Radiogenomic approach combining CT-based radiomics and liquid biopsy improves prognostic stratification in patients with advanced NSCLC

Background: Radiomics and liquid biopsy represent minimally invasive approaches to assess disease characteristics in solid tumors. We integrated computed tomography (CT) radiomics and circulating tumor DNA (ctDNA) analysis to enhance prognostic stratification and longitudinal monitoring in patients with advanced non-small cell lung cancer (NSCLC). Methods: This study prospectively enrolled 91 patients with advanced NSCLC. Baseline molecular profiling was performed on both tumor tissue and plasma ctDNA using targeted next-generation sequencing. Radiomic features were extracted from baseline CT lung lesions using PyRadiomics, and radiomic scores (RS) were developed using LASSO-regularized Cox models. A subgroup of 21 patients with actionable molecular alterations underwent longitudinal CT scans and liquid biopsies during targeted therapy. Clinical, radiomic, and molecular associations with overall survival (OS) and disease-free survival (DFS) were evaluated using log-rank tests and included in multivariable models. Results: Overall concordance between tissue and ctDNA (n = 67 patients) was 85%. In the combined clinical-radiomic-genetic model (C-index: 0.73), the RS (p < 0.001) and the presence of actionable alterations (p = 0.041) were independent OS predictors. For DFS, the integrated model achieved a cross-validated C-index of 0.77, outperforming the clinical-only model (0.59). In patients with EGFR-mutant NSCLC, detectable baseline ctDNA was significantly associated with a higher risk of disease progression (p = 0.018). In this subgroup, the combined clinical-radiogenomic model achieved a cross-validated C-index of 0.80 for DFS. Longitudinal analysis showed that 17 of 21 patients achieved molecular clearance of ctDNA at the first follow-up, correlating with treatment response. Conclusions: Integrating radiomics with liquid biopsy provides a more robust prognostic assessment of advanced NSCLC than clinical or molecular data alone. This multi-modal approach may offer a minimally invasive strategy for personalized risk stratification and monitoring of treatment response in patients with NSCLC. Clinicaltrials.gov identifier: NCT06331975.