Yan’an Hospital Affiliated to Kunming Medical University, Yunnan Kunming 650051, China , lidb88@163.com
Abstract: (9 Views)
Background:Ground-glass nodules (GGNs) represent early-stage lung adenocarcinoma (LUAD) and exhibit substantial genomic and radiomic heterogeneity. Integrating computed tomography (CT) radiomic features with genomic and epigenomic alterations may improve prediction of nodule progression and radiotherapy response. Materials and Methods: A systematic literature search was conducted across PubMed, Scopus, and Web of Science (2010–2024) using predefined terms related to GGNs, radiogenomics, LUAD, CT radiomics, and radiosensitivity. Studies were included if they reported (1) human GGN data, (2) genomic or epigenomic characterization, and (3) radiomic features or CT phenotypes. Two reviewers independently screened articles, extracted data, and validated radiogenomic associations. Results: A total of 4,820 patients from eligible studies were analyzed. Distinct CT radiomic features - including attenuation, solidity ratio, textural entropy, vascular convergence, and shape irregularity - corresponded with recurrent genomic drivers. EGFR-mutant GGNs typically presented as pure or mixed GGNs with smooth margins, whereas KRAS-, TP53-, and KEAP1/NRF2-altered lesions showed higher solidity and increased heterogeneity. Radiomic complexity correlated with mutational burden, copy-number alterations, and pathway dysregulation in PI3K/AKT/mTOR, MAPK, Hippo/YAP, and TGF-β signaling. Several radiogenomic signatures also corresponded to predicted radiosensitivity or radioresistance, particularly features associated with oxidative stress pathways and immune microenvironment states. Conclusion: Radiogenomic integration provides critical insight into the biological heterogeneity of GGN-associated LUAD. CT radiomic features reflect underlying genomic alterations and may predict progression and radiotherapy responsiveness. This review establishes a structured framework for the radiogenomic interpretation of GGNs and outlines future applications in precision oncology and radiotherapy planning.