Prevalence of Interstitial Lung Abnormalities (ILAs) in Italian Lung Cancer Screening Programs: A Monocentric Study

Background: Because of the increased awareness of the clinical importance of ILAs on chest CT, this study aims to determine the prevalence of ILAs in an Italian health cohort undergoing CT for a lung cancer screening (LCS) program and quantify ILA using both visual and deep learning-based analyses. Methods: In this observational, retrospective monocentric study, 500 participants (ITALUNG2, n = 100; RISP, n = 400) underwent low-dose CT (CTDI < 2mGy). Two radiologists retrospectively reviewed the images and determined the presence and extent of ILAs, classifying them as fibrotic or non-fibrotic, while a lung texture analysis was performed by using commercially available deep learning–based software. Results: ILAs were present in 34 patients (11 females and 23 males), with a prevalence of 6,8%, with similar rates across both screening cohorts taken individually. Interobserver agreement between radiologists was almost perfect, whereas concordance between visual and automated quantification was substantial. Visual assessment tended to yield higher estimates of ILA extent compared with software-based analysis. Conclusions: These findings confirm that ILAs are relatively common in LCS populations and highlight the importance of their detection and characterization, particularly for fibrotic patterns. Differences between visual and automated approaches underline the need for further refinement and validation of quantitative tools.