Hotspots and trends of radiomics research for breast cancer:a bibliometric analysis
10.3969/j.issn.1672-8270.2025.11.017
- VernacularTitle:乳腺癌影像组学研究热点和趋势的文献计量学分析
- Author:
Pei WANG
1
;
Shuping MENG
1
;
Xiao SUN
1
;
Jing JIA
1
;
Huairong ZHANG
1
;
Li ZHU
1
Author Information
1. 宁夏医科大学总医院放射科 银川 750004
- Publication Type:Journal Article
- Keywords:
Breast cancer;
Radiomics;
Bibliometric analysis;
VOSviewer software;
CiteSpace software
- From:
China Medical Equipment
2025;22(11):104-109
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the research hotspots and trends in the radiomics field based on bibliometric for breast cancer.Methods:Publications related to radiomics for breast cancer during January 2012 to June 2024 were retrieved from the Web of Science Core Collection databases.Then,the R software's package"bibliometric"tool,VOSviewer and CiteSpace softwares were used to conduct visual analysis of radiomics-related bibliometric for breast cancer,which involved to publication trends,countries,institutions,journals,authors,keywords,and highlight keywords.Results:A total of 683 radiomics-related literatures for breast cancer were obtained,and 518 articles were finally included after non-English literatures and non-Article literatures were excluded.China and Sun Yat-sen University emerged as the leading country(326 articles)and institution(83 articles).The top three journals with the most of published articles were respectively,and.Professor Mao Ning has the largest number of articles,followed by Pinker Katja and Liang Changhong.The results of keywords and highlight keywords showed that current radiomics researches for breast cancer mainly focused on the applications of magnetic resonance imaging(MRI),machine learning,deep learning,artificial intelligence,and radiogenomics in prediction for diseases'prognosis,and assessment for treatment's response.Conclusion:The applications of machine learning,deep learning and multi-parameter imaging belongs to hot-research fields in assessment for personalized treatment.Future research directions would more and more tend to integrate artificial intelligence and multi-omics analysis,so as to promote prognostic assessment and personalized treatment.
