Paper
27 March 2002 In vivo detection of cervical dysplasia with near-infrared Raman spectroscopy
Amy Robichaux, Chad A. Lieber, Heidi Shappell M.D., Beth Huff, Howard Jones III, Anita Mahadevan-Jansen
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Abstract
Raman spectroscopy has been shown to have the potential for providing differential diagnosis in the cervix with high sensitivity and specificity in previous in vitro and in vivo studies. A clinical study was designed at Vanderbilt University Medical Center to further evaluate the potential of near IR Raman spectroscopy for in vivo detection of squamous intra-epithelial neoplasia, a pre-cursor to cervical cancer, in a clinical setting. In this pilot in vivo clinical study, using a portable system, Raman spectra are collected using clinically feasible integration times during colposcopic evaluation. Multiple Raman spectra were acquired form colposcopically normal and abnormal sites prior to excision of tissue from patients with known abnormalities of the cervix. Measured Raman spectra were processed for nosie and background fluorescence using novel signal processing techniques. The resulting spectra were correlated with the corresponding histological diagnosis to determine empirical differences in spectra between different diagnostic categories. Using histology as the gold standard, multivariate statistical techniques were also used to develop discrimination algorithms with the hopes of developing this technique into a real time, non-invasive diagnostic tool.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amy Robichaux, Chad A. Lieber, Heidi Shappell M.D., Beth Huff, Howard Jones III, and Anita Mahadevan-Jansen "In vivo detection of cervical dysplasia with near-infrared Raman spectroscopy", Proc. SPIE 4614, Biomedical Vibrational Spectroscopy II, (27 March 2002); https://doi.org/10.1117/12.460793
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Cited by 4 scholarly publications.
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KEYWORDS
Raman spectroscopy

Tissues

Pathology

In vivo imaging

Cervix

Algorithm development

Principal component analysis

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