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      Near-Infrared Gold Nanocages as a New Class of Tracers for Photoacoustic Sentinel Lymph Node Mapping on a Rat Model

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          Abstract

          This work demonstrated the use of Au nanocages as a new class of lymph node tracers for noninvasive photoacoustic (PA) imaging of a sentinel lymph node (SLN). Current SLN mapping methods based on blue dye and/or nanometer-sized radioactive colloid injection are intraoperative due to the need for visual detection of the blue dye and low spatial resolution of Geiger counters in detecting radioactive colloids. Compared to the current methods, PA mapping based on Au nanocages shows a number of attractive features: noninvasiveness, strong optical absorption in the near-infrared region (for deep penetration), and the accumulation of Au nanocages with a higher concentration than the initial solution for the injection. In an animal model, these features allowed us to identify SLNs containing Au nanocages as deep as 33 mm below the skin surface with good contrast. Most importantly, compared to methylene blue Au nanocages can be easily bioconjugated with antibodies for targeting specific receptors, potentially eliminating the need for invasive axillary staging procedures in addition to providing noninvasive SLN mapping.

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          Author and article information

          Journal
          101088070
          22479
          Nano Lett
          Nano Lett.
          Nano letters
          1530-6984
          1530-6992
          10 January 2020
          January 2009
          28 January 2020
          : 9
          : 1
          : 183-188
          Affiliations
          Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899
          Author notes
          [* ]Corresponding authors. (L.V.W for photoacoustic imaging) lhwang@ 123456biomed.wustl.edu ; (Y.X. for nanocages) xia@ 123456biomed.wustl.edu .
          Article
          PMC6986311 PMC6986311 6986311 nihpa1067152
          10.1021/nl802746w
          6986311
          19072058
          4809d5d9-f3dd-4111-8607-ae2774b0b601
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