We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.

La presente invention concerne des modules optiques unitaires qui integrent diverses fonctions de gestion de la lumiere afin d'effectuer la spectroscopie optique, telle que la spectroscopie Raman. L'invention concerne egalement des systemes de spectroscopie optique qui comprennent un ou plusieurs de ces modules optiques unitaires. L'invention concerne egalement des procedes d'utilisation des modules et des systemes.

Using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy, we have developed an algorithm that successfully classifies normal breast tissue, fibrocystic change, fibroadenoma, and infiltrating ductal carcinoma in terms of physically meaningful parameters. We acquire 202 spectra from 104 sites in freshly excised breast biopsies from 17 patients within 30 min of surgical excision. The broadband diffuse reflectance and fluorescence spectra are collected via a portable clinical spectrometer and specially designed optical fiber probe. The diffuse reflectance spectra are fit using modified diffusion theory to extract absorption and scattering tissue parameters. Intrinsic fluorescence spectra are extracted from the combined fluorescence and diffuse reflectance spectra and analyzed using multivariate curve resolution. Spectroscopy results are compared to pathology diagnoses, and diagnostic algorithms are developed based on parameters obtained via logistic regression with cross-validation. The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy (total efficiency) of the algorithm are 100, 96, 69, 100, and 91%, respectively. All invasive breast cancer specimens are correctly diagnosed. The combination of diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy yields promising results for discrimination of breast cancer from benign breast lesions and warrants a prospective clinical study.

Currently breast cancer diagnosis is made clinically through triple assessment: annual clinical breast examination, x-ray mammography or breast ultrasound imaging, and biopsy. The majority of women with suspicious breast lesions undergo either stereotactic (needle) or surgical (excisional) biopsy. Due to a high incidence of "false positives" at clinical breast diagnosis and "false negatives" at surgery, a large number of women undergo unnecessary and costly breast surgery. We describe our program of development of techniques and instrumentation for clinical application of NIR Raman spectroscopy for improved breast cancer diagnosis.

Elastic scattering spectroscopy (ESS) has shown to be a useful technology for determining morphological changes associated with the progression of intra-epithelial neoplasia; however, the origins of differences seen in ESS spectra with the progression of disease is not well understood. We use a two-layer tissue model to study the effects of nuclear size and density on ESS spectra collected via an optical fiber probe. The presence of various sizes and densities of epithelial nuclei distort the diffuse reflectance spectrum; however, information regarding the nuclear size and density is preserved.