SpekPy is a free toolkit for modelling x-ray tube spectra with the Python programming language. In this article, the advances in version 2.0 (v2) of the software are described, including additional target materials and more accurate modelling of the heel effect. Use of the toolkit is also demonstrated.Methods: The predictions of SpekPy are illustrated in comparison to experimentally determined spectra: three radiation quality reference (RQR) series tungsten spectra and one mammography spectrum with a molybdenum target. The capability of the software to correctly model changes in tube output with tube potential is also assessed, using the example of a GE Revolution™ CT scanner (GE Healthcare, Waukesha, WI, USA) and specifications in the system's Technical Reference Manual. Further, we note that there are several physics models available in SpekPy. These are compared on and off the central axis, to illustrate the differences.Results: SpekPy agrees closely with the experimental spectra over a wide range of tube potentials, both visually and in terms of first and second half-value-layers (within 2% here). The CT scanner spectrum output (normalized to 120 kV tube potential) agreed within 4% over the range of 70 to 140 kV. The default physics model (casim) is adequate in most situations. The advanced option (kqp) should be used if high accuracy is desired for modelling the anode heel-effect, as it it fully includes the effects of bremsstrahlung anisotropy.Conclusions: SpekPy v2 can reliably predict on-and off-axis spectra for tungsten and molybdenum targets. SpekPy's open-source MIT license allows users the freedom to incorporate this powerful toolkit into their own projects.
The fluence rate on a CT detector reaches 3 ⋅ 10(8) - 6 ⋅ 10(8) mm(-2) s(-1) in standard imaging protocols, with the highest rates occurring for ECG gated chest and miscentered head scans. These results will be useful to developers of CT detectors, in particular photon counting detectors.
Objective: The aim of this study was to make a comprehensive evaluation of how variable scan settings can affect the performance of automatic tube current modulation (ATCM) in recent CT scanners from the four major manufacturers. Methods: A phantom was designed and manufactured for the purpose of evaluating ATCM. The phantom was scanned with four categories of systematically varied settings (scan projection radiograph, technique and reconstruction parameters and phantom miscentring). The performance of ATCM, in terms of applied tube current and noise uniformity, for the scans with varied settings was compared with a reference scan using subjective and quantitative approaches. Results: The ATCM implemented by each manufacturer is based on different principles and any affect to the performance of the ATCM, when varying scan settings, will manifest differently among the vendors. The results are summarized in four tables corresponding to the categories of varied settings. Conclusion: The developed phantom proved useful for evaluating the ATCM. It is important to understand how different implementations (vendor specific) of ATCM perform in order to make informed decisions about the selection of scan settings when designing protocols. The resulting tables can serve as a reference for understanding the different implementations of ATCM and highlight settings that should be taken into consideration when adjusting an imaging protocol.
Advances in knowledge:The results from this work can serve as a reference for how changes in geometry or scan settings can affect the performance of ATCM, in terms of tube current and noise.
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