Forner J, Florez N, Valero Merino C, Marti-Bonmati L, Moratal D, Piquer J, Elso L, Arana E
Servicio de Radiología, Hospital Quirón, Valencia.
Neurologia. 2007 May;22(4):213-20.
A combination of good clinical selection with reliable quantification of diverse parameters that characterize the dynamics of cerebrospinal fluid (CSF) flow from phase-contrast magnetic resonance imaging may identify patients with idiopathic normal pressure hydrocephalus (NPH).
We have carried out a quantitative analysis of 38 subjects (19 healthy subjects and 19 patients with suspected idiopathic NPH). The images were acquired using a 1.5 T MR unit with a phase-contrast sequence in an oblique-transversal plane perpendicular to the Sylvius aqueduct codified to 20 cm/s and with 27 observations per cardiac cycle by means of retrospective synchronization. The area was defined to half the height of the peak velocity, to maximize accuracy. Parameters quantified were mean flow, maximum systolic and diastolic flow, maximum systolic and diastolic velocity, mean velocity, CSF production and stroke volume.
All the parameters measured showed a significant difference (ANOVA: p<or=0,05) between controls and patient except for the maximum systolic velocity (p=0.17). It was observed in the discriminant analysis that the two groups (controls and patients) were classified correctly in 92.1% with the use of the maximum systolic flow and CSF production.
Semiautomatic quantification of the dynamics of CSF by means of MRI differentiates patients with hyperdynamic state from the control subjects, with significant differences that can be used to classify idiopathic HNP.
将良好的临床选择与对多种参数进行可靠量化相结合,这些参数可通过相位对比磁共振成像来表征脑脊液(CSF)流动的动态变化,这可能有助于识别特发性正常压力脑积水(NPH)患者。
我们对38名受试者(19名健康受试者和19名疑似特发性NPH患者)进行了定量分析。使用1.5T磁共振设备,通过回顾性同步,在垂直于中脑导水管的斜横断面采用相位对比序列进行成像,编码速度为20cm/s,每个心动周期进行27次观察。面积定义为峰值速度高度的一半,以最大限度提高准确性。量化的参数包括平均流量、最大收缩期和舒张期流量、最大收缩期和舒张期速度、平均速度、脑脊液生成量和每搏输出量。
除最大收缩期速度外(p = 0.17),所有测量参数在对照组和患者组之间均显示出显著差异(方差分析:p≤0.05)。在判别分析中观察到,使用最大收缩期流量和脑脊液生成量时,两组(对照组和患者组)的正确分类率为92.1%。
通过MRI对脑脊液动力学进行半自动量化,可将高动力状态患者与对照受试者区分开来,其显著差异可用于对特发性HNP进行分类。