ArticleBMJ open respiratory research2026
Automated identification of interstitial lung abnormalities in lung screening using quantitative CT.
Article in BMJ open respiratory research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesInterstitial lung abnormalities (ILAs) are an important incidental finding in lung screening. Quantitative CT (qCT) offers a promising approach to standardising ILA assessment; however, its adoption into routine clinical practice remains limited, largely due to the need for further clinical validation.
settingWe evaluated the performance of e-Lung (Brainomix), a commercially available qCT tool in assessing ILAs for participants attending a lung cancer screening programme.
participantsAll participants invited to attend the West London lung cancer screening pilot programme between 2018 and 2020. PRIMARY OUTCOME MEASURES: To define the optimal qCT biomarker thresholds that identified ILA as defined by expert thoracic radiologists.
resultse-Lung qCT biomarkers had an area under the curve of between 0.82 and 0.88, and between 0.84 and 0.87 for visually quantified ILA extent thresholds of at least 5% and >10%, respectively.
conclusione-Lung is a qCT tool with potential utility in the automated identification of ILA in participants undergoing lung screening.
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