Visualization and Characterization of Cerebrospinal Fluid Motion Based on Magnetic Resonance Imaging

Purpose: To characterize cardiac- and respiratory-driven cerebrospinal fluid (CSF) motions in intracranial space noninvasively, four-dimensional velocity mapping (4D-VM), correlation mapping, and power and frequency mapping with cardiac-gated and/or asynchronous magnetic resonance (MR) phase contrast (PC) techniques were conducted

Visualization of pulsatile CSF motion around membrane-like structures with both 4D velocity mapping and time-SLIP technique

Purpose: We compared the depiction of pulsatile CSF motion obtained by 4-dimensional phase-contrast velocity mapping (4D-VM) with that by time-spatial labeling inversion pulse (time-SLIP) technique in the presence of membrane structures. Materials and Methods: We compared the 2 techniques using a flow phantom comprising tubes with and without a thin rubber membrane and applied the techniques to 6 healthy volunteers and 2 patients to analyze CSF dynamics surrounding thin membrane structures, such as the Liliequist membrane (LM), or the wall of an arachnoid cyst. Results: Phantom images exhibited propagation of the flow and pressure gradient beyond the membrane in the tube. In contrast, fluid labeled by the time-SLIP technique showed little displacement from the blockage of spin travelling by the membrane. A similar phenomenon was observed around the LM in healthy volunteers and the arachnoid cyst wall in a patient. Conclusion: Four-dimensional phase-contrast velocity mapping permitted visualization of the propagation of CSF pulsation through the intracranial membranous structures. This suggests that 4D-VM and the time-SLIP technique provide different information on flow and that both techniques are useful for classifying the pathophysiological status of CSF and elucidating the propagation pathway of CSF pulsation in the cranium

Characterization of cardiac- and respiratory-driven cerebrospinal fluid motion based on asynchronous phase-contrast magnetic resonance imaging in volunteers

Abstract Background A classification of cardiac- and respiratory-driven components of cerebrospinal fluid (CSF) motion has been demonstrated using echo planar imaging and time-spatial labeling inversion pulse techniques of magnetic resonance imaging (MRI). However, quantitative characterization of the two motion components has not been performed to date. Thus, in this study, the velocities and displacements of the waveforms of the two motions were quantitatively evaluated based on an asynchronous two-dimensional (2D) phase-contrast (PC) method followed by frequency component analysis. Methods The effects of respiration and cardiac pulsation on CSF motion were investigated in 7 healthy subjects under guided respiration using asynchronous 2D-PC 3-T MRI. The respiratory and cardiac components in the foramen magnum and aqueduct were separated, and their respective fractions of velocity and amount of displacement were compared. Results For velocity in the Sylvian aqueduct and foramen magnum, the fraction attributable to the cardiac component was significantly greater than that of the respiratory component throughout the respiratory cycle. As for displacement, the fraction of the respiratory component was significantly greater than that of the cardiac component in the aqueduct regardless of the respiratory cycle and in the foramen magnum in the 6- and 10-s respiratory cycles. There was no significant difference between the fractions in the 16-s respiratory cycle in the foramen magnum. Conclusions To separate cardiac- and respiratory-driven CSF motions, asynchronous 2D-PC MRI was performed under respiratory guidance. For velocity, the cardiac component was greater than the respiratory component. In contrast, for the amount of displacement, the respiratory component was greater

Cerebrospinal fluid image segmentation using spatial fuzzy clustering method with improved evolutionary expectation maximization

Visualization of cerebrospinal fluid (CSF), that flow in the brain and spinal cord, plays an important role to detect neurodegenerative diseases such as Alzheimer's disease. This is performed by measuring the substantial changes in the CSF flow dynamics, volume and/or pressure gradient. Magnetic resonance imaging (MRI) technique has become a prominent tool to quantitatively measure these changes and image segmentation method has been widely used to distinguish the CSF flows from the brain tissues. However, this is often hampered by the presence of partial volume effect in the images. In this paper, a new hybrid evolutionary spatial fuzzy clustering method is introduced to overcome the partial volume effect in the MRI images. The proposed method incorporates Expectation Maximization (EM) method, which is improved by the evolutionary operations of the Genetic Algorithm (GA) to differentiate the CSF from the brain tissues. The proposed improvement is incorporated into a spatial-based fuzzy clustering (SFCM) method to improve segmentation of the boundary curve of the CSF and the brain tissues. The proposed method was validated using MRI images of Alzheimer's disease patient. The results presented that the proposed method is capable to filter the CSF regions from the brain tissues more effectively compared to the standard EM, FCM, and SFCM methods

A multi-stage clustering approach for cerebrospinal fluid image segmentation

Analysis of the cerebro spinal fluid (CSF) flow within brain has become increasingly important to diagnose a number of neuro degenerative disorders. Magnetic resonance imaging (MRI) is utilised to measure the CSF volumetric change in patients. However, the quality of the images is often hampered by partial volume effect, which blurred the boundary between the brain tissues and the CSF. Consequently, the accuracy of CSF analysis is reduced significantly. In this paper, we introduce a new multi-stage clustering approach to overcome this limitation. Firstly, the T1-weigthed images are fused with the corresponding T2-weigthed images. Next, the resulting images are subjected to partial volume estimation using Gaussian mixture model. The model produced by these images is later used as input in a spatial fuzzy clustering algorithm to segment the CSF flow from the brain tissues. Benchmark images obtained from Brain Web are used to validate the performance of the proposed approach. In addition, we also presented the performance of the proposed method using real MRI images taken from a number of Alzheimer’s disease patients, which evidently showed the effectiveness of the method in quantifying the CSF flow within the brain

Hyperdynamic CSF motion profiles found in idiopathic normal pressure hydrocephalus and Alzheimer’s disease assessed by fluid mechanics derived from magnetic resonance images

Abstract Background Magnetic resonance imaging (MRI) does not only ascertain morphological features, but also measures physiological properties such as fluid velocity or pressure gradient. The purpose of this study was to investigate cerebrospinal fluid (CSF) dynamics in patients with morphological abnormalities such as enlarged brain ventricles and subarachnoid spaces. We used a time-resolved three dimensional phase contrast (3D-PC) MRI technique to quantitatively evaluate CSF dynamics in the Sylvian aqueduct of healthy elderly individuals and patients with either idiopathic normal pressure hydrocephalus (iNPH) or Alzheimer’s disease (AD) presenting with ventricular enlargement. Methods Nineteen healthy elderly individuals, ten iNPH patients, and seven AD patients (all subjects ≥ 60 years old) were retrospectively evaluated 3D-PC MRI. The CSF velocity, pressure gradient, and rotation in the Sylvian aqueduct were quantified and compared between the three groups using Kolmogorov–Smirnov and Mann–Whitney U tests. Results There was no statistically significant difference in velocity among the three groups. The pressure gradient was not significantly different between the iNPH and AD groups, but was significantly different between the iNPH group and the healthy controls (p < 0.001), and similarly, between the AD group and the healthy controls (p < 0.001). Rotation was not significantly different between the iNPH and AD groups, but was significantly different between the iNPH group and healthy controls (p < 0.001), and similarly, between the AD group and the healthy controls (p < 0.001). Conclusions Quantitative analysis of CSF dynamics with time resolved 3D-PC MRI revealed differences and similarities in the Sylvian aqueduct between healthy elderly individuals, iNPH patients, and AD patients. The results showed that CSF motion is in a hyperdynamic state in both iNPH and AD patient groups compared to healthy elderly individuals, and that iNPH patients and AD patients display similar CSF motion profiles

Quantitative analysis of cerebrospinal fluid pressure gradients in healthy volunteers and patients with normal pressure hydrocephalus

Magnetic resonance imaging (MRI) can depict not only anatomical information, but also physiological factors such as velocity and pressure gradient. Measurement of these physiological factors is necessary to understand the cerebrospinal fluid (CSF) environment. In this study we quantified CSF motion in various parts of the CSF space, determined changes in the CSF environment with aging, and compared CSF pressure gradient between patients with idiopathic normal pressure hydrocephalus (iNPH) and healthy elderly volunteers. Fifty-seven healthy volunteers and six iNPH patients underwent four-dimensional (4D) phase-contrast (PC) MRI. CSF motion was observed and the pressure gradient of CSF was quantified in the CSF space. In healthy volunteers, inhomogeneous CSF motion was observed whereby the pressure gradient markedly increased in the center of the skull and gradually decreased in the periphery of the skull. For example, the pressure gradient at the ventral surface of the brainstem was 6.6 times greater than that at the convexity of the cerebrum. The pressure gradient was statistically unchanged with aging. The pressure gradient of patients with iNPH was 3.2 times greater than that of healthy volunteers. The quantitative analysis of 4D-PC MRI data revealed that the pressure gradient of CSF can be used to understand the CSF environment, which is not sufficiently given by subjective impression of the anatomical image