Fushen Xu

TL;DR: The Monte Carlo-based inverse model of diffuse reflectance described in part I of this pair of companion papers was applied to a set of 17 malignant and 24 normal-benign ex vivo human breast tissue samples and produced a cross-validated sensitivity and specificity of 82% and 92%, respectively.

TL;DR: The fluorescence excitation-emission wavelengths identified as being diagnostic from the PCA-SVM algorithm suggest that the important fluorophores for breast cancer diagnosis are most likely tryptophan, NAD(P)H and flavoproteins.

TL;DR: In this paper, a statistically significant difference would be demonstrated between benign and malignant breast tissues on the basis of their unique fluorescence and reflectance properties, which are due to endogenous fluorophores.

TL;DR: The results show that using the integrated fluorescence intensities recorded at a single excitation wavelength at all three illumination-collection separations can discriminate malignant from nonmalignant breast tissues with similar classification accuracy to that using spectral data measured at several excitation wavelengths with a single illumination- collection separation.

TL;DR: A statistically significant difference was demonstrated in the diffuse reflectance and fluorescence emission spectra of benign and malignant breast tissue, which could be exploited in the development of adjuncts to diagnostic and surgical procedures.