Evidence map›Paper›PMID 41674935›Full record

ArticleTranslational cancer research2026

Temporal-spatial evolution of tumor habitat analysis: a bibliometric study on research hotspots and trends in medical imaging (2014-2025).

Xuanle Li, Yongde Guo, Shichen Xu, Huixin Ouyang, Ye Li, Dong Liang, Xin Liu, Hairong Zheng, Zhanli Hu, Bo Yuan and 1 more

Abstract read
In one paragraph

Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xuanle LiFaculty of Data Science, City University of Macau, Macau SAR, China.ORCID https://orcid.org/0009-0001-3925-5137
Yongde GuoFaculty of Data Science, City University of Macau, Macau SAR, China.
Shichen XuChu Kochen Honors College, Zhejiang University, Hangzhou, China.
Huixin OuyangImperial College London, South Kensington, London, UK.
Ye LiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Dong LiangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Xin LiuShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Hairong ZhengShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Zhanli HuShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Bo YuanThe Fourth People's Hospital of Shenzhen, Shenzhen, China.
Na ZhangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID https://orcid.org/0000-0001-9510-4520

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tumor habitat analysis holds significant application potential in oncology, yet systematic bibliometric studies to characterize its research landscape remain limited. This study aims to comprehensively assess the current status, hotspots, and trends in this field using rigorous bibliometric methods, providing a theoretical framework for future research. Methods: English publications on medical imaging applications in tumor habitat analysis indexed in Web of Science Core Collection (WOSCC) and PubMed (inception to April 2025) were retrieved. VOSviewer and CiteSpace were used to visualize and analyze country/region contributions, authors, journals, references, and keyword co-occurrences. Results: A final set of 127 studies was included, revealing a rapid acceleration in research; annual output grew from a single article in 2014 to a peak of 36 in 2024, with 30 articles already published by April 2025. China was the most productive country, while the United States anchored the densest international collaboration network. Key contributors included the University of Ulsan, the journal Conclusions: Tumor habitat analysis research is growing rapidly, but methodological standardization and data integration remain critical challenges. Addressing these gaps will enhance result comparability and advance translational oncology.

Indexed as

artificial intelligence (AI)bibliometricsmedical imagingradiomicsTumor habitat analysis

Identifiers

PMID41674935
PMCPMC12885878

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.