The Identification and Differentiation of Secondary Colorectal Cancer in Human Liver Tissue Using X-ray Fluorescence, Coherent Scatter Spectroscopy, and Multivariate Analysis

Abstract

Secondary colorectal liver cancer is the most widespread malignancy in patients with colorectal cancer. The aim of this study is to identify and differentiate between normal liver tissue and malignant secondary colorectal liver cancer tissue using X-ray scattering and X-ray fluorescence spectroscopy to investigate the best combination of data that can be used to enable classification of these two tissue types. X-ray fluorescence (XRF) and coherent scatter data were collected for 24 normal and 24 tumor matched pair tissue samples. The levels of 12 elements (P, S, K, Ca, Cr, Fe, Cu, Zn, As, Se, Br, and Rb) were measured in all samples. When comparisons were made between normal and tumor tissues, statistically significant differences were determined for K ( p = 0.046), Ca ( p = 0.040), Cr ( p = 0.011), Fe, Cu, Zn, Br, and Rb ( p < 0.01). However, for P, S, As, and Se, no statistically significant differences were found ( p > 0.05). For the coherent scatter spectra collected, three peaks due to adipose, fibrous content, and water content of tissue were observed. The amplitude, full width half-maximum, and area under both fibrous content and water content peaks were found to be significantly higher in secondary colorectal liver tumors compared with surrounding normal liver tissue ( p < 0.05). However, no significant differences were found for the adipose peak parameters ( p > 0.05). Soft independent modeling of class analogy was performed using the XRF, coherent scatter, and elemental ratio data separately, and the accuracy of the classification of 20 unknown samples was found to be 50, 30, and 80%, respectively. Further analysis has shown that using a combination of the XRF and coherent scatter data in a single combined model gave improved normal and tumor liver tissue classification, with an accuracy that was found to be 85%.