Mapping Knowledge Landscapes and Emerging Trends in Contrast-Enhanced Ultrasound for Breast Cancer: A Bibliometric and Visualization Analysis.
Authors
Affiliations (3)
Affiliations (3)
- Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, China.
- Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, China; Department of Ultrasound, Guangdong Provincial People's Hospital, Zhuhai Hospital (Jinwan Central Hospital of Zhuhai), China.
- Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, China. Electronic address: [email protected].
Abstract
Breast cancer remains a leading threat to women's health worldwide and reducing mortality hinges on early detection. Contrast-enhanced ultrasound (CEUS), an emerging technique for blood-pool imaging, enables assessment of microvascular perfusion in breast lesions and addresses limitations of conventional ultrasound. Although CEUS plays an increasingly important role in breast cancer diagnosis, a comprehensive bibliometric evaluation of CEUS research in breast oncology has not yet been undertaken. This study applied bibliometric analysis to delineate the developmental trajectory of CEUS in breast cancer, identify prevailing research hotspots, and anticipate future directions. Using publications retrieved from the Web of Science Core Collection (1996 to May 2025), we conducted a systematic assessment of co-authorship patterns; institutional and national collaboration networks; journal and author productivity; and keyword co-occurrence and clustering. In total, 503 publications met the inclusion criteria, with annual output accelerating notably since 2020. China and the United States were the principal contributors, both in publication volume and collaborative partnerships. Forsberg Flemming and the Journal of Ultrasound in Medicine were identified as the most prolific author and journal, respectively. Thematic cluster analysis highlighted key research domains, including optimization of microbubble agents, diagnostic performance, treatment response monitoring and integration of artificial intelligence (AI). Collectively, these trends indicate the field's progression from a primarily diagnostic modality toward predictive, therapeutic, and real-time AI-enabled applications driven by ongoing technological innovation.