Model-Based Noninvasive Estimation of Intracranial Pressure from Cerebral Blood Flow Velocity and Arterial Pressure

Intracranial pressure (ICP) is affected in many neurological conditions. Clinical measurement of pressure on the brain currently requires placing a probe in the cerebrospinal fluid compartment, the brain tissue, or other intracranial space. This invasiveness limits the measurement to critically ill patients. Because ICP is also clinically important in conditions ranging from brain tumors and hydrocephalus to concussions, noninvasive determination of ICP would be desirable. Our model-based approach to continuous estimation and tracking of ICP uses routinely obtainable time-synchronized, noninvasive (or minimally invasive) measurements of peripheral arterial blood pressure and blood flow velocity in the middle cerebral artery (MCA), both at intra-heartbeat resolution. A physiological model of cerebrovascular dynamics provides mathematical constraints that relate the measured waveforms to ICP. Our algorithm produces patient-specific ICP estimates with no calibration or training. Using 35 hours of data from 37 patients with traumatic brain injury, we generated ICP estimates on 2665 nonoverlapping 60-beat data windows. Referenced against concurrently recorded invasive parenchymal ICP that varied over 100 millimeters of mercury (mmHg) across all records, our estimates achieved a mean error (bias) of 1.6 mmHg and SD of error (SDE) of 7.6 mmHg. For the 1673 data windows over 22 hours in which blood flow velocity recordings were available from both the left and the right MCA, averaging the resulting bilateral ICP estimates reduced the bias to 1.5 mmHg and SDE to 5.9 mmHg. This accuracy is already comparable to that of some invasive ICP measurement methods in current clinical use.National Institutes of Health (U.S.) (R01 EB001659)CIMIT: Center for Integration of Medicine and Innovative Technolog

Monitoring of Intracranial Pressure in Patients with Traumatic Brain Injury

Since Monro published his observations on the nature of the contents of the intracranial space in 1783 there has been investigation of the unique relationship between the contents of the skull and the intracranial pressure (ICP). This is particularly true following traumatic brain injury (TBI), where it is clear that elevated ICP due to the underlying pathological processes is associated with a poorer clinical outcome. Consequently, there is considerable interest in monitoring and manipulating ICP In patients with TBI.The two techniques most commonly used in clinical practice to monitor ICP are via an intraventricular or intraparenchymal catheter with a microtransducer system. Both of these techniques are invasive and are thus associated with complications such as haemorrhage and infection. For this reason, significant research effort has been directed towards development of a non-invasive method to measure ICP. These include imaging based studies using computed tomography (CT) and magnetic resonance imaging (MRI), transcranial Doppler sonography (TCD), near-infrared spectroscopy (NIRS), tympanic membrane displacement (TMD), visual-evoked potentials (VEPs), measurements of optic nerve sheath diameter (ONSD) and other measurements of the optic nerve, retina, pupil and ophthalmic artery.The principle aims of ICP monitoring in TBI are to allow early detection of secondary haemorrhage or ischaemic processes and to guide therapies that limit intracranial hypertension and optimise cerebral perfusion. However, information from the ICP value and the ICP waveform can also be used to estimate intracranial compliance, assess cerebrovascular pressure reactivity and attempt to forecast future episodes of intracranial hypertension

Mathematical model of the cerebral circulation and distribution of cerebrospinal fluid

Shifts in cerebral fluid are known to be important in a number of diseases, and in conditions of microgravity such as space travel. In this work we develop a fluid mechanical model from firstprinciples incorporating key features of the flow of both blood and cerebrospinal fluid (CSF) in the intracranial and spinal spaces. For the cerebral blood vessels, we model the arteries and veins as symmetric bifurcating trees with constant geometrical scaling factors between generations, assume one-dimensional flow in each vessel and account for elastic effects via a pressure-area relationship, and we assume the capillaries have a constant resistance. We treat the vessel walls as porous media to find the transmural flux of plasma. We assume flow between the other compartments to be proportional to the pressure difference; additionally, the flow to the outer-dural space is assumed to be one-way. The set of ordinary differential equations for the evolution of the fluid pressures and volumes of each compartment can be solved numerically. Additional features include autoregulation, which we model by ensuring constant pressure at the microcirculation, meaning the resulting model must be solved iteratively. Also, we can model the effect of postural changes by including hydrostatic effects in the spinal column. The results are in accordance with physiological measurements and indicate that the pressure in the vasculature is highly sensitive to changes in vessel geometry, which also affects the transmural flux, whilst ventricular and spinal subarachnoid spaces are sensitive to compliances. We investigate transitions from supine to standing and upside down positions and also the effect of the external pressure surrounding the outer-dural spinal compartment. The model is computationally inexpensive and can be used as a platform for further analysis of cerebrovascular behaviour.Open Acces

Modeling and estimation for non-invasive monitoring of intracranial pressure and cerebrovascular autoregulation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 187-202).Brain tissue is highly vulnerable to unbalanced oxygen demand and supply. A few seconds of oxygen deficit may trigger neurological symptoms, and sustained oxygen deprivation over a few minutes may result in severe and often irreversible brain damage. The rapid dynamics coupled with the potential for severe injury necessitate continuous cerebrovascular monitoring in the populations at greatest risk for developing or exacerbating brain injury. Intracranial pressure (ICP), which is the pressure of the cerebrospinal fluid, is a vitally important variable to monitor in a wide spectrum of medical conditions involving the brain, such as traumatic brain injury, stroke, hydrocephalus, or brain tumors. However, clinical measurement of ICP is highly invasive, as it requires neurosurgical penetration of the skull and placement of a pressure sensor in the brain tissue or ventricular spaces. Measurement of ICP is thus currently limited to only those patient populations in which the benefits of obtaining the measurement outweigh the significant attendant risks, thus excluding a large pool of patients who could potentially benefit from ICP monitoring. The primary goal of our work is to address the non-invasive monitoring of ICP. A secondary aim of this work is to develop methods for the assessment of cerebrovascular autoregulation, which is the innate ability of the vasculature to maintain cerebral blood flow in the face of changes in cerebral perfusion pressure. Cerebrovascular autoregulation is often impaired in patients with brain trauma or stroke, and also in pre-term neonates, as their cerebrovascular system is not fully matured. We develop methods for non-invasive, continuous, calibration-free and patientspecific ICP monitoring. Specifically, we present a model-based approach to providing real-time estimates of ICP and cerebrovascular resistance and compliance, for each cardiac cycle, from non- or minimally-invasive time-synchronized measurements of arterial blood pressure and cerebral blood flow velocity in a major cerebral artery. In the first step, our approach exploits certain features of cerebrovascular physiology, along with model reduction ideas, to deduce a simple mathematical model of the cerebrovascular system. In the second step, we develop algorithms to compute robust estimates of model parameters by processing the measured waveforms through the constraints provided by the models dynamic equation. For validation, our non-invasive estimates of ICP were compared against invasive measurements from 45 comatose brain-injury patients, with a total of 35 hours of data (over 150,000 beats), providing more than 3,500 independent ICP estimates. Our estimates track measured ICP closely over a range of dynamic variations. Pooling all independent estimates resulted in a mean estimation error (bias) of less than 2 mmHg and a standard deviation of error of about 8 mmHg. We also suggest how variations in estimated cerebrovascular resistance and compliance in response to variations in cerebral perfusion pressure may be used to provide novel approaches for assessment of cerebrovascular autoregulation.by Faisal M. Kashif.Ph.D

Physiological and pharmacological modelling in neurological intensive care and anaesthesia

Mathematical models of physiological processes can be used in critical care and anaesthesia to improve the understanding of disease processes and to guide treatment. This thesis provides a detailed description of two studies that are related through their shared aim of modelling different aspects of brain physiology. The Relationship Between Transcranial Bioimpedance and Invasive Intracranial Pressure Measurement in Traumatic Brain Injury Patients (BioTBI) Study describes an attempt to model intracranial pressure (ICP) in patients admitted with severe traumatic brain injury (TBI). It is introduced with a detailed discussion of the monitoring and modelling of ICP in patients with TBI alongside the rationale for considering transcranial bioimpedance (TCB) as a non-invasive approach to estimating ICP. The BioTBI Study confirmed a significant relationship between TCB and invasively measured ICP in ten patients admitted to the neurological intensive care unit (NICU) with severe TBI. Even when using an adjusted linear modelling technique to account for patient covariates, the magnitude of the relationship was small (r-squared = 0.32) and on the basis of the study, TCB is not seen as a realistic technique to monitor ICP in TBI. Target controlled infusion (TCI) of anaesthetic drugs exploit known pharmacokinetic pharmacodynamic (PKPD) models to achieve set concentrations in the plasma or an effect site. Following a discussion of PKPD model development for the anaesthetic drug propofol, the Validation Study of the Covariates Model (VaSCoM) describes a joint PKPD study of the Covariates Model. Pharmacokinetic validation of plasma concentrations predicted by the model in forty patients undergoing general anaesthesia confirmed a favourable overall bias (3%) and inaccuracy (25%) compared to established PKPD models. The first description of the pharmacodynamic behaviour of the Covariates Model is provided with an estimated rate constant for elimination from the effect site compartment (ke0) of 0.21 to 0.27 min-1

An Electromechanical Hydrocephalus Shunting System

Hydrocephalus (HC) is a disease that occurs as a result of the increased cerebrospinal fluid (CSF) amount in the brain. The disease is managed by what is termed a shunt, which is a medical tool that is implanted surgically to divert CSF from the brain. As a result of their passive design nature, these shunts have multiple fundamental shortcomings and failures, causing considerable inconvenience and risks to the patient. The aim of this research is to design an agile and active HC management framework that is capable of addressing the shortcomings and failures of the currently used CSF shunts in the most convenient manner for the patient and to advance research regarding hydrocephalus management. Thus, this work proposes an active patient shunting and monitoring system layout for CSF drainage and patient follow-up. The system layout is designed so that each component is put in place to address the shortcomings of passive shunts. To achieve this, the shunting system proposed is a closed-loop system that consists of multiple sensory inputs for patient monitoring and CSF drainage control to keep the patient's intracranial pressure (ICP) at the required level. As various studies looked at new shunting systems concepts from the perspective of algorithms, the novelty and focus of this work is on the hardware side of the active shunting system. The proposed electromechanical shunting system's core hardware component is the valve it uses. Hence, this study provides a detailed design and methodology of a novel electromechanical valve. This is where the main gap of knowledge has been identified, as current research is still focused on passive valves. Mathematical modelling was conducted during the valve conceptualisation process. The results showcased that although current passive valves cannot address hydrostatic pressure effects, they are three times more active than automated valves and can generate a smoother pressure profile. Based on this, a novel concept of a hybrid electromechanical valve that utilises an ultrasonic element attached to a ball-in-cone system is proposed. The design methodology of the valve components included the use of computer modelling, where forces inside the flow compartment were obtained using computational fluid dynamics (CFD). Spring sizing and ultrasonic element design were carried out using finite element analysis (FEA). The designed valve operates under a 3.5 V high-frequency current, has a 10 – 20 mmHg range, and can drain CSF up to 300 mL/h. The proposed electromechanical valve showcased that it possesses multiple features that the current passive valves do not. This includes malfunction detection, event recognitions, and wireless pressure settings revisions. Its main drawback is its lack of blockage management. A wearable device was developed to diagnose and monitor normal pressure hydrocephalus (NPH) patients, as NPH is not associated with increased intracranial pressure (ICP). The device consists of a 3-axis ± 3.7 g accelerometer to measure gait patterns, an HC-05 bluetooth module, a 3.7 V battery, and an Attiny85 microcontroller. A functionality test was carried out on the device by conducting a vibrational analysis assessment using a miniature shaker. After calibration, the device proved that it could supply accurate acceleration data on all three axes. The device range, sensitivity, placement, and multi-axis use show that it may produce more accurate results compared to those used in the literature

A Review of Physiological Simulation Models of Intracranial Pressure Dynamics

This paper reviews the literature regarding the development, testing, and application of physiology-based computer simulation models of intracranial pressure dynamics. Detailed comparative information is provided in tabular format about the model variables and logic, any data collected, model testing and validation methods, and model results. Several syntheses are given that summarize the research carried out by influential research teams and researchers, review important findings, and discuss the methods employed, limitations, and opportunities for further research