Department of Radiology, University Medical Centre Utrecht, Utrecht 3584CX, The Netherlands.
Med Phys. 2011 Jun;38(6):3212-21. doi: 10.1118/1.3592639.
Development and evaluation of a realistic hybrid head phantom for the validation of quantitative CT brain perfusion methods.
A combination, or hybrid, of CT images of an anthropomorphic head phantom together with clinically acquired MRI brain images was used to construct a dynamic hybrid head phantom. Essential CT imaging parameters such as spatially dependent noise, effects of resolution, tube settings, and reconstruction parameters were intrinsically included by scanning a skull phantom using CT perfusion (CTP) protocols with varying mAs. These data were combined with processed high resolution 7T clinical MRI images to include healthy and diseased brain parenchyma, as well as the cerebral vascular system. Time attenuation curves emulating contrast bolus passage based on perfusion as observed in clinical studies were added. Using the phantom, CTP images were generated using three brain perfusion calculation methods: bcSVD, sSVD, and fit-based deconvolution, and the linearity and accuracy of the three calculation methods was assessed. Dependency of perfusion outcome on calculation method was compared to clinical data. Furthermore, the potential of the phantom to optimize brain perfusion packages was investigated.
All perfusion calculation methods showed overestimation of low perfusion values and underestimation of high perfusion values. Good correlation in behavior between phantom and clinical data was found (R2 = 0.84).
A dynamic hybrid head phantom constructed from CT and MRI data was demonstrated to realistically represent clinical CTP studies, which is useful for assessing CT brain perfusion acquisition, reconstruction, and analysis.
开发和评估用于定量 CT 脑灌注方法验证的逼真混合头颅体模。
采用 CT 灌注（CTP）协议对头颅体模进行扫描，获得不同毫安值的 CT 图像，将其与临床采集的 MRI 脑图像相结合，构建动态混合头颅体模。通过扫描，内在地包含了空间依赖噪声、分辨率、管设置和重建参数等基本 CT 成像参数。这些数据与经过处理的高分辨率 7T 临床 MRI 图像相结合，包括健康和患病的脑组织以及脑血管系统。添加了模拟临床研究中观察到的对比剂团注通过的时间衰减曲线。使用体模，使用三种脑灌注计算方法（bcSVD、sSVD 和基于拟合的反卷积）生成 CTP 图像，并评估三种计算方法的线性度和准确性。比较了灌注结果对计算方法的依赖性与临床数据。此外，还研究了该体模优化脑灌注方案的潜力。
所有灌注计算方法均显示低灌注值高估和高灌注值低估。发现体模和临床数据之间的行为具有良好的相关性（R2 = 0.84）。
从 CT 和 MRI 数据构建的动态混合头颅体模被证明能够真实地代表临床 CTP 研究，这对于评估 CT 脑灌注采集、重建和分析非常有用。
