This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The excellent results of our studies on fresh-frozen tissue demonstrated that Raman spectroscopy can classify breast lesions with high accuracy. The study thus supported moving the technique to a clinical setting for further testing of its efficacy in breast cancer diagnosis. As a result, we pursued clinical study. We collected data in the University Hospitals of Cleveland pathology suite, typically within half an hour of excision during partial and whole mastectomy. The main goals of this study are to validate our in vitro diagnostic algorithm on a large data set which closely mimics an in vivo environment and to elucidate differences between the Raman spectra of fresh-frozen and fresh breast tissues. Additional goals include expanding our diagnostic algorithm to include pathologies not seen in our ex vivo laboratory data and targeting microcalcifications.
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