Methodological considerations in bibliometric retrieval for ultrasound-derived skeletal muscle research

Sun et al. recently published a bibliometric analysis in Quantitative Imaging in Medicine and Surgery titled “Advancing insights: a bibliometric analysis of evolutionary patterns and research frontiers in ultrasound-derived quantitative assessment of skeletal muscle” (1). The authors reported that their dataset was retrieved using searches of article titles (TI), abstracts (AB), and author keywords (AK) within the Science Citation Index Expanded (SCI-EXPANDED).

From a historical perspective, bibliometric investigations using the Web of Science platform traditionally relied on topic (TS) or title searches, reflecting the default options available in earlier database interfaces. The TS field integrates terms from titles, abstracts, author keywords, and Keywords Plus (KP). However, KP is algorithmically generated rather than author-assigned (2), which could lead to the inclusion of research that is irrelevant to the intended research topic (3). Such inclusions can introduce bias and reduce the interpretive clarity of bibliometric outcomes.

To mitigate this issue, the so-called “front page” filtering strategy was introduced to improve retrieval accuracy. This approach confines eligible records to those in which search terms explicitly appear on the article’s front page, that is, within the title, abstract, or author keywords. The concept was first proposed by Ho’s research group in 2011 (4) and subsequently formalized in an SCI-EXPANDED-indexed journal (5). Multiple empirical evaluations have demonstrated that excluding records retrieved solely through KP enhances dataset transparency, strengthens methodological rigor, and supports reproducibility.

Importantly, neglecting to apply “front page” filtering has been shown to substantially distort bibliometric results. Documented discrepancies include deviations of 55% in studies of radiotherapy for glioma (6), 31% in research on endothelin A receptor antagonists in kidney care (7), and 25% in research on artificial intelligence and machine learning in kidney care (8). These findings illustrate that “front page” filtering is not a marginal technical adjustment but a core methodological consideration with significant analytical consequences.

Following subsequent upgrades to the Web of Science interface, which allowed independent querying of TI, AB, AK, and KP, the original “front page” concept was refined into the TI-AB-AK search configuration (9). This refined methodology has since been adopted widely in contemporary bibliometric research, including numerous medicine-related studies published in recent years (10-13).

Proper citation of methodological origins is essential for maintaining scholarly integrity, enabling readers to trace conceptual development, and facilitating informed methodological evaluation (14). Failure to acknowledge foundational methodological contributions may obscure their intellectual provenance and impede transparency, reproducibility, and further methodological refinement. Moreover, failure to acknowledge established methodological frameworks may raise concerns regarding appropriate attribution of prior scholarly contributions (15,16).

In this correspondence, we highlight a critical methodological consideration in the bibliometric study by Sun et al. concerning their search strategy for ultrasound-derived quantitative assessment of skeletal muscle (1). While the authors appropriately employed the TI-AB-AK filtering approach, the intellectual origins and methodological foundations of this approach were not acknowledged.

The “front-page” filtering methodology, first introduced by Wang and Ho in 2011 (4) and formally published by Fu et al. in 2012 (5), represents a substantial advancement in bibliometric research rigor. By excluding algorithmically generated KP from search queries, this approach prevents the inclusion of irrelevant records and significantly improves data quality. Empirical evidence demonstrates that neglecting this filtering can introduce substantial distortions, ranging from 25% to 55% deviation in various medical research domains, thereby compromising the validity and reliability of bibliometric findings.

The evolution from the original “front page” concept to the contemporary TI-AB-AK configuration reflects the maturation of bibliometric methodology in response to database interface developments. This refinement has been widely adopted across medical bibliometric studies, underscoring its recognized value in the research community.

We emphasize that proper citation of methodological innovations is not merely a matter of academic courtesy but a fundamental requirement for scholarly integrity. Appropriate attribution enables: (I) transparent tracking of methodological evolution; (II) informed evaluation of analytical approaches by readers and reviewers; (III) reproducibility of research findings; and (IV) recognition of intellectual contributions that advance the field.

Moving forward, we strongly encourage authors conducting bibliometric analyses to explicitly acknowledge the “front page” or TI-AB-AK filtering methodology and cite its foundational literature. Such practices uphold the principles of academic transparency, promote appropriate scholarly attribution, and contribute to the continued refinement of bibliometric research standards in medical and scientific literature.

Appendix 1: Response to “Methodological considerations in bibliometric retrieval for ultrasound-derived skeletal muscle research”.

Acknowledgments

None.

Footnote

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2026-1476/coif). The authors have no 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/.

References

1. Sun Z, Tang J, Wang L, Ma J, Zhou T, Li H, Liu X, Yu X, Zhang B. Advancing insights: a bibliometric analysis of evolutionary patterns and research frontiers in ultrasound-derived quantitative assessment of skeletal muscle. Quant Imaging Med Surg 2025;15:1912-26. [Crossref] [PubMed]
2. Garfield E. KeyWords Plus: ISI’s breakthrough retrieval method. Part 1. Expanding your searching power on Current Contents on Diskette. Current Contents 1990;32:5-9.
3. Fu HZ, Ho YS. Top cited articles in thermodynamic research. J Engin Thermophys 2015;24:68-85. [Crossref]
4. Wang MH, Ho YS. Research articles and publication trends in environmental sciences from 1998 to 2009. Arch Environ Sci 2011;5:1-10.
5. Fu HZ, Wang MH, Ho YS. The most frequently cited adsorption research articles in the Science Citation Index (Expanded). J Colloid Interface Sci 2012;379:148-56. [Crossref] [PubMed]
6. Ho YS. Letter to the editor regarding “Global research trends in radiotherapy for gliomas: A systematic bibliometric analysis”. World Neurosurg 2023;170:251. [Crossref] [PubMed]
7. Cheungpasitporn W, Krisanapan P, Suppadungsuk S, Thongprayoon C, Fülöp T, Miao J, Soliman KM, Ho YS. Research trends and performance of endothelin A receptor antagonist in kidney care: a bibliometric analysis. Ren Fail 2025;47:2487212. [Crossref] [PubMed]
8. Ho YS, Fülöp T, Krisanapan P, Soliman KM, Cheungpasitporn W. Artificial intelligence and machine learning trends in kidney care. Am J Med Sci 2024;367:281-95. [Crossref] [PubMed]
9. Usman M, Ho YS. COVID-19 and the emerging research trends in environmental studies: a bibliometric evaluation. Environ Sci Pollut Res Int 2021;28:16913-24. [Crossref] [PubMed]
10. Yang Z, Xie Z, Wan J, Yi B, Xu T, Shu X, Zhao Z, Tang C. Current Trends and Research Hotspots in Pancreatic Stellate Cells: A Bibliometric Study. Front Oncol 2022;12:896679. [Crossref] [PubMed]
11. Ho YS, Shekofteh M, Moghadasi AN. Research Focuses and Trends in Multiple Sclerosis: A Scientometric Analysis. Basic Clin Neurosci 2023;14:273-87. [Crossref] [PubMed]
12. Hu JH, Zhang X, Yang HM, Xu YL, Zhang M, Niu X. A bibliometric analysis of the relationship between traumatic brain injury and Alzheimer's disease (1993-2023). Front Aging Neurosci 2024;16:1462132. [Crossref] [PubMed]
13. Gu J, Wu Y, Shen Y, Yu H, Chen Y. Current Trends and Research Hot Spots in Traumatic Birth: A Bibliometric Analysis. Clin Nurs Res 2025;34:287-303. [Crossref] [PubMed]
14. Ho YS. Comments on “Adsorption characteristics and behaviors of graphene oxide for Zn(II) removal from aqueous solution”. Appl Surf Sci 2014;301:584. [Crossref]
15. Moss AA, Hunter TB. Point-counterpoint: Critical review. Acad Radiol 1994;1:191-2. [Crossref]
16. Noè LF, Batten DJ. ‘Publish or perish’: The pitfalls of duplicate publication. Palaeontology 2006;49:1365-7. [Crossref]