Assessment of ex vivo and in vivo near-infrared Raman spectroscopy for the classification of dysplasia within Barrett's esophagus

Martin G. Shim, Louis Michel Wong Kee Song, Norman Marcon, Shirley Hassaram, Brian C. Wilson

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


The purpose of this study is to assess if Raman spectroscopy can classify dysplastic (DYS) and early neoplastic lesions within Barrett's esophagus (BE). In BE, the normal squamous epithelium (SQ) lining the esophagus is replaced by columnar epithelium (intestinal metaplasia). These patients have a 30-125 fold excess risk of developing adenocarcinoma. Raman spectroscopy may provide diagnostic information so that tissue transformation may be detected at an early stage (dysplasia) and improve the patient's prognosis. Ex vivo measurements were carried out initially on biopsy samples obtained from BE patients undergoing routine endoscopic and biopsy surveillance. Differences were noted in the spectral regions 1200-1350 cm-1 and 1550-1640 cm-1 when comparing different histopathologic grades. Principal component analysis of the spectra led to good separation between SE and BE but not between BE and DYS. Improved results were obtained using a probabilistic artificial neural network, with a resultant sensitivity and specificity of 77% and 93% in differentiating SQ/BE from dysplasia, respectively. Recently, in vivo endoscopic measurements have been performed. These preliminary results indicate that RS in combination with endoscopy may be a useful technique to screen BE patients for dysplastic/early neoplastic lesions.

Original languageEnglish (US)
Pages (from-to)114-119
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2000
EventBiomedical Spectroscopy: Vibrational Spectroscopy and other Novel Techniques - San Jose, CA, USA
Duration: Jan 26 2000Jan 27 2000

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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