ArticleGland surgery2026
Mapping the research landscape of photoacoustic imaging in breast cancer: a text-based bibliometric analysis.
Article in Gland surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Photoacoustic imaging (PAI) is a noninvasive functional imaging modality capable of assessing tissue oxygenation and other tumor-related biological characteristics, and it has been increasingly explored in both preclinical and clinical breast cancer research. However, bibliometric evidence regarding the developmental trajectory and knowledge structure of this field remains limited. To address this gap, this study reviews PAI literature for breast cancer assessment and summarizes the research status and emerging hotspots. Methods: Publications on PAI in breast cancer were retrieved from the Science Citation Index Expanded of the Web of Science Core Collection, with a data cutoff of December 31, 2025. After screening and exclusion of non-English publications, review articles, meeting abstracts, and other ineligible document types, eligible research articles were included for bibliometric analysis. VOSviewer and the bibliometrix R package were used to analyze publication trends, geographic and institutional distributions, author collaboration, journal characteristics, and keyword evolution. Results: A total of 214 research articles were included. Annual publication output increased progressively between 2004 and 2025, reaching a peak of 27 articles in 2025. China and the United States were the dominant contributors, jointly accounting for 71% of all publications; China ranked first in publication volume (n=89), whereas the United States showed the highest total citations (n=4,053). Jinan University was the most productive institution (n=17). Conclusions: Research on PAI in breast cancer has expanded steadily over the past two decades, with the field evolving from technology-driven system development toward clinically oriented applications. Current hotspots indicate a growing emphasis on artificial intelligence-assisted diagnosis and predictive modeling. Future work should prioritize multicenter validation, cross-platform standardization, and deeper integration of PAI with multimodal imaging and intelligent analytical methods to facilitate broader clinical translation.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.