Bibliometric Analysis of Pulmonary Fibrosis Imaging Research: Knowledge Graph Construction Based on the Web of...

Area of Science:

• Medical Imaging
• Pulmonary Medicine
• Radiology

Background:

• Pulmonary fibrosis (PF) imaging research has seen significant growth.
• Understanding publication trends and collaboration networks is crucial for advancing the field.

Purpose of the Study:

• To quantify publication trends in PF imaging from 2015-2024.
• To map international collaboration networks and identify dominant and emerging research themes.

Main Methods:

• A systematic search of Web of Science identified 1,159 articles.
• CiteSpace, VOSviewer, and Scimago Graphica were used for bibliometric analysis, including trend assessment, keyword co-occurrence, and network visualization.

Main Results:

• Publication volume showed sustained linear growth.
• The US and China were leading contributors, with a strong collaboration axis between Western Europe and North America.
• Key themes included idiopathic pulmonary fibrosis, high-resolution computed tomography (HRCT), usual interstitial pneumonia (UIP), and survival.
• Deep learning emerged as a significant research burst from 2021-2024.

Conclusions:

• PF imaging research is shifting towards quantitative CT biomarkers and AI-driven phenotyping.
• AI generalizability is hindered by geographic fragmentation and limited multicenter validation.
• Future research should focus on standardized protocols, multicenter validation, and integrating AI with multi-omics for precise prognostics.