Lindstrøm Erika Kristina, Schreiner Jakob, Ringstad Geir Andre, Haughton Victor, Eide Per Kristian, Mardal Kent-Andre
1 Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Norway.
2 Center for Biomedical Computation, Simula Research Laboratory, Norway.
Neuroradiol J. 2018 Jun;31(3):292-298. doi: 10.1177/1971400918759812. Epub 2018 Feb 21.
Background Investigators use phase-contrast magnetic resonance (PC-MR) and computational fluid dynamics (CFD) to assess cerebrospinal fluid dynamics. We compared qualitative and quantitative results from the two methods. Methods Four volunteers were imaged with a heavily T2-weighted volume gradient echo scan of the brain and cervical spine at 3T and with PC-MR. Velocities were calculated from PC-MR for each phase in the cardiac cycle. Mean pressure gradients in the PC-MR acquisition through the cardiac cycle were calculated with the Navier-Stokes equations. Volumetric MR images of the brain and upper spine were segmented and converted to meshes. Models of the subarachnoid space were created from volume images with the Vascular Modeling Toolkit. CFD simulations were performed with a previously verified flow solver. The flow patterns, velocities and pressures were compared in PC-MR and CFD flow images. Results PC-MR images consistently revealed more inhomogeneous flow patterns than CFD, especially in the anterolateral subarachnoid space where spinal nerve roots are located. On average, peak systolic and diastolic velocities in PC-MR exceeded those in CFD by 31% and 41%, respectively. On average, systolic and diastolic pressure gradients calculated from PC-MR exceeded those of CFD by 11% and 39%, respectively. Conclusions PC-MR shows local flow disturbances that are not evident in typical CFD. The velocities and pressure gradients calculated from PC-MR are systematically larger than those calculated from CFD.
背景 研究人员使用相位对比磁共振成像(PC-MR)和计算流体动力学(CFD)来评估脑脊液动力学。我们比较了这两种方法的定性和定量结果。方法 对4名志愿者进行3T场强下的脑部和颈椎重T2加权容积梯度回波扫描以及PC-MR成像。根据PC-MR计算心动周期各阶段的速度。通过纳维-斯托克斯方程计算PC-MR采集过程中整个心动周期的平均压力梯度。对脑部和上脊柱的容积磁共振图像进行分割并转换为网格。使用血管建模工具包从容积图像创建蛛网膜下腔模型。使用先前验证过的流动求解器进行CFD模拟。比较PC-MR和CFD流动图像中的流动模式、速度和压力。结果 PC-MR图像显示的流动模式始终比CFD更不均匀,尤其是在脊神经根所在的蛛网膜下腔前外侧。平均而言,PC-MR中的收缩期和舒张期峰值速度分别比CFD中的高出31%和41%。平均而言,由PC-MR计算出的收缩期和舒张期压力梯度分别比CFD的高出11%和39%。结论 PC-MR显示出典型CFD中不明显的局部血流紊乱。由PC-MR计算出的速度和压力梯度系统性地大于由CFD计算出的结果。