Measuring intracranial pressure (ICP) is typically a highly invasive procedure, in which a ventricular catheter or pressure sensor is placed into the brain. To improve the availability of ICP measurements in non-intensive care patients and research and to reduce the invasiveness and underlying risks of ICP sensing, we developed a non-invasive method to measure ICP with Diffuse Correlation Spectroscopy (DCS) and machine learning. ICP baseline changes were induced in non-human primates <i>(Macaca mulatta)</i> through adjusting the height of a saline reservoir connected to the lateral ventricle via a catheter. ICP was precisely measured with an invasive parenchymal pressure sensor. Cerebral blood flow (CBF) was measured with DCS. The DCS system was operated by a software correlator able to resolve cardiac pulse waves at a sampling rate of 100Hz. To increase signal-to-noise ratio, multiple cardiac pulse waves in CBF were averaged based on systolic peak maximum in invasively measured arterial blood pressure. We hypothesized that the cerebral blood flow pulse waves will change their shape with increasing ICP. The shape of the curve was expressed in numerical features and passed into a regression forest training algorithm. Preliminary results show successful prediction of underlying ICP baselines by the decision forest in one animal. The prediction of non-invasive ICP was achieved with a sampling rate of 1 Hz, an equivalent of about 120 averaged pulses. A larger data set for increased generalizability is the next step to push this approach further.
Guiding treatment in traumatic brain injury based on managing and optimizing cerebral perfusion pressure, which is the difference between mean arterial blood pressure and intracranial pressure (ICP), has been demonstrated to improve patient outcome. However, this requires ICP to be measured, which currently is only possible by placing pressure probes inside the brain. The feasibility of optical systems to measure ICP non-invasively has shown preliminary promising evidence of feasibility. To pursue the goal of non-invasive ICP acquisition further, an understanding of the influence of different pressure changes on the brain and their hemodynamic response is necessary. To investigate the frequency content of hemodynamic reactions to pressure changes in both ICP as well as arterial blood pressure (ABP), we induced changes of both pressures in non-human primates. We then demonstrate that ABP and ICP changes both influence cerebral blood flow and hemoglobin concentrations, measured with diffuse correlation spectroscopy (DCS) and near-infrared spectroscopy (NIRS), respectively. We found that the magnitude of induced oscillations is dependent on the frequency of the oscillation. Our data suggests, changes in ABP and ICP influence the hemodynamics differently, which we can use as a basis for non-invasive ICP measurements.
Cerebral microvascular changes are influenced by intracranial pressure (ICP) as well as mean arterial blood pressure (MAP). The mechanism maintaining blood flow despite changes in either pressure is called cerebral autoregulation. This mechanism is known to be impaired in many diseases, including traumatic brain injury and stroke. Maintaining adequate cerebral blood flow and autoregulation is known to improve long term patient outcomes. However, the influence on the microvasculature and autoregulation of blood pressure vs. fluid increase, hence intracranial pressure, is not well understood. Furthermore, while blood pressure changes can readily be measured, intracranial pressure sensors are invasive and there is a need to overcome this invasiveness. We have recently shown that changes in cerebral perfusion pressure, which is the difference between blood pressure and intracranial pressure, can be correlated to total hemoglobin concentration, as measured non-invasively with near-infrared spectroscopy (NIRS) in non-human primates. These results showed that non-invasive intracranial pressure monitoring should be possible by means of vascular changes as measured with NIRS. In order to quantify autoregulation and differentiate between blood pressure and fluid increase driven vascular changes, we collected data on non-human primates. The primates’ brains were cannulated to induce rapid changes in ICP. Exsanguination was performed to reduce blood pressure. Data was collected with a combined frequency domain NIRS (OxiplexTS, ISS Inc.) and diffuse correlation spectroscopy (DCS) system for measuring hemoglobin concentration changes as well as blood flow changes, respectively. We will present on the experimental implementation as well as data analysis for quantifying cerebral autoregulation.
Although it is well documented that abnormal levels of either intraocular (IOP) or intracranial pressure (ICP) can lead to potentially blinding conditions, such as glaucoma and papilledema, little is known about how the pressures actually affect the eye. Even less is known about potential interplay between their effects, namely how the level of one pressure might alter the effects of the other. Our goal was to measure in-vivo the pressure-induced stretch and compression of the lamina cribrosa due to acute changes of IOP and ICP. The lamina cribrosa is a structure within the optic nerve head, in the back of the eye. It is important because it is in the lamina cribrosa that the pressure-induced deformations are believed to initiate damage to neural tissues leading to blindness. An eye of a rhesus macaque monkey was imaged in-vivo with optical coherence tomography while IOP and ICP were controlled through cannulas in the anterior chamber and lateral ventricle, respectively. The image volumes were analyzed with a newly developed digital image correlation technique. The effects of both pressures were highly localized, nonlinear and non-monotonic, with strong interactions. Pressure variations from the baseline normal levels caused substantial stretch and compression of the neural tissues in the posterior pole, sometimes exceeding 20%. Chronic exposure to such high levels of biomechanical insult would likely lead to neural tissue damage and loss of vision. Our results demonstrate the power of digital image correlation technique based on non-invasive imaging technologies to help understand how pressures induce biomechanical insults and lead to vision problems.
The mechanism that maintains a stable blood flow in the brain despite changes in cerebral perfusion pressure (CPP), and therefore guaranties a constant supply of oxygen and nutrients to the neurons, is known as cerebral auto-regulation (CA). In a certain range of CPP, blood flow is mediated by a vasomotor adjustment in vascular resistance through dilation of blood vessels. CA is known to be impaired in diseases like traumatic brain injury, Parkinson’s disease, stroke, hydrocephalus and others. If CA is impaired, blood flow and pressure changes are coupled and thee oxygen supply might be unstable. Lassen’s blood flow auto-regulation curve describes this mechanism, where a plateau of stable blood flow in a specific range of CPP corresponds to intact auto-regulation. Knowing the limits of this plateau and maintaining CPP within these limits can improve patient outcome. Since CPP is influenced by both intracranial pressure and arterial blood pressure, long term changes in either can lead to auto-regulation impairment. Non-invasive methods for monitoring blood flow auto-regulation are therefore needed. We propose too use Near infrared spectroscopy (NIRS) too fill this need. NIRS is an optical technique, which measures microvascular changes in cerebral hemoglobin concentration. We performed experiments on non-human primates during exsanguination to demonstrate that thee limits of blood flow auto-regulation can be accessed with NIRS.