Quantitative Cone-Beam CT Imaging in Radiotherapy: Parallel Computation and Comprehensive Evaluation on the TrueBeam System

Cone-beam CT (CBCT) imaging is used in the patient setup on the advance image-guided radiation therapy. However, the scatter contamination causes spatial non-uniformity, the error of the CT number, and image contrast loss, which is considered as one of the fundamental limitations for CBCT application. In this paper, we use both scatter correction and noise suppression for improving the quality of CBCT image and comprehensively evaluate our method on patient data. A CBCT software package with parallel computation is designed, which is easily compatible with the existing CBCT system of radiotherapy device with high computing efficiency and CT number accuracy. The primary signals of projections are estimated through the use of the forward projections from the registered planning CT (pCT). The errors of low frequency in the raw projections are obtained through subtracting the forward projections and the low-pass filter implementation. The penalty-weighted-least-square (PWLS) method is applied to reduce the high-frequency noise in the corrected CBCT projections. We use the graphics-processing unit (GPU) NVidia Tesla C2075 card with CUDA C programming to accelerate the time-consuming processes. The CBCT projections of a pelvis phantom and the two pelvis patients are obtained from the Varian TrueBeam system, which is a machine for the radiotherapy. The maximum errors of CT number are reduced over 70 HU on the TrueBeam result to below 15 HU, and the errors of spatial non-uniformity are decreased by a factor of around 7. The computation time is about 25 min on the GPU, which is reduced over 10 h on the CPU. The proposed software shows superior performance over the existing reconstruction. The proposed software demonstrates the reliability of the high-accuracy CBCT-based image-guided radiotherapy (IGRT), providing the high-precise CBCT with less computation time.