Analysis of trace elements in human hair through X-ray fluorescence spectroscopy for screening of prostate cancer.

Use of hair samples to analyze the trace element concentrations is one of the interesting fields among many researchers. X-ray fluorescence (XRF) is considered as one of the most common methods in studying the concentration of elements in tissues and also crystalline materials, using low energy X-ray. In the present study, we aimed to evaluate the concentration of the trace elements in the scalp hair sample through XRF spectroscopy using signal processing techniques as a screening tool for prostate cancer. Hair samples of 22 men (including 11 healthy and 11 patients) were analyzed. All the sample donors were Iranian men. EDXRF method was used for the measurements. Signals were analyzed, and signal features such as mean, root-mean-square (RMS), variance, and standard deviation, skewness, and energy were investigated. The Man-Whitney U test was used to compare the trace element concentrations. The analysis of variance (ANOVA) test was used to identify which extracted feature could help to identify healthy and patient people. P values ≤ 0.05 were considered statistically significant. Statistical analysis was performed using SPSS 16.0 software. The mean±SD age was 67.8±8.7 years in the patient group and 61.4±6.9 years in the healthy group. There were statistically significant differences in the aluminum (Al, P<0.001), silicon (Si, P=0.006), and phosphorus (P, P=0.028) levels between healthy and patient groups. Skewness and variance were found to be relevant in identifying people with cancer, as signal features. The use of EDXRF is a feasible method to study the concentration of elements in the hair sample, and this technique may be effective in prostate cancer screening. Further study with a large sample size will be required to elucidate the efficacy of the present method in prostate cancer screening.