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Journal of Biomedical Optics

Use of an endoscope-compatible probe to detect colonic dysplasia with Fourier transform infrared spectroscopy
Author(s): Mark A. Mackanos; John T. Hargrove; Rolf Wolters; Christine B. Du; Shai Friedland; Roy M. Soetikno; Christopher H. Contag; May R. Arroyo; James M. Crawford; Thomas D. Wang
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Paper Abstract

Fourier transform infrared (FTIR) spectroscopy is sensitive to the molecular composition of tissue and has the potential to identify premalignant tissue (dysplasia) as an adjunct to endoscopy. We demonstrate collection of mid-infrared absorption spectra with a silver halide (AgCl0.4Br0.6) optical fiber and use spectral preprocessing to identify optimal subranges that classify colonic mucosa as normal, hyperplasia, or dysplasia. We collected spectra (n=83) in the 950 to 1800 cm-1 regime on biopsy specimens obtained from human subjects (n=37). Subtle differences in the magnitude of the absorbance peaks at specific wave numbers were observed. The best double binary algorithm for distinguishing normal-versus-dysplasia and hyperplasia-versus-dysplasia was determined from an exhaustive search of spectral intervals and preprocessing techniques. Partial least squares discriminant analysis was used to classify the spectra using a leave-one-subject-out cross-validation strategy. The results were compared with histology reviewed independently by two gastrointestinal pathologists. The optimal thresholds identified resulted in an overall sensitivity, specificity, accuracy, and positive predictive value of 96%, 92%, 93%, and 82%, respectively. These results indicated that mid-infrared absorption spectra collected remotely with an optical fiber can be used to identify colonic dysplasia with high accuracy, suggesting that continued development of this technique for the early detection of cancer is promising.

Paper Details

Date Published: 1 July 2009
PDF: 8 pages
J. Biomed. Opt. 14(4) 044006 doi: 10.1117/1.3174387
Published in: Journal of Biomedical Optics Volume 14, Issue 4
Show Author Affiliations
Mark A. Mackanos, Stanford Univ. (United States)
John T. Hargrove, BAE Systems (United States)
Rolf Wolters, STI Medical Systems (United States)
Christine B. Du, Stanford Univ. School of Medicine (United States)
Shai Friedland, Stanford Univ. School of Medicine (United States)
Roy M. Soetikno, Veterans Affairs Palo Alto Health Care System (United States)
Christopher H. Contag, Stanford Univ. School of Medicine (United States)
May R. Arroyo, Univ. of Florida College of Medicine (United States)
James M. Crawford, Univ. of Florida College of Medicine (United States)
Thomas D. Wang, Univ. of Michigan (United States)

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