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Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening.

ABSTRACT: To measure reader agreement in determining whether lung nodules detected at baseline screening computed tomography (CT) had changed at subsequent screening examinations and to evaluate the variability in recommendations for further follow-up.All subjects were enrolled in the National Lung Screening Trial (NLST), and each participant consented to the use of their de-identified images for research purposes. The authors randomly selected 100 cases of nodules measuring at least 4.0 mm at 1-year screening CT that were considered by the original screening CT reader to be present on baseline CT scans; nodules considered by the original reader to have changed were oversampled. Selected images from each case showing the entire nodule at both examinations were preloaded on a picture archiving and communication system workstation. Nine radiologists served as readers, and they evaluated whether the nodule was present at baseline and recorded the bidimensional measurements and nodule characteristics at each examination, presence or absence of change, results of screening CT, and follow-up recommendations (high-level follow-up, low-level follow-up, no follow-up).On the basis of reviews during case selection, five nodules seen at follow-up were judged not to have been present at baseline; for 19 of the remaining 95 cases, at least one reader judged the nodule not to have been present at baseline. For the 76 nodules that were unanimously considered to have been present at baseline, 21%-47% (mean ± standard deviation, 30% ± 9) were judged to have grown. The ? values were similar for growth (? = 0.55) and a positive screening result (? = 0.51) and were lower for a change in margins and attenuation (? = 0.27-0.31). The ? value in the recommendation of high- versus low-level follow-up was high (? = 0.66).Reader agreement on nodule growth and screening result was moderate to substantial. Agreement on follow-up recommendations was lower.

SUBMITTER: Singh S

PROVIDER: S-EPMC3064819 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening.

Singh Satinder S Pinsky Paul P Fineberg Naomi S NS Gierada David S DS Garg Kavita K Sun Yanhui Y Nath P Hrudaya PH

Radiology 20110119 1

<h4>Purpose</h4>To measure reader agreement in determining whether lung nodules detected at baseline screening computed tomography (CT) had changed at subsequent screening examinations and to evaluate the variability in recommendations for further follow-up.<h4>Materials and methods</h4>All subjects were enrolled in the National Lung Screening Trial (NLST), and each participant consented to the use of their de-identified images for research purposes. The authors randomly selected 100 cases of no ...[more]

PMID: 21248232

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Project description:IntroductionA non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice.Methods and analysisA retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers' performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty.Ethics and disseminationThe study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal.Trial registration numberNCT06018545.

Project description:BackgroundLung cancer screening (LCS) via chest computed tomography (CT) scans can save lives by identifying early-stage tumors. However, most smokers die of comorbid smoking-related diseases. LCS scans contain information about smoking-related conditions that is not currently systematically assessed. Identifying these common comorbid diseases on CT could increase the value of screening with minimal impact on LCS programs. We determined the prevalence of 3 comorbid diseases from LCS eligible scans and quantified related adverse outcomes.MethodsWe studied COPD Genetic Epidemiology study (COPDGene®) participants (n=4078) who met criteria for LCS screening at enrollment (age > 55 years, and < 80 years, > 30 pack years smoking, current smoker or former smoker within 15 years of smoking cessation). CT scans were assessed for coronary artery calcification (CAC), emphysema, and vertebral bone density. We tracked the following clinically significant events: myocardial infarctions (MIs), strokes, pneumonia, respiratory exacerbations, and hip and vertebral fractures.ResultsOverall, 77% of eligible CT scans had one or more of these diagnoses identified. CAC (> 100 mg) was identified in 51% of scans, emphysema in 44%, and osteoporosis in 54%. Adverse events related to the underlying smoking-related diseases were common, with 50% of participants reporting at least one. New diagnoses of cardiovascular disease, emphysema and osteoporosis were made in 25%, 7% and 46%, of participants respectively. New diagnosis of disease was associated with significantly more adverse events than in participants who did not have CT diagnoses for both osteoporosis and cardiovascular risk.ConclusionsExpanded analysis of LCS CT scans identified individuals with evidence of previously undiagnosed cardiovascular disease, emphysema or osteoporosis that corresponded with adverse events. LCS CT scans can potentially facilitate diagnoses of these smoking-related diseases and provide an opportunity for treatment or prevention.

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Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening.

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Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening.

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