Sincomb S, Coenen W, Gutiérrez-Montes C, Martínez Bazán C, Haughton V, Sánchez A L
Department of Mechanical and Aerospace Engineering, UC San Diego, La Jolla, CA 92093-0411, USA.
Grupo de Mecánica de Fluidos, Universidad Carlos III de Madrid, Leganés (Madrid) 28911, Spain.
J Fluid Mech. 2022 May 25;939. doi: 10.1017/jfm.2022.215. Epub 2022 Mar 30.
The monitoring of intracranial pressure (ICP) fluctuations, which is needed in the context of a number of neurological diseases, requires the insertion of pressure sensors, an invasive procedure with considerable risk factors. Intracranial pressure fluctuations drive the wave-like pulsatile motion of cerebrospinal fluid (CSF) along the compliant spinal canal. Systematically derived simplified models relating the ICP fluctuations with the resulting CSF flow rate can be useful in enabling indirect evaluations of the former from non-invasive magnetic resonance imaging (MRI) measurements of the latter. As a preliminary step in enabling these predictive efforts, a model is developed here for the pulsating viscous motion of CSF in the spinal canal, assumed to be a linearly elastic compliant tube of slowly varying section, with a Darcy pressure-loss term included to model the fluid resistance introduced by the which are thin collagen-reinforced columns that form a web-like structure stretching across the spinal canal. Use of Fourier-series expansions enables predictions of CSF flow rate for realistic anharmonic ICP fluctuations. The flow rate predicted using a representative ICP waveform together with a realistic canal anatomy is seen to compare favourably with phase-contrast MRI measurements at multiple sections along the spinal canal. The results indicate that the proposed model, involving a limited number of parameters, can serve as a basis for future quantitative analyses targeting predictions of ICP temporal fluctuations based on MRI measurements of spinal-canal anatomy and CSF flow rate.
在许多神经系统疾病的情况下，对颅内压（ICP）波动进行监测需要插入压力传感器，这是一种具有相当多风险因素的侵入性操作。颅内压波动驱动脑脊液（CSF）沿顺应性椎管做波状脉动运动。系统推导的将颅内压波动与由此产生的脑脊液流速相关联的简化模型，有助于通过对后者进行非侵入性磁共振成像（MRI）测量来间接评估前者。作为实现这些预测工作的初步步骤，本文建立了一个模型，用于描述椎管内脑脊液的脉动粘性运动，假设椎管是一个截面缓慢变化的线性弹性顺应性管道，并包含一个达西压力损失项来模拟由薄胶原增强柱引入的流体阻力，这些薄胶原增强柱形成一个横跨椎管延伸样结构横跨椎管。使用傅里叶级数展开能够预测实际非谐波颅内压波动下的脑脊液流速。使用具有代表性的颅内压波形以及实际的椎管解剖结构预测的流速，与沿椎管多个截面的相位对比MRI测量结果相比表现良好。结果表明，所提出的模型涉及的参数数量有限，可作为未来基于椎管解剖结构和脑脊液流速的MRI测量进行颅内压时间波动预测的定量分析基础。
