Multi-contrast K-edge imaging on a bench-top photon-counting CT system: acquisition parameter study

Abstract

Purpose. Photon-counting computed tomography (PCCT) shows promise for medical imaging in regards to material separation and imaging of multiple contrast agents. However, many PCCT setups are under development and are not optimized for specific contrast agents or use cases. Here, we demonstrate how experimental system parameters may be varied in order to enhance performance and we propose a set of recommendations to achieve this based on contrast agent.Approach. A table-top PCCT system with a cadmium zinc telluride (CZT) detector capable of separating six energy bins was used to image multiple contrast agents in a small phantom. The contrast agents were separated and the concentration was quantified using K-edge subtraction. To increase system performance, we investigated three parameters: beam filter type and thickness, projection acquisition time, and energy bin width. The results from the parameters were compared based on PCCT signal and contrast to noise ratio (CNR) or noise in K-edge images. The concentrations of the contrast agents were quantified in K-edge images and compared to known concentrations.Results. The bench-top PCCT system was able to successfully quantify the contrast agents through K-edge subtraction. Decreasing projection acquisition time showed a decrease in K-edge CNR. However, it did not scale as the square root of time. Filter type and bin width demonstrated a dependence on the specific contrast agent.Conclusions. The presented bench-top system demonstrated the ability to separate contrast agents using K-edge subtraction and accurately determine contrast concentration in K-edge images. Specific parameters for future use will be chosen based on contrast agent.

A detective quantum efficiency for spectroscopic X‐ray imaging detectors

“…This system has been described by Richtsmeier et al 16 . and Dunning et al 16,17 . and uses an MXR 160/22 X‐ray tube from Comet Technologies (San Jose, CA).…”

“…The CdZnTe detector is from Redlen Technologies and is incorporated into a bench-top X-ray imaging system at The University of Victoria (Victoria, Canada). This system has been described by Richtsmeier et al 16 and Dunning et al 16,17 and uses an MXR 160/22 X-ray tube from Comet Technologies (San Jose, CA). The source-to-detector distance used for all the experiments in this work was 84.5 cm.…”

“…We performed a simulation study to validate the assumptions that led to Equations ( 12), (16), and ( 23), and to demonstrate how the spectral Swank noise factor depends on the amount of CS, electronic noise and the number of energy bins.…”

“…PCDs and SXDs offer a number of potential advantages over EIDs, including rejection of electronic noise, singleshot material decomposition, and single-shot pseudomonoenergetic imaging. [12][13][14][15][16][17][18] However, the stochastic nature of X-ray interaction and detection impairs the imaging performance of PCDs and SXDs. For example, Faby et al 19 showed that realistic SXDs will increase noise by greater than 50% relative to ideal systems in CT applications, resulting in image quality similar to or worse than dual-energy approaches that use EIDs.…”

Normalization of the task-dependent detective quantum efficiency of spectroscopic x-ray imaging detectors

“…Spectroscopic x-ray imaging detectors (SXDs) perform crude estimates of the shape of diagnostic x-ray spectra, 1-3 enabling single-shot basis-material decomposition, pseudo monoenergetic imaging, and optimal energy weighting. [4][5][6][7][8][9][10][11][12] An active research area is the development of frameworks for evaluating the performance of SXDs. [13][14][15][16][17][18] The challenge is two-fold: (1) SXDs record multiple images for each exposure and these images are correlated with each other, and (2) the spectral data recorded by SXDs can be used for a number of different tasks, for example energy weighting, basis-material decomposition, or pseudo-monoenergetic imaging.…”