PROJECT SUMMARY
Established methods for early cancer detection rely on simple tissue visualization methods, accompanied by
biopsy and histopathological evaluation, which is primarily based on morphological tissue features. These
approaches are inaccurate or inefficient. Our long-term objective is to transform pre- and early epithelial cancer
diagnosis through the use of functional metabolic, morphological and biomechanical tissue biomarkers that are
extracted non-invasively, automatically and in near real time from fiber-probe-based endogenous two-photon
images. Endogenous two-photon imaging is uniquely capable to provide label-free, functional, high resolution
tissue images. In this proposal, we aim to establish and validate such measurements and biomarkers for the
detection of human cervical pre-cancers using freshly excised tissues. The cervix is an ideal organ for developing
and testing our approach as it relaxes some of the size limitations presented for endoscopic applications,
enabling us to focus on demonstrating the principles of this innovative platform. In addition, we expect that our
proposed methods will enable significant improvements in the specificity of detection of cervical pre-cancers. To
achieve our goals, we will acquire images from fifty freshly excised human cervical tissue specimens from
patients undergoing colposcopy, loop electrosurgical excision procedure, or hysterectomy. We will acquire
endogenous two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) images and
extract signals attributed to NADH, FAD, and collagen. We will process these images using methods we
developed to assess: a) the depth-dependent optical redox ratio, mitochondrial organization and nuclear to
cytoplasmic ratio variations from FAD and NADH TPEF images of the epithelium, and b) the collagen fiber
organization and crosslinking from SHG and TPEF images of the stroma. We will use discriminant analysis to
develop algorithms that include the optimal combination of the extracted optical parameters to distinguish high-
grade from non-high grade cervical lesions, relying on histopathology as the gold standard. Our algorithms will
be entirely automated and fast and will yield a diagnosis based on functional tissue characteristics. Thus, we
expect that results from this study will motivate the development of a probe-based 2P imaging system for clinical
in vivo imaging translation to enable real-time, highly accurate detection of cervical pre-cancerous lesions.
Ultimately, we anticipate that probe-based 2P imaging will transform early cancer diagnosis for a wide range of
tissues, such as the oral cavity, the esophagus, the colon, and the bladder.