDFJ Clin Med
December 2024
Faculty of Medicine, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland.
Abdom Radiol (NY)
January 2025
Department of Radiology, Peking University People's Hospital, Beijing, China.
Purpose: Correctly classifying uterine fibroids is essential for treatment planning. The objective of this study was to assess the accuracy and reliability of the FIGO classification system in categorizing uterine fibroids via organ-axial T2WI and to further investigate the factors associated with uterine compression.
Methods: A total of 130 patients with ultrasound-confirmed fibroids were prospectively enrolled between March 2023 and May 2024.
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