The use of combined trace element XRF and EDXRD data as a histopathology tool using a multivariate analysis approach in characterizing breast tissue

AbstractThe concentrations of K, Fe, Cu and Zn were measured in 77 breast tissue samples (38 classified as normal and 39 classified as diseased) using x‐ray fluorescence (XRF) techniques. The coherent scattering profiles were also measured using energy‐dispersive x‐ray diffraction (EDXRD), from which the proportions of adipose and fibrous tissue in the samples were estimated. The data from 30 normal samples and 30 diseased samples were used as a training set to construct two calibration models, one using a partial least‐squares (PLS) regression and one using a principal component analysis (PCA) for a soft independent modelling of class analogy (SIMCA) technique. The data from the remaining samples, eight normal and nine diseased, were presented to each model and predictions were made of the tissue characteristics. Three data groups were tested, XRF, EDXRD and a combination of both. The XRF data alone proved to be most unreliable indicator of disease state with both types of analysis. The EDXRD data were an improvement, but with both methods of modelling the ability to predict the tissue type most accurately was by using a combination of the data. Copyright © 2004 John Wiley & Sons, Ltd.

The use of combined trace element XRF and EDXRD data as a histopathology tool using a multivariate analysis approach in characterizing breast tissue Conferences