Paper
8 May 2000 Diagnostic tool for early detection of ovarian cancers using Raman spectroscopy
Chad A. Lieber, Kelly Molpus, Kevin Brader, Anita Mahadevan-Jansen
Author Affiliations +
Abstract
With an overall survival rate of about 35 percent, ovarian cancer claims more than 13,000 women in the US each year. It is estimated that roughly 1 in 70 women will develop ovarian cancer. Current screening techniques are challenged due to cost-effectiveness, variable false-positive results, and the asymptomatic nature of the early stages of ovarian cancer. The predominant screening method for ovarian cancers is transvaginal sonography (TVS). TVS is fairly accomplished at ovarian cancer detection, however it is inefficient in distinguishing between benign and malignant masses. Accurate diagnosis of the ovarian tumor relies on exploratory laparotomy, thus increasing the cost and hazard of false- positive screening methods. Raman spectroscopy has been sued successfully as a diagnostic tool in several organ systems in vitro. These studies have shown that Raman spectroscopy can be used to provide diagnosis of subtle changes in tissue pathology with high accuracy. Based on this success, we have developed a Raman spectroscopic system for application in the ovary. Using this system, the Raman signatures of normal and various types of non-normal human ovarian tissues were characterized in vitro. Raman spectra are being analyzed, and empirical as well as multivariate discriminatory algorithms developed. Based on the result of this study, a strategy for in vivo trials will be planned.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chad A. Lieber, Kelly Molpus, Kevin Brader, and Anita Mahadevan-Jansen "Diagnostic tool for early detection of ovarian cancers using Raman spectroscopy", Proc. SPIE 3918, Biomedical Spectroscopy: Vibrational Spectroscopy and Other Novel Techniques, (8 May 2000); https://doi.org/10.1117/12.384934
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Cited by 8 scholarly publications.
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KEYWORDS
Raman spectroscopy

Tissues

Ovarian cancer

Diagnostics

Luminescence

Algorithm development

Tumors

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