New technologies in breast cancer sentinel lymph node biopsy; from the current gold standard to artificial intelligence.

Anna Cykowska, Luigi Marano, Alessia D'Ignazio, Daniele Marrelli, Maciej Swierblewski, Janusz Jaskiewicz, Franco Roviello, Karol Polom

Journal: Surgical oncology 2021;34():324-335

PMID: 32791443

Abstract

Sentinel lymph node biopsy is an important diagnostic procedure performed in early breast cancer patients with clinically negative axillary lymph nodes. Detection and examination of sentinel lymph nodes determine further therapy decisions, therefore a choice of optimal technique minimising the risk of false-negative results is of great importance. Currently, the gold standard is the dual technique comprising the blue dye and radiotracer, however, this method creates a logistical problem for many medical units. The intrinsic constraints of the existing methods led to the development of a very wide range of alternatives with varying clinical efficiency and feasibility. While each method presents with its own advantages and disadvantages, many techniques have improved enough to become a non-inferior alternative in the sentinel lymph node biopsy. Along with the improvement of the existing technologies, there are evolving trends such as multimodality of the techniques maximising the diagnostic outcome or an emerging use of artificial intelligence (AI) improving the workflow of the procedure. This literature review aims to give an overview of the current status of the standard techniques and emerging cutting-edge technologies in the sentinel lymph node biopsy.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Address: Department of Clinical and Biological Sciences, University of Turin, Orbassano, 10043, Italy. Electronic address: [email protected].; Department of Medicine, Surgery and Neurosciences, Unit of General Surgery and Surgical Oncology, University of Siena, Strada Delle Scotte, 4, 53100, Siena, Italy.; Department of Surgical Oncology, Medical University of Gdansk, Gdańsk, 80-211, Poland.
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