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Systematic evaluation of the biological variance within the Raman based colorectal tissue diagnostics.

Nadine Vogler1, Thomas Bocklitz2, Firas Subhi Salah3,4

  • 1Leibniz Institute of Photonic Technology, 07745, Jena, Germany.

Journal of Biophotonics
|December 22, 2015
PubMed
Summary

Early diagnosis of colorectal cancer is crucial. Raman microspectroscopy, combined with advanced statistical analysis, shows 95% accuracy in distinguishing healthy tissue from cancerous growths, even in biopsies.

Keywords:
Raman microspectroscopycancer diagnosischemometrics

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Area of Science:

  • Biomedical Optics
  • Cancer Diagnostics
  • Spectroscopy

Background:

  • Colorectal cancer is a leading global cancer, necessitating effective screening and early diagnosis.
  • Raman microspectroscopy offers a label-free, non-invasive, and non-destructive method for potential early cancer detection.

Purpose of the Study:

  • To systematically evaluate statistical analysis workflows for Raman microspectroscopy in colorectal cancer diagnosis.
  • To assess the accuracy, sensitivity, and specificity of different statistical approaches.

Main Methods:

  • Utilized a genotypically identical colon cancer mouse model.
  • Performed a systematic evaluation of various statistical analysis workflows.
  • Employed leave-one-individual-out cross-validation for model assessment.

Main Results:

  • Estimated biological variance from inter-individual Raman spectral variations.
  • Achieved a 95% accuracy in discriminating healthy tissue from adenoma and carcinoma.
  • Demonstrated successful transfer of diagnostic models from tissue to biopsy specimens.

Conclusions:

  • Advanced statistical analysis workflows are essential for reliable Raman microspectroscopy-based colorectal cancer diagnosis.
  • The developed methodology shows high clinical relevance for early detection and diagnosis.
  • The technique's applicability extends from tissue analysis to biopsy specimens.