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Understanding the research trend and evolution in radiogenomics (2005-2023): A bibliometric analysis (Preprint)

预印本 放射基因组学 计算机科学 人工智能 无线电技术 万维网
作者
Meng Wang,Yun Peng,Ya Wang,Dehong Luo
出处
期刊:Interactive journal of medical research [JMIR Publications Inc.]
卷期号:13: e51347-e51347
标识
DOI:10.2196/51347
摘要

Background Radiogenomics is an emerging technology that integrates genomics and medical image–based radiomics, which is considered a promising approach toward achieving precision medicine. Objective The aim of this study was to quantitatively analyze the research status, dynamic trends, and evolutionary trajectory in the radiogenomics field using bibliometric methods. Methods The relevant literature published up to 2023 was retrieved from the Web of Science Core Collection. Excel was used to analyze the annual publication trend. VOSviewer was used for constructing the keywords co-occurrence network and the collaboration networks among countries and institutions. CiteSpace was used for citation keywords burst analysis and visualizing the references timeline. Results A total of 3237 papers were included and exported in plain-text format. The annual number of publications showed an increasing annual trend. China and the United States have published the most papers in this field, with the highest number of citations in the United States and the highest average number per item in the Netherlands. Keywords burst analysis revealed that several keywords, including “big data,” “magnetic resonance spectroscopy,” “renal cell carcinoma,” “stage,” and “temozolomide,” experienced a citation burst in recent years. The timeline views demonstrated that the references can be categorized into 8 clusters: lower-grade glioma, lung cancer histology, lung adenocarcinoma, breast cancer, radiation-induced lung injury, epidermal growth factor receptor mutation, late radiotherapy toxicity, and artificial intelligence. Conclusions The field of radiogenomics is attracting increasing attention from researchers worldwide, with the United States and the Netherlands being the most influential countries. Exploration of artificial intelligence methods based on big data to predict the response of tumors to various treatment methods represents a hot spot research topic in this field at present.

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