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Low-Dose CT Screening of Persistent Subsolid Lung Nodules: First-Order Features in Radiomics
Background Nondisappearing subsolid nodules requiring follow-up are often detected during lung cancer screening, but changes in their invasiveness can be overlooked owing to slow growth. We aimed to develop a method for automatic identification of invasive tumors among subsolid nodules during multiple health checkups using radiomics technology based on low-dose computed tomography (LD-CT) and examine its effectiveness.
Methods We examined patients who underwent LD-CT screening from 2014 to 2019 and had lung adenocarcinomas resected after 5-year follow-ups. They were categorized into the invasive or less-invasive group; the annual growth/change rate (Δ) of the nodule voxel histogram using three-dimensional CT (e.g., tumor volume, solid volume percentage, mean CT value, variance, kurtosis, skewness, and entropy) was assessed. A discriminant model was designed through multivariate regression analysis with internal validation to compare its efficacy with that of a volume doubling time of < 400 days.
Results The study included 47 tumors (23 invasive, 24 less invasive), with no significant difference in the initial tumor volumes. Δskewness was identified as an independent predictor of invasiveness (adjusted odds ratio, 0.021; p = 0.043), and when combined with Δvariance, it yielded high accuracy in detecting invasive lesions (88% true-positive, 80% false-positive). The detection model indicated surgery 2 years earlier than the volume doubling time, maintaining accuracy (median 3 years vs.1 year before actual surgery, p = 0.011).
Conclusion LD-CT radiomics showed promising potential in ensuring timely detection and monitoring of subsolid nodules that warrant follow-up over time.
Keywordslung cancer treatment (surgery medical) - lung cancer - diagnosis (includes staging imaging fiducials) - minimally invasive surgery (includes port access minithoracotomy)
Data collection: N.Y., D.Y.; design of the study: N.Y., F.K., T.B.; statistical analysis: N.Y., K.H.; analysis and interpretation of the data: N.Y., K.H., D.Y., F.K., T.B.; drafting the manuscript: N.Y., K.H., F.K., T.B.; critical revision of the manuscript: N.Y., D.Y., K.H., F.K., T.B.
Received: 07 July 2023
Accepted: 17 August 2023
Accepted Manuscript online:
22 August 2023
Article published online:
25 September 2023
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