| Abstrakt: |
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 vitrotissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivoclinical data set that closely mimics the in vivoenvironment. 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 vitrocalibration and ex vivoprospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided. [ABSTRACT FROM AUTHOR] |
