Assessment of different computational models for generation of x‐ray spectra in diagnostic radiology and mammography

Abstract

Different computational methods based on empirical or semi-empirical models and sophisticated Monte Carlo calculations have been proposed for prediction of x-ray spectra both in diagnostic radiology and mammography. In this work, the x-ray spectra predicted by various computational models used in the diagnostic radiology and mammography energy range have been assessed by comparison with measured spectra and their effect on the calculation of absorbed dose and effective dose (ED) imparted to the adult ORNL hermaphroditic phantom quantified. This includes empirical models (TASMIP and MASMIP), semi-empirical models (X-rayb&m, X-raytbc, XCOMP, IPEM, Tucker et al., and Blough et al.), and Monte Carlo modeling (EGS4, ITS3.0, and MCNP4C). As part of the comparative assessment, the K x-ray yield, transmission curves, and half value layers (HVLs) have been calculated for the spectra generated with all computational models at different tube voltages. The measured x-ray spectra agreed well with the generated spectra when using X-raytbc and IPEM in diagnostic radiology and mammography energy ranges, respectively. Despite the systematic differences between the simulated and reference spectra for some models, the student's t-test statistical analysis showed there is no statistically significant difference between measured and generated spectra for all computational models investigated in this study. The MCNP4C-based Monte Carlo calculations showed there is no discernable discrepancy in the calculation of absorbed dose and ED in the adult ORNL hermaphroditic phantom when using different computational models for generating the x-ray spectra. Nevertheless, given the limited flexibility of the empirical and semi-empirical models, the spectra obtained through Monte Carlo modeling offer several advantages by providing detailed information about the interactions in the target and filters, which is relevant for the design of new target and filter combinations and optimization of radiological imaging protocols.

Evaluation of characteristic-to-total spectrum ratio: Comparison between experimental and a semi-empirical model

“…Previous works attempt for the criteria of characteristic-to-total spectrum area for validating the amplitude of the characteristic peaks of the X-ray spectrum (Archer and Wagner, 1988;Ay et al, 2005;Bhat et al, 1998). Characteristic-to-total spectrum ratio, R, was adopted to evaluate the fractional contribution of the characteristic photons in the total spectrum.…”

Current status and new horizons in Monte Carlo simulation of X-ray CT scanners

“…The impact of target angle on off-axis spectra, which is an important factor for covering the whole detector aperture by the X-ray beam in CT particularly for multi-slice systems, was also investigated. Although different analytical computational models with varying degrees of accuracy can be used for generation of X-ray spectra [38], MC simulations offer many additional advantages including the possibility of optimizing tube design and developing new target/filter combinations to improve image quality and reduce patient dose. The optimization of geometrical magnification in X-ray CT, which depends on the source to detector and iso-center distances, has been investigated using theoretical calculations [3,9].…”

"Espectrometria de raios X em mamografia aplicada à proteção radiológica"

“…A comparação realizada entre os resultados obtidos a partir de medições efetuadas com a câmara de ionização e com o detector CZTé valida para qualquer sistema de raios X pelo fato da câmara utilizada (Radcal 10 x 5 -6M) apresentar uma resposta aproximadamente constante com a energia do feixe de raios X [73]. Por outro lado, trabalhos recentes na literatura mostram que os modelos semi-empíricos de TBC [13] e TBW [41] produzem espectros de raios X que representam a forma do espectro experimental com boa precisão [27,74]. Os espectros teóricos devem ser simulados de forma a apresentar o mesmo valor de camada semi-redutora dos experimentais [27].…”