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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 conduct the four following
specific sub-projects:
- collect spectral data of cellular and
extra-cellular constituents of normal and
transformed ovarian tissue;
- characterize optical tissue signals in
vivo and obtain biopsies from the same interrogated
tissue volume;
- use these biopsies to study etiology of
the optical signals in an in vitro tissue
culture model; and
- 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.
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