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Intraoperative assessment of resection margins by Raman spectroscopy to guide oral cancer surgery

*Corresponding author for this work
  • RiverD International B.V.
  • art Photonics GmbH
  • Antwerp University Hospital
  • University of Antwerp

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)

Abstract

Patients with oral cavity cancer are almost always treated with surgery. The goal is to remove the tumor with a margin of more than 5 mm of surrounding healthy tissue. Unfortunately, this is only achieved in about 15% to 26% of cases. Intraoperative assessment of tumor resection margins (IOARM) can dramatically improve surgical results. However, current methods are laborious, subjective, and logistically demanding. This hinders broad adoption of IOARM, to the detriment of patients. Here we present the development and validation of a high-wavenumber Raman spectroscopic technology, for quick and objective intraoperative measurement of resection margins on fresh specimens. It employs a thin fiber-optic needle probe, which is inserted into the tissue, to measure the distance between a resection surface and the tumor. A tissue classification model was developed to discriminate oral cavity squamous cell carcinoma (OCSCC) from healthy oral tissue, with a sensitivity of 0.85 and a specificity of 0.92. The tissue classification model was then used to develop a margin length prediction model, showing a mean difference between margin length predicted by Raman spectroscopy and histopathology of −0.17 mm.

Original languageEnglish
Pages (from-to)4116-4126
Number of pages11
JournalAnalyst
Volume148
Issue number17
DOIs
Publication statusPublished - 2023

Bibliographical note

Funding Information:
Financial support – the Dutch Cancer Society (Project 106467) and the EU-Eurostars-programme (Project 12076 – RA-SURE).

Publisher Copyright:
© 2023 The Royal Society of Chemistry.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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