Leveraging non-contrast head CT to improve the image quality of cerebral CT perfusion maps

Purpose: The purpose of our work is to present a method that utilizes high-quality non-contrast CT (NCCT) images to reduce the noise of CT perfusion (CTP) baseline images to improve the visibility of infarct core in cerebral blood volume (CBV) maps. Methods: First, a theoretical analysis of the CTP imaging system was performed to demonstrate that for both deconvolution- and non-deconvolution-based CTP systems. The noise of CBV maps is profoundly influenced by the baseline image noise. Consequently, baseline noise reduction is extremely effective in improving the contrast-to-noise ratio (CNR) of ischemic lesions in CBV maps. Second, a method was proposed to fuse the freely available NCCT images with the original CTP baseline images. An optimal weighting scheme was derived such that the noise of the fused baseline image is minimized. Third, the impact of the proposed NCCT-baseline fusion method was investigated using five in vivo canine subjects with different infarct core sizes. NCCT and CTP scans were performed following a clinical stroke CT imaging protocol using a 64-slice MDCT. Two of the subjects also received a diffusion-weighted imaging scan using a 3T-MRI scanner to establish the reference diagnosis for the infarct core. Results: For all five canine subjects, the proposed method led to lower CBV noise and better conspicuity of the infarct core. Compared with a standard CTP postprocessing method, the proposed method reduced the CBV noise standard deviation by $$ and increased the CNR of infarct core by $$ ( $$ ). Conclusions: By utilizing the high-quality NCCT images to reduce CTP baseline image noise, the quality of CBV maps and the conspicuity of ischemic infarct core can be effectively improved. The proposed method can be readily implemented with minimal interruption to the existing clinical workflow.