Back to all papers

Bibliometric Analysis of Whole-Body MRI from 2015 to 2025 Across Clinical Applications, Quantitative Imaging, and Artificial Intelligence.

August 8, 2026pubmed logopapers

Authors

Lee J,Lee C,Cyphers ED,Bonzell C,Kim S,Repajic M,Assadsangabi R,Clifford TG,Duddalwar V,Beutler BD

Affiliations (5)

  • Department of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
  • Department of Radiology, Keck School of Medicine of USC, Los Angeles, CA 90033, USA.
  • Radiomics Lab, Department of Radiology, University of Southern California, Los Angeles, CA 90033, USA.
  • Alfred E. Mann Department of Biomedical Engineering, USC Viterbi School of Engineering, Los Angeles, CA 90089, USA.
  • Institute of Urology, University of Southern California, Los Angeles, CA 90033, USA.

Abstract

Whole-body magnetic resonance imaging (WB-MRI) has become established for selected clinical indications and is increasingly studied across many fields including but not limited to oncologic, musculoskeletal, pediatric, and computational imaging applications. This study characterizes recent trends and the evolution of WB-MRI research using a bibliometric analysis reported using the PRISMA 2020 guidelines and identifies dominant clinical, quantitative, and artificial intelligence (AI) themes shaping the field. Publications were identified from Scopus, Web of Science, and PubMed using WB-MRI and its variant search terms and filtered to articles and reviews from 2015 through to 2025. Bibliometric analyses summarized publication output, contributors, citations, and keywords, and used exploratory keyword rules to classify major clinical and technical themes. Of 1511 included WB-MRI publications, annual output increased from 124 in 2015 to 180 in 2025. The journals with the highest publication counts were European Radiology, PLoS ONE, and the European Journal of Radiology. Parsed author affiliations most frequently represented the United States, Germany, and the United Kingdom. Research centered on oncologic applications, particularly myeloma and prostate cancer, alongside musculoskeletal disease, diffusion-weighted imaging, and AI-based segmentation. AI-related publications increased from 5 in 2015 to 20 in 2025. Broader clinical use of WB-MRI will require standardized acquisition, reproducible quantitative measures, and multicenter validation.

Topics

Journal Article

Ready to Sharpen Your Edge?

Subscribe to join 11k+ peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.