Worldwide research landscape of radiomics in lung cancer: A scientometric study

Background The main cause of cancer-related deaths around the world is lung cancer. Therefore, the diagnosis and treatment of lung cancer make up the majority of clinical research focused on cancer. In recent years, there have been significant advancements in the application of radiomics in lung cancer. However, there are no studies on global research trends in the application of radiomics in lung cancer. To address this gap, this study investigates the current state of research and key application areas of radiomics in lung cancer, while predicting future research directions. Methods On 21 October, 2024, we identified 2057 papers on the application of radiomics in lung cancer from the Web of Science database Core Collection database. In order to examine and graph trends and proportions of publications by country, GraphPad Prism software was used. CiteSpace and VOSviewer were used to visualize and analyze the papers published from 1 January 2010 to 21 October 2024. Results The collection included 2057 papers published from 2010 to 2024, of which most were articles (1734, 84.30%) and a few were reviews (323, 15.70%), contributed by 9539 authors from 61 countries/regions. There was an upward trend in both the number of publications per year and the total number of citations. China, accounting for 47.79% with 983 papers, and the USA, accounting for 25.86% with 532 papers, have made notable contributions in this domain. General Electric was the most productive institution (n = 86). Lambin (n = 919 citations) was the most co-cited author, whereas Aerts, Hugo J. W. L., was placed first among the top ten authors. The most published journal was Frontiers in Oncology (178 publications; IF 2023, 3.5; Q2). It is important for different countries and institutions to strengthen their cooperation in the future. Radiomics, features, images, CT, and survival were the most commonly used keywords. The analysis of references and keywords shows that the research hotspot of lung cancer radiomics is more inclined towards clinical applications. In the future, radiomics was mainly used for the classification, diagnosis, detection, and prediction of lung cancer, especially in immunotherapy. Conclusion In summary, the bibliometric analysis comprehensively and quantitatively presents the research status, research hotspots, and development trends of radiomics applied in lung cancer. The application of radiomics to lung cancer is a highly promising research area based on our results. Multicenter studies are a trend in the development of lung cancer radiomics, and we advocate strengthening cooperation between countries/regions, institutions, and authors to break down academic barriers. The research hotspot of lung cancer radiomics is more inclined towards clinical applications, including screening, diagnosis, and prediction of clinical outcome. Immunotherapy is currently a hot research area in this field, and the efficacy and prognosis of personalized immunotherapy for lung cancer is the future development trend. Furthermore, deep learning can provide strong technical support for radiomics. Multimodal learning for information fusion is another crucial development trend; we should pay more attention to multi-omics integration in the future.