Improving material decomposition by spectral optimization of photon counting computed tomography

Photon counting detectors in computed tomography facilitate measurements of spectral distributions of detected X-ray quanta in discrete energy bins. Along with the dependency on wavelength and atomic number of the mass attenuation coefficient, this information allows for reconstruction of CT images of different material bases. Decomposition of two materials is considered standard in today’s dual-energy techniques. With photon-counting detectors the decomposition of more than two materials becomes achievable. Efficient detection of CT-typical X-ray spectra is a hard requirement in a clinical environment. This is fulfilled by only a few sensor materials such as CdTe or CdZnTe. In contrast to energy integrating CT-detectors, the pixel dimensions must be reduced to avoid pulse pile-up problems at clinically relevant count rates. However, reducing pixel sizes leads to increased K-escape and charge sharing effects. As a consequence, the correlation between incident and detected X-ray energy is reduced. This degradation is quantified by the detector response function. The goal of this study is to improve the achievable material decomposition by adapting the incident X-ray spectrum with respect to the properties (i.e. the detector response function) of a photon counting detector. A significant improvement of a material decomposition equivalent metric is achievable when using specific materials as X-ray pre-filtration (K-edge filtering) while maintaining the applied patient dose and image quality.