Global trends and developments in pulmonary magnetic resonance imaging research: a bibliometric analysis of the past decade
Year: 2025
Type: article
Abstract: Background: Pulmonary magnetic resonance imaging (MRI) has the advantage of nonionizing radiation and multiparameter imaging of structure and function, facilitating its clinical use in a variety of pulmonary diseases. This study aimed to identify the research trends and emerging topics in pulmonary MRI by conducting a comprehensive bibliometric analysis of the field over the past decade. Methods: A search of the Web of Science Core Collection database was conducted with the words "lung" and "MRI" for literature published from 2014 to 2023. The data were further analyzed with R and CiteSpace software in terms of annual publications and citations, collaborative networks (countries, institutions, and authors), source's local impact, keyword clustering, and burst analysis. Results: . The most productive country was the United States, and the countries with the strongest collaborative links were the United States and the United Kingdom. The most productive institutions and authors were Ruprecht Karls University Heidelberg (articles, n=309) and Wild JM (articles, n=86), respectively. Keyword cluster analysis identified five clusters: "lung cancer", "magnetic resonance imaging", "lung MRI", "cystic fibrosis", and "congenital diaphragmatic hernia". Keyword burst analysis showed that the keywords with the highest burst intensity in the first 5 years and the last 5 years were "mice" and "standardization", respectively. Conclusions: Over the past decade, research trends in pulmonary MRI have focused on lung cancer and cystic fibrosis as the dominant clinical diseases. Research has been centered on standardizing pulmonary MRI to promote its clinical application.
Authors: Ting Wu, Linyu Wu, Yufan Chen, Jun Wu, Chen Gao, Maosheng Xu
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4409911175