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Published on: September 25, 2019
Mapping the landscape of MRI research in post-stroke cognitive impairment: A bibliometric analysis from 2000 to 2026
Lihui Yan1, Siyu Gu1, Xiaolu Xu2
1Department of Radiology, Affiliated Hospital 6 of Nantong University (Yancheng Third People's Hospital), Yancheng, Jiangsu, China.
Objective:
Magnetic Resonance Imaging (MRI) is essential for understanding post-stroke cognitive impairment (PSCI), yet the global research landscape remains unclear. This study aimed to analyze the trends and hotspots in MRI research on PSCI through bibliometric analysis.
Methods:
Publications were retrieved from the Web of Science Core Collection on June 2, 2026, covering January 1, 2000 to June 2, 2026. Only English-language records classified as "Article" were included. Bibliometric indicators, collaboration networks, and keyword dynamics were analyzed using VOSviewer (version 1.6.20), CiteSpace (version 6.4.R1), and the R package bibliometrix (version 4.5.3).
Results:
A total of 2,022 articles were included. The USA (438 corresponding-author articles) and China (422) were the leading contributors. The USA had the highest total citations (25,505), while average citation impact was higher in the UK and the Netherlands than in China. The University of California System (314 publications), Boston University (295), and Harvard University (272) were the most productive institutions. Stroke published the most articles (171) and showed the strongest network prominence in journal analyses. Keyword co-occurrence revealed five major thematic clusters spanning vascular risk and cerebral small vessel disease markers, cognitive phenotype and assessment, and network-oriented neuroimaging. Burst detection indicated current research frontiers through 2026 centered on "white matter hyperintensities," "cerebral small vessel disease," "functional connectivity," "connectivity," and "recovery."
Conclusion:
MRI research on PSCI expanded substantially over the study period, while thematic emphasis shifted from mainly structural and vascular lesion markers toward network-based and prognosis-oriented imaging. Future progress will require stronger international collaboration, more standardized MRI and analytic workflows, and external validation of multimodal prediction models in well-phenotyped cohorts before clinical translation.
