PMID: 40235738 https://pubmed.ncbi.nlm.nih.gov/40235738/

Abstract

BACKGROUND: Transient elastography (TE) has become a prominent technique for the detection of fibrosis, owing to its non-invasive nature, rapid execution, safety, and ease of repetition. This study aims to conduct a bibliometric analysis of the historical development and trends in the application of TE for the assessment of liver fibrosis.

METHODS: In the Web of Science (Core Collection database), we selected the Science Citation Index Expanded database to search for relevant literature from 1 January 1983 to 20 November 2023. We performed a search using the following topic words: transient elastography, liver fibrosis. After screening according to the title, abstract and keyword and removing the repetition, the literature included in the study was finally determined, and full records were downloaded. Bibliometric analysis was performed using VOSviewer and CiteSpace.

RESULTS: Through the bibliometric visualization analysis of 577 articles, it was found that since TE was first reported for the measurement of liver fibrosis in 2003, the number of publications in this field has generally shown an upward trend, and the distribution of publications has shown a bimodal distribution, with peaks in 2010 and 2019. France and China have shown a high contribution in this field with a high number of publications. In terms of contributions from individual research centers, Yonsei University stands out prominently. Throughout the history of research in this field, early studies focused on chronic viral hepatitis, by comparing TE and Fibrosis-4, aspartate aminotransferase to platelet ratio index, FibroTest, liver biopsy and other liver fibrosis detection indicators to verify its diagnostic efficacy. Subsequently, the focus of research gradually shifted to non-alcoholic fatty liver disease and other liver diseases, and the scope of research extended to the establishment of prediction models and efficacy evaluation through TE.

CONCLUSIONS: The application scope of TE is gradually expanding, and its safety, simplicity, rapidity, high accuracy, quantitative results, repeatability and good tolerance make it popular in clinical practice. Nowadays, the application of TE is not limited to the diagnosis of liver fibrosis, but has been extended to the establishment of prognostic models and efficacy evaluation of various liver diseases. To explore the deeper value of TE through new research methods such as machine learning models, radiate the advantages of TE to more liver diseases, and combine TE with a variety of non-invasive detection indicators to improve its application value, may be the future development and application prospect of TE in the field of liver fibrosis.