Stationary spectral encoding for multi-energy CT with energy-integrated detectors

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Multi-material decomposition using spectral CT provides quantitative information on tissue composition. This information is beneficial for many clinical applications including CT imaging of the cardiac vasculature and the abdomen. Clinical implementation for spectral CT has taken different paths, such as using dual-source, fast kVp switching, and photon counting or sandwich detectors; each of these solutions has its own strengths and weaknesses. In particular, the limited spectral diversity of existing solutions limits the number of differentiated materials, leaving many clinical questions unanswered. The unmet clinical need for a satisfying spectral CT solution that is capable of multi-material decomposition motivates this proposal. We propose a practical solution to spectral CT using stationary spectral encoding. This technique is simple enough to be implemented at low engineering cost on all energy-integrating CT scanners. The key element in our solution is a ring- shaped, stationary spectral encoder that can be attached to the CT gantry opening. The spectral encoder is made of thin materials of spectrally diverse properties arranged around its perimeter. As the x-ray tube and the detector rotate around the patient, the emitted rays are continuously modulated by the encoder materials, thereby providing essentially endless possibilities in terms of spectral diversity. Multi-material decomposition is accomplished by advanced material decomposition algorithms that reconstructs the material maps directly from the spectral encoder CT data. The goal of this proposal is to develop and optimize the spectral encoder towards future physical construction and clinical evaluation studies. In Aim 1 we will build a computational platform to generate the spectral encoder CT data, and develop material decomposition algorithms. In Aim 2 we will optimize the stationary spectral encoder design parameters for the best possible material decomposition performance. These aims collectively provide a practical pathway for clinical translation: the results from these aims will guide prototype development, which then will be followed by real data acquisition with physical phantoms and patient studies. The proposed spectral encoder can be used for all CT scanners and will make multi-material decomposition widely available.