Brain pulsations enlightened

Mechanistic-mathematical modeling of intracranial pressure (ICP) profiles over a single heart cycle. The fundament of the ICP curve form

The intracranial pressure (ICP) curve with its different peaks has been comprehensively studied, but the exact physiological mechanisms behind its morphology has not been revealed. If the pathophysiology behind deviations from the normal ICP curve form could be identified, it could be vital information to diagnose and treat each single patient. A mathematical model of the hydrodynamics in the intracranial cavity over single heart cycles was developed. A Windkessel model approach was generalized but the unsteady Bernoulli equation was utilized for blood flow and CSF flow. This is a modification of earlier models using the extended and simplified classical Windkessel analogies to a model that is based on mechanisms rooted in the laws of physics. The improved model was calibrated with patient data for cerebral arterial inflow, venous outflow, cerebrospinal fluid (CSF), and ICP over one heart cycle from 10 neuro-intensive care unit patients. A priori model parameter values were obtained by considering patient data and values taken from earlier studies. These values were used as an initial guess for an iterated constrained-ODE (ordinary differential equation) optimization problem with cerebral arterial inflow data as input into the system of ODEs. The optimization routine found patient-specific model parameter values that produced model ICP curves that showed excellent agreement with clinical measurements while model venous and CSF flow were within a physiologically acceptable range. The improved model and the automated optimization routine gave better model calibration results compared to previous studies. Moreover, patient-specific values of physiologically important parameters like intracranial compliance, arterial and venous elastance, and venous outflow resistance were determined. The model was used to simulate intracranial hydrodynamics and to explain the underlying mechanisms of the ICP curve morphology. Sensitivity analysis showed that the order of the three main peaks of the ICP curve was affected by a decrease in arterial elastance, a large increase in resistance to arteriovenous flow, an increase in venous elastance, or a decrease in resistance to CSF flow in the foramen magnum; and the frequency of oscillations were notably affected by intracranial elastance. In particular, certain pathological peak patterns were caused by these changes in physiological parameters. To the best of our knowledge, there are no other mechanism-based models associating the pathological peak patterns to variation of the physiological parameters.

Cerebrovascular impedance estimation with near-infrared and diffuse correlation spectroscopy

SIGNIFICANCE

Cerebrovascular impedance (CVI) is related to cerebral autoregulation (CA), which is the mechanism of the brain to maintain near-constant cerebral blood flow (CBF) despite changes in cerebral perfusion pressure (CPP). Changes in blood vessel impedance enable the stabilization of blood flow. Due to the interplay between CVI and CA, assessment of CVI may enable quantification of CA and may serve as a biomarker for cerebral health.

AIM

We developed a method to quantify CVI based on a combination of diffuse correlation spectroscopy (DCS) and continuous wave (CW) near-infrared spectroscopy (NIRS). Data on healthy human volunteers were used to validate the method.

APPROACH

A combined high-speed DCS-NIRS system was developed, allowing for simultaneous, noninvasive blood flow, and volume measurements in the same tissue compartment. Blood volume was used as a surrogate measurement for blood pressure and CVI was calculated as the spectral ratio of blood volume and blood flow changes. This technique was validated on six healthy human volunteers undergoing postural changes to elicit CVI changes.

RESULTS

Averaged across the six subjects, a decrease in CVI was found for a head of bed (HOB) tilting of - 40    deg . These impedance changes were reversed when returning to the horizontal (0 deg) HOB baseline.

CONCLUSIONS

We developed a combined DCS-NIRS system, which measures CBF and volume changes, which we demonstrate can be used to measure CVI. Using CVI as a metric of CA may be beneficial for assessing cerebral health, especially in patients where CPP is altered.

Increased Intracranial Pressure Attenuates the Pulsating Component of Cerebral Venous Outflow

Background

The underlying physiology of the intracranial pressure (ICP) curve morphology is still poorly understood. If this physiology is explained it could be possible to extract clinically relevant information from the ICP curve. The venous outflow from the cranial cavity is pulsatile, and in theory the pulsatile component of venous outflow from the cranial cavity should be attenuated with increasing ICP. In this study, we explored the relationship between ICP and the pulsatility of the venous outflow from the intracranial cavity.

Methods

Thirty-seven neuro-intensive care patients that had been examined with phase-contrast magnetic resonance imaging regarding cerebral blood flow (CBF) through the internal carotid and vertebral arteries and venous flow in the internal jugular veins were retrospectively included. The pulsatility of the jugular flow was determined by calculating the venous pulsatile index. The results were correlated to clinical data registered in the patient data monitoring system, including ICP and cerebral perfusion pressure (CPP).

Results

CBF was 996 ± 298 ml/min, and the flow in the internal jugular veins equaled 67 ± 17% of the CBF, with a range of 22–97%. The venous pulsatile index correlated negatively to ICP (R = − 0.47 p = 0.003). The lowest flow in the internal jugular veins over the cardiac cycle (F_min) was not correlated to ICP. Temperature, end-tidal CO₂, MAP, and CPP were not correlated to venous pulsatility.

Conclusion

An increase in ICP correlates to a lower pulsatility of the venous outflow from the cranial cavity. A lower pulsatility could be due to increased pressure requirements to compress intracranial veins with increasing ICP.

Measuring intracranial pressure by invasive, less invasive or non-invasive means: limitations and avenues for improvement

Sixty years have passed since neurosurgeon Nils Lundberg presented his thesis about intracranial pressure (ICP) monitoring, which represents a milestone for its clinical introduction. Monitoring of ICP has since become a clinical routine worldwide, and today represents a cornerstone in surveillance of patients with acute brain injury or disease, and a diagnostic of individuals with chronic neurological disease. There is, however, controversy regarding indications, clinical usefulness and the clinical role of the various ICP scores. In this paper, we critically review limitations and weaknesses with the current ICP measurement approaches for invasive, less invasive and non-invasive ICP monitoring. While risk related to the invasiveness of ICP monitoring is extensively covered in the literature, we highlight other limitations in current ICP measurement technologies, including limited ICP source signal quality control, shifts and drifts in zero pressure reference level, affecting mean ICP scores and mean ICP-derived indices. Control of the quality of the ICP source signal is particularly important for non-invasive and less invasive ICP measurements. We conclude that we need more focus on mitigation of the current limitations of today's ICP modalities if we are to improve the clinical utility of ICP monitoring.

Validation of a mathematical model for understanding intracranial pressure curve morphology

The physiology underlying the intracranial pressure (ICP) curve morphology is not fully understood. Recent research has suggested that the morphology could be dependent on arterial cerebral inflow and the physiological and pathophysiological properties of the intracranial cavity. If understood, the ICP curve could provide information about the patient’s cerebrovascular state important in individualizing treatment in neuro intensive care patients. A mathematical model based on known physiological properties of the intracranial compartment was created. Clinical measurements from ten neuro intensive care patients in whom intracranial arterial blood inflow, venous blood outflow and cerebrospinal fluid flow over the foramen magnum had been measured with phase contrast MRI, concomitant with ICP measurements were used to validate the model. In nine patients the mathematical model was able to create an ICP curve mimicking the measured by using arterial intracranial inflow and adjusting physiological parameters of the model. The venous outflow and cerebrospinal fluid (CSF) flow over the foramen magnum predicted by the model were within physiologically reasonable limits and in most cases followed the MRI measured values in close adjunct. The presented model could produce an ICP curve in close resemblance of the in vivo measured curves. This strengthens the hypothesis that the ICP curve is shaped by the arterial intracranial inflow and the physiological properties of the intracranial cavity.