Research hotspots and trend of the heart-brain axis by MRI: a bibliometric analysis
Haoran Wang1,2, Yang Jia1,2, Yi Liao1,2
1Department of Radiology, Sichuan University West China Second University Hospital, Chengdu, China.
Insights
This bibliometric analysis maps the evolving Heart-Brain Axis (HBA) research landscape, revealing key themes like technology, function, risk, and hemodynamics. Future directions emphasize AI integration for a deeper understanding of HBA interactions.
Area of Science:
- Cardiovascular Sciences
- Neuroscience
- Medical Imaging
- Bibliometrics
Background:
- The Heart-Brain Axis (HBA) is an emerging interdisciplinary field linking cardiac function to brain development.
- Cardiac dysfunction's impact on the brain is increasingly recognized, especially with advanced imaging like MRI.
- Existing literature on HBA is fragmented, necessitating systematic synthesis.
Purpose of the Study:
- To systematically analyze and map the knowledge structure, research hotspots, and collaborative networks in Heart-Brain Axis (HBA) research.
- To identify thematic evolution and emerging trends within the HBA research domain.
- To provide insights for future research directions and policy-making in HBA studies.
Main Methods:
- Bibliometric analysis of 6,446 English-language articles and reviews from the Web of Science Core Collection (1984-2025).
- Validation using a PubMed dataset (n=6,389; 1984-2025) to compare publication trends and keywords.
- Utilized VOSviewer, CiteSpace, SCImago Graphica, and Excel for data analysis and visualization.
Main Results:
- Strong concordance in publication trends between Web of Science and PubMed datasets (Pearson r=0.988).
- Identified four main research clusters: 'Technology & Development', 'Function & Regulation', 'Risk & Pathology', and 'Hemodynamics & Perfusion'.
- Key high-impact keywords include 'MRI', 'functional connectivity', 'dementia', and 'hemodynamics'; leading contributors are the US, Germany, and UK. 'Artificial intelligence' emerged as a recent significant keyword.
Conclusions:
- The study offers a systematic overview of HBA research trends and thematic evolution, showing sustained growth in publications.
- Findings highlight the increasing academic attention and technological advancements, such as AI, in HBA research.
- Provides valuable insights for researchers, clinicians, and policymakers, guiding future research towards AI integration and multi-organ network modeling.
Background:
The "Heart-Brain Axis" (HBA) represents an emerging interdisciplinary domain in which cardiac dysfunction is increasingly recognized to affect brain development, particularly with the advancement of imaging technologies such as MRI. Despite growing interest, the literature remains fragmented and lacks systematic synthesis.
Methods:
We performed a bibliometric analysis of 6,446 English-language articles and reviews in the Web of Science Core Collection (1984-2025), using VOSviewer, CiteSpace, SCImago Graphica, and Excel to map knowledge structures, research hotspots, and collaborative networks. A PubMed dataset (n = 6,389; 1984-2025) provided validation, comparing annual publication trends and high-frequency keyword structures.
Results:
The annual publication trends showed strong concordance between the WoSCC and PubMed datasets (Pearson r = 0.988, R2 = 0.976). Keyword co-occurrence analysis identified four primary clusters: "Technology & Development", "Function & Regulation", "Risk & Pathology", and "Hemodynamics & Perfusion". In the WoSCC keyword co-occurrence network, representative high-TLS keywords included "MRI" (TLS = 2799), "functional connectivity" (TLS = 1,224), "dementia" (TLS = 1,425), and "hemodynamics" (TLS = 1,036). The United States, Germany, and the United Kingdom were the leading contributors, with prominent institutions including the University of Toronto and Harvard Medical School. Citation bursts and recent keywords such as "artificial intelligence" reflect the technological evolution of the field.
Conclusion:
This study provides a systematic overview of HBA research trends and thematic evolution. The sustained growth in publications reflects increasing academic attention. Findings offer insights for researchers, clinicians, and policymakers, emphasizing future directions including AI integration and multi-organ network modeling.
