The objective of this work is to determine the etiology of endogenous optical signals from ovarian tissue. This research will serve as the basis for development of a minimally invasive method for the diagnosis of pre-malignant changes as well as early ovarian cancer using fluorescence and reflectance spectroscopy.

The hypothesis that drives the proposed research is that developing a series of experimental and mathematical models will allow us to explain the differences in optical signatures of normal ovaries, premalignant changes, and malignant transformations. By understanding this contrast, we will be able to derive effective early diagnostic methods for ovarian cancer and improve early detection of this highly fatal disease.

Diagnostic techniques will be most useful in women at high risk of developing ovarian cancer to identify those women who need to undergo an oophorectomy. Once a serum based screening test is available for the low risk population it will be of utmost importance to perform a second lock diagnostic procedure because even excellent tests will generate a large number of false positive results.

We propose the four following specific sub-projects:
1) collect spectral data of cellular and extra-cellular constituents of normal and transformed ovarian tissue;
2) characterize optical tissue signals in vivo and obtain biopsies from the same interrogated tissue volume;
3) use these biopsies to study etiology of the optical signals in an in vitro tissue culture model; and
4) synthesize mathematical models of remitted optical signals based on all collected data to explain the biophysical sources of spectral variations and to develop novel diagnostic metrics.

The projects will advance present knowledge of the development of cancer, a health problem which, notwithstanding significant medical advances over the past fifty years, remains the second leading cause of death in the United States as we enter the new millennium. The proposed project will take an important step toward improving the overall survival in ovarian cancer, a statistic that has not changed in the last 50 years.

Figure: Overview of the proposed studies and their exchange of information. Aim (1) gathering published data and combining with data of cells suspensions and tissue phantoms, Aim (2) includes an in-vivo study to gather spectroscopic data, Aim (3) addresses the development of an in-vitro tissue model and the mapping of optically active molecules. Aim (4) combines all data into a biophysical model resulting in effective algorithms for ovarian cancer screening.