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绘制PET/MR领域的知识图谱:一项多维度文献计量分析。

Mapping the knowledge landscape of the PET/MR domain: a multidimensional bibliometric analysis.

作者信息

Hu Xiaofei, Peng Jianding, Huang Min, Huang Lin, Wang Qing, Huang Dingde, Tian Mei

机构信息

Department of Nuclear Medicine, The First Hospital Affiliated of Army Medical University (Southwest Hospital), 30 Gaotanyanzheng St., Shapingba district, Chongqing, 400038, China.

School of Basic Medicine, Capital Medical University, Beijing, 100086, China.

出版信息

Eur J Nucl Med Mol Imaging. 2025 Apr;52(5):1805-1821. doi: 10.1007/s00259-024-07043-8. Epub 2025 Jan 4.

Abstract

OBJECTIVE

This study aims to conduct a bibliometric analysis to explore research trends, collaboration patterns, and emerging themes in the PET/MR field based on published literature from 2010 to 2024.

METHODS

A detailed literature search was performed using the Web of Science Core Collection (WoSCC) database with keywords related to PET/MR. A total of 4,349 publications were retrieved and analyzed using various bibliometric tools, including VOSviewer and CiteSpace.

RESULTS

The analysis revealed an initial increase in PET/MR publications, peaking at 495 in 2021, followed by a slight decline. The USA, Germany, and China were the most prolific countries, with the USA demonstrating strong collaborative networks. Key institutions included the Stanford University, Technical University of Munich and University of Duisburg-Essen. Prominent authors were primarily from Germany, with significant contributions from University Hospital Essen. Major journals in the field included the European Journal of Nuclear Medicine, Journal of Nuclear Medicine, and Physics in Medicine and Biology. Emerging research areas focused on oncology, neurological disorders, and cardiovascular diseases, with keywords such as "prostate cancer," "Alzheimer's disease," and "breast cancer" showing high research activity. Recent trends also highlight the growing integration of AI, particularly deep learning, to improve imaging reconstruction and diagnostic accuracy.

CONCLUSION

The findings emphasize the need for continuous investment, strategic planning, and technological innovations to expand PET/MR's clinical applications. Future research should focus on optimizing imaging techniques, fostering international collaborations, and integrating emerging technologies like artificial intelligence to enhance PET/MR's diagnostic and therapeutic potential in precision medicine.

摘要

目的

本研究旨在基于2010年至2024年发表的文献进行文献计量分析,以探索PET/MR领域的研究趋势、合作模式和新兴主题。

方法

使用Web of Science核心合集(WoSCC)数据库,以与PET/MR相关的关键词进行详细的文献检索。共检索到4349篇出版物,并使用包括VOSviewer和CiteSpace在内的各种文献计量工具进行分析。

结果

分析显示PET/MR出版物最初呈上升趋势,在2021年达到495篇的峰值,随后略有下降。美国、德国和中国是发文量最多的国家,美国展示出强大的合作网络。主要机构包括斯坦福大学、慕尼黑工业大学和杜伊斯堡-埃森大学。杰出作者主要来自德国,埃森大学医院贡献显著。该领域的主要期刊包括《欧洲核医学杂志》《核医学杂志》以及《医学与生物学物理》。新兴研究领域集中在肿瘤学、神经疾病和心血管疾病,“前列腺癌”“阿尔茨海默病”和“乳腺癌”等关键词显示出较高的研究活跃度。近期趋势还突出了人工智能,尤其是深度学习的日益融合,以改善成像重建和诊断准确性。

结论

研究结果强调需要持续投资、战略规划和技术创新,以扩大PET/MR的临床应用。未来的研究应专注于优化成像技术、促进国际合作以及整合人工智能等新兴技术,以增强PET/MR在精准医学中的诊断和治疗潜力。

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