Combining near-infrared-excited autofluorescence and Raman spectroscopy improves in vivo diagnosis of gastric cancer

Biosens Bioelectron. 2011 Jun 15;26(10):4104-10. doi: 10.1016/j.bios.2011.04.005. Epub 2011 Apr 12.

Abstract

This study aims to evaluate the diagnostic utility of the combined near-infrared (NIR) autofluorescence (AF) and Raman spectroscopy for improving in vivo detection of gastric cancer at clinical gastroscopy. A rapid Raman endoscopic technique was employed for in vivo spectroscopic measurements of normal (n=1098) and cancer (n=140) gastric tissues from 81 gastric patients. The composite NIR AF and Raman spectra in the range of 800-1800 cm(-1) were analyzed using principal component analysis (PCA) and linear discriminant (LDA) to extract diagnostic information associated with distinctive spectroscopic processes of gastric malignancies. High quality in vivo composite NIR AF and Raman spectra can routinely be acquired from the gastric within 0.5s. The integrated intensity over the range of 800-1800 cm(-1) established the diagnostic implications (p=1.6E-14) of the change of NIR AF intensity associated with neoplastic transformation. PCA-LDA diagnostic modeling on the in vivo tissue NIR AF and Raman spectra acquired yielded a diagnostic accuracy of 92.2% (sensitivity of 97.9% and specificity of 91.5%) for identifying gastric cancer from normal tissue. The integration area under the receiver operating characteristic (ROC) curve using the combined NIR AF and Raman spectroscopy was 0.985, which is superior to either the Raman spectroscopy or NIR AF spectroscopy alone. This work demonstrates that the complementary Raman and NIR AF spectroscopy techniques can be integrated together for improving the in vivo diagnosis and detection of gastric cancer at endoscopy.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biosensing Techniques / instrumentation
  • Biosensing Techniques / methods*
  • Female
  • Gastroscopy / instrumentation
  • Gastroscopy / methods
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Principal Component Analysis
  • ROC Curve
  • Spectrometry, Fluorescence / instrumentation
  • Spectrometry, Fluorescence / methods
  • Spectroscopy, Near-Infrared / instrumentation
  • Spectroscopy, Near-Infrared / methods*
  • Spectrum Analysis, Raman / instrumentation
  • Spectrum Analysis, Raman / methods*
  • Stomach Neoplasms / diagnosis*
  • Stomach Neoplasms / pathology