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

Background: Accurate identification and protection of parathyroid glands are crucial in both thyroid and parathyroid surgery. Near-infrared autofluorescence (NIRAF) imaging has emerged as a key technique to achieve this goal. Despite growing research interest in recent years, the rapidly expanding body of literature in this field lacks a systematic bibliometric analysis. This study aims to map the research landscape, identify hotspots, and trace emerging trends in NIRAF-based parathyroid identification and protection, thereby providing guidance for future investigations. Methods: Publications related to NIRAF for parathyroid applications from 2006 to January 2026 were retrieved from the Web of Science Core Collection. Bibliometric analyses were conducted using VOSviewer and CiteSpace. Results: A total of 371 articles were included in this review. The annual publication count remained relatively stable at a low level until a sharp increase beginning in 2019. The United States and China were the top two countries in terms of publication output. The Cleveland Clinic and Vanderbilt University emerged as leading research institutions. Eren Berber was the most productive author, whereas Anita Mahadevan-Jansen was the most cited. Surgery was the most influential journal in this field. Keyword and co-citation network analyses identified parathyroid function preservation as the core research theme, with NIRAF as the mainstream technique and indocyanine green (ICG) fluorescence acting as a complementary adjunct. Three main research directions were identified: clinical application scenarios, technical evolution, and biological mechanisms. The 2018 U.S. Food and Drug Administration (FDA) approval of NIRAF systems represented a pivotal milestone in the field. Over time, the research focus has evolved from initial clinical problems and conventional localization techniques toward deeper investigations into NIRAF mechanisms, clinical applications, and fluorescence-guided surgery. Conclusions: NIRAF research on parathyroid identification and protection is advancing rapidly and is currently focused on clinical translation and technological refinement. Future efforts should integrate artificial intelligence and advanced label-free imaging modalities.