A simple mathematical model of intracranial pressure (ICP) dynamics oriented to clinical practice is presented. It includes the hemodynamics of the arterial-arteriolar cerebrovascular bed, cerebrospinal fluid (CSF) production and reabsorption processes, the nonlinear pressure-volume relationship of the craniospinal compartment, and a Starling resistor mechanism for the cerebral veins. Moreover, arterioles are controlled by cerebral autoregulation mechanisms, which are simulated by means of a time constant and a sigmoidal static characteristic. The model is used to simulate interactions between ICP, cerebral blood volume, and autoregulation. Three different related phenomena are analyzed: the generation of plateau waves, the effect of acute arterial hypotension on ICP, and the role of cerebral hemodynamics during pressure-volume index (PVI) tests. Simulation results suggest the following: 1) ICP dynamics may become unstable in patients with elevated CSF outflow resistance and decreased intracranial compliance, provided cerebral autoregulation is efficient. Instability manifests itself with the occurrence of self-sustained plateau waves. 2) Moderate acute arterial hypotension may have completely different effects on ICP, depending on the value of model parameters. If physiological compensatory mechanisms (CSF circulation and intracranial storage capacity) are efficient, acute hypotension has only negligible effects on ICP and cerebral blood flow (CBF). If these compensatory mechanisms are poor, even modest hypotension may induce a large transient increase in ICP and a significant transient reduction in CBF, with risks of secondary brain damage. 3) The ICP response to a bolus injection (PVI test) is sharply affected, via cerebral blood volume changes, by cerebral hemodynamics and autoregulation. We suggest that PVI tests may be used to extract information not only on intracranial compliance and CSF circulation, but also on the status of mechanisms controlling CBF.

The relationships among cerebral blood flow, cerebral blood volume, intracranial pressure (ICP), and the action of cerebrovascular regulatory mechanisms (autoregulation and CO2 reactivity) were investigated by means of a mathematical model. The model incorporates the cerebrospinal fluid (CSF) circulation, the intracranial pressure-volume relationship, and cerebral hemodynamics. The latter is based on the following main assumptions: the middle cerebral arteries behave passively following transmural pressure changes; the pial arterial circulation includes two segments (large and small pial arteries) subject to different autoregulation mechanisms; and the venous cerebrovascular bed behaves as a Starling resistor. A new aspect of the model exists in the description of CO2 reactivity in the pial arterial circulation and in the analysis of its nonlinear interaction with autoregulation. Simulation results, obtained at constant ICP using various combinations of mean arterial pressure and CO2 pressure, substantially support data on cerebral blood flow and velocity reported in the physiological literature concerning both the separate effects of CO2 and autoregulation and their nonlinear interaction. Simulations performed in dynamic conditions with varying ICP underline the existence of a significant correlation between ICP dynamics and cerebral hemodynamics in response to CO2 changes. This correlation may significantly increase in pathological subjects with poor intracranial compliance and reduced CSF outflow. In perspective, the model can be used to study ICP and blood velocity time patterns in neurosurgical patients in order to gain a deeper insight into the pathophysiological mechanisms leading to intracranial hypertension and secondary brain damage.

The aim of this work was to analyze changes in cerebral hemodynamics and intracranial pressure (ICP) evoked by mean systemic arterial pressure (SAP) and arterial CO(2) pressure (Pa(CO(2))) challenges in patients with acute brain damage. The study was performed by means of a new simple mathematical model of intracranial hemodynamics, particularly aimed at routine clinical investigation. The model was validated by comparing its results with data from transcranial Doppler velocity in the middle cerebral artery (V(MCA)) and ICP measured in 44 tracings on 13 different patients during mean SAP and Pa(CO(2)) challenges. The validation consisted of individual identification of 6 parameters in all 44 tracings by means of a best fitting algorithm. The parameters chosen for the identification summarize the main aspects of intracranial dynamics, i.e., cerebrospinal fluid circulation, intracranial elastance, and cerebrovascular control. The results suggest that the model is able to reproduce the measured time patterns of V(MCA) and ICP in all 44 tracings by using values for the parameters that lie within the ranges reported in the pathophysiological literature. The meaning of parameter estimates is discussed, and comments on the main virtues and limitations of the present approach are offered.

A mathematical model of cerebral hemodynamics during vasospasm is presented. The model divides arterial hemodynamics into two cerebral territories: with and without spasm. It also includes collateral circulation between the two territories, cerebral venous hemodynamics, cerebrospinal fluid circulation, intracranial pressure (ICP) and the craniospinal storage capacity. Moreover, the pial artery circulation in both territories is affected by cerebral blood flow (CBF) autoregulation mechanisms. In this work, a numerical value to model parameters was given assuming that vasospasm affects only a single middle cerebral artery (MCA). In a first stage, the model is used to simulate some clinical results reported in the literature, concerning the patterns of MCA velocity, CBF and pressure losses during vasospasm. The agreement with clinical data turns out fairly good. In a second stage, a sensitivity analysis on some model parameters is performed (severity of caliber reduction, longitudinal extension of the spasm, autoregulation gain, ICP, resistance of the collateral circulation, and mean systemic arterial pressure) to clarify their influence on hemodynamics in the spastic territory. The results suggest that the clinical impact of vasospasm depends on several concomitant factors, which should be simultaneously taken into account to reach a proper diagnosis. In particular, while a negative correlation between MCA velocity and cross sectional area can be found until CBF is well preserved, a positive correlation may occur when CBF starts to decrease significantly. This might induce false-negative results if vasospasm is assessed merely through velocity measurements performed by the transcranial Doppler technique.

The information contained in the TCD waveform is affected by many factors, including ICP, SAP, autoregulation. and intracranial compliance. Model results indicate that only a comparative analysis of the concomitant changes in ultrasonographic quantities during multimodality monitoring may permit the assessment of several aspects of intracranial dynamics (cerebral blood flow changes, vascular pulsatility, ICP changes, intracranial compliance, CPP, and autoregulation).