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<p>The clinical application of adaptive radiotherapy (ART) remains limited in practice, mainly due to equipment limitations and time constraints. This analysis aims to uncover prevalent research patterns, emerging trends, and collaborative networks to guide future directions in clinical research on ART. A systematic bibliometric analysis was conducted using the Web of Science Core Collection (1999–2024) with the search query: cancer and adaptive radiotherapy in title, abstract and keywords. Data analysis was performed using CiteSpace 6.3.R2 for network visualization and Excel for trend analysis. The bibliometric analysis identified 3,941 adaptive radiotherapy publications (1999–2024) with 63,951 citations, demonstrating sustained research growth and peaking productivity during 2021–2023 (annual average: 405 publications). Leading researchers included Tanderup K (78 publications) and Pötter R (629 citations), with Yan D showing influential contributions to adaptive radiotherapy research. Keyword analysis revealed evolving research trends from organ motion/dose escalation (2005–2015) to current focuses on deep learning and MR-guided radiotherapy (2020–2023). Co-citation analysis revealed the evolutionary trajectory of adaptive radiotherapy research, progressing from early prostate cancer studies to current focuses on MR-guided brachytherapy and adaptive proton therapy, with seminal contributions from Pötter R and Sturdza A. This bibliometric analysis documents the rapid evolution of adaptive radiotherapy as a transformative approach in radiation oncology, driven by image-guidance technological advances and demonstrating substantial clinical translation progress.</p>

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A global bibliometric and visualization study of the adaptive radiotherapy research landscape

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月20日

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  • Zhengyu Zhou,
  • Chuan Huang,
  • Xiaoying Li,
  • Yihan Ye,
  • Man Wang,
  • Qiongyu Lan,
  • Qing Li

摘要

The clinical application of adaptive radiotherapy (ART) remains limited in practice, mainly due to equipment limitations and time constraints. This analysis aims to uncover prevalent research patterns, emerging trends, and collaborative networks to guide future directions in clinical research on ART. A systematic bibliometric analysis was conducted using the Web of Science Core Collection (1999–2024) with the search query: cancer and adaptive radiotherapy in title, abstract and keywords. Data analysis was performed using CiteSpace 6.3.R2 for network visualization and Excel for trend analysis. The bibliometric analysis identified 3,941 adaptive radiotherapy publications (1999–2024) with 63,951 citations, demonstrating sustained research growth and peaking productivity during 2021–2023 (annual average: 405 publications). Leading researchers included Tanderup K (78 publications) and Pötter R (629 citations), with Yan D showing influential contributions to adaptive radiotherapy research. Keyword analysis revealed evolving research trends from organ motion/dose escalation (2005–2015) to current focuses on deep learning and MR-guided radiotherapy (2020–2023). Co-citation analysis revealed the evolutionary trajectory of adaptive radiotherapy research, progressing from early prostate cancer studies to current focuses on MR-guided brachytherapy and adaptive proton therapy, with seminal contributions from Pötter R and Sturdza A. This bibliometric analysis documents the rapid evolution of adaptive radiotherapy as a transformative approach in radiation oncology, driven by image-guidance technological advances and demonstrating substantial clinical translation progress.