Karki Pragalv, Murphy Matthew C, Ganji Sandeep, Gunter Jeffrey L, Graff-Radford Jonathan, Jones David T, Botha Hugo, Cutsforth-Gregory Jeremy K, Elder Benjamin D, Jack Clifford R, Huston John, Cogswell Petrice M
Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA.
J Neuroimaging. 2025 Jan-Feb;35(1):e70000. doi: 10.1111/jon.70000.
In idiopathic normal pressure hydrocephalus (iNPH) patients, cerebrospinal fluid (CSF) flow is typically evaluated with a cardiac-gated two-dimensional (2D) phase-contrast (PC) MRI through the cerebral aqueduct. This approach is limited by the evaluation of a single location and does not account for respiration effects on flow. In this study, we quantified the cardiac and respiratory contributions to CSF movement at multiple intracranial locations using a real-time 2D PC-MRI and evaluated the diagnostic value of CSF dynamics biomarkers in classifying iNPH patients.
This study included 37 participants: 16 iNPH, 10 Alzheimer's disease (AD), and 11 cognitively unimpaired (CU) controls. Anatomical and real-time (non-gated) PC images were acquired in a 3T Philips scanner. CSF flow was assessed at the foramen magnum, fourth ventricle, Sylvian fissure, lateral ventricle, and cerebral aqueduct. We calculated three CSF dynamics biomarkers: mean velocity amplitude, cardiac signal power, and respiratory signal power. Biomarkers from each location were evaluated for classifying iNPH versus AD and CU using support vector machine (SVM). A p-value of 0.05 or less was considered statistically significant.
The velocity amplitude and cardiac signal power were significantly reduced in iNPH compared to CU (p < 0.005) and AD (p < 0.05) at the lateral ventricle. The SVM model using biomarkers from the lateral ventricle performed significantly better at classifying iNPH than the other locations in terms of accuracy (p < 0.005) and diagnostic odds ratio (p < 0.05).
Evaluation of CSF movement beyond the cerebral aqueduct may aid in identifying patients with and understanding the pathophysiology of iNPH.
在特发性正常压力脑积水（iNPH）患者中，通常通过心脏门控二维（2D）相位对比（PC）MRI评估中脑导水管的脑脊液（CSF）流动。这种方法受限于对单一位置的评估，且未考虑呼吸对流动的影响。在本研究中，我们使用实时2D PC-MRI量化了心脏和呼吸对多个颅内位置CSF运动的贡献，并评估了CSF动力学生物标志物在iNPH患者分类中的诊断价值。
本研究纳入37名参与者：16名iNPH患者、10名阿尔茨海默病（AD）患者和11名认知未受损（CU）对照者。在3T飞利浦扫描仪中采集解剖学和实时（非门控）PC图像。在枕骨大孔、第四脑室、大脑外侧裂、侧脑室和中脑导水管评估CSF流动。我们计算了三种CSF动力学生物标志物：平均速度幅值、心脏信号功率和呼吸信号功率。使用支持向量机（SVM）评估每个位置的生物标志物对iNPH与AD和CU进行分类的情况。p值小于或等于0.05被认为具有统计学意义。
与CU（p < 0.005）和AD（p < 0.05）相比，iNPH患者侧脑室的速度幅值和心脏信号功率显著降低。使用来自侧脑室生物标志物的SVM模型在分类iNPH方面，在准确性（p < 0.005）和诊断比值比（p < 0.05）方面显著优于其他位置。
评估中脑导水管以外的CSF运动可能有助于识别iNPH患者并理解其病理生理学。
