Synergistic efficiency of methylene blue and carbon nanoparticles for sentinel lymph node biopsy in early breast cancer: A large-scale real-world cohort study of 1,355 patients.

583 Background: Sentinel lymph node biopsy (SLNB) using radioisotopes and fluorescence imaging is the gold standard but remains inaccessible in many resource-limited regions due to high costs and the lack of nuclear medicine infrastructure. Methylene blue (MB) is a globally available, low-cost tracer, but often lacks consistent nodal yield. This study evaluates a radiation-free, dual-tracer protocol combining MB with carbon nanoparticles (CN) to provide a highly accessible and reliable axillary staging method for diverse clinical settings. Methods: In this single-center retrospective cohort study, 1,355 female patients with cT1-2N0M0 breast cancer (May 2019 to December 2022) were stratified into the MB group (n=675) or the MB+CN group (n=680). Primary endpoints were the SLN detection rate and mean node retrieval (MNR). Sensitivity analyses adjusted for confounders, including Ki67 status, using multivariate regression. The goal was to determine if this dual-dye approach could match the reliability of high-cost methods without specialized equipment. Results: The MB+CN group achieved a comparable detection rate to MB alone (96.32% vs. 96.44%; P=0.905). Crucially, the dual-tracer protocol significantly increased the MNR (2.43±1.64 vs. 2.10±1.35; P<0.001). Adjusted linear regression confirmed a robust increase in node count (β=0.36, 95% CI: 0.19–0.52, P<0.001). Subgroup analysis demonstrated enhanced utility in aggressive molecular profiles, with significantly higher node retrieval in high-Ki67 (P=0.002), T2 stage (P=0.032), and ER-positive (P<0.001) cohorts. No significant differences in detection rates were observed across any clinicopathological subgroups. Conclusions: The MB+CN dual-tracer strategy significantly enhances nodal yield while maintaining high detection rates. By eliminating the need for radioactive tracers and expensive imaging hardware, this approach offers a precise, safe, and cost-effective SLNB solution. It is particularly suited for large-scale implementation in developing countries and rural healthcare systems, bridging the gap in breast cancer surgical standards globally. Comparison of SLNB outcomes between MB and MB+CN groups. Outcome MB Group (n=675) MB+CN Group (n=680) Univariate P Adjusted Estimate (95% CI) Multivariate P Detection Rate, % (n 1​ /n) 96.44% (651/675) 96.32% (655/680) 0.905 OR: 0.83 (0.64–1.09) 0.182 Mean Node Retrieval (SD) 2.10 (1.35) 2.43 (1.64) <0.001 β: 0.36 (0.19–0.52) <0.001