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Publications [#342620] of Tuan Vo-Dinh

Papers Published

  1. Odion, RA; Strobbia, P; Crawford, BM; Vo-Dinh, T, Direct detection of nanostar probes through a monkey skull using inverse surface-enhanced spatially offset Raman spectroscopy (SESORS), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10868 (January, 2019), ISBN 9781510623781 [doi]
    (last updated on 2024/03/28)

    Abstract:
    While the use of nanomaterials in medical diagnostics has received increasing interest, in vivo detection of nanoparticles using optical techniques is still a challenge. Among other techniques, surface-enhanced Raman scattering (SERS)-labeled nanoparticles offer many potential applications in the field of disease diagnostics and biomedical monitoring, due to the advantages offered by SERS. We have previously developed a unique plasmonics-active nanoplatform, gold nanostars (GNS) for in vitro and in vivo multiplexed detection and diagnostics. To date conventional optical setups are typically limited in obtaining SERS signals at the sample surface, due to the strong attenuation caused by the highly scattering and absorbing tissue. Herein, we utilize spatially offset Raman spectroscopy (SORS) to overcome this depth limitation and obtain specific spectrochemical signatures of SERS-labeled nanoparticles, such as gold nanostars, beneath thick material and bone. In particular, we developed an optical setup for inverse spatially offset Raman spectroscopy to improve the robustness of the method developed. The efficacy of this method, referred to as inverse Surface-Enhanced Spatially Offset Raman Spectroscopy (SESORS) is demonstrated through the detection of layer-specific and subsurface SERS signals beneath different layers and substrates: (1) 4-mm tissue phantom, (2) 4-mm paraffin film, and (3) 5 mm bone of a macaque skull. Additionally, we show the possibility of recovering the pure SERS signal that belongs to a specific layer within a two-layer system using scaled subtraction. We will discuss the use of inverse SESORS in applications relevant to biomedical research.


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