The efficacy of intra-operative injection of [99mTc] labelled colloidal nanoparticles for sentinel lymph nodes identification in breast cancer
Year: 2026
Type: article
Abstract: BACKGROUND: Sentinel lymph node (SLN) biopsy is a critical component of axillary staging in breast cancer management. Traditionally, Technetium-99m (Tc-99m) labelled colloidal nanoparticles is injected preoperatively in the nuclear medicine suite, followed by imaging, while blue dye is injected intraoperatively. Despite the use of topical anesthetics, preoperative radio-tracer injections can be painful, time-intensive, and resource-demanding. To address these limitations, we implemented intraoperative radio-tracer injection under anesthesia, instead of the traditional procedure at the nuclear imaging suite. This study evaluates whether intraoperative Tc-99m labelled colloidal nanoparticles administration affects SLN identification rates. MATERIALS AND METHODS: A retrospective analysis of breast cancer patients who underwent surgery at Rambam Health Care Campus (2020-2023). Unfiltered Tc-99m sulphur colloid and blue dye were injected intraoperatively, and SLN detection rates were assessed. RESULTS: Among 350 patients (352 procedures), radioactive SLNs were successfully identified using Tc-99m in 89.5 % of cases. When both Tc-99m labelled colloidal nanoparticles and blue dye were used, the identification rate increased to 93.2 %. SLN detection was higher in upfront surgery compared to neoadjuvant therapy cases (radio-tracer alone: 92.2 % vs. 85.1 %, p = 0.048; dual tracer: 95.9 % vs. 88.8 %, p = 0.015). Advanced T-stage (OR 5.1, 95 %CI 2.3, 11.3; p < 0.001) and N-stage (OR 3.7, 95 %CI 1.8, 7.3; p < 0.001) were associated with lower SLN detection rates. CONCLUSIONS: Intraoperative Tc-99m labelled colloidal nanoparticles injection is an effective alternative to preoperative injection, achieving comparable SLN detection rates while eliminating patient discomfort, reducing procedural complexity, and optimizing surgical workflow.
Source: The Breast
Authors: Or Barkai, Itamar Ashkenazi, Aviad Hoffman
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,200
OpenAlex ID: W7118326547
