Understanding of cerebrospinal fluid (CSF) dynamics is important in brain pathophysiology. Visualization of CSF motion by four-dimensional velocity mapping (4D-VM) based on phase contrast technique has been performed.^1-4 However, interpretation of the cine images is difficult because of the complex flow pattern in the CSF cavity structure. Therefore, a novel technique called correlation mapping, composed of delay time and correlation coefficient mapping, was proposed.^5,6 This technique visualizes propagation of CSF motion from a particular region to the other spaces in still images depicting propagation delay and velocity waveform preservation. Since CSF is incompressible, the presence of the propagation delay and waveform change may be attributed to the compliance in the CSF space and brain parenchyma. Brain compliance decreases with age and/or development of idiopathic normal pressure hydrocephalus (iNPH).^7,8 To characterize propagation properties of the pulsatile CSF motion of the elderly and iNPH in terms of compliance of CSF space, the correlation mapping technique was applied. The present study was approved by the institutional review board (IRB). All the volunteers were examined after obtaining appropriate informed consent. The correlation mapping technique was applied to 11 young healthy (25±4 y-o), 12 elderly healthy (72±8 y-o), and 10 iNPH patient (76±6 y-o) subjects. Imaging by 4D-VM was performed on a clinical 1.5T scanner with the following conditions: flow-encoding directions, IS, RL and AP; TR, 9.7-13.7 ms; TE, 6.7-7.6 ms; FA, 20º; FOV, 28×28 cm²; reconstruction matrix, 320×320; slice thickness, 0.98 mm; VENC, 5-60 cm/s; temporal points in a cardiac cycle, 32; slice direction, sagittal. Image reconstruction was synchronized retrospectively based on the trigger pulses from electrocardiograph or a finger plethysmograph. The region for taking reference velocity waveform was set at a CSF region near the basilar artery because it has been reported that the pressure around this space is significantly higher than other CSF spaces.⁹ Cyclic color-coding was used in delay time map because CSF motion is periodic. It was expected that pulsation at certain point might arise earlier than that at the reference; therefore, delay time was represented as from -50% to 50% of a cardiac cycle. The average and the standard deviation of the correlation coefficient distributing in the intracranial CSF space above C1 level segmented by spatial-based fuzzy clustering¹⁰ were quantified. To assist clinicians to understand the propagation properties of the CSF motion, each voxel of the correlation coefficient maps was weighted with its brightness of the color; the brightness was lowered when peak-to-peak amplitude of the velocity waveform at an arbitrary point was lower than that at the reference, while it was not changed when the amplitude was higher or equal to. Delay time maps of the subjects exhibited pulsatile CSF motion propagation in the space with different compliance (Fig. 1a-c). The delay map in Fig. 1c showed an apparently more complicated distribution near the brainstem than the healthy volunteers. Maximum correlation maps presented difference of the propagation properties reflecting the CSF space compliance (Fig. 1d-f). The brightness was lower in the further spatial region from the reference region. The variation of the correlation coefficients in the patient group was clearly larger than those in the healthy groups. The average correlation values in the intracranial CSF space were plotted in Fig. 2. A significant difference between the young and the others appeared. The standard deviation represented in Fig. 3 exhibited significant differences among the three groups.

The correlation mapping technique applied to the subjects demonstrated that CSF space compliance varied by aging and iNPH. In particular, delay time map of iNPH patient subject presented that iNPH varies and complicates the propagation properties.

Maximum correlation coefficient maps improved the amplitude-based clearly presented the propagation properties in the groups. Since the difference among the groups was revealed by the approach, which will help clinicians to understand the propagation properties and diagnose neurological diseases.

Quantification result of the average correlation reflected the variation of the compliance with aging, although the elderly healthy group and the iNPH group could not be differentiated. Decrease in the tissue compliance may lead to direct motion propagation, which lowers the spatial dispersion in the correlation distribution. Hence, standard deviation of the correlation distribution was quantified, and in consequence, the groups were classified.

In conclusions, the correlation mapping technique may classify iNPH group from the healthy group in view of the CSF space compliance. The technique will help clinicians to understand CSF dynamics and diagnose neurological diseases such as iNPH.