Cerebral perfusion computed tomography (CPCT) can depict the functional status of cerebral circulation at the tissue level; hence, it has been increasingly used to diagnose patients with cerebrovascular disease. However, there is a significant concern that CPCT scanning protocol could expose patients to excessive radiation doses. Although reducing the x-ray tube current when acquiring CPCT projection data is an effective method for reducing radiation dose, this technique usually results in degraded image quality. To enhance the image quality of low-dose CPCT, we present a prior image induced diffusion tensor (PIDT) for statistical iterative reconstruction, based on the penalized weighted least-squares (PWLS) criterion, which we referred to as PWLS-PIDT, for simplicity. Specifically, PIDT utilizes the geometric features of pre-contrast scanned high-quality CT image as a structure prior for PWLS reconstruction; therefore, the low-dose CPCT images are enhanced while preserving important features in the target image. An effective alternating minimization algorithm is developed to solve the associated objective function in the PWLS-PIDT reconstruction. We conduct qualitative and quantitative studies to evaluate the PWLS-PIDT reconstruction with a digital brain perfusion phantom and patient data. With this method, the noise in the reconstructed CPCT images is more substantially reduced than that of other competing methods, without sacrificing structural details significantly. Furthermore, the CPCT sequential images reconstructed via the PWLS-PIDT method can derive more accurate hemodynamic parameter maps than those of other competing methods.

脑灌注计算机断层扫描（CPCT）可以在组织层面描绘脑循环的功能状态；因此，它越来越多地用于诊断脑血管疾病患者。然而，CPCT 扫描协议可能会使患者暴露在过量的辐射剂量下，这是一个重大问题。虽然在采集 CPCT 投影数据时降低 X 射线管电流是降低辐射剂量的有效方法，但这种技术通常会导致图像质量下降。为了提高低剂量 CPCT 的图像质量，我们基于惩罚加权最小二乘 (PWLS) 标准，我们将其称为 PWLS-PIDT，提出了一种用于统计迭代重建的先验图像诱导扩散张量 (PIDT)，用于简单。具体来说，PIDT利用对比前扫描的高质量CT图像的几何特征作为PWLS重建的先验结构；因此，在保留目标图像中的重要特征的同时，增强了低剂量 CPCT 图像。开发了一种有效的交替最小化算法来解决 PWLS-PIDT 重建中的相关目标函数。我们进行定性和定量研究，以使用数字脑灌注模型和患者数据评估 PWLS-PIDT 重建。使用这种方法，重建的 CPCT 图像中的噪声比其他竞争方法显着减少，而不会显着牺牲结构细节。此外，