Visualizing research trends and collaboration networks in surgery: a case study of bilateral axillo-breast approach surgery [2007–2024]

Introduction

Background

The bilateral axillo-breast approach (BABA) is a remote-access thyroidectomy technique involving surgical incisions in the axillar and periareolar regions (1,2). This method preserves the advantages of conventional thyroid surgery while avoiding visible neck scars (3,4). BABA surgery has received growing international attention, with most studies focusing on clinical outcomes (5,6). However, few studies have examined research trends and academic impact.

Rationale and knowledge gap

Bibliometric analysis is a quantitative method used to evaluate research trends and academic impact by focusing on publications, citations, authors, and journals (7,8). It helps identify key contributors and influential studies (9,10). Data are typically collected from databases like Web of Science (WoS), Scopus, and PubMed, followed by citation, co-authorship, co-citation, and keyword analyses. Overall, bibliometric analysis serves as a powerful tool for mapping the research environment and assessing scholarly impact. Bibliometric analysis serves as a valuable tool for identifying research trends and evaluating scholarly impact. This methodology demonstrates particular efficacy in conducting quantitative, temporal, and network analyses, thereby establishing a systematic framework for understanding disciplinary progression and recognizing influential contributors within academic domains (11,12).

Objective

This study conducted a bibliometric analysis of 18 years of BABA surgery research to identify key trends and contributors through citation, co-authorship, and keyword analyses. It aimed to provide an overview of the field’s academic development and impact. We present this article in accordance with the BIBLIO reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-167/rc).

Methods

This study conducted a comprehensive visual analysis using WoS and PubMed. WoS and PubMed are among the most widely used bibliometric databases for retrieving citation information and have traditionally served as standard sources for calculating citation indices. In this study, data were collected using predefined search queries to identify articles published prior to 2024. A total of 831 and 297 articles were retrieved from WoS and PubMed, respectively. After removing duplicates and excluding irrelevant studies, 170 articles were finalized for analysis. Visualization tools such as VOSviewer, CiteSpace, and SCImago Graphica were employed to analyze clustering patterns, temporal trends, and citation networks. To ensure data accuracy, author names and institutional affiliations were standardized. In addition, various network analyses, including citation, co-authorship, co-citation, and co-occurrence analyses, were conducted to derive comprehensive bibliometric insights. VOSviewer excels at intuitive clustering visualization of large-scale data, CiteSpace is particularly effective for analyzing research trends and knowledge structures over time, and SCImago Graphica is advantageous for generating high-quality graphics and customized visualization (13-15). The research methodology is visually summarized in the schematic diagram shown in Figure 1.

Figure 1 Research concept of bibliometric analysis of BABA thyroidectomy: data collection, data cleaning, analysis methods, and visualization tools. BABA, bilateral axillo-breast approach.

Sources of the dataset

This study employed PubMed and WoS, two of the most widely recognized bibliometric databases, to perform a visual analysis based on bibliometric methodologies. WoS is well-known for its reliability and broad disciplinary coverage, providing robust tools for citation tracking, evaluation of research performance, and analysis of international collaboration. In addition, it supports efficient data retrieval and is regularly updated to ensure access to the most current academic literature. PubMed is a trusted biomedical and life sciences database offering access to over 34 million publications across disciplines like medicine, nursing, and public health. Supported by the National Library of Medicine and National Institutes of Health, it ensures reliability and regular updates. As a free, open-access platform, PubMed allows systematic searches using medical subject headings (MeSH) terms and Boolean operators, and provides access to full-text articles via integration with PubMed Central. It also supports citation tracking and data export in formats such as comma-separated values (CSV) and extensible markup language (XML).

Data collection and pre-processing

Data collection from WoS targeted articles published before August 31, 2024 to prevent future changes to the bibliometric dataset. The search query utilized the “or” operator between keywords, formatted as “bilateral axillo-breast approach” OR “BABA [title]”. This search retrieved 831 articles. Similarly, PubMed data were retrieved using the same timeframe and search query, resulting in the collection of 297 articles.

Data visualization and verification of visualization

The collected data were analyzed using various visualization tools, including VOSviewer, CiteSpace, and SCImago Graphica. SCImago Graphica is well-suited for multi-purpose data visualization and excels in analyzing and visualizing diverse datasets, including bibliometric data (16). VOSviewer was employed for clustering visualization, while time zone mapping and period-based trend analysis were conducted using CiteSpace. Citation relationships between countries/regions were visualized geographically using SCImago Graphica. VOSviewer is well-suited for visualizing bibliometric networks and performing clustering analysis, providing intuitive and easily interpretable visual outputs (17). CiteSpace effectively captures temporal research trends and reveals underlying knowledge structures, offering insights into the evolution of research fields and emerging scientific innovations.

Data analysis

The foundation of this study is a corpus of 170 academic papers focused on BABA. These publications were meticulously selected through a rigorous data collection and pre-processing phase. The subsequent analysis employed a framework based on four primary categories: keywords, country/region, organization, author. This methodological approach enables a structured examination of the key contributors and intellectual trends within the BABA research landscape.

Results

Based on the collected data, various aspects of research publications were analyzed, including annual publication trends, co-citation analysis, keyword analysis, publication relationships by country/region and institution, and a temporal analysis of keywords using time zones. Additionally, author analysis and publisher-related research were conducted to provide deeper insights into the academic landscape.

Annual publication trends

The annual publication trends of BABA-related papers are shown in Figure 2. The X-axis represents the publication year, while the Y-axis depicts the number of papers published each year. Blue bars indicate the annual number of BABA-related publications, while the orange line represents the cumulative count. The first publications on this topic appeared in 2007, when two articles were published. Since 2010, the annual number of publications has steadily increased. A significant rise was noted in 2021 with 19 publications, followed by a peak of 24 publications in 2023. The cumulative total, depicted by the line graph, shows a growth pattern, with a sharp increase from 2020 onward, reaching approximately 170 by 2024.

Figure 2 Annual trends in BABA-related publications [2003–2024]. Blue bars represent the yearly number of publications, while the orange line indicates the cumulative total, showing exponential growth since 2020. BABA, bilateral axillo-breast approach.

Co-citation analysis

For the co-citation analysis, we analyzed the top 10 co-cited papers, as shown in Table 1. The top 10 co-cited papers from research on BABA were summarized. The most frequently cited paper is Professor Choe’s 2007 study, which has been cited 64 times. Among these 10 papers, seven were published primarily in South Korea, while three were published in other countries/regions. The papers published outside of Korea are Hüscher’s 1997 study, Shimazu’s 2003 study, and Gagner’s 1996 study, which are considered to have had a significant influence on BABA surgery (25). Additionally, Chung’s 2007 paper and Kang’s 2009 paper, which focused on trans-axillary surgery using different surgical techniques, also served as important external reference points (25).

The results of the co-citation analysis according to timeline are illustrated in Figure 3, which is divided into two parts: A and B. Figure 3A presents a visualization of the time zone, showing when the papers cited by the BABA papers were published and how often each paper was cited by the BABA papers. The horizontal axis represents the publication year of each paper, while the vertical axis indicates which paper, among those published each year, was most frequently cited by the BABA papers. The size of the nodes (circles) reflects the number of citations by the BABA papers. For the time zone, labels are attached only to documents cited at least 10 times. Gagner’s study in 1996 and Hüscher’s study in 1997 had a great influence on the early stage of BABA surgery. Choe’s study in 2007 and Lee’s study in 2009 had the largest citation sizes. These two studies had the greatest influence on BABA over time. Lee and Kim’s study in 2011 and Choi’s study in 2012 had a medium influence. The later studies had medium or small influence circle sizes. The output of BABA-related papers was highest in 2016.

Figure 3 Citation analysis of influential studies on BABA surgery. (A) The time zone visualization illustrates the publication years and citation frequencies of key studies, with node size proportional to the citation count, thereby reflecting the relative influence of each study over time. (B) The burst analysis identifies peak citation periods for the top 20 references, showing evolving influences. The visualizations in (A,B) were generated using CiteSpace (v6.4.R1). BABA, bilateral axillo-breast approach.

Figure 3B presents a burst analysis visualization, illustrating the periods when papers cited by BABA-related studies experienced peak citation activity. The red bar for each paper represents the period during which it received the highest number of citations. The bibliometric analysis results are as follows. From 2007 to 2015, the papers by Ikeda, Hüscher, Ohgami, and Shimazu influenced BABA surgery. From 2009 to 2014, the papers by Chung and Choe influenced BABA research. From 2011 to 2017, the papers by Lee and Cooper influenced BABA research. From 2014 to 2016, the papers by Kang and Lee influenced BABA. From 2015 to 2020, the papers by Tae and Lee influenced BABA. From 2016 to 2020, the papers by Choi, Kim, Berber, and Anupong influenced BABA research. From 2020 to 2024, the papers by Tae, Kim, Chai, and Liang influenced BABA surgery.

Keyword analysis

Table 2 presents the top 10 keywords based on the number of articles in which they appear among the keywords in BABA papers. ‘Bilateral axillo-breast approach’ appeared 61 times, ‘thyroidectomy’ appeared 50 times, ‘robotic thyroidectomy’ appeared 31 times, and ‘endoscopic thyroidectomy’ appeared 20 times.

The cluster visualization of keywords in BABA-related papers is shown in Figure 4A. The size of each node represents the number of papers in which the keyword appears. If two keywords are found together in a paper, they are connected by a line. The thicker the line, the more frequently the keywords co-occur in multiple papers. Only keywords appearing more than twice are displayed. Of 290 keywords, 79 are shown. The keywords ‘bilateral axillo-breast approach’, ‘thyroidectomy’, ‘robotic thyroidectomy’, and ‘endoscopic thyroidectomy’ appear at the center as large circles. The time zone visualization in Figure 4B highlights when certain keywords in BABA-related papers first appeared and how often they are featured. The size of each node reflects the number of papers that the keyword appears in. If two keywords appear together in a paper, they are connected by a line. Labels are attached to keywords appearing at least four times. Keywords such as ‘bilateral axillo-breast approach’, ‘thyroidectomy’, ‘robotic thyroidectomy’, and ‘endoscopic thyroidectomy’ have appeared since 2010 and continue to have a significant presence. Over time, keyword diversity has increased and many related terms have emerged. The burst analysis visualization, illustrating the periods during which certain keywords in BABA-related papers appeared most frequently, is presented in Figure 4C. Until 2010 and 2012, the keywords ‘endoscopic thyroid surgery’ and ‘endoscopic thyroidectomy’ appeared frequently. In 2015 and 2017, the keyword ‘robotic thyroidectomy’ appeared. Since 2020, the keywords ‘neck dissection’, ‘complication’, ‘parathyroid gland’, ‘meta-analyses’, and ‘learning curve’ have been observed.

Figure 4 Keyword analysis of BABA-related scientific literature [2007–2024]. (A) The cluster visualization illustrates the co-occurrence of keywords, where larger nodes represent higher frequencies and thicker lines indicate stronger associations. Prominent themes include various thyroidectomy techniques. (B) The temporal analysis highlights the emergence and continuity of keywords, showing an increase in keyword diversity starting from 2010. (C) The burst analysis reveals shifts in research focus over time, demonstrating how areas of medical interest have evolved through keyword trends. For the visualizations in the figure, two software programs were used: (A) VOSviewer (v1.6.20) and (B,C) CiteSpace (v6.4.R1). BABA, bilateral axillo-breast approach.

Analysis of publication relationships by country/region and institution

Out of the 170 publications identified, South Korea contributed the largest share with 106 BABA-related publications (62.4%), underscoring its prominent role in this research field. It was followed by China with 37 publications (21.8%) and the United States with 19 publications (11.2%). Italy and India each contributed 9 publications (5.3%), Taiwan contributed 7 publications (4.1%), Spain contributed 6 publications (3.5%), Saudi Arabia contributed 3 publications (1.8%), and Thailand and Egypt each contributed 2 publications (1.2%). These findings are summarized in Table 3, which presents an overview of the top 10 countries/regions contributing to BABA research.

The cluster visualization, illustrating the number of BABA-related publications from each country/region and the frequency of cross-country/region citations among BABA papers, is presented in Figure 5A. The size of each node represents the number of BABA papers published by a country/region. Lines indicate citations of one country/region’s BABA papers by another’s. The thicker the line, the more frequent citations occur between the two countries/regions. We can observe the connections between other countries/regions around South Korea, which has published the most research results. The map-based visualization in Figure 5B also shows the number of BABA-related publications by country/region and the citation frequencies between them. The number of papers published by country/region or region is as follows. South Korea led the field with 106 publications, followed by China with 37, the United States with 19, Italy and India with 9 each, Taiwan with 7, and Spain with 6 papers.

Figure 5 Global and institutional collaboration in BABA-related research. (A) The cluster visualization illustrates cross-country/region citation networks, with South Korea identified as the leading contributor. Extensive connections to countries/regions like China and the United States are observed. Node size represents publication volume, while line thickness indicates citation frequency, emphasizing the intensity of collaboration among nations. (B) The map-based visualization highlights South Korea’s dominance in publication output (106 papers), followed by China (37 papers) and the United States (19 papers). Notable citation links among these countries/regions underscore their pivotal roles in advancing BABA research globally. (C) The institutional collaboration network reveals that Seoul National University is the central hub of research activity, which is connected to other major institutions worldwide through frequent citations. Node size reflects publication volume by institution, while line thickness indicates citation frequency, showcasing the collaborative framework within the academic landscape. The visualizations were created using three software programs: (A) VOSviewer (v1.6.20), (B) SCImago Graphica (v1.0.37), and (C) CiteSpace (v6.4.R1). BABA, bilateral axillo-breast approach.

Figure 5C presents a cluster visualization showing the number of BABA publications from each institution and how frequently BABA papers from one institution cite those from another. The size of each node represents the number of BABA papers published by an institution. Lines indicate citations of one institution’s BABA papers by another’s. The thicker the line, the more frequent citations occur between the two institutions. This visualization only displays institutions that have published at least two papers. Out of 148 institutions, only 50 are shown. Seoul National University, which published the most research results, has the largest circle size, and other institutions are distributed around it.

The number of papers published by each institution is summarized in Table 4. Seoul National University had the most with 52, followed by South Korea University with 12, Inje University with 10, Catholic University of Korea and Sungkyunkwan University with 9, and Chung-Ang University with 8. The 960th Hospital in China had 7.

Author analysis

The authors who have published the most papers in the field of BABA research are presented in Table 5. Kyu Eun Lee has published the most papers at 43, followed by June Young Choi with 36 papers. Su-jin Kim has 26 papers, Young Jun Chai has 24 papers, Yeo-Kyu Youn has 22 papers, and Hyeong Won Yu has 20 papers.

The number of BABA-related publications by each author and the frequency with which these publications cite those of other authors are visualized as a cluster map in Figure 6. The size of each node represents the number of BABA papers published by an author. Lines indicate citations of one author’s BABA papers by another’s. The thicker the line, the more frequent citations occur between the two authors. This cluster visualization displays only authors who have published at least five papers. Out of 524 authors, only 41 are shown. Researchers are observed around Kyu Eun Lee and June Young Choi, who have published the most research results.

Figure 6 Visualization of author citations in BABA research. Cluster map of authors with significant publication and citation records, highlighting major contributors and citation relationships within the research community. The visualization in the figure was generated using VOSviewer (v1.6.20). BABA, bilateral axillo-breast approach.

Research in relation to publishers

According to Table 6, BABA-related research has been published 22 times in Surgical Laparoscopy, Endoscopy & Percutaneous Techniques, 15 times in World Journal of Surgery, and 14 times in Surgical Endoscopy. Additionally, eight articles have been published in Annals of Surgical Treatment and Research, while Gland Surgery, Frontiers in Endocrinology, and Head & Neck have each published seven articles. The International Journal of Surgery has published six articles, Journal of Robotic Surgery has published five articles, and Surgery has published four articles.

Discussion

Key findings

Since its initial development in 2008, the BABA surgical technique has gained recognition as an innovative method that preserves the advantages of conventional open thyroid surgery while eliminating visible scars (3,26-28). Originating from South Korea, this technique has been acknowledged and widely adopted by surgeons worldwide (29-31). However, no quantitative and comprehensive visual analysis has been conducted to substantiate its origins and global dissemination. This study aimed to address this gap by performing bibliometric analysis to uncover previously inconspicuous visual patterns and provide evidence that although BABA surgery originated in South Korea, it has been extensively utilized worldwide.

Strengths and limitations

This study represents the first comprehensive bibliometric evaluation of BABA robotic thyroidectomy, analyzing 18 years of scholarly output. By integrating advanced bibliometric tools such as VOSviewer, CiteSpace, and SCImago Graphica, it offers a multidimensional perspective on publication trends, author networks, institutional collaborations, and thematic developments. Through visual analytics, the study enhances interpretability and uncovers patterns that were previously difficult to identify, providing new insights into the global dissemination and academic advancement of the BABA technique. However, several limitations should be acknowledged. This analysis primarily relied on literature indexed in databases such as WoS and PubMed, which may have excluded relevant studies published in non-indexed regional journals. Furthermore, the interpretation of this study’s findings may vary depending on the author’s perspective. Moreover, while bibliometric indicators are valuable for understanding publication and citation dynamics, they do not directly reflect clinical impact or the methodological rigor of individual studies. Despite these limitations, the findings of this study offer a solid foundation for understanding the scholarly progression of BABA robotic thyroidectomy. They may serve as a useful resource for guiding future research directions and fostering international collaborations in the field.

Comparison with similar research

Previous bibliometric studies on robot-assisted and endoscopic thyroidectomy have provided only indirect insights into the research trends and development of the BABA approach, due to their broad focus on thyroid surgery as a whole (32). However, this study is the first bibliometric analysis specifically dedicated to BABA thyroidectomy.

Explanations of findings

This bibliometric analysis systematically revealed the academic evolution and global dissemination of BABA robotic thyroidectomy. First, the network analysis of co-authors, countries/regions, and institutions identified South Korea, the United States, and China as the primary contributors, with researchers from these countries/regions demonstrating high levels of productivity and influence. In particular, South Korea has played a leading role in the development and initial clinical application of the BABA technique, which aligns with its historical significance in the field. Second, Visual analyses have confirmed a gradual increase in the number of BABA-related publications from other countries/regions. However, interest in this technique remains primarily concentrated in a few regions, notably China and the United States. This suggests that while international interest is growing, the global adoption of this technique is currently limited to specific geographical areas. Moreover, it was observed that 10% of BABA-related research was published in the most traditional periodicals. Therefore, it is necessary to continuously monitor its distribution in the future, engage in a more comprehensive discussion of its spread, and build more extensive datasets for future analyses. Third, temporal analyses of keywords and co-citations revealed a clear shift in research focus. While early studies primarily addressed the safety and feasibility of the BABA technique, more recent research has increasingly focused on the integration of robotic technologies, long-term surgical outcomes, and comparative effectiveness with other surgical approaches. This thematic transition reflects the maturing of BABA research as the technique gains clinical stability and efficacy, thereby expanding both its scope of application and academic discourse. Collectively, these findings highlight the progressive development of BABA robotic thyroidectomy research and offer a foundational basis for shaping future research directions and fostering international collaboration in this field.

Implications and actions needed

This study offers significant implications for understanding the current status and future trajectory of BABA robotic thyroidectomy through a bibliometric perspective. The application of visualization-based network analysis allows for an intuitive presentation of citation relationships, changes in keywords, relevance between studies, and central research institutions, which may facilitate broader engagement from a wider range of countries/regions and institutions. To further advance global recognition and academic dissemination of the BABA technique, it is recommended to leverage platforms such as international conferences, collaborative research networks, and multinational researcher support programs.

Conclusions

This study was conducted through a bibliometric analysis of BABA-related papers over the past 18 years, identifying key trends and patterns regarding the academic development and global dissemination of BABA robotic thyroidectomy. Network analysis of co-authors, countries/regions, and institutions revealed that researchers from South Korea, the United States, and China appear frequently in the overall publications. Additionally, research contributions from other countries/regions have gradually increased, indicating a growing international participation.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-167/rc

Peer Review File: Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-167/prf

Funding: This work was supported by the Seoul National University Bundang Hospital Research Fund (No. 18-2024-0006) and an Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIT) (Artificial Intelligence Graduate School Program at Seoul National University) (No. RS-2021-II211343).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-167/coif). All authors report the funding from Seoul National University Bundang Hospital Research Fund (No. 18-2024-0006) and an Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIT) (Artificial Intelligence Graduate School Program at Seoul National University) (No. RS-2021-II211343). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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