Background & Objectives: Sentinel lymph node biopsy (SLNB) is an accurate and reliable method for staging the axilla in early breast cancer. The gold standard technique for localizing the sentinel lymph node (SLN) is the use of radioisotope with or without blue dye. However, this technique has its limitations. Various alternatives have been explored to overcome the disadvantages of the standard SLNB technique and superparamagnetic iron oxide mapping agents have garnered significant attention. The SMART study aims to compare the magnetic technique using the superparamagnetic iron oxide particles (SPIO, Sienna+®) to the radioisotope technique (Tc99) +/- blue dye, for SLN identification in patients with early breast cancer.

Methods: A prospective, multicenter study was done that recruited 109 clinically node-negative early-stage breast cancer patients from five centres in the United Kingdom (UK). The patients received radioisotope ± blue dye injections, followed by intraoperative injection of magnetic tracer prior to SLNB. The sentinel node identification rate was compared between the magnetic and standard techniques to evaluate detection rate (per patient and per node), non-inferiority and concordance.

Results: Data was analysed for 107 patients. The per patient detection rate was 98.13% (105/107) when using the magnetic tracer and 92.26% (103/107) when using the standard technique. The nodal detection rate was 93.07% (188/202 nodes) when using the magnetic tracer and 96.53% (195/202) when using the standard technique. Of the 31 patients with positive sentinel lymph nodes (SLNs), all 31 (100%) were detected by both techniques.

Conclusion: Our study demonstrates that the magnetic technique is a feasible method for SLNB, with an identification rate that is not inferior to the standard technique. The magnetic technique offers a suitable alternative to the standard technique thereby avoiding the need for the complexities of nuclear medicine, the hazards of radiation and the anaphylaxis risk of blue dye.

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http://dx.doi.org/10.1016/j.surge.2022.04.006DOI Listing

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