Sensitivity of Photon-Counting Based ${\rm K}$-Edge Imaging in X-ray Computed Tomography

Abstract

The feasibility of K-edge imaging using energy-resolved, photon-counting transmission measurements in X-ray computed tomography (CT) has been demonstrated by simulations and experiments. The method is based on probing the discontinuities of the attenuation coefficient of heavy elements above and below the K-edge energy by using energy-sensitive, photon counting X-ray detectors. In this paper, we investigate the dependence of the sensitivity of K-edge imaging on the atomic number Z of the contrast material, on the object diameter D , on the spectral response of the X-ray detector and on the X-ray tube voltage. We assume a photon-counting detector equipped with six adjustable energy thresholds. Physical effects leading to a degradation of the energy resolution of the detector are taken into account using the concept of a spectral response function R(E,U) for which we assume four different models. As a validation of our analytical considerations and in order to investigate the influence of elliptically shaped phantoms, we provide CT simulations of an anthropomorphic Forbild-Abdomen phantom containing a gold-contrast agent. The dependence on the values of the energy thresholds is taken into account by optimizing the achievable signal-to-noise ratios (SNR) with respect to the threshold values. We find that for a given X-ray spectrum and object size the SNR in the heavy element's basis material image peaks for a certain atomic number Z. The dependence of the SNR in the high- Z basis-material image on the object diameter is the natural, exponential decrease with particularly deteriorating effects in the case where the attenuation from the object itself causes a total signal loss below the K-edge. The influence of the energy-response of the detector is very important. We observed that the optimal SNR values obtained with an ideal detector and with a CdTe pixel detector whose response, showing significant tailing, has been determined at a synchrotron differ by factors of about two to three. The potentially very important impact of scattered X-ray radiation and pulse pile-up occurring at high photon rates on the sensitivity of the technique is qualitatively discussed.

Vision 20/20: Single photon counting x‐ray detectors in medical imaging

“…Compensation of PCD degradation factors can be achieved by incorporating a PCD model as part of the forward imaging process, and iteratively estimating either the imaged object or the line integrals using a maximum likelihood approach. 6,[73][74][75] This can be formed as a well-posed problem, and the method is depicted in Fig. 8.…”

“…The stochastic nature of the count rate-independent spectral distortions leads to a probability distribution of the recorded energy E given the true photon energy E 0 , which can be described as a spectral response function SRF(E, E 0 ). 6,73 The function holds well as long as the properties of PCDs are FIG. 9.…”

“…One simulation study showed that with optimal energy weighting, the contrast-to-noise ratios of PCD-CT images were better than those of EID-CT images by 15%-57% depending on the materials. 98 When the effect of count rate-independent spectral distortion was incorporated, contrast-to-noise ratios of PCD-CT images were improved from EID-CT by 1.4%-11.6% in one study 73 and by 40%-63% in another study. 74 An experimental study using PCD-CT and clinical dual-energy CT, contrast-to-noise ratio of oil and water improved by 57%-96%.…”

Photon counting spectral CT component analysis of coronary artery atherosclerotic plaque samples

“…The choice in the number of energy bins was made based on previous studies: it is higher than the absolute minimum number of three bins that would allow successful differentiation between the three attenuation components, and it takes into account the fact that increasing N to higher and higher values results in an increase in the detector's complexity and cost with no considerable improvement in signal-to-noise ratio (SNR) in the K-edge image. 13,14 To fit with iodine K-edge (33.2 keV; Figure 2), the thresholds were set to 25, 33, 39, 44, 49 and 55 keV, respectively. The measurement of the emission spectrum of the X-ray tube Mass attenuation coefficients for PA decrease when X-ray energy increases, whereas CS remains nearly constant.…”

Feasibility of spectral CT imaging for the detection of liver lesions with gold-based contrast agents – A simulation study

“…One of the first K-edge imaging simulations was applied to an atherosclerotic coronary vessel phantom with an arterial gadolinium concentration of 31.76 mg/mL (approximately 3.2 wt% gadolinium) [3]. Roessl et al simulated spectral CT in a Forbild phantom resembling a (strongly simplified) axial abdominal slice with a central circular gold-containing insert (diameter: 10 mm, concentration: 0.2 mol/L, i. e., about 4 wt%) [25]. Baturin et al applied the K-edge decomposition algorithm to a small (diameter: 30 mm) calibration phantom containing 1.4e3.4 mg/L gold (approximately 0.14e0.34 wt%) and to a realistic chest phantom with a single point of interest (diameter: 2 mm) enhanced by a water-based iodineegoldecalcium mixture (concentration not specified), in which the gold could be clearly detected [26].…”