Research status and frontier trends of near-infrared autofluorescence for parathyroid identification and protection: a bibliometric analysis from 2006 to 2026

Introduction

The parathyroid glands are situated in close proximity to the thyroid gland and play a crucial endocrine role in maintaining calcium and phosphate homeostasis through the secretion of parathyroid hormone (PTH). Consequently, accurate identification of these glands is critical during thyroid, parathyroid, and other neck surgeries. Thyroidectomy is a common treatment for benign thyroid diseases and the primary intervention for thyroid cancer, whose incidence has gradually increased in recent years (1). Parathyroid injury is a common complication of thyroid surgery, occurring in 5% to 20% of cases (2-4). This injury frequently leads to postoperative hypocalcemia, tetany, and prolonged hospitalization (5-8). This complication significantly diminishes patients’ quality of life, often requiring daily calcium/vitamin D supplementation and posing a risk of mortality (6,9-14). In contrast, parathyroidectomy for primary hyperparathyroidism focuses on locating pathological glands while preserving intact parathyroid tissue.

Various intraoperative localization techniques have been developed to address this problem. Among them, near-infrared autofluorescence (NIRAF) has emerged as a key technology for parathyroid identification and protection. When illuminated with near-infrared light (typically 785 nm), parathyroid glands emit autofluorescence at longer wavelengths (approximately 820–830 nm) (15). This technique offers several advantages: it is non-invasive, real-time, and highly precise. Meta-analyses and randomized controlled trials (RCTs) show that NIRAF reduces transient hypoparathyroidism, but its effect on long-term hypoparathyroidism (6 months) is unclear (16-21). In recent years, research on NIRAF for parathyroid protection has increased steadily worldwide, covering diverse areas such as clinical applications, technical optimization, and underlying biological mechanisms. Both NIRAF and indocyanine green (ICG) fluorescence are used for parathyroid gland identification and preservation. With similar excitation and emission wavelengths (ICG detected near 830 nm) and nearly identical imaging systems, ICG serves as a complementary auxiliary technique to NIRAF for vascular assessment rather than a standalone modality.

Traditional literature reviews, while valuable for summarizing existing knowledge, are inherently limited in their ability to quantify research trends or visualize scholarly networks. Bibliometric analysis addresses this limitation by enabling the quantitative evaluation of research activity within a given field (22,23). Through analysis of co-authorship networks, co-citation relationships, and keyword dynamics, this approach can reveal a field’s intellectual structure and evolving frontiers (24,25). The present study therefore applies bibliometric methods to systematically map the global literature on NIRAF for parathyroid protection. We present this article in accordance with the BIBLIO reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-2026-0154/rc).

Methods

Search strategy

We conducted a literature search on the Web of Science Core Collection (WoSCC) database on January 24, 2026. The search formula was ((TS = (Parathyroid OR Parathyroids OR “Parathyroid gland” OR “Parathyroid glands”)) AND TS = (“Autofluorescence” OR “Near-infrared” OR “Fluorescence” OR “NIRAF” OR “Near-infrared autofluorescence” OR “NIR”)) AND LA = (English), and the type of documents was set to “Article” and “Review”. The time span was set to 2006–2026, as early exploration of parathyroid autofluorescence commenced in 2006. Notably, “indocyanine green” or “ICG” was not included as an independent search term. This search strategy ensures that the core focus remains on autofluorescence-based parathyroid identification while allowing for the inclusion of studies that employ ICG as a complementary perfusion assessment tool.

Data selection and standardization

All publications extracted from the database were imported into EndNote for subsequent classification. The literature underwent a screening process based on titles and abstracts, with full-text assessment performed when necessary. Studies irrelevant to the research topic were excluded. Specifically, studies relying exclusively on ICG fluorescence without NIRAF assessment were excluded. Before performing the bibliometric analysis, we standardized the data. To reduce the bias, the different expressions representing the same author or same keyword were standardized with the same representation, which was manually completed by the authors. Two researchers (Y.H. and Y.L.) independently completed the entire procedure and then cross-verified it. When there was any disagreement, the two researchers discussed it with a third researcher (S.W.) until a consensus was reached.

Data analysis

VOSviewer (version 1.6.20) is a bibliometric analysis software that can extract key information from numerous publications (26), which is often used to build collaboration, co-citation and co-occurrence networks (27). In our study, the software was mainly used to conduct the following analyses: national analysis, institutional analysis, journal and co-cited journal analysis, author and co-cited author analysis, and co-citation reference analysis. In the map produced by VOSviewer, a node represents an item such as a country, institution, journal, or author. The node size and color indicate the number and classification of these items, respectively. The line thickness between nodes reflects the degree of collaboration or co-citation of the items (28,29). It should be noted that all English terms in VOSviewer-generated maps are in lowercase (the software’s default format), which does not affect term meaning or analysis results. To comply with academic standards, corresponding terms in the text are capitalized to ensure consistency and rigor.

CiteSpace (version 6.4.R1), developed by Professor C. Chen, can be used for bibliometric analysis and visualization (27). In this study, CiteSpace was employed to perform keyword co-occurrence analysis and cluster analysis, and keyword burst detection was used to investigate research trends and hotspots in the field.

The R package “bibliometrix” (version 3.2.1) (https://www.bibliometrix.org) was applied to extract the publication volume data of different countries, which were subsequently compiled into a table for clear presentation (28,30).

Microsoft Office Excel 2019 was used to quantitatively analyze the annual publication volumes in this field from 2006 to January 2026.

Results

Literature screening and selection

A total of 550 publications were initially retrieved from the databases. After duplicate removal and strict screening, 371 publications were finally included in this study, consisting of 307 articles and 64 reviews. The detailed literature selection process is shown in Figure 1.

Figure 1 Publications screening flowchart.

Annual growth trend

Based on the trend of annual publications (Figure 2), the overall pattern was one of initial stability, followed by rapid growth. The entire study period can be divided into three phases: Phase 1 (2006–2013), Phase 2 (2014–2018), and Phase 3 (2019–2025). Data from January 2026 were not considered because of unavailability. As shown in Figure 2, the number of publications was extremely low in Phase 1, indicating that related research was in an initial stage with low attention. In Phase 2, the number of publications increased steadily, with an average of approximately 10.2 publications per year, suggesting that the field entered a growth stage with gradually rising attention. In Phase 3, the number of publications increased markedly, with an average of approximately 44.1 publications per year. The number of publications in 2019 was approximately twice that in 2018 and reached a peak of 54 in 2025 during the entire statistical period. Over the 7 years of Phase 3, the number of publications in this field showed an overall fluctuating upward trend, reflecting a continuous increase in research enthusiasm.

Figure 2 Trend in annual number of publications from 2006 to 2026.

National analysis

The national collaboration network analysis was based on the country of the corresponding author and used the full-counting method. This approach can intuitively reflect the participation of each country in international cooperation, although it may lead to a total count higher than the actual number of articles owing to multinational co-authorship. A total of 371 articles from 45 countries were included, and the total publication count was 493 based on full counting, with the United States and China ranking the highest (Table 1).

The network structure demonstrated that the United States and China served as two core nodes with extensive collaborations, acting as key hubs for international cooperation (Figure 3). Europe formed a close regional cluster centered on France, Germany, Italy, and the United Kingdom. Asia featured active academic exchanges led by China, South Korea, and Japan. South American countries, such as Argentina and Brazil, also collaborated with core nations, reflecting high global participation.

Figure 3 National collaboration network graph.

Institutions analysis

Institutional collaboration network analysis showed that the Cleveland Clinic and Vanderbilt University consistently occupied core positions in the network, with the largest node sizes and densest connections, demonstrating their long-standing leading roles in this field. This finding is consistent with publication statistics: these two institutions ranked first and second with 32 and 22 publications, respectively, and both exhibited high centrality in the network (Figure 4, Table 2). From a temporal perspective (Figure 4), the field showed obvious spatiotemporal evolution and a core–periphery structure from 2019 to 2024. In the early stage (2019–2020, blue-purple), a European cluster centered at Leiden University, covering the Netherlands, Sweden, and the UK, was dominant. In the middle stage (2021–2022, yellow-green), the Cleveland Clinic emerged as the largest node and formed a close North American medical cluster with its Florida branch, Vanderbilt University, and The Ohio State University. In the recent stage (2023–2024, orange-red), research collaboration further expanded to emerging institutions, such as the All India Institute of Medical Sciences and Sarasota Memorial Health Care System.

Figure 4 Institutions collaborative network.

Journals analysis

The results from the journal co-occurrence network (Figure 5A, Table 3) showed that journals in this field exhibited a multidisciplinary feature centered on surgery and endocrinology, including Surgery (n=23), Frontiers in Endocrinology (n=20), and Gland Surgery (n=19). The color gradient from blue (2020) to red (2023) indicated that early publications focused on traditional surgical journals and have gradually expanded to multidisciplinary journals in recent years. The emergence of photobiology journals further highlighted the value of autofluorescence technology.

Figure 5 Journals and co-cited journals. (A) Journal co-occurrence network. (B) Journal co-citation network.

The journal co-citation network revealed three major clusters corresponding to surgical techniques, endocrine surgery and oncology, as well as head and neck minimally invasive surgery (Figure 5B). Close co-citation connections among clusters reflected deep multidisciplinary integration. Surgery and World Journal of Surgery were located at the junction of clusters with the highest co-citation centrality and disciplinary integration function.

Authors analysis

A statistical analysis of authorship from 2006 to 2026 (Table 4) showed that Eren Berber (Cleveland Clinic, Cleveland, USA) ranked first with 31 publications and 876 citations, reflecting his high productivity and academic influence. Frederic Triponez (University Hospital Geneva, Geneva, Switzerland) had 19 publications and 392 citations, while Carmen C. Solorzano (Vanderbilt University, Nashville, USA) produced 17 publications and 720 citations; they ranked second and third, respectively. Anita Mahadevan-Jansen (Vanderbilt University, Nashville, USA) contributed 16 publications and 969 citations, ranking fourth in publication output but first in total citations and demonstrating her pioneering contributions.

The author collaboration network (Figure 6A) identified several stable clusters. Eren Berber’s cluster (red nodes) focused on parathyroid surgery; Anita Mahadevan-Jansen and Carmen C. Solorzano (green nodes) specialized in optical imaging and biomedical engineering; Frederic Triponez and Benmiloud Fares (blue nodes) concentrated on endocrine surgery and clinical translation. The network was multicentric and interdisciplinary; however, weak connections between clusters suggested insufficient cross-field collaboration.

Figure 6 Authors and co-cited authors. (A) Authors collaboration network graph. (B) Co-cited authors network graph.

The co-cited author network (Figure 6B) illustrates the knowledge foundation of this field. Melanie Ann McWade and Sung Won Kim (blue nodes) were central and highly cited, representing fundamental work. Jordi Vidal Fortuny and Nisar Zaidi (red nodes) corresponded to clinical studies on parathyroid protection, whereas Fares Benmiloud and Aimee Nicole Di Marco (green nodes) centered on intraoperative fluorescence and image-guided technologies. The yellow cluster led by Thomas A. Lang and Mathieu Lorent mainly concentrates on surgical parathyroid protection and postoperative complication management. This co-citation network reflects a clear clinical-technical research framework and offers solid theoretical references for subsequent investigations.

References analysis

Based on the co-citation network analysis of the literature (Figure 7), a clear foundation of classic literature and knowledge evolution context has been formed in this field. The network presents a tricolor (red-green-blue) clustering structure corresponding to three research directions: the red cluster, centered on Jordi Vidal Fortuny et al. (2016, 2018), constitutes a mature classic literature group on thyroid surgical techniques (e.g., recurrent laryngeal nerve monitoring and parathyroid function protection); the green cluster, with Anders Bergenfelz et al. (2020) as the core, forms the knowledge base of endocrine surgery and evidence-based medicine with high recent academic activity; and the blue cluster, centered on Melanie Ann McWade et al. (2016), represents the field of minimally invasive surgery and energy instrument application, closely connected to the red cluster through bridging literature, such as Fares Benmiloud (2018, 2020). In addition, Cedric Paras’s article (2011) in the blue cluster is the first highly cited article in the co-citation network (Table 5). This paper represents the first core foundational study in the field of parathyroid autofluorescence, and it is also a landmark research that systematically verified the feasibility of this technology for intraoperative parathyroid gland identification for the first time.

Figure 7 Co-citation network of references.

Keywords analysis

Co-citation network of keywords

Based on keyword co-occurrence network analysis using CiteSpace (Figure 8), the field presents a research theme clustering and evolutionary path centered on parathyroid function protection. The network included 391 nodes and 1,794 links, with a modularity index Q=0.5278 and a mean silhouette value S=0.8341, indicating a significant clustering structure and reasonable topic division. The statistics of high-frequency keywords (Table 6) showed that, in addition to “parathyroid glands” (n=176), “identification” (n=126), and “surgery” (n=82), “indocyanine green fluorescence” (n=126), “fluorescence” (n=87), and “near-infrared autofluorescence” (n=85) ranked high, reflecting the extensive application of fluorescence navigation technology in surgery. Furthermore, keywords such as “primary hyperparathyroidism” (n=35) and “cancer” (n=38) indicated an expanding trend of the disease spectrum, whereas “perfusion” (n=39) and “angiography” (n=44) reflected the integration of functional evaluation techniques.

Figure 8 Co-occurrence keywords from 2006 to 2026.

Keyword clustering

Keyword clustering analysis was performed using the log-likelihood ratio (LLR) algorithm, and a total of 11 research clusters were identified (Figure 9A). Among them, “#0 hypocalcemia” is the core of research in this field, as a key outcome indicator for intraoperative parathyroid function protection; its occurrence is closely related to clinical operations and technical applications such as thyroid surgery and ICG fluorescence imaging. “#1 parathyroid-related disorders”, “#2 thyroid cancer” and “#7 primary hyperparathyroidism” together constitute the core disease research system of this field, which fully supports the clinical application framework of parathyroid autofluorescence localization and protection technology from a disease basis and main indications to primary disease treatment. “#8 fluorescence-guided surgery” represents the development direction of intraoperative navigation technology, highlighting interdisciplinary integration and clinical transformation potential. The remaining clusters include “#3 volume”, “#4 methylene blue”, “#5 tissue distribution”, “#6 aminolevulinic acid”, “#9 extracellular nucleotides” and “#10 gamma probe identification”.

Figure 9 Keyword clusters. (A) The clusters were identified by utilizing the log-likelihood ratio statistic. (B) The clusters were identified by utilizing the mutual information statistic.

Based on the CiteSpace mutual information (MI) algorithm, keyword clustering analysis identified 11 research clusters centered on the clinical application of parathyroid autofluorescence (Figure 9B). Cluster “#0 minimally invasive video-assisted thyroidectomy” represents the core surgical platform, closely associated with ICG fluorescence and NIRAF, demonstrating the integration of minimally invasive techniques with fluorescence-guided navigation. Cluster “#9 hypoparathyroidism” serves as the primary clinical endpoint for parathyroid protection, forming a closed-loop relationship with cluster #0 between technological intervention and functional outcome. Additional clusters include “#1 collagen linearity”, “#2 outcomes”, “#3 perioperative bleeding”, “#4 thyroid carcinoma”, “#5 tissue distribution”, “#6 multicolor fluorescence imaging”, “#7 autophagy”, “#8 Delphi survey”, and “#10 gamma probe identification”. Herein, “collagen linearity” cluster primarily focuses on the exploration and mechanistic interpretation of tissue autofluorescence. Among multiple potential influencing factors, changes in collagen structural characteristics, including linear arrangement, have been proposed as one plausible mechanism to explain the variation in fluorescence signals.

Discussion

This bibliometric analysis systematically mapped the global research landscape of NIRAF for parathyroid identification and protection over the past two decades (2006–2026). Overall, the field has experienced a striking development from the initial exploratory stage to a rapidly growing phase, with a sharp surge in research output since 2019. Geographically, the United States and China lead the global research effort, with the Cleveland Clinic and Vanderbilt University standing out as the most influential research institutions worldwide. Eren Berber is the most productive scholar in this field, while Anita Mahadevan-Jansen has the highest citation impact. Surgery emerges as the most influential journal, and the research hotspots are centered on parathyroid function protection, with NIRAF and ICG fluorescence serving as the two core applied technologies.

Annual publications in this field increased markedly after 2019 (Figure 2), following the 2018 U.S. Food and Drug Administration (FDA) De Novo clearance of the first two NIRAF systems for intraoperative parathyroid identification: the probe-based PTeye (USA) and the imaging-based Fluobeam 800 Clinic (France) (31). This regulatory milestone cleared the path for clinical adoption and catalyzed a rapid expansion of research worldwide. The distinct technical origins and commercialization pathways of these two platforms have since shaped the global research landscape, with their influence extending to the geographic distribution of research activity and the structure of international collaboration networks.

In the United States, the dominant role in country and institutional networks is closely tied to the local development of the PTeye System (Figures 3,4). This device originated from the Mahadevan-Jansen group at Vanderbilt University, which explains why Anita Mahadevan-Jansen emerged as the most cited author in our analysis (32) (Figure 6A). Her pioneering work established the academic foundation for the technology and positioned her team and affiliated institutions at the core of the institutional collaboration network (Figure 4). The device was later commercialized by AiBiomed, which was acquired by Medtronic in 2020. After regulatory authorization by the FDA, the Cleveland Clinic, Vanderbilt University, and other centers conducted extensive clinical validation, further consolidating the central role of these US institutions. Meanwhile, European countries including Germany, Italy, and the Netherlands maintain close collaborative ties with the United States (Figure 3). Institutions such as Leiden University and the Karolinska Institutet are highly active, with most studies utilizing the Fluobeam 800 system. The system was initially developed by Fluoptics and later acquired by Getinge. Benmiloud Fares, a key contributor to this system, also demonstrated prominent centrality in the co-cited author network (Figure 6B), a finding that echoes his pivotal role in advancing this technology (33). Upon receiving market access approval, Benmiloud and other European teams rapidly initiated multicenter validation studies and promoted the technology across Europe through collaboration with US institutions. This transatlantic dynamic, characterized by innovation in the United States followed by collaborative validation and adoption in Europe, is clearly reflected in the institutional co-occurrence network identified in our study.

Facilitating the sound development of domestic parathyroid autofluorescence research and inspiring future research directions is one of the important research objectives of this study. In the field of parathyroid autofluorescence, China currently ranks second globally in terms of publication output; however, its institutional co-occurrence network lacks prominent core nodes (Table 1, Figure 4), indicating that domestic research efforts remain fragmented without globally influential centers. This pattern reflects the current landscape of autofluorescence device adoption in China, in which no foreign systems have been approved for parathyroid identification and all clinically used devices have been domestically developed. However, a relatively late start in research and development has resulted in technological gaps and limited clinical evidence, thereby constraining broader adoption. To address these challenges, China should prioritize innovation in core technologies, foster industry-academia partnerships, and strengthen both domestic collaborations and international engagement. These efforts will help cultivate leading research centers and enhance China’s global competitiveness in this field.

The journal co-occurrence and co-citation analyses revealed three distinct clusters of publications on NIRAF for parathyroid protection (Figure 5, Table 3). The first cluster comprised clinical application journals, exemplified by Surgery and JAMA Surgery, that emphasized technical validation and outcome assessment, mirroring the surgical community’s demand for precise parathyroid localization and reduced complications. The second cluster, including optics and biophotonics journals such as the Journal of Biophotonics, concentrated on imaging mechanisms and device development, thereby laying the groundwork for clinical translation. The third cluster comprised interdisciplinary journals, such as Frontiers in Endocrinology, which acted as conduits between laboratory findings and surgical practice, enabling bidirectional translation. The interplay among these clusters underscores a recurring pattern in which clinical needs spur technological innovation, and that innovation, in turn, refines surgical care.

The keyword co-occurrence and clustering analyses in this study (Figures 8,9) revealed that research on NIRAF for parathyroid protection centers on several interconnected themes, including clinical applications, technical evolution, biological mechanisms, and emerging technologies. The following sections discuss these hotspots in detail.

Clinical application scenarios

The clinical spectrum of NIRAF applications has expanded significantly, primarily centered on thyroid and parathyroid pathologies. This aligns with our keyword clustering results (Figure 9A), where #1 parathyroid-related disorders, #2 thyroid cancer, and #7 primary hyperparathyroidism collectively constitute the core disease research framework in this field. For thyroidectomy, the efficacy of NIRAF in identifying parathyroid glands and reducing postoperative hypocalcemia has been rigorously validated by multiple RCTs and systematic meta-analyses. A landmark multicenter RCT by Benmiloud et al. (2020) (16) demonstrated that NIRAF-guided surgery significantly reduced the rate of inadvertent parathyroidectomy compared to conventional visualization (2.5% vs. 11.7%, P=0.006). Subsequent meta-analyses by Weng et al. (2021) (34) and Safia et al. (2024) (20) confirmed that NIRAF significantly decreases transient hypoparathyroidism and postoperative hypocalcemia. These high-level evidence studies establish NIRAF as a standard-of-care adjunct in thyroid surgery. The ongoing surge of “thyroid cancer” (2022–2026) in Figure 10 confirms that this disease context remains a central focus of NIRAF research.

Figure 10 Top 15 keywords with the strongest citation bursts.

Conversely, the clinical utility of NIRAF in primary hyperparathyroidism (PHPT) remains investigational. Although promising for identifying ectopic glands, current outcomes lack the consistency observed in thyroid surgery (35,36). Recent pilot studies suggest that NIRAF intensity may correlate with gland function, with adenomatous tissue exhibiting heterogeneous fluorescence patterns compared to normal parenchyma (37-39). This marks a critical transition from established surgical protection to exploratory functional localization, though prospective validation is required before clinical adoption.

Technical evolution

Methylene blue and carbon nanoparticles have historically been employed for parathyroid identification; however, their application is limited by potential tissue toxicity, permanent staining, and lack of real-time feedback (40-42). The keyword burst analysis (Figure 10) illustrates this decline, with “methylene blue” exhibiting a strong citation burst from 2014 to 2019 but disappearing thereafter, confirming its gradual obsolescence. The methodology has since evolved into advanced fluorescence-guided systems. ICG was initially adapted from hepatobiliary surgery, and primarily utilized for parathyroid identification. Initial reports by Vidal Fortuny et al. (2018) established its feasibility for this anatomical labeling purpose (43-45). However, ICG requires intravenous administration and provides transient signal kinetics (peak intensity at 30–60 s), prompting the development of label-free alternatives.

NIRAF has emerged as a non-invasive, continuous monitoring modality that is optimal for anatomical localization without exogenous contrast. In our keyword co-occurrence network (Table 6, Figure 8), “near-infrared autofluorescence” (n=85) and “indocyanine green fluorescence” (n=126) exhibited high co-occurrence frequency. NIRAF has gradually become the dominant fluorescence-guided technology for parathyroid identification and preservation, taking over the anatomical recognition function previously undertaken by ICG. Meanwhile, ICG has been transformed into a key adjunctive tool, focusing on hemodynamic evaluation. Notably, “near-infrared autofluorescence” has shown a robust and ongoing burst since 2024, indicating sustained research interest in this technology (Figure 10). Nevertheless, NIRAF is restricted to structural identification and cannot assess hemodynamic integrity post-dissection. Indocyanine green angiography (ICGA) remains the gold standard for evaluating vascular perfusion and predicting postoperative parathyroid function (46). NIRAF guides anatomical navigation during dissection. ICG is used for perfusion assessment prior to gland preservation or resection. This sequential strategy maximizes the complementary strengths of both technologies while minimizing their individual limitations. Notably, recent RCTs suggest that sequential NIRAF followed by ICG holds promise in reducing the risk of long-term hypoparathyroidism (46,47).

Biological mechanisms

Deciphering the histological origin of NIRAF represents a fundamental research priority in this field. The prevailing hypothesis proposed by Paras et al. (2011) and McWade et al. (2014) attributes intrinsic fluorescence to high expression of the calcium-sensing receptor (CaSR) in parathyroid chief cells (15,47). Both studies are listed in the top 15 highly cited publications (Table 7). Stable signal-to-background ratios in ex vivo and fixed tissue specimens confirm the substantial protein stability of this fluorophore (48). Baregamian et al. (2023) utilized organoid models to demonstrate preserved NIRAF characteristics in three-dimensional collagen matrices without vascular perfusion, establishing a structural rather than vascular origin for this signal (49). Elucidating these mechanisms is essential for optimizing recognition algorithms and reducing false-positive interference from adipose or lymphatic tissue.

Future directions

A critical frontier is the integration of artificial intelligence (AI) to establish objective numerical thresholds from NIRAF data. Machine learning algorithms can analyze fluorescence intensity patterns, texture features, and spatial heterogeneity to eliminate inter-observer variability inherent in qualitative visual assessment (37,50-54). Concurrently, label-free technologies such as laser speckle contrast imaging (LSCI) and diffuse reflectance spectroscopy (DRS) have emerged as significant advancements (55-61). Unlike ICGA, these modalities quantify microvascular perfusion and tissue metabolic status without exogenous contrast agents. However, these modalities remain in the preliminary validation phase and their clinical maturation requires further large-cohort standardization. The ultimate vision for this field is the development of an integrated intraoperative platform characterized by precise quantification, functional preservation, and AI-assisted decision support.

Strengths and limitations

To our knowledge, this study is the first comprehensive bibliometric analysis to systematically summarize the global research status, hotspots, and trends of autofluorescence imaging in parathyroid gland identification and protection. In addition, the long-term time span and standardized screening process ensure the objectivity and reliability of the results, which can provide valuable insights for future research.

However, this study has several limitations. First, only publications from the WoSCC were included, which may have led to the omission of relevant literature from Scopus, Embase, and grey literature. Second, the analysis was restricted by the algorithms and visualization parameter settings of VOSviewer and CiteSpace, resulting in a certain degree of subjectivity in the results. Third, the inclusion was limited to English-language articles only, thereby excluding relevant Chinese publications and potentially underestimating research and clinical experience from non-English-speaking regions, such as Japan and South Korea. In addition, from a bibliometric perspective, CiteSpace-based analyses may inherently carry a theoretical risk of publication bias. However, no robust evidence verifies that such bias substantially affects the overall research landscape.

Conclusions

A bibliometric analysis of NIRAF for parathyroid localization and protection from 2006 to January 2026 revealed rapid development in this field. Notably, the sharp increase in publications after 2019 was closely related to the 2018 FDA approval of NIRAF devices, which greatly promoted clinical translation. In addition, NIRAF and ICG fluorescence are complementary intraoperative techniques that effectively reduce hypocalcemia and accidental parathyroid resection. Currently, research hotspots have shifted from anatomical identification to functional evaluation. Therefore, the integration of AI and label-free optical imaging represents the key future direction for precise intraoperative protection.

In conclusion, NIRAF is a reliable, non-invasive, real-time imaging tool for parathyroid protection. Further optimization, clinical translation, and interdisciplinary collaboration will help establish intelligent integrated platforms to improve surgical safety and patient quality of life.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-2026-0154/rc

Peer Review File: Available at https://gs.amegroups.com/article/view/10.21037/gs-2026-0154/prf

Funding: This study was supported by the Ministry of Education Industry-University Cooperation Collaborative Education Project (No. 230902331264216, No. 231002331091720); Guangdong Provincial Education Science Planning Project (Higher Education Special Project) (No. 2025GXJK0131); Tertiary Education Scientific research project of Guangzhou Municipal Education Bureau (No. 2024312260); Clinical key specialty construction project funding of Guangdong Province (Guangdong Health Medical Letter [2023] No. 02); and Guangdong Provincial College Students’ Innovation and Entrepreneurship Training Program (No. S202510570092).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-2026-0154/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/.

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