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Accurate tumor detection using plasmonic-enhanced shifted-excitation Raman difference spectroscopy (SERDS). | LitMetric

AI Article Synopsis

  • Surgery is the main treatment for most cancer patients, but accurately removing tumors while preserving surrounding tissue is challenging due to limited imaging techniques.
  • Surface-enhanced Raman scattering (SERS) is a promising non-invasive method for identifying tumors, but traditional Raman detection requires dark environments, which are impractical during surgery.
  • The study presents a new method using SERS nanoprobes and shifted-excitation Raman difference spectroscopy (SERDS) to detect tumors in a mouse model under normal lighting, improving sensitivity and accuracy compared to standard methods.

Article Abstract

For the majority of cancer patients, surgery is the primary method of treatment. In these cases, accurately removing the entire tumor without harming surrounding tissue is critical; however, due to the lack of intraoperative imaging techniques, surgeons rely on visual and physical inspection to identify tumors. Surface-enhanced Raman scattering (SERS) is emerging as a non-invasive optical alternative for intraoperative tumor identification, with high accuracy and stability. However, Raman detection requires dark rooms to work, which is not consistent with surgical settings. Herein, we used SERS nanoprobes combined with shifted-excitation Raman difference spectroscopy (SERDS) detection, to accurately detect tumors in xenograft murine model. We demonstrate for the first time the use of SERDS for tumor detection in a murine model under ambient light conditions. We compare traditional Raman detection with SERDS, showing that our method can improve sensitivity and accuracy for this task. Our results show that this method can be used to improve the accuracy and robustness of Raman/SERS biomedical application, aiding the process of clinical translation of these technologies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977455PMC
http://dx.doi.org/10.7150/thno.53101DOI Listing

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