2468 - Quantifying Radiation-Induced Pulmonary Fibrosis: A Novel CT-Based Approach to Measuring Lung Scarring after SBRT

Purpose/Objective(s): Radiation-induced pulmonary fibrosis (RPIF) is a common late effect of lung radiotherapy, with significant variation in severity among patients. Few efficient, low-resource methods exist for quantifying lung tissue scarring. This study proposes a novel method, treatment area combined density change (TACDC), to measure RPIF using existing computed tomography (CT) scans. This approach enables retrospective analysis of radiotherapy outcomes and may help identify patient factors contributing to RPIF susceptibility.

Materials/Methods: A retrospective analysis was conducted on 12 patients diagnosed with stage 1 lung cancer and treated with stereotactic body radiation therapy (SBRT) between May 2022 and June 2024. All patients received 50 Gy in five fractions using the treatment planning software, with treatment delivered on the Varian EDGE system. The cohort had a mean age of 73 years (SD = 7.68) and included three male and nine female patients. To quantify RPIF, Hounsfield unit (HU) densities were measured in three predefined circular regions on axial CT images at three time points: pre-treatment, early post-treatment (3–5 months), and late post-treatment (5–15 months). The primary measurement was a circular region encompassing the largest cross-section of the tumor. Two adjacent 1 cm diameter circular regions were selected within the lung parenchyma—one tangent to the treatment area and another extending further into the lung tissue. The 1 cm diameter ensured consistent, reproducible sampling of fibrotic changes.

Results: TACDC was computed as the sum of average HU densities across these three regions. Differences between post-treatment and pre-treatment TACDC values were defined as TACDC 1 (early post-treatment) and TACDC 2 (late post-treatment). A positive TACDC indicated increased lung density, suggesting fibrosis progression. TACDC 2 showed strong internal consistency with TACDC 1 (r = 0.719, p < .05), supporting method reliability. Correlations with patient demographics revealed younger age (r = -0.600, p = .06) and higher weight (r = 0.571, p = .08) were associated with increased fibrosis. Prior smoking history correlated negatively (r = -0.671, p < .05), while prior chemotherapy (r = 0.631, p = .05) and immunotherapy (r = 0.741, p = .01) were associated with greater fibrosis progression. TACDC 1 showed similar trends but with greater variability, reflecting early post-radiation changes.

Conclusion: This study introduces TACDC as a quantitative and computationally simple method for assessing RPIF using routine CT imaging. Findings suggest that age, weight, smoking history, and prior systemic therapies influence RPIF severity. Given the small sample size, future research should validate TACDC on larger datasets and explore its integration with automated imaging analysis or machine learning models to improve fibrosis risk prediction and radiation treatment planning.