Optimization of beam quality for photon-counting spectral computed tomography in head imaging: simulation study

Abstract

Abstract. Head computed tomography (CT) plays an important role in the comprehensive evaluation of acute stroke. Photon-counting spectral detectors, as promising candidates for use in the next generation of x-ray CT systems, allow for assigning more weight to low-energy x-rays that generally contain more contrast information. Most importantly, the spectral information can be utilized to decompose the original set of energy-selective images into several basis function images that are inherently free of beam-hardening artifacts, a potential advantage for further improving the diagnosis accuracy. We are developing a photon-counting spectral detector for CT applications. The purpose of this work is to determine the optimal beam quality for material decomposition in two head imaging cases: nonenhanced imaging and K-edge imaging. A cylindrical brain tissue of 16-cm diameter, coated by a 6-mm-thick bone layer and 2-mm-thick skin layer, was used as a head phantom. The imaging target was a 5-mm-thick blood vessel centered in the head phantom. In K-edge imaging, two contrast agents, iodine and gadolinium, with the same concentration (5 mg∕mL) were studied. Three parameters that affect beam quality were evaluated: kVp settings (50 to 130 kVp), filter materials (Z ¼ 13 to 83), and filter thicknesses [0 to 2 half-value layer (HVL)]. The image qualities resulting from the varying x-ray beams were compared in terms of two figures of merit (FOMs): squared signal-difference-to-noise ratio normalized by brain dose (SDNR 2 ∕BD) and that normalized by skin dose (SDNR 2 ∕SD). For nonenhanced imaging, the results show that the use of the 120-kVp spectrum filtered by 2 HVL copper (Z ¼ 29) provides the best performance in both FOMs. When iodine is used in K-edge imaging, the optimal filter is 2 HVL iodine (Z ¼ 53) and the optimal kVps are 60 kVp in terms of SDNR 2 ∕BD and 75 kVp in terms of SDNR 2 ∕SD. A tradeoff of 65 kVp was proposed to lower the potential risk of skin injuries if a relatively long exposure time is necessarily performed in the iodinated imaging. In the case of gadolinium imaging, both SD and BD can be minimized at 120 kVp filtered with 2 HVL thulium (Z ¼ 69). The results also indicate that with the same concentration and their respective optimal spectrum, the values of SDNR 2 ∕BD and SDNR 2 ∕SD in gadolinium imaging are, respectively, around 3 and 10 times larger than those in iodine imaging. However, since gadolinium is used in much lower concentrations than iodine in the clinic, iodine may be a preferable candidate for K-edge imaging.

Photon-counting CT: Technical Principles and Clinical Prospects

“…tissue with a small cross-section diameter, such as in children (12,54), contrast media with higher atomic number and higher k-edge energies, such as gadolinium or targeted nanoparticles, may be better suited for performing imaging studies in large patients (12,48,49,55).…”

“…Examples include gold and platinum (86,87); xenon, bismuth, lutetium, tungsten, silver, and ytterbium could also be evaluated for use in photon-counting CT (88). Chen et al (55) showed that, with similar molar concentrations of gadolinium and iodine, the signal (in terms of squared signal difference-to-noise ratio normalized by skin dose) with gadolinium is three to 10 times higher than that with iodine. However, the clinically acceptable doses of gadolinium are lower compared with iodine doses.…”

A framework for performance characterization of energy‐resolving photon‐counting detectors

“…Several studies have been published on how to model the frequency‐dependent detective quantum efficiency of photon‐counting detectors, but these studies do not take energy information into account. At the same time, the impact of detector nonidealities on spectral imaging tasks has been studied by several authors . However, these publications only study the zero‐spatial‐frequency performance and do not investigate the frequency‐dependent spectral performance.…”

“…At the same time, the impact of detector nonidealities on spectral imaging tasks has been studied by several authors. [21][22][23][24][25][26][27] However, these publications only study the zero-spatial-frequency performance and do not investigate the frequency-dependent spectral performance. Shikhaliev et al 28 studied the effect of characteristic x rays on the spectrum shape and on the spatial resolution.…”

Generation and analysis of clinically relevant breast imaging x-ray spectra

“…Tabulated or computer-generated x-ray spectra are useful for computer simulations pertaining to modeling of beam shaping filter performance, 1,2 imaging performance modeling, [3][4][5][6] validation of x-ray spectral measurements, 7-9 radiation dose, 10,11 modeling of photon counting spectral/dual-energy imaging systems, 8,[12][13][14] and many other applications. Recently, a tungsten anode spectral model using interpolating cubic splines (TASMICS 15 ) was proposed to update the previous tungsten anode spectral model using interpolating polynomials (TASMIP 16 ).…”