Evolutionary landscape and collaborative networks of global theranostic research in nuclear medicine: a visual bibliometric analysis
Year: 2026
Type: article
Abstract: BACKGROUND: Theranostics, integrating diagnostic imaging with targeted radionuclide therapy, has become central to nuclear medicine, but its global research landscape and collaboration patterns remain incompletely mapped. OBJECTIVE: To characterize publication dynamics, cooperative networks, and emerging topics in theranostic research from 2006 to 2024. METHODS: Articles and reviews indexed in the Web of Science Core Collection were retrieved for bibliometric analysis. Excel, CiteSpace, VOSviewer, Scimago Graphica, ArcGIS, and the R package bibliometrix were used for quantitative analysis and visualization. RESULTS: A total of 1801 articles and reviews were included, with a compound annual growth rate of 18.7%. The USA, Germany, and China were the leading producer countries, and the USA-Germany collaboration showed the strongest bilateral link strength. The Helmholtz Association, Memorial Sloan Kettering Cancer Center, and the University of California System were the most productive institutions, while Herrmann K., Wester H.J., and Werner R.A. led individual output. Keyword co-occurrence analysis identified five major themes: prostate-specific membrane antigen (PSMA)-targeted imaging and therapy, somatostatin receptor-based peptide therapy, neuroendocrine tumors, alpha-particle therapy, and fibroblast activation protein-targeted probes. Burst detection showed that fibroblast activation protein, actinium-225, and 177 Lu-PSMA-617 have emerged as recent research hotspots. CONCLUSION: Theranostic research in nuclear medicine has expanded rapidly over the past two decades, with a trans-Atlantic and Asia-Pacific collaborative pattern. Current frontiers are shifting from beta-emitters toward alpha-emitters and tumor-microenvironment-targeted probes. Greater intercontinental cooperation and continued focus on novel radionuclides and under-explored targets may support future innovation and clinical translation.
Source: Nuclear Medicine Communications
Authors: Ying-nan Jia, Qian Wu, Pei-hui Liu
Institution: Xuzhou Central Hospital
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7162134871