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Few studies are interested in the noninvasive determination of propagation parameters. Reflected waves can be used as an intelligent tool for therapeutic measures. The amplitude and arrival time of reflected wave play an interesting role in investigating cardiovascular diseases. Therefore, this study aims to implement a method based on cepstral analysis for noninvasive decomposition of the incident and reflected waves and determination of local propagation parameters. The cepstral analysis is applied to the blood velocity, which is measured by using phase-contrast magnetic resonance imaging (PCMR) in 20 subjects. The determination of propagation parameters: arrival time, attenuation coefficient, reflection amplitude, and reflection coefficient is based on a mathematical model developed in the previous work. To evaluate the precision of the proposed approach, we focused on the effect of age. In addition, we intended to compare the obtained results to those obtained by the wave intensity analysis (WIA) method. A statistical test analysis was conducted to establish the relationship between the propagation parameters and the age. Our experimental results showed that there is no significant difference in terms of propagation parameters with age (p > 0. 0 5). Our experimental results correlated with reference values reported in previous studies conducted on the internal arterial carotid. The propagate parameters obtained by the proposed method varied slightly with age. Moreover, the reflection coefficient detected using our proposed method was close to that detected using WIA. We can conclude that the technique described in this paper offers a promising and efficient approach to separating measured velocity waveforms into their incident and reflected components noninvasively. [ABSTRACT FROM AUTHOR]

Our knowledge of cerebrospinai fluid (CSF) hydrodynamics has been considerably improved with the recent introduction of phase-contrast magnetic resonance imaging (phase-contrast MRI), which can provide CSF and blood flow measurements throughout the cardiac cycle. Key temporal and amplitude parameters can be calculated at different sites to elucidate the role played by the various CSF compartments during vascular brain expansion. Most of the models reported in the literature do not take into account CSF oscillation during the cardiac cycle and its kinetic energy impact on the brain. We propose a new lumped-parameter compartmental model of CSF and blood flows in healthy subjects during the cardiac cycle. The system was divided into five submodels representing arterial blood, venous blood, ventricular CSF, cranial subarachnoid space, and spinal subarachnoid space. These submodels are connected by resistances and compliances. The model developed was used to reproduce certain functional characteristics observed in seven healthy volunteers, such as the distribution (amplitude and phase shift) of arterial, venous, and CSF flows. The results show a good agreement between measured and simulated intracranial CSF and blood flows. Index Terms--Blood flow, compliance, conductance, CSF flow, hydrodynamics, phase-contrast MRI.

Background Changes in blood volume in the intracranial arteries and the resulting oscillations of brain parenchyma have been presumed as main initiating factors of cerebrospinal fluid (CSF) pulsations. However, respiration has been recently supposed to influence CSF dynamics via thoracic pressure changes. Purpose To measure blood and CSF cervical flow and quantify the contribution of cardiac and respiratory cycles on the subsequent signal evolution. Material and Methods Sixteen volunteers were enrolled. All participant underwent two-dimensional fast field echo echo planar imaging (FFE-EPI). Regions of interest were placed on internal carotids, jugular veins, and rachidian canal to extract temporal profiles. Spectral analysis was performed to extract respiratory and cardiac frequencies. The contribution of respiration and cardiac activity was assessed to signal evolution by applying a multiple linear model. Results Mean respiratory frequency was 14.6 ± 3.9 cycles per min and mean heart rate was 66.8 ± 9 cycles per min. Cardiac contribution was higher than breathing for internal carotids, explaining 74.68% and 10.27% of the signal variance, respectively. For the jugular veins, respiratory component was higher than the cardiac one contributing 44.28% and 6.53% of the signal variance, respectively. For CSF, breathing and cardiac component contributed less than half of signal variance (12.61% and 23.23%, respectively). Conclusion Respiration and cardiac activity both influence fluid flow at the cervical level. Arterial inflow is driven by the cardiac pool whereas venous blood aspiration seems more due to thoracic pressure changes. CSF dynamics acts as a buffer between these two blood compartments. [ABSTRACT FROM AUTHOR]