Fully automated, real-time, calibration-free, continuous noninvasive estimation of intracranial pressure in children

Intracranial pressure-flow relationships in traumatic brain injury patients expose gaps in the tenets of models and pressure-oriented management

Background: The protocols and therapeutic guidance established for treating traumatic brain injury (TBI) in neurointensive care focus on managing cerebral blood flow (CBF) and brain tissue oxygenation based on pressure signals. The decision support process relies on assumed relationships between cerebral perfusion pressure (CPP) and blood flow, pressure-flow relationships (PFRs), and shares this framework of assumptions with mathematical intracranial hemodynamics models. These foundational assumptions are difficult to verify, and their violation can impact clinical decision-making and model validity. Methods: A hypothesis- and model-driven method for verifying and understanding the foundational intracranial hemodynamic PFRs is developed and applied to a novel multi-modality monitoring dataset. Results: Model analysis of joint observations of CPP and CBF validates the standard PFR when autoregulatory processes are impaired as well as unmodelable cases dominated by autoregulation. However, it also identifies a dynamical regime -or behavior pattern-where the PFR assumptions are wrong in a precise, data-inferable way due to negative CPP-CBF coordination over long timescales. This regime is of both clinical and research interest: its dynamics are modelable under modified assumptions while its causal direction and mechanistic pathway remain unclear. Conclusion: Motivated by the understanding of mathematical physiology, the validity of the standard PFR can be assessed a) directly by analyzing pressure reactivity and mean flow indices (PRx and Mx) or b) indirectly through the relationship between CBF and other clinical observables. This approach could potentially help to personalize TBI care by considering intracranial pressure and CPP in relation to other data, particularly CBF. The analysis suggests a threshold using clinical indices of autoregulation jointly generalizes independently set indicators to assess CA functionality. These results support the use of increasingly data-rich environments to develop more robust hybrid physiological-machine learning models.

Influence of age on the relation between body position and noninvasively acquired intracranial pulse waves

The capacitive measurement of the head's dielectric properties has been recently proposed as a noninvasive method for deriving surrogates of craniospinal compliance (CC), a parameter used in the evaluation of space-occupying neurological disorders. With the higher prevalence of such disorders in the older compared to the younger population, data on the head's dielectric properties of older healthy individuals would be of particularly high value before assessing pathologic changes. However, so far only measurements on young volunteers (< 30 years) were reported. In the present study, we have investigated the capacitively obtained electric signal known as W in older healthy individuals. Thirteen healthy subjects aged > 60 years were included in the study. W was acquired in the resting state (supine horizontal position), and during head-up and head-down tilting. AMP, the peak-to-valley amplitude of W related to cardiac action, was extracted from W. AMP was higher in this older cohort compared to the previously investigated younger one (0°: 5965 ± 1677 arbitrary units (au)). During head-up tilting, AMP decreased (+ 60°: 4446 ± 1620 au, P < 0.001), whereas it increased during head-down tilting (- 30°: 7600 ± 2123 au, P < 0.001), as also observed in the younger cohort. Our observation that AMP, a metric potentially reflective of CC, is higher in the older compared to the younger cohort aligns with the expected decrease of CC with age. Furthermore, the robustness of AMP is reinforced by the consistent relative changes observed during tilt testing in both cohorts.

Noninvasive Neuromonitoring Modalities in Children Part I: Pupillometry, Near-Infrared Spectroscopy, and Transcranial Doppler Ultrasonography

BACKGROUND

Noninvasive neuromonitoring in critically ill children includes multiple modalities that all intend to improve our understanding of acute and ongoing brain injury.

METHODS

In this article, we review basic methods and devices, applications in clinical care and research, and explore potential future directions for three noninvasive neuromonitoring modalities in the pediatric intensive care unit: automated pupillometry, near-infrared spectroscopy, and transcranial Doppler ultrasonography.

RESULTS

All three technologies are noninvasive, portable, and easily repeatable to allow for serial measurements and trending of data over time. However, a paucity of high-quality data supporting the clinical utility of any of these technologies in critically ill children is currently a major limitation to their widespread application in the pediatric intensive care unit.

CONCLUSIONS

Future prospective multicenter work addressing major knowledge gaps is necessary to advance the field of pediatric noninvasive neuromonitoring.

An update on pediatric traumatic brain injury

INTRODUCTION

Traumatic brain injury (TBI) remains the commonest neurological and neurosurgical cause of death and survivor disability among children and young adults. This review summarizes some of the important recent publications that have added to our understanding of the condition and advanced clinical practice.

METHODS

Targeted review of the literature on various aspects of paediatric TBI over the last 5 years.

RESULTS

Recent literature has provided new insights into the burden of paediatric TBI and patient outcome across geographical divides and the severity spectrum. Although CT scans remain a standard, rapid sequence MRI without sedation has been increasingly used in the frontline. Advanced MRI sequences are also being used to better understand pathology and to improve prognostication. Various initiatives in paediatric and adult TBI have contributed regionally and internationally to harmonising research efforts in mild and severe TBI. Emerging data on advanced brain monitoring from paediatric studies and extrapolated from adult studies continues to slowly advance our understanding of its role. There has been growing interest in non-invasive monitoring, although the clinical applications remain somewhat unclear. Contributions of the first large scale comparative effectiveness trial have advanced knowledge, especially for the use of hyperosmolar therapies and cerebrospinal fluid drainage in severe paediatric TBI. Finally, the growth of large and even global networks is a welcome development that addresses the limitations of small sample size and generalizability typical of single-centre studies.

CONCLUSION

Publications in recent years have contributed iteratively to progress in understanding paediatric TBI and how best to manage patients.

Non-Invasive Intracranial Pressure Monitoring and Its Applicability in Spaceflight

INTRODUCTION: Neuro-ophthalmic findings collectively defined as Spaceflight-Associated Neuro-ocular Syndrome (SANS) are one of the leading health priorities in astronauts engaging in long duration spaceflight or prolonged microgravity exposure. Though multifactorial in etiology, similarities to terrestrial idiopathic intracranial hypertension (IIH) suggest these changes may result from an increase or impairing in intracranial pressure (ICP). Finding a portable, accessible, and reliable method of monitoring ICP is, therefore, crucial in long duration spaceflight. A review of recent literature was conducted on the biomedical literature search engine PubMed using the search term “non-invasive intracranial pressure”. Studies investigating accuracy of noninvasive and portable methods were assessed. The search retrieved different methods that were subsequently grouped by approach and technique. The majority of publications included the use of ultrasound-based methods with variable accuracies. One of which, noninvasive ICP estimation by optical nerve sheath diameter measurement (nICP_ONSD), presented the highest statistical correlation and prediction values to invasive ICP, with area under the curve (AUC) ranging from 0.75 to 0.964. One study even considers a combination of ONSD with transcranial Doppler (TCD) for an even higher performance. Other methods, such as near-infrared spectroscopy (NIRS), show positive and promising results [good statistical correlation with invasive techniques when measuring cerebral perfusion pressure (CPP): r = 0.83]. However, for its accessibility, portability, and accuracy, ONSD seems to present itself as the up to date, most reliable, noninvasive ICP surrogate and a valuable spaceflight asset.Félix H, Santos Oliveira E. Non-invasive intracranial pressure monitoring and its applicability in spaceflight. Aerosp Med Hum Perform. 2022; 93(6):517–531.

Transcranial Doppler Ultrasound, a Review for the Pediatric Intensivist

The use of transcranial Doppler ultrasound (TCD) is increasing in frequency in the pediatric intensive care unit. This review highlights some of the pertinent TCD applications for the pediatric intensivist, including evaluation of cerebral hemodynamics, autoregulation, non-invasive cerebral perfusion pressure/intracranial pressure estimation, vasospasm screening, and cerebral emboli detection.

Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries

Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making 'go/no-go' decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute andearly-stagemTBIs have insufficient sensitivity and specificity. This results in uncertainty in clinical decision-making regarding diagnosis and returning to activity or requiring further medical treatment. Therefore, it is important to identify relevant physiological biomarkers that can be integrated into a mutually complementary set and provide a combination of data modalities for improved on-site diagnostic sensitivity of mTBI. In recent years, the processing power, signal fidelity, and the number of recording channels and modalities of wearable healthcare devices have improved tremendously and generated an enormous amount of data. During the same period, there have been incredible advances in machine learning tools and data processing methodologies. These achievements are enabling clinicians and engineers to develop and implement multiparametric high-precision diagnostic tools for mTBI. In this review, we first assess clinical challenges in the diagnosis of acute mTBI, and then consider recording modalities and hardware implementation of various sensing technologies used to assess physiological biomarkers that may be related to mTBI. Finally, we discuss the state of the art in machine learning-based detection of mTBI and consider how a more diverse list of quantitative physiological biomarker features may improve current data-driven approaches in providing mTBI patients timely diagnosis and treatment.

Neurocritical Care and Brain Monitoring

The goal of neurocritical care (NCC) is to improve the outcome of patients with neurologic insults. NCC includes the management of the primary brain injury and prevention of secondary brain injury; this is achieved with standardized clinical care for specific disorders along with neuromonitoring. Neuromonitoring uses multiple modalities, with certain modalities better suited to certain disorders. The term "multimodality monitoring" refers to using multiple modalities at the same time. This article reviews pediatric NCC, the various physiologic parameters used, especially continuous electroencephalographic monitoring.

Practice Recommendations for Transcranial Doppler Ultrasonography in Critically Ill Children in the Pediatric Intensive Care Unit: A Multidisciplinary Expert Consensus Statement

Transcranial Doppler ultrasonography (TCD) is being used in many pediatric intensive care units (PICUs) to aid in the diagnosis and monitoring of children with known or suspected pathophysiological changes to cerebral hemodynamics. Standardized approaches to scanning protocols, interpretation, and documentation of TCD examinations in this setting are lacking. A panel of multidisciplinary clinicians with expertise in the use of TCD in the PICU undertook a three-round modified Delphi process to reach unanimous agreement on 34 statements and then create practice recommendations for TCD use in the PICU. Use of these recommendations will help to ensure that high quality TCD images are captured, interpreted, and reported using standard nomenclature. Furthermore, use will aid in ensuring reproducible and meaningful study results between TCD practitioners and across PICUs.

Clinical Decision Support for Traumatic Brain Injury: Identifying a Framework for Practical Model-Based Intracranial Pressure Estimation at Multihour Timescales

BACKGROUND

The clinical mitigation of intracranial hypertension due to traumatic brain injury requires timely knowledge of intracranial pressure to avoid secondary injury or death. Noninvasive intracranial pressure (nICP) estimation that operates sufficiently fast at multihour timescales and requires only common patient measurements is a desirable tool for clinical decision support and improving traumatic brain injury patient outcomes. However, existing model-based nICP estimation methods may be too slow or require data that are not easily obtained.

OBJECTIVE

This work considers short- and real-time nICP estimation at multihour timescales based on arterial blood pressure (ABP) to better inform the ongoing development of practical models with commonly available data.

METHODS

We assess and analyze the effects of two distinct pathways of model development, either by increasing physiological integration using a simple pressure estimation model, or by increasing physiological fidelity using a more complex model. Comparison of the model approaches is performed using a set of quantitative model validation criteria over hour-scale times applied to model nICP estimates in relation to observed ICP.

RESULTS

The simple fully coupled estimation scheme based on windowed regression outperforms a more complex nICP model with prescribed intracranial inflow when pulsatile ABP inflow conditions are provided. We also show that the simple estimation data requirements can be reduced to 1-minute averaged ABP summary data under generic waveform representation.

CONCLUSIONS

Stronger performance of the simple bidirectional model indicates that feedback between the systemic vascular network and nICP estimation scheme is crucial for modeling over long intervals. However, simple model reduction to ABP-only dependence limits its utility in cases involving other brain injuries such as ischemic stroke and subarachnoid hemorrhage. Additional methodologies and considerations needed to overcome these limitations are illustrated and discussed.

Long-duration spaceflight alters estimated intracranial pressure and cerebral blood velocity

Key points

During long‐duration spaceflights, some astronauts develop structural ocular changes including optic disc oedema that resemble signs of intracranial hypertension.

In the present study, intracranial pressure was estimated non‐invasively (nICP) using a model‐based analysis of cerebral blood velocity and arterial blood pressure waveforms in 11 astronauts before and after long‐duration spaceflights.

Our results show that group‐averaged estimates of nICP decreased significantly in nine astronauts without optic disc oedema, suggesting that the cephalad fluid shift during long‐duration spaceflight rarely increased postflight intracranial pressure.

The results of the two astronauts with optic disc oedema suggest that both increases and decreases in nICP are observed post‐flight in astronauts with ocular alterations, arguing against a primary causal relationship between elevated ICP and spaceflight associated optical changes.

Cerebral blood velocity increased independently of nICP and spaceflight‐associated ocular alterations. This increase may be caused by the reduced haemoglobin concentration after long‐duration spaceflight.

Abstract

Persistently elevated intracranial pressure (ICP) above upright values is a suspected cause of optic disc oedema in astronauts. However, no systematic studies have evaluated changes in ICP from preflight. Therefore, ICP was estimated non‐invasively before and after spaceflight to test whether ICP would increase after long‐duration spaceflight. Cerebral blood velocity in the middle cerebral artery (MCAv) was obtained by transcranial Doppler sonography and arterial pressure in the radial artery was obtained by tonometry, in the supine and sitting positions before and after 4−12 months of spaceflight in 11 astronauts (10 males and 1 female, 46 ± 7 years old at launch). Non‐invasive ICP (nICP) was computed using a validated model‐based estimation method. Mean MCAv increased significantly after spaceflight (ANOVA, P = 0.007). Haemoglobin decreased significantly after spaceflight (14.6 ± 0.8 to 13.3 ± 0.7 g/dL, P < 0.001). A repeated measures correlation analysis indicated a negative correlation between haemoglobin and mean MCAv (r = −0.589, regression coefficient = −4.68). The nICP did not change significantly after spaceflight in the 11 astronauts. However, nICP decreased significantly by 15% in nine astronauts without optic disc oedema (P < 0.005). Only one astronaut increased nICP to relatively high levels after spaceflight. Contrary to our hypothesis, nICP did not increase after long‐duration spaceflight in the vast majority (>90%) of astronauts, suggesting that the cephalad fluid shift during spaceflight does not systematically or consistently elevate postflight ICP in astronauts. Independently of nICP and ocular alterations, the present results of mean MCAv suggest that long‐duration spaceflight may increase cerebral blood flow, possibly due to reduced haemoglobin concentration.

During long‐duration spaceflights, some astronauts develop structural ocular changes including optic disc oedema that resemble signs of intracranial hypertension.

In the present study, intracranial pressure was estimated non‐invasively (nICP) using a model‐based analysis of cerebral blood velocity and arterial blood pressure waveforms in 11 astronauts before and after long‐duration spaceflights.

Our results show that group‐averaged estimates of nICP decreased significantly in nine astronauts without optic disc oedema, suggesting that the cephalad fluid shift during long‐duration spaceflight rarely increased postflight intracranial pressure.

The results of the two astronauts with optic disc oedema suggest that both increases and decreases in nICP are observed post‐flight in astronauts with ocular alterations, arguing against a primary causal relationship between elevated ICP and spaceflight associated optical changes.

Cerebral blood velocity increased independently of nICP and spaceflight‐associated ocular alterations. This increase may be caused by the reduced haemoglobin concentration after long‐duration spaceflight.

A Spectral Approach to Model-Based Noninvasive Intracranial Pressure Estimation

BACKGROUND

Intracranial pressure (ICP) normally ranges from 5 to 15 mmHg. Elevation in ICP is an important clinical indicator of neurological injury, and ICP is therefore monitored routinely in several neurological conditions to guide diagnosis and treatment decisions. Current measurement modalities for ICP monitoring are highly invasive, largely limiting the measurement to critically ill patients. An accurate noninvasive method to estimate ICP would dramatically expand the pool of patients that could benefit from this cranial vital sign.

METHODS

This article presents a spectral approach to model-based ICP estimation from arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) measurements. The model captures the relationship between the ABP, CBFV, and ICP waveforms and utilizes a second-order model of the cerebral vasculature to estimate ICP.

RESULTS

The estimation approach was validated on two separate clinical datasets, one recorded from thirteen pediatric patients with a total duration of around seven hours, and the other recorded from five adult patients, one hour and 48 minutes in total duration. The algorithm was shown to have an accuracy (mean error) of 0.4 mmHg and -1.5 mmHg, and a precision (standard deviation of the error) of 5.1 mmHg and 4.3 mmHg, in estimating mean ICP (range of 1.3 mmHg to 24.8 mmHg) on the pediatric and adult data, respectively. These results are comparable to previous results and within the clinically relevant range. Additionally, the accuracy and precision in estimating the pulse pressure of ICP on a beat-by-beat basis were found to be 1.3 mmHg and 2.9 mmHg respectively.

CONCLUSION

These contributions take a step towards realizing the goal of implementing a real-time noninvasive ICP estimation modality in a clinical setting, to enable accurate clinical-decision making while overcoming the drawbacks of the invasive ICP modalities.

Adaptive Maximal Blood Flow Velocity Estimation From Transcranial Doppler Echos

OBJECTIVE

Novel applications of transcranial Doppler (TCD) ultrasonography, such as the assessment of cerebral vessel narrowing/occlusion or the non-invasive estimation of intracranial pressure (ICP), require high-quality maximal flow velocity waveforms. However, due to the low signal-to-noise ratio of TCD spectrograms, measuring the maximal flow velocity is challenging. In this work, we propose a calibration-free algorithm for estimating maximal flow velocities from TCD spectrograms and present a pertaining beat-by-beat signal quality index.

METHODS

Our algorithm performs multiple binary segmentations of the TCD spectrogram and then extracts the pertaining envelopes (maximal flow velocity waveforms) via an edge-following step that incorporates physiological constraints. The candidate maximal flow velocity waveform with the highest signal quality index is finally selected.

RESULTS

We evaluated the algorithm on 32 TCD recordings from the middle cerebral and internal carotid arteries in 6 healthy and 12 neurocritical care patients. Compared to manual spectrogram tracings, we obtained a relative error of -1.5%, when considering the whole waveform, and a relative error of -3.3% for the peak systolic velocity.

CONCLUSION

The feedback loop between the signal quality assessment and the binary segmentation yields a robust algorithm for maximal flow velocity estimation. Clinical Impact: The algorithm has already been used in our ICP estimation pipeline. By making the code and the data publicly available, we hope that the algorithm will be a useful building block for the development of novel TCD applications that require high-quality flow velocity waveforms.

Review: pathophysiology of intracranial hypertension and noninvasive intracranial pressure monitoring

Measurement of intracranial pressure (ICP) is crucial in the management of many neurological conditions. However, due to the invasiveness, high cost, and required expertise of available ICP monitoring techniques, many patients who could benefit from ICP monitoring do not receive it. As a result, there has been a substantial effort to explore and develop novel noninvasive ICP monitoring techniques to improve the overall clinical care of patients who may be suffering from ICP disorders. This review attempts to summarize the general pathophysiology of ICP, discuss the importance and current state of ICP monitoring, and describe the many methods that have been proposed for noninvasive ICP monitoring. These noninvasive methods can be broken down into four major categories: fluid dynamic, otic, ophthalmic, and electrophysiologic. Each category is discussed in detail along with its associated techniques and their advantages, disadvantages, and reported accuracy. A particular emphasis in this review will be dedicated to methods based on the use of transcranial Doppler ultrasound. At present, it appears that the available noninvasive methods are either not sufficiently accurate, reliable, or robust enough for widespread clinical adoption or require additional independent validation. However, several methods appear promising and through additional study and clinical validation, could eventually make their way into clinical practice.

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.

Estimating intracranial pressure using pulsatile cerebral blood flow measured with diffuse correlation spectroscopy

Measuring intracranial pressure (ICP) is necessary for the treatment of severe head injury but measurement systems are highly invasive and introduce risk of infection and complications. We developed a non-invasive alternative for quantifying ICP using measurements of cerebral blood flow (CBF) by diffuse correlation spectroscopy. The recorded cardiac pulsation waveform in CBF undergoes morphological changes in response to ICP changes. We used the pulse shape to train a randomized regression forest to estimate the underlying ICP and demonstrate in five non-human primates that DCS-based estimation can explain over 90% of the variance in invasively measured ICP.

Pseudo-Bayesian Model-Based Noninvasive Intracranial Pressure Estimation and Tracking

OBJECTIVE

A noninvasive intracranial pressure (ICP) estimation method is proposed that incorporates a model-based approach within a probabilistic framework to mitigate the effects of data and modeling uncertainties.

METHODS

A first-order model of the cerebral vasculature relates measured arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) to ICP. The model is driven by the ABP waveform and is solved for a range of mean ICP values to predict the CBFV waveform. The resulting errors between measured and predicted CBFV are transformed into likelihoods for each candidate ICP in two steps. First, a baseline ICP estimate is established over five data windows of 20 beats by combining the likelihoods with a prior distribution of the ICP to yield an a posteriori distribution whose median is taken as the baseline ICP estimate. A single-state model of cerebral autoregulatory dynamics is then employed in subsequent data windows to track changes in the baseline by combining ICP estimates obtained with a uniform prior belief and model-predicted ICP. For each data window, the estimated model parameters are also used to determine the ICP pulse pressure.

RESULTS

On a dataset of thirteen pediatric patients with a variety of pathological conditions requiring invasive ICP monitoring, the method yielded for mean ICP estimation a bias (mean error) of 0.6 mmHg and a root-mean-squared error of 3.7 mmHg.

CONCLUSION

These performance characteristics are well within the acceptable range for clinical decision making.

SIGNIFICANCE

The method proposed here constitutes a significant step towards robust, continuous, patient-specific noninvasive ICP determination.