Global Trends and Research Hotspots in Lung Cancer Radiomics: A Bibliometric Analysis From 2015 to 2025

Background: Radiomics in lung cancer has experienced rapid development in recent years, yet its global research landscape and emerging hotspots remain insufficiently characterized. This study aims to systematically describe the development trends, contribution patterns, hotspot evolution, and emerging directions of lung cancer radiomics using bibliometric methods. Methods: Literature related to “lung cancer radiomics” published between January 1, 2015, and December 31, 2025, was retrieved from the Web of Science Core Collection. Bibliometric analysis was conducted using the CiteSpace and R package bibliometrix. Metrics included annual publication output, national and institutional contributions, collaborative networks, author productivity, keyword clustering, co-citation networks, and hotspot evolution. Results: A total of 2116 publications (376 reviews and 1740 articles) from 2015 to 2025 were included. China contributed the largest number of publications, whereas the United States showed the highest H-index and citation impact. Shandong First Medical University was the most productive institution, and Robert J. Gillies was the most prolific author. High-frequency keywords formed five clusters, summarizing four major research themes: diagnostic imaging modalities (computed tomography, positron emission tomography), application directions (classification, diagnosis), imaging indicators (textural features, signatures), and prognosis (survival, pulmonary nodules, prognostic value). Recent research hotspots focus on artificial intelligence–based computer-aided clinical applications and precision oncology. Conclusion: Radiomics in lung cancer is undergoing rapid expansion, with research focus shifting toward artificial intelligence and bioinformatic imaging features. Enhancing research quality and international collaboration, particularly in China, is crucial for advancing the clinical translation of radiomics.