Energy-resolved computed tomography: first experimental results

First experimental results with energy-resolved computed tomography (CT) are reported. The contrast-to-noise ratio (CNR) in CT has been improved with x-ray energy weighting for the first time. Further, x-ray energy weighting improved the CNR in material decomposition CT when applied to CT projections prior to dual-energy subtraction. The existing CT systems use an energy (charge) integrating x-ray detector that provides a signal proportional to the energy of the x-ray photon. Thus, the x-ray photons with lower energies are scored less than those with higher energies. This underestimates contribution of lower energy photons that would provide higher contrast. The highest CNR can be achieved if the x-ray photons are scored by a factor that would increase as the x-ray energy decreases. This could be performed by detecting each x-ray photon separately and measuring its energy. The energy selective CT data could then be saved, and any weighting factor could be applied digitally to a detected x-ray photon. The CT system includes a photon counting detector with linear arrays of pixels made from cadmium zinc telluride (CZT) semiconductor. A cylindrical phantom with 10.2 cm diameter made from tissue-equivalent material was used for CT imaging. The phantom included contrast elements representing calcifications, iodine, adipose and glandular tissue. The x-ray tube voltage was 120 kVp. The energy selective CT data were acquired, and used to generate energy-weighted and material-selective CT images. The energy-weighted and material decomposition CT images were generated using a single CT scan at a fixed x-ray tube voltage. For material decomposition the x-ray spectrum was digitally spilt into low- and high-energy parts and dual-energy subtraction was applied. The x-ray energy weighting resulted in CNR improvement of calcifications and iodine by a factor of 1.40 and 1.63, respectively, as compared to conventional charge integrating CT. The x-ray energy weighting was also applied to low- and high-energy CT projections used for material decomposition. This improved the CNR in images of decomposed calcification and iodine by a factor of 1.57 and 1.46, respectively, as compared to conventional charge integrating CT. Some limitations were observed due to hole trapping in CZT and charge sharing between the detector pixels. First experimental results demonstrate that energy-resolved CT is coming close to its practical applications. Although hole trapping and charge sharing in CZT deteriorates x-ray spectrum and limits CNR improvement with energy weighting and detector count rate, this problem has a feasible solution, which is discussed in this paper and is a matter of ongoing research.