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The aim of this study is to clarify biophysics of normal pressure hydrocephalus (NPH) based on non-invasive intracranial compliance measurement using magnetic resonance imaging (MRI). Patients with NPH after subarachnoid hemorrhage (NPH group, n = 5), brain atrophy or asymptomatic ventricular dilation (VD group, n = 5), and healthy volunteers (control group, n = 12) were included in this study. Net blood flow (bilateral internal carotid and vertebral arteries, and jugular veins) and cerebrospinal fluid (CSF) flow in subarachnoid space at the C2 level of cervical vertebra were measured using phase-contrast cine MRI. CSF pressure gradient and intracranial volume changes during a cardiac cycle were calculated based on Alperin’s method. Compliance index (Ci = delta V/delta P) was obtained from the maximum pressure gradient and volume changes. Pressure volume response (PVR) was measured in the NPH group during a shunt operation. Ci in the NPH group was the lowest among the three studies groups. No difference was found between the control and VD groups. There was a linear correlation between Ci and PVR. In conclusion, intracranial compliance can be determined by cine MRI non-invasively. It is well known that NPH has relatively low intracranial compliance, this non-invasive method can be used for the diagnosis of NPH.

The monitoring of craniospinal compliance is uncommonly used clinically despite it’s value. The Spiegelberg compliance monitor calculates intracranial compliance (C = ΔV/ΔP) from a moving average of small ICP perturbations (ΔP) resulting from a sequence of up to 200 pulses of added volume (ΔV = 0.1 ml, total V = 0.2 ml) made into a double lumen intraventricular balloon catheter. The objective of this study was thus to determine the effectiveness of the decompressive craniectomy done on the worst brain site with regard to compliance (CI), pressure volume index (PVI), jugular oximetry (SjVo), autoregulation abnormalties, brain tissue oxygen (TiO) and cerebral blood flow (CBF). This is a prospective cohort study of 17 patients who were enrolled after consent and approval of the ethics committee between the beginning of the year 2001 and end of the year 2002. For pre and post assessment on compliance and PVI, all 12 patients who survived were reported to become normal after decompressive craniectomy. There is no significant association between pre and post craniectomy assessment in jugular oxymetry (p > 0.05), autoregulation (p > 0.05), intracranial brain oxymetry (p = 0.125) and cerebral blood flow (p = 0.375). Compliance and PVI improved dramatically in all alive patients who received decompressive craniectomy. Compliance and PVI monitoring may be crucial in improving the outcome of severe head injured patients after decompressive craniectomy.

A model of intracranial pressure (ICP) dynamics that uses fluid volumes as primary state variables is presented, along with clinical data for two subjects with elevated ICP. The data includes annotations to indicate the precise timing of clinical changes in cerebral spinal fluid drainage, head of bed elevation, and minute ventilation. The response to changes in the clinical parameters was used to calibrate the model to correspond to specific subjects by estimating values for key characteristics such as hematoma volume and CSF uptake resistance. The error in mean ICP predicted by the model was less than 2 mmHg when cerebral spinal fluid is drained and the head of bed elevation was increased. The error in mean ICP predicted by the model exceeded 5 mmHg during an episode when the head of bed was decreased and also during a reduction in minute ventilation. The estimated values for hematoma volume and other subject characteristics were plausible but could not be verified empirically.

The controlled cortical impact model has been used extensively to study focal traumatic brain injury. Although the impact variables can be well defined, little is known about the biomechanical trauma as delivered to different brain regions. This knowledge however could be valuable for interpretation of experiment (immunohistochemistry etc.), especially regarding the comparison of the regional biomechanical severity level to the regional magnitude of the trauma sequel under investigation. We used finite element (FE) analysis, based on high resolution T2-weighted MRI images of rat brain, to simulate displacement, mean stress, and shear stress of brain during impact. Young’s Modulus E, to describe tissue elasticity, was assigned to each FE in three scenarios: in a constant fashion (E=50 kPa), or according to the MRI intensity in a linear (E=[10; 100] kPa) and inverse-linear fashion (E=[100; 10] kPa). Simulated tissue displacement did not vary between the 3 scenarios, however mean stress and shear stress were largely different. The linear scenario showed the most likely distribution of stresses. In summary, FE analysis seems to be a suitable tool for biomechanical simulation, however, to be closest to reality tissue elasticity needs to be determined with a more specific approach, e.g. by means of MRI elastography.

Spontaneous slow waves are present in the systemic circulation including the intracranial compartment. They are supposed to reflect the cerebral autoregulation. We hypothesised that in the absence of cardio respiratory variability, during cardiopulmonary bypass (CPB), we should reveal extreme physiologic controls.

. Ten patients were included. Arterial blood pressure (ABP, radial invasive), extracorporeal circuitry pressure and cerebral blood flow velocity (CBFV, middle cerebral artery) were recorded. We analysed the slow waves in the B (8 to 50) and the UB (> 50 to 200) bands (in milli-Hz). The analysis, before and during CPB, was performed in the tine domain (correlation coefficient, entropy, mean quantity of mutual information, relative entropy) and in the frequency domain (spectrogram, frequency spectrum, coherence).

. CPB dramatically changed monitored signals decreasing their entropy and revealing a dominant CBFV 70 mHz-frequency and a dominant ABP 9 mHz-frequency. There was no association between the signals ( p<0.05). Before CPB we found complex patterns where B and UB waves were present.

. We hypothesised that CPB provoked a highly protective mechanism, reducing the fluctuations of CBF, by a deactivation of B waves, revealing monotonous UB waves.