Inferring cerebrovascular changes from latencies of systemic and intracranial pulses: a model-based latency subtraction algorithm

Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach

OBJECTIVE

We present a framework for analyzing the morphology of intracranial pressure (ICP). The analysis of ICP signals is challenging due to the non-linear and non-Gaussian characteristics of the signal dynamics, inevitable corruption by noise and artifacts, and variations in ICP pulse morphology among individuals with different neurological conditions. Existing frameworks make unrealistic assumptions regarding ICP dynamics and are not tuned for individual patients.

APPROACH

We propose a dynamic Bayesian network for automated detection of three major ICP pulsatile components. The proposed model captures the non-linear and non-Gaussian dynamics of ICP morphology and further adapts to a patient as the individual's ICP measurements are received. To make the approach more robust, we leverage evidence reversal and present an inference algorithm to obtain the posterior distribution over the locations of pulsatile components.

MAIN RESULTS

We evaluate our approach on a dataset with over 700 h of recordings from 66 neurological patients, where the pulsatile components were annotated by prior studies. The algorithm obtains accuracies of 96.56%, 92.39%, and 94.04% for the detection of each pulsatile component in the test set, showing significant improvement over existing approaches.

SIGNIFICANCE

Continuous ICP monitoring is essential in guiding the treatment of neurological conditions such as traumatic brain injuries. An automated approach for ICP morphology analysis is a step towards enhancing patient care with minimal supervision. Compared to previous methods, our framework offers several advantages. It learns the parameters that model each patient's ICP in an unsupervised manner, resulting in an accurate morphology analysis. The Bayesian model-based framework provides uncertainty estimates and reveals interesting facts about the ICP dynamics. The framework can readily be applied to replace existing morphological analysis methods and support the use of ICP pulse morphological features to aid the monitoring of pathophysiological changes of relevance to the care of patients with acute brain injuries.

Cardiac-gated steady-state multifrequency magnetic resonance elastography of the brain: Effect of cerebral arterial pulsation on brain viscoelasticity

In-vivo brain viscoelasticity measured by magnetic resonance elastography (MRE) is a sensitive imaging marker for long-term biophysical changes in brain tissue due to aging and disease; however, it is still unknown whether MRE can reveal short-term periodic alterations of brain viscoelasticity related to cerebral arterial pulsation (CAP). We developed cardiac-gated steady-state MRE (ssMRE) with spiral readout and stroboscopic sampling of continuously induced mechanical vibrations in the brain at 20, 31.25, and 40 Hz frequencies. Maps of magnitude |G*| and phase ϕ of the complex shear modulus were generated by multifrequency dual visco-elasto inversion with a temporal resolution of 40 ms over 4 s. The method was tested in 12 healthy volunteers. During cerebral systole, |G*| decreased by 6.6 ± 1.9% (56 ± 22 Pa, p < 0.001, mean ± SD), whereas ϕ increased by 0.5 ± 0.5% (0.006 ± 0.005 rad, p = 0.002). The effect size of CAP-induced softening slightly decreased with age by 0.10 ± 0.05% per year (p = 0.04), indicating lower cerebral vascular compliance in older individuals. Our data show for the first time that the brain softens and becomes more viscous during systole, possibly due to an effect of CAP-induced arterial expansion and increased blood volume on effective-medium tissue properties. This sensitivity to vascular-solid tissue interactions makes ssMRE potentially useful for detection of cerebral vascular disease.

Phase-shift between arterial flow and ICP pulse during infusion test

BACKGROUND

The dynamic relationship between pulse waveform of intracranial pressure (ICP) and transcranial Doppler (TCD) cerebral blood flow velocity (CBFV) may contain information about cerebrospinal compliance. This study investigated the possibility by focusing on the phase shift between fundamental harmonics of CBFV and ICP.

METHODS

Thirty-seven normal pressure hydrocephalus patients (20 men, mean age 58) underwent the cerebrospinal fluid (CSF) infusion tests. The infusion was performed via pre-implanted Ommaya reservoir. The TCD FV was recorded in the middle cerebral artery. Resulting continuous ICP and pressure-volume (PV) signals were analyzed by ICM+ software.

RESULTS

In initial stage of the CSF infusion, the phase shift was negative (median value = -11°, range = +60 to -117). There was significant inverse association of phase shift with brain elasticity (R = -0.51; p = 0.0009). In all tests, phase shift consistently decreased during gradual elevation of ICP (p = 0.00001). Magnitude of decrease in phase shift was inversely related to the peak-to-peak amplitude of ICP pulse waveform at a baseline (R = -0.51; p = 0.001).

CONCLUSIONS

Phase shift between fundamental harmonics of ICP and TCD waveforms decreases during elevation of ICP. This is caused by an increase of time delay between systolic peak of flow velocity wave and ICP pulse.

Continuous detection of cerebral vasodilatation and vasoconstriction using intracranial pulse morphological template matching

Although accurate and continuous assessment of cerebral vasculature status is highly desirable for managing cerebral vascular diseases, no such method exists for current clinical practice. The present work introduces a novel method for real-time detection of cerebral vasodilatation and vasoconstriction using pulse morphological template matching. Templates consisting of morphological metrics of cerebral blood flow velocity (CBFV) pulse, measured at middle cerebral artery using Transcranial Doppler, are obtained by applying a morphological clustering and analysis of intracranial pulse algorithm to the data collected during induced vasodilatation and vasoconstriction in a controlled setting. These templates were then employed to define a vasodilatation index (VDI) and a vasoconstriction index (VCI) for any inquiry data segment as the percentage of the metrics demonstrating a trend consistent with those obtained from the training dataset. The validation of the proposed method on a dataset of CBFV signals of 27 healthy subjects, collected with a similar protocol as that of training dataset, during hyperventilation (and CO₂ rebreathing tests) shows a sensitivity of 92% (and 82%) for detection of vasodilatation (and vasoconstriction) and the specificity of 90% (and 92%), respectively. Moreover, the proposed method of detection of vasodilatation (vasoconstriction) is capable of rejecting all the cases associated with vasoconstriction (vasodilatation) and outperforms other two conventional techniques by at least 7% for vasodilatation and 19% for vasoconstriction.

Steady-state indicators of the intracranial pressure dynamic system using geodesic distance of the ICP pulse waveform

Normal functioning of the brain depends on the homeostasis (∼ steady state) of its various physiological sub-systems, one of which is the intracranial pressure (ICP) dynamic system. The ICP dynamic system of an injured brain is susceptible to various acute changes that should ideally be detected by ICP monitoring even for comatose patients. However, the status quo of ICP monitoring solely targets mean ICP. We aimed to demonstrate a novel approach to detect acute deviation from steady state of an ICP dynamic system in an absence of significant mean ICP changes. We hypothesized that steady state of ICP dynamic systems is reflected as ICP pulses of similar mean ICP levels resembling each other for a given subject. A general framework was used to derive such a steady-state indicator that can accommodate different metrics of inter-pulse distance and different statistics of the distance histograms. In addition to conventional Euclidean distance and Pearson correlation, geodesic distance between pulses was introduced as a novel metric. These different ways of calculating steady-state indicators under the proposed framework were evaluated on three types of continuous ICP recordings: (1) those between two consecutive brain imaging studies that demonstrated acute ventricular enlargement for slit ventricle syndrome (SVS) patients undergoing a trial of shunt externalization and clamping (SVS+); (2) those between consecutive brain imaging studies from the SVS patients under the same trial but without ventricular enlargement (SVS-); (3) overnight recordings from normal pressure hydrocephalus (NPH) patients. It was observed that only the standard deviation of geodesic distance correctly differentiated between SVS+ and SVS- and between SVS+ and NPH while avoiding discriminating between SVS- and NPH. It was also found that 45% SVS+ cases had a multimodal geodesic distance histogram while none of SVS- and 3.8% of NPH cases had such a multimodal histogram. Pulses with a large number of distant pulses for the five multimodal-histogram SVS+ cases fell in short time windows indicating that acute ventricular changes may have occurred in these confined time windows during which no significant changes of mean ICP were observed. In contrast, the pulses with a large number of distant pulses for the two multimodal-histogram NPH cases did not cluster temporally. In conclusion, the geodesic inter-pulse distance is a promising metric to quantify distance intrinsic to the underneath geometric structure of ICP signals and hence is a more suitable way to derive a steady-state indicator of an ICP dynamic system.

Latency relationships between cerebral blood flow velocity and intracranial pressure

Pulsatile intracranial pressure (ICP) is a key to the understanding of several neurological disorders in which compliance is altered, e.g., hydrocephalus. A recently proposed model suggests that ICP pulse is a standing wave and not a transmitted wave. The present work, aimed at obtaining a better understanding of the pulsatility in the cranium, tries to test the following hypotheses: first, ICP pulse onset latency would be lower than that of cerebral blood flow velocity (CBFV) pulses measured at a distal vessel; second, CBFV pulse at different intracranial arteries will have different pulse onset latencies, and hence they are not generated as a standing wave. The dataset used in the present study consists of ICP and CBFV signals collected from 60 patients with different diagnoses. The results reveal that the ICP pulse leads CBFV for 90% of the patients regardless of the diagnosis and mean ICP value. In addition, we show that CBFV pulse onset latency is roughly determined by the distance of the measurement point to the heart. We conclude that the ICP signal is not generated as a standing wave and that ICP pulse onset may be related to the arteries proximal to the heart.

Consistent changes in intracranial pressure waveform morphology induced by acute hypercapnic cerebral vasodilatation

BACKGROUND

Intracranial pressure (ICP) remains a pivotal physiological signal for managing brain injury and subarachnoid hemorrhage (SAH) patients in neurocritical care units. Given the vascular origin of the ICP, changes in ICP waveform morphology could be used to infer cerebrovascular changes. Clinical validation of this association in the setting of brain trauma, and SAH is challenging due to the multi-factorial influences on, and uncertainty of, the state of the cerebral vasculature.

METHODS

To gain a more controlled setting, in this articel, we study ICP signals recorded in four uninjured patients undergoing a CO2 inhalation challenge in which hypercapnia induced acute cerebral vasodilatation. We apply our morphological clustering and analysis of intracranial pressure (MOCAIP) algorithm to identify six landmarks on individual ICP pulses (based on the three established ICP sub-peaks; P1, P2, and P3) and extract 128 ICP morphological metrics. Then by comparing baseline, test, and post-test data, we assess the consistency and rate of change for each individual metric.

RESULTS

Acute vasodilatation causes consistent changes in a total of 72 ICP pulse morphological metrics and the P2 sub-region responds to cerebral vascular changes in the most consistent way with the greatest change as compared to P1 and P3 sub-regions.

CONCLUSIONS

Since the dilation/constriction of the cerebral vasculature resulted in detectable consistent changes in ICP MOCIAP metrics, by an extended monitoring practice of ICP that includes characterizing ICP pulse morphology, one can potentially detect cerebrovascular changes, continuously, for patients under neurocritical care.

An extended model of intracranial latency facilitates non-invasive detection of cerebrovascular changes

A method has been recently developed to reduce the confounding factors of extracranial origins on the intracranial latency (the time interval between the electrocardiogram QRS component and the initial inflection of the resulting pulse). Although, the proposed model was shown to portray a better characterization of cerebral vasculature, the parameters of the model and their physiological interpretations have not been fully explored. The present work improves the physiological understanding of these parameters, refines the model and extends its ability to monitor real-time changes in overall cerebrovascular resistance. We show that the slope of the linear model which relates the latency of arterial blood pressure to that of the cerebral blood flow velocity, could be a measure of resistance, and that the intercept is a function of slope and pre-ejection period. A dataset of cerebral blood flow velocity and arterial blood pressure signals from 18 normal subjects at rest was used to validate the derived parameters of the model. Also, the results of further data processing verified our hypothesis that the slope of the model would significantly increase during a period of CO₂ rebreathing, due to dilation of the vessels and reduction of cerebrovascular resistance (p ≤ 0.02). Finally as the slope of the proposed model is shown to be highly correlated with other conventional measures of cerebrovascular resistance, (resistance area product and critical closing pressure), we conclude that the derived slope metric is a measure of overall cerebrovascular resistance and therefore could be useful in guiding the non-invasive cerebrovascular management of patients.

Intracranial pressure pulse morphological features improved detection of decreased cerebral blood flow

We investigated whether intracranial pressure (ICP) pulse morphological metrics could be used to realize continuous detection of low cerebral blood flow. Sixty-three acutely brain injured patients with ICP monitoring, daily (133)Xenon cerebral blood flow (CBF) and daily transcranial Doppler (TCD) assessments were studied. Their ICP recordings were time-aligned with the CBF and TCD measurements so that a 1 h ICP segment near the CBF and TCD measurements was obtained. Each of these recordings was processed by the Morphological Cluster and Analysis of Intracranial Pressure (MOCAIP) algorithm to extract pulse morphological metrics. Then the differential evolution algorithm was used to find the optimal combination of the metrics that provided, using the regularized linear discriminant analysis, the largest combined positive predictivity and sensitivity. At a CBF threshold of 20 ml/min/100 g, a sensitivity of 81.8 +/- 0.9% and a specificity of 50.1 +/- 0.2% were obtained using the optimal combination of conventional TCD and blood analysis metrics as input to a regularized linear classifier. However, using the optimal combination of the MOCAIP metrics alone we were able to achieve a sensitivity of 92.5 +/- 0.7% and a specificity of 84.8 +/- 0.8%. Searching the optimal combination of all available metrics, we achieved the best result that was marginally better than those from using MOCAIP alone. This study demonstrated that the potential role of ICP monitoring may be extended to provide an indicator of low global cerebral blood perfusion.