Li Xia, Hu Zhen, Wang Chujun, Cao Shuangyi, Zhang Chunquan
Department of Ultrasound, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1, Minde Road, Donghu District, Nanchang, Jiangxi, 330006, People's Republic of China.
J Robot Surg. 2025 Sep 4;19(1):555. doi: 10.1007/s11701-025-02741-3.
Technological innovations in robot-assisted ultrasound (RAUS) have remarkably advanced the development of precision and intelligent medical imaging diagnosis. This study aims to use bibliometric methods to systematically analyze the technological evolution and research frontiers in the RAUS field, providing valuable insights for future research. This study used the Web of Science Core Collection database to retrieve English-language research papers and reviews related to RAUS published between 2000 and 2024. Using analytical tools such as R (with the Bibliometrix package), VOSviewer, and CiteSpace, the study conducted a bibliometric analysis from multiple angles, including literature distribution, collaboration networks, and knowledge clustering. The visualization of analysis results comprehensively revealed the hot topics and emerging research frontiers within the RAUS field. The results reveal an exponential growth trend in RAUS research, with China leading in publication output (accounting for 28.51% of total publications), while the USA leads in terms of citation impact and international collaboration networks. Institutions such as Johns Hopkins University and Chinese Academy of Sciences emerge as highly productive core contributors. The research field has formed a multidimensional interdisciplinary landscape encompassing "mathematical sciences-engineering technology-medical health." The focus is on the integration of artificial intelligence (AI) and its clinical application translation. From 2000 to 2014, the development of "mobile robots" laid the cornerstone for further advancements. From 2015 to 2018, research focused on the development of "surgery" and "tumors" for medical applications. From 2019 to 2024, the core focus will be on "medical robots and systems," "artificial intelligence" and "robotic ultrasound," highlighting the transformation of technology into an AI-driven model. This study systematically reviewed the development of RAUS through bibliometric methods, enriching academic understanding of the field and providing valuable guidance for future technological iterations, clinical translation, and global cooperation to ultimately achieve precision medicine and balanced medical resources.
机器人辅助超声（RAUS）技术创新显著推动了精准智能医学影像诊断的发展。本研究旨在运用文献计量学方法，系统分析RAUS领域的技术演进与研究前沿，为未来研究提供有价值的见解。本研究利用科学网核心合集数据库检索2000年至2024年间发表的与RAUS相关的英文研究论文和综述。通过使用R（搭配Bibliometrix软件包）、VOSviewer和CiteSpace等分析工具，从文献分布、合作网络和知识聚类等多个角度进行文献计量分析。分析结果的可视化全面揭示了RAUS领域的热点话题和新兴研究前沿。结果显示，RAUS研究呈指数增长趋势，中国在发文量方面领先（占总发文量的28.51%），而美国在被引影响力和国际合作网络方面领先。约翰·霍普金斯大学和中国科学院等机构成为高产的核心贡献者。该研究领域已形成涵盖“数学科学 - 工程技术 - 医疗卫生”的多维度跨学科格局。重点在于人工智能（AI）的整合及其临床应用转化。2000年至2014年，“移动机器人”的发展为进一步进步奠定了基础。2015年至2018年，研究聚焦于医疗应用中“手术”和“肿瘤”的发展。2019年至2024年，核心重点将是“医疗机器人与系统”“人工智能”和“机器人超声”，突出了技术向人工智能驱动模式的转变。本研究通过文献计量学方法系统回顾了RAUS的发展，丰富了对该领域的学术理解，为未来技术迭代、临床转化和全球合作提供了有价值的指导，最终实现精准医疗和医疗资源均衡。
