Identification of Healthy Tissue from Malignant Tissue in Surgical Margin Using Raman Spectroscopy in Oral Cancer Surgeries

Mukta Sharma, Ying Chang Li, S. N. Manjunatha, Chia Lung Tsai*, Ray Ming Lin, Shiang Fu Huang, Liann Be Chang

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

4 Scopus citations

Abstract

Accurate identification of tissue types in surgical margins is essential for ensuring thecomplete removal of cancerous cells and minimizing the risk of recurrence. The objective of thisstudy was to explore the clinical utility of Raman spectroscopy for the detection of oral squamous cellcarcinoma (OSCC) in both tumor and healthy tissues obtained from surgical resection specimens duringsurgery. This study enrolled a total of 64 patients diagnosed with OSCC. Among the participants,approximately 50% of the cases were classified as the most advanced stage, referred to as T4. Ramanexperiments were conducted on cryopreserved tissue samples collected from patients diagnosedwith OSCC. Prominent spectral regions containing key oral biomarkers were analyzed using thepartial least squares–support vector machine (PLS–SVM) method, which is a powerful multivariateanalysis technique for discriminant analysis. This approach effectively differentiated OSCC tissuefrom non-OSCC tissue, achieving a sensitivity of 95.7% and a specificity of 93.3% with 94.7% accuracy.In the current study, Raman analysis of fresh tissue samples showed that OSCC tissues containedsignificantly higher levels of nucleic acids, proteins, and several amino acids compared to the adjacenthealthy tissues. In addition to differentiating between OSCC and non-OSCC tissues, we have alsoexplored the potential of Raman spectroscopy in classifying different stages of OSCC. Specifically, wehave investigated the classification of T1, T2, T3, and T4 stages based on their Raman spectra. Thesefindings emphasize the importance of considering both stage and subsite factors in the applicationof Raman spectroscopy for OSCC analysis. Future work will focus on expanding our tissue samplecollection to better comprehend how different subsites influence the Raman spectra of OSCC atvarious stages, aiming to improve diagnostic accuracy and aid in identifying tumor-free marginsduring surgical interventions.

Original languageEnglish
Article number1984
JournalBiomedicines
Volume11
Issue number7
DOIs
StatePublished - 13 07 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Keywords

  • Raman spectroscopy
  • oral cancer
  • partial least squares
  • support vector machine
  • tissue

Fingerprint

Dive into the research topics of 'Identification of Healthy Tissue from Malignant Tissue in Surgical Margin Using Raman Spectroscopy in Oral Cancer Surgeries'. Together they form a unique fingerprint.

Cite this