Uncertainty estimation and statistical comparative methodology for mammography x-ray energy spectra

Numerical models are an alternative to measurements of x-ray energy spectra when validated by comparative methods that assess the similarity of experimental and calculated spectra. In this work, we compared x-ray energy spectra using several methodologies and determined the methodology with highest statistical power among them. Experiments and Monte Carlo (MC) simulations were used to generate a set of 65 experimental and simulated x-ray mammography spectra pairs typically used in mammography applications. They were generated using Tungsten and Molybdenum targets and Molybdenum and Rhodium filters. The x-ray beams were transmitted through breast tissue equivalent material (bTEM) plates with different glandularities and thicknesses, and the transmitted beam was detected using solid-state x-ray spectrometry with a Cadmium Telluride (CdTe) diode. The MC simulations used the PENELOPE code. Additional uncertainties, beyond that from counting, were propagated using the MC method. Quantitative comparative methods based on the [Formula: see text] statistics, the first and second half-value layers, the mean energy, the effective energy, and the non-parametric u-test were applied and their specificity (true negative rate) was assessed. The polyenergetic normalized glandular dose (DgNp) to a 6 cm breast of 50/50 glandularity was derived from the spectra. In this work, the [Formula: see text] statistics attained the highest score; therefore, it is the most indicated metric for the x-ray energy spectra comparative evaluations. The contribution of the additional uncertainties was important, being responsible for up to 98% of the spectra total uncertainty and shifting the mean of the evaluated [Formula: see text] to 1.2(1), compatible with its expected value. The use of non-parametric test is discouraged by our results, since it failed to distinguish spectra pairs that resulted in up to 72% discrepant DgNp.