Multi-material decomposition in spectral CT with angular tube voltage modulation

As one of the most advanced CT imaging modalities, spectral CT plays important roles in generating material-specific information and adding vital clinical values for disease diagnosis and therapy. To obtain the spectral CT images, currently, advanced X-ray source or detector assembly is often required, which significantly increases the hardware cost and the patient burden. As a consequence, the accessibility of spectral CT is strongly limited and has not been widely implemented in daily clinics. To solve such difficulty, this work attempts to investigate a new CT data acquisition protocol and spectral CT image reconstruction algorithm. In particular, the X-ray tube voltage is slowly modulated during the gantry rotation. By doing so, spectral information that varies from one projection view to another can be acquired in one single CT scan. Afterwards, a model-based material decomposition algorithm that reconstructs the CT image from the acquired projections is utilized to perform multi-material decomposition. To evaluate the performance of this novel spectral CT imaging approach, a numerical phantom containing iodine and gadolinium solutions is imaged with different kVp modulations, i.e., different number of modulation periods per rotation. Results demonstrate that the proposed spectral CT image reconstruction algorithm can be used to accurately decompose the water, iodine and gadolinium basis images for different tube voltage modulation rates. Moreover, high-quality monochromatic images can be synthesized as well. In conclusion, a low-cost multi-material spectral CT imaging approach is developed based on the slow tube voltage modulation method.