Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, China.
Medicine (Baltimore). 2024 Aug 30;103(35):e39463. doi: 10.1097/MD.0000000000039463.
Breast cancer is the most prevalent form of cancer worldwide. Therefore, improved disease detection has emerged as a focal point in clinical studies. At the forefront of innovation, radiomics has the capability to extract comprehensive insights from medical images, ultimately enhancing the accuracy of diagnostic procedures. There has been rapid growth in the field of radiomics research on breast cancer in the past few years. We explored pertinent research articles in the Web of Science Core Collection database to gain a thorough understanding of breast cancer radiomics. We used CiteSpace to conduct a bibliometric analysis of the annual distribution of different nations, institutions, journals, authors, keywords, and references in the field of breast cancer radiomics. GraphPad Prism software was used to examine and graph yearly and country-specific trends and the proportions of publications. The tools utilized for the visualization of science mapping included CiteSpace and VOSviewer. Of the 891 publications, most were original articles (731, 91.09%) and a few were reviews (160, 8.91%). Most academic research has been published in China and the United States. The study centers predominantly consisted of major academic institutions, such as Fudan University and the Chinese Academy of Sciences, with some of their members being prominent figures in the field. Pinker, Katja has published the largest number of research papers. The majority of these studies have been published in medical journals focusing on radiology and oncology in recent years. In the realm of cutting-edge medical research, the top two keywords, magnetic resonance imaging and machine learning stand at the forefront as current areas of intense focus. Breast cancer radiomics is advancing rapidly, presenting numerous opportunities and obstacles. Our study of the literature in this academic area aimed to pinpoint the primary themes addressed in the studies and anticipate prospective avenues for research.
乳腺癌是全球最常见的癌症类型。因此，提高疾病检测能力已成为临床研究的重点。在创新前沿，放射组学能够从医学图像中提取全面的见解，最终提高诊断程序的准确性。在过去几年中，乳腺癌放射组学的研究领域取得了快速发展。我们在 Web of Science Core Collection 数据库中探索了相关研究文章，以深入了解乳腺癌放射组学。我们使用 CiteSpace 对不同国家、机构、期刊、作者、关键词和参考文献在乳腺癌放射组学领域的年度分布进行了文献计量分析。GraphPad Prism 软件用于检查和绘制每年以及特定国家的趋势和出版物比例。科学图谱可视化工具包括 CiteSpace 和 VOSviewer。在 891 篇出版物中，大多数是原始文章（731 篇，91.09%），少数是综述（160 篇，8.91%）。大部分学术研究发表在中国和美国。研究中心主要由复旦大学和中国科学院等主要学术机构组成，其中一些成员是该领域的知名人士。Pinker, Katja 发表的研究论文数量最多。这些研究大多发表在近年来专注于放射学和肿瘤学的医学期刊上。在前沿医学研究领域，磁共振成像和机器学习这两个最热门的关键词位居前列，是当前的研究热点。乳腺癌放射组学正在迅速发展，带来了众多机遇和挑战。我们对该学术领域文献的研究旨在确定研究中涉及的主要主题，并预测未来的研究方向。
