van den Boom Rieneke, Manniesing Rashindra, Oei Marcel T H, van der Woude Willem-Jan, Smit Ewoud J, Laue Hendrik O A, van Ginneken Bram, Prokop Mathias
Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6500 HB Nijmegen, The Netherlands.
Department of Radiology and Nuclear Medicine, Radboud University Medical Center, 6500 HB Nijmegen, The Netherlands and Department of Radiology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands.
Med Phys. 2014 Jul;41(7):071907. doi: 10.1118/1.4881520.
Optimizing CT brain perfusion protocols is a challenge because of the complex interaction between image acquisition, calculation of perfusion data, and patient hemodynamics. Several digital phantoms have been developed to avoid unnecessary patient exposure or suboptimum choice of parameters. The authors expand this idea by using realistic noise patterns and measured tissue attenuation curves representing patient-specific hemodynamics. The purpose of this work is to validate that this approach can realistically simulate mean perfusion values and noise on perfusion data for individual patients.
The proposed 4D digital phantom consists of three major components: (1) a definition of the spatial structure of various brain tissues within the phantom, (2) measured tissue attenuation curves, and (3) measured noise patterns. Tissue attenuation curves were measured in patient data using regions of interest in gray matter and white matter. By assigning the tissue attenuation curves to the corresponding tissue curves within the phantom, patient-specific CTP acquisitions were retrospectively simulated. Noise patterns were acquired by repeatedly scanning an anthropomorphic skull phantom at various exposure settings. The authors selected 20 consecutive patients that were scanned for suspected ischemic stroke and constructed patient-specific 4D digital phantoms using the individual patients' hemodynamics. The perfusion maps of the patient data were compared with the digital phantom data. Agreement between phantom- and patient-derived data was determined for mean perfusion values and for standard deviation in de perfusion data using intraclass correlation coefficients (ICCs) and a linear fit.
ICCs ranged between 0.92 and 0.99 for mean perfusion values. ICCs for the standard deviation in perfusion maps were between 0.86 and 0.93. Linear fitting yielded slope values between 0.90 and 1.06.
A patient-specific 4D digital phantom allows for realistic simulation of mean values and standard deviation in perfusion data and makes it possible to retrospectively study how the interaction of patient hemodynamics and scan parameters affects CT perfusion values.
由于图像采集、灌注数据计算和患者血流动力学之间存在复杂的相互作用，优化CT脑灌注方案具有挑战性。已经开发了几种数字体模，以避免不必要的患者辐射或参数选择不当。作者通过使用逼真的噪声模式和代表患者特定血流动力学的测量组织衰减曲线来拓展这一理念。这项工作的目的是验证这种方法能够真实地模拟个体患者灌注数据的平均灌注值和噪声。
所提出的4D数字体模由三个主要部分组成：（1）体模内各种脑组织的空间结构定义；（2）测量的组织衰减曲线；（3）测量的噪声模式。使用灰质和白质中的感兴趣区域在患者数据中测量组织衰减曲线。通过将组织衰减曲线分配到体模内相应的组织曲线，回顾性模拟特定患者的CTP采集。通过在各种曝光设置下重复扫描拟人化颅骨体模来获取噪声模式。作者选择了20例因疑似缺血性中风而接受扫描的连续患者，并使用个体患者的血流动力学构建特定患者的4D数字体模。将患者数据的灌注图与数字体模数据进行比较。使用组内相关系数（ICC）和线性拟合确定体模数据与患者数据之间在平均灌注值和灌注数据标准差方面的一致性。
平均灌注值的ICC在0.92至0.99之间。灌注图标准差的ICC在0.86至0.93之间。线性拟合产生的斜率值在0.90至1.06之间。
特定患者的4D数字体模能够真实地模拟灌注数据的平均值和标准差，并使得回顾性研究患者血流动力学与扫描参数之间的相互作用如何影响CT灌注值成为可能。
