Quantitative CT lung fibrosis and immune checkpoint inhibitor–related pneumonitis in NSCLC.

e20531 Background: Interstitial lung abnormalities (ILAs) are established risk factors for immune checkpoint inhibitor–related pneumonitis (ICI-P), but qualitative ILA assessment is subjective. We evaluated whether quantitative lung fibrosis (QLF) metrics from pretreatment computed tomography (CT) are associated with ICI-P in patients with non–small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs). Methods: We retrospectively analyzed 241 patients with metastatic NSCLC treated with ICIs. Pretreatment CT scans underwent quantitative analysis using commercial software (VIDA) to extract QLFs representing consolidation, ground-glass opacity (GGO), emphysema, reticulation, and honeycombing. QLFs were quantified by percentage, volume, and estimated mass at total lung, lobar (upper vs lower), and subregional (core [central] vs peel [peripheral]) levels. Associations between QLFs and ICI-P were evaluated using univariate logistic regression. Results: Regional QLFs demonstrated differential associations with ICI-P. Upper-lobe QLFs were not associated with pneumonitis (all p≥0.13). In contrast, lower-lobe mass-based fibrosis metrics were associated with increased ICI-P risk, including GGO mass (OR 1.005, 95% CI 1.001–1.010; p=0.030), quantitative ILD (QILD) mass (OR 1.004, 95% CI 1.000–1.008; p=0.031), and quantitative ILA (QILA) mass (OR 1.004, 95% CI 1.001–1.007; p=0.024). Total-lung QILA mass showed a trend toward association (OR 1.002, 95% CI 1.000–1.004; p=0.086). Subregional analysis demonstrated stronger associations in peripheral (peel) regions; peel consolidation volume was associated with ICI-P (OR 1.102, 95% CI 1.013–1.198; p=0.023), whereas no core metric reached significance. Conclusions: Quantitative fibrosis metrics from pretreatment CT, particularly lower-lobe and peripheral mass-based QLFs, are associated with immune checkpoint inhibitor–related pneumonitis in NSCLC. Incorporation of regional quantitative fibrosis measures into baseline imaging assessment may help identify patients at elevated pneumonitis risk and inform surveillance strategies. These findings support further multivariable validation of quantitative CT fibrosis metrics as imaging biomarkers for immunotherapy-related pneumonitis. Associations between quantitative lung fibrosis metrics and immune checkpoint inhibitor–related pneumonitis in NSCLC. Region Metric (Mass-based QLF) (gm) OR 95% CI p-value Lower lobe GGO Mass 1.005 1.001–1.010 0.030 Lower lobe QILD Mass 1.004 1.000–1.008 0.031 Lower lobe QILA Mass 1.004 1.001–1.007 0.024 Upper lobe No significant predictors — — ≥0.13 Total lung QILA Mass 1.002 1.000–1.004 0.086

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Journal
Journal of Clinical Oncology
Published
2026-05-28
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.e20531
Primary Topic
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
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article
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article

Quantitative CT lung fibrosis and immune checkpoint inhibitor–related pneumonitis in NSCLC.

Rupali Sood, Mohammad I. Ghanbar, Joshua Schirm, Eman Showkatian et al.
Journal of Clinical Oncology
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
article

Quantitative CT lung fibrosis and immune checkpoint inhibitor–related pneumonitis in NSCLC.

Rupali Sood, Mohammad I. Ghanbar, Joshua Schirm, Eman Showkatian, Kevin Ho, Karthik Suresh, SARAH FORSYTHE, Mazen Aiche, Felipe Soto, M Altan, G Shroff, G Gaskey, S Peterson, A Sheshadri, S A Faiz, M C Boshkos, A Naing, A Muneer, Ferando Camacho, Jia Wu
article en

Abstract

e20531 Background: Interstitial lung abnormalities (ILAs) are established risk factors for immune checkpoint inhibitor–related pneumonitis (ICI-P), but qualitative ILA assessment is subjective. We evaluated whether quantitative lung fibrosis (QLF) metrics from pretreatment computed tomography (CT) are associated with ICI-P in patients with non–small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs). Methods: We retrospectively analyzed 241 patients with metastatic NSCLC treated with ICIs. Pretreatment CT scans underwent quantitative analysis using commercial software (VIDA) to extract QLFs representing consolidation, ground-glass opacity (GGO), emphysema, reticulation, and honeycombing. QLFs were quantified by percentage, volume, and estimated mass at total lung, lobar (upper vs lower), and subregional (core [central] vs peel [peripheral]) levels. Associations between QLFs and ICI-P were evaluated using univariate logistic regression. Results: Regional QLFs demonstrated differential associations with ICI-P. Upper-lobe QLFs were not associated with pneumonitis (all p≥0.13). In contrast, lower-lobe mass-based fibrosis metrics were associated with increased ICI-P risk, including GGO mass (OR 1.005, 95% CI 1.001–1.010; p=0.030), quantitative ILD (QILD) mass (OR 1.004, 95% CI 1.000–1.008; p=0.031), and quantitative ILA (QILA) mass (OR 1.004, 95% CI 1.001–1.007; p=0.024). Total-lung QILA mass showed a trend toward association (OR 1.002, 95% CI 1.000–1.004; p=0.086). Subregional analysis demonstrated stronger associations in peripheral (peel) regions; peel consolidation volume was associated with ICI-P (OR 1.102, 95% CI 1.013–1.198; p=0.023), whereas no core metric reached significance. Conclusions: Quantitative fibrosis metrics from pretreatment CT, particularly lower-lobe and peripheral mass-based QLFs, are associated with immune checkpoint inhibitor–related pneumonitis in NSCLC. Incorporation of regional quantitative fibrosis measures into baseline imaging assessment may help identify patients at elevated pneumonitis risk and inform surveillance strategies. These findings support further multivariable validation of quantitative CT fibrosis metrics as imaging biomarkers for immunotherapy-related pneumonitis. Associations between quantitative lung fibrosis metrics and immune checkpoint inhibitor–related pneumonitis in NSCLC. Region Metric (Mass-based QLF) (gm) OR 95% CI p-value Lower lobe GGO Mass 1.005 1.001–1.010 0.030 Lower lobe QILD Mass 1.004 1.000–1.008 0.031 Lower lobe QILA Mass 1.004 1.001–1.007 0.024 Upper lobe No significant predictors — — ≥0.13 Total lung QILA Mass 1.002 1.000–1.004 0.086

Journal of Clinical OncologyVol. 44(16_suppl)
The University of Texas MD Anderson Cancer Center (US), Johns Hopkins University (US), Johns Hopkins Hospital (US), The Ohio State University (US)
Good health and well-being
Openalex Percentile: Top 6%
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
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