Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 9200942, Japan.
Department of Radiology, Okazaki City Hospital, 3-1 Goshoai, Koryuji-cho, Okazaki, Aichi, 4448553, Japan.
Med Phys. 2017 May;44(5):1646-1654. doi: 10.1002/mp.12182. Epub 2017 Mar 30.
A novel cranial phantom was developed to simulate the relationships among factors such as blood perfusion, water diffusion, and biomechanics in intracranial tissue.
The cranial phantom consisted of a high-density polypropylene filter (mimicking brain parenchyma) with intra- and extrafilter spaces (mimicking cerebral artery and vein, respectively), and a capacitor space (mimicking the cerebrospinal fluid space). Pulsatile and steady flow with different flow rates were applied to the cranial phantom using a programmable pump. On 3.0-T MRI, the measurements of the internal pressure in the phantom, apparent diffusion coefficient (ADC) with monoexponential analysis in the filter, and total simulated cerebral blood flow (tSCBF) into the phantom were synchronized with the pulsatile flow. We obtained their maximum changes during the pulsation period (ΔP, ΔADC, and ΔtSCBF, respectively). Then, the compliance index (CI) was calculated by dividing the volume change (ΔV) by the ΔP in the phantom. Moreover, the same measurements were repeated after the compliance of the phantom was reduced by increasing the water volume in the capacitor space. Under steady flow conditions, we determined the regional SCBF (rSCBF) and perfusion-related and restricted diffusion coefficients (D* and D, respectively) with biexponential analysis in the filter.
The internal pressure, ADC, and tSCBF varied over the pulsation period depending on the input flow. Moreover, the ΔP, ΔADC, ΔtSCBF, and rSCBF increased with the input flow rate. Compared to the high compliance condition, in the low compliance condition, the ΔP and ΔADC were higher by factors of 2.5 and 1.3, respectively, and the CI was smaller by a factor of 2.7, whereas the ΔV was almost unchanged. The D* was strongly affected by the input flow.
Our original phantom models the relationships among the blood perfusion, water diffusion, and biomechanics of the intracranial tissue, potentially facilitating the validation of novel MRI techniques and optimization of imaging parameters.
开发了一种新型颅腔模型，以模拟血液灌注、水扩散和颅内组织生物力学等因素之间的关系。
颅腔模型由高密度聚丙烯过滤器（模拟脑实质）和过滤器内外空间（分别模拟脑动脉和静脉）以及电容器空间（模拟脑脊液空间）组成。使用可编程泵向颅腔模型施加脉动和稳定的不同流速的流动。在 3.0T MRI 上，与脉动流同步测量模型内的内部压力、过滤器中单指数分析的表观扩散系数（ADC）和进入模型的总模拟脑血流（tSCBF）。我们获得了它们在脉动周期内的最大变化（分别为ΔP、ΔADC 和ΔtSCBF）。然后，通过将模型中的体积变化（ΔV）除以内部压力的变化（ΔP）来计算顺应性指数（CI）。此外，通过增加电容器空间中的水量来降低模型的顺应性后，重复了相同的测量。在稳定流动条件下，我们通过过滤器中的双指数分析确定了局部脑血流（rSCBF）和灌注相关及限制扩散系数（D*和 D）。
内部压力、ADC 和 tSCBF 在脉动周期内随输入流量而变化。此外，ΔP、ΔADC、ΔtSCBF 和 rSCBF 随输入流速增加而增加。与高顺应性条件相比，在低顺应性条件下，ΔP 和ΔADC 分别增加了 2.5 倍和 1.3 倍，CI 减小了 2.7 倍，而ΔV 几乎不变。D* 受输入流量的强烈影响。
我们的原始模型模拟了颅内组织的血液灌注、水扩散和生物力学之间的关系，可能有助于验证新的 MRI 技术和优化成像参数。
