Temporal-spatial evolution of tumor habitat analysis: a bibliometric study on research hotspots and trends in medical imaging (2014–2025)

Background: Tumor habitat analysis holds significant application potential in oncology, yet systematic bibliometric studies to characterize its research landscape remain limited. This study aims to comprehensively assess the current status, hotspots, and trends in this field using rigorous bibliometric methods, providing a theoretical framework for future research. Methods: English publications on medical imaging applications in tumor habitat analysis indexed in Web of Science Core Collection (WOSCC) and PubMed (inception to April 2025) were retrieved. VOSviewer and CiteSpace were used to visualize and analyze country/region contributions, authors, journals, references, and keyword co-occurrences. Results: A final set of 127 studies was included, revealing a rapid acceleration in research; annual output grew from a single article in 2014 to a peak of 36 in 2024, with 30 articles already published by April 2025. China was the most productive country, while the United States anchored the densest international collaboration network. Key contributors included the University of Ulsan, the journal Frontiers in Oncology, and the most prolific author, Young-Hoon Kim, while Zhou, Mu was the most-cited author. Co-citation analysis revealed two dominant intellectual clusters: one centered on the tumor microenvironment and imaging biology (led by Gillies and Gatenby), and another focused on radiomics and machine learning for prognosis. Keyword analysis confirmed a clear trend toward integrating artificial intelligence (AI), multi-parametric magnetic resonance imaging (MRI), and multi-omics, with a growing emphasis on reproducibility. Conclusions: Tumor habitat analysis research is growing rapidly, but methodological standardization and data integration remain critical challenges. Addressing these gaps will enhance result comparability and advance translational oncology.