Can a new noninvasive method for assessment of intracranial pressure predict intracranial hypertension and prognosis?

Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine

A wide range of acute brain injuries, including both traumatic and non-traumatic causes, can result in elevated intracranial pressure (ICP), which in turn can cause further secondary injury to the brain, initiating a vicious cascade of propagating injury. Elevated ICP is therefore a neurological injury that requires intensive monitoring and time-sensitive interventions. Patients at high risk for developing elevated ICP undergo placement of invasive ICP monitors including external ventricular drains, intraparenchymal ICP monitors, and lumbar drains. These monitors all generate an ICP waveform, but each has its own unique caveats in monitoring and accuracy. Current ICP monitoring and management clinical guidelines focus on the mean ICP derived from the ICP waveform, with standard thresholds of treating ICP greater than 20 ​mmHg or 22 ​mmHg applied broadly to a wide range of patients. However, this one-size fits all approach has been criticized and there is a need to develop personalized, evidence-based and possibly multi-factorial precision-medicine based approaches to the problem. This paper provides historical and physiological context to the problem of elevated ICP, provides an overview of the challenges of the current paradigm of ICP management strategies, and discusses advances in ICP waveform analysis, emerging non-invasive ICP monitoring techniques, and applications of machine learning to create predictive algorithms.

Prospective comparative clinical trials of novel non-invasive intracranial pressure pulse wave monitoring technologies: preliminary clinical data

Intracranial pressure (ICP) monitoring is crucial in the management of traumatic brain injury (TBI) and other neurological conditions. Elevated ICP or too low intracranial compliance (ICC) can compromise brain perfusion. Simultaneous monitoring of ICP and ICC is needed to optimize patient-specific brain perfusion in pathological conditions. Surrogate ICC changes can be extracted by analysis of ICP pulse wave morphology. Non-invasive, fully passive sensor and ICC changes monitoring are needed. This study introduces Archimedes, a novel, fully passive, non-invasive ICP wave monitor that utilizes mechanical pulsatile movement of the eyeball to assess ICP pulse waveforms. Preliminary findings indicate a high correlation r = [0.919; 0.96] between non-invasive and invasive ICP pulse wave morphologies, demonstrating the device's potential for accurate ICP pulse waveform monitoring. Additionally, the monitor can discern ICC changes, providing valuable insights for TBI and normal tension glaucoma patients according to the shape of non-invasive measured ICP pulse wave. The k-nearest neighbours algorithm used in preliminary glaucoma studies yielded promising diagnostic performance, with an accuracy of 0.89, sensitivity of 0.82, specificity of 1.0 and area under curve 0.91. Ethical approvals for ongoing studies have been secured. Initial results indicate that Archimedes real-time ICC non-invasive monitor is safe, cost-effective alternative to conventional monitoring techniques.

NON-INVASIVE METHOD OF MONITORING INTRACRANIAL PRESSURE FOR THE EVALUATION OF HEPATIC ENCEPHALOPATHY

BACKGROUND

Liver diseases often occur with hepatic encephalopathy (HE), whose pathophysiology may involve increased intracranial pressure (ICP). Tools for monitoring ICP and its pulse morphology can be useful for assessing HE. The use of a non-invasive and sensitive procedure would be extremely useful in managing these cases.

OBJECTIVE

To evaluate the feasibility and performance of a new, non-invasive method of monitoring ICP, as an alternative to invasive methods, and to correlate the clinical diagnosis of HE with the morphological findings of ICP.

METHODS

This is a cross-sectional analytical study, conducted in a tertiary hospital and pioneer in the application of Brain4Care® BWS equipment. The ICP pulse morphology is parallel to the arterial one, where there are three frequent peaks: percussion peak (P1), due to plasma extravasated by the choroid plexus; tidal wave (P2), due to the degree of intracranial compliance to the reflection of P1, and dicrotic notch (P3), due to the closure of the aortic valve. Normality indicates P1>P2>P3. These peaks determine intracranial compliance through their relationship with cerebral blood volume, where P2/P1 ratio >1 suggests a pathological morphology, with a sustained increase in ICP and decreased compliance. Another way to evaluate this would be by a change in the time-to-peak (TTP). These data were compared between patients with and without clinical signs indicative of HE. The study was approved by the Institution's Research Ethics Committee (number 5.493.775).

RESULTS

A total of 40 liver disease patients were evaluated, of which, at the time of collection, 20 did not have a clinical picture of HE (59.5±9.3 years; 70.0% male) and 20 had a clinical picture of HE (59.6±11.9 years; 65.0% male). The groups are demographically, clinically and laboratory similar; and statistically significant differences were identified in the morphological patterns of ICP between the groups evaluated, as well as trends in the parameters. The difference in the P2/P1 ratio was not significant (Mann Whitney: two-tailed P=0.2978); however, TTP proved to be a parameter with a statistically significant difference between the groups (Mann Whitney: two-tailed P=0.0282; median difference = 0.04). Analysis using the C statistic, using the ROC curve, suggested P2/P1=1.31 (AUROC: 0.5975) and TTP=0.22 (AUROC: 0.7013) as optimal cutoff points, where the presence of HE in liver disease patients would be associated with obtaining parameters below these thresholds.

CONCLUSION

The brain4care® BWS system proved to be feasible for use in liver disease patients with or without clinical signs of hepatic encephalopathy and was able to differentiate them. Pathophysiological explanations, however, still require better causality explanation and understanding of the intracerebral hydrodynamic picture in hepatic encephalopathy. Given the low sample power found, new studies need better clinical heterogeneity and longer-term follow-up for definitive conclusions.

An ultrasensitive multimodal intracranial pressure biotelemetric system enabled by exceptional point and iontronics

The accurate monitoring of vital physiological parameters, exemplified by heart rate, respiratory rate, and intracranial pressure (ICP), is of paramount importance, particularly for managing severe cranial injuries. Despite the rapid development of implantable ICP sensing systems over the past decades, they still suffer from, for example, wire connection, low sensitivity, poor resolution, and the inability to monitor multiple variables simultaneously. Here, we propose an ultrasensitive multimodal biotelemetric system that amalgamates an iontronic pressure transducer with exceptional point (EP) operation for the monitoring of ICP signals. The proposed system can exhibit extraordinary performance regarding the detection of minuscule ICP fluctuation, demonstrated by the sensitivity of 115.95 kHz/mmHg and the sensing resolution down to 0.003 mmHg. Our system excels not only in the accurate quantification of ICP levels but also in distinguishing respiration and cardiac activities from ICP signals, thereby achieving the multimodal monitoring of ICP, respiratory, and heart rates within a single system. Our work may provide a pragmatic avenue for the real-time wireless monitoring of ICP and thus hold great potential to be extended to the monitoring of other vital physiological indicators.

Noninvasive intracranial pressure profile in 31 patients submitted to fullendoscopic spine surgery

PURPOSE

Full-endoscopic spine surgery (FESS) is associated with specific complications, possibly linked to increased intracranial pressure (ICP) resulting from continuous saline infusion into the epidural space. This study aimed to assess the impact of saline irrigation and its correlation with noninvasively obtained ICP waveform changes.

METHODS

Patients undergoing FESS between January 2019 and November 2020 were included. Noninvasive ICP (n-ICP) monitoring utilized an extracranial strain sensor generating ICP waveforms, from which parameters P2/P1 ratio and time to peak (TTP) values were derived and correlated to irrigation and vital parameters. Documentation occurred at specific surgical intervals (M0-preoperatively; M1 to M4-intraoperatively; M5-postoperatively). Mixed-model analysis of variance and multiple comparisons tests were applied, with M0 as the baseline.

RESULTS

Among 31 enrolled patients, three experienced headaches unrelated to increased ICP at M5. The P2/P1 ratio and TTP decreased during surgery (p < 0.001 and p < 0.004, respectively). Compared to baseline, P2/P1 ratio and vital parameters remained significantly lower at M5. No significant differences were observed for fluid parameters throughout surgery.

CONCLUSIONS

This study demonstrated a decline in the n-ICP parameters after anesthetic induction despite the anticipated increase in ICP due to constant epidural irrigation. The n-ICP parameters behaved independently of fluid parameters, suggesting a potential protective effect of anesthesia.

Intracranial pressure monitoring in adult patients with traumatic brain injury: challenges and innovations

Intracranial pressure monitoring enables the detection and treatment of intracranial hypertension, a potentially lethal insult after traumatic brain injury. Despite its widespread use, robust evidence supporting intracranial pressure monitoring and treatment remains sparse. International studies have shown large variations between centres regarding the indications for intracranial pressure monitoring and treatment of intracranial hypertension. Experts have reviewed these two aspects and, by consensus, provided practical approaches for monitoring and treatment. Advances have occurred in methods for non-invasive estimation of intracranial pressure although, for now, a reliable way to non-invasively and continuously measure intracranial pressure remains aspirational. Analysis of the intracranial pressure signal can provide information on brain compliance (ie, the ability of the cranium to tolerate volume changes) and on cerebral autoregulation (ie, the ability of cerebral blood vessels to react to changes in blood pressure). The information derived from the intracranial pressure signal might allow for more individualised patient management. Machine learning and artificial intelligence approaches are being increasingly applied to intracranial pressure monitoring, but many obstacles need to be overcome before their use in clinical practice could be attempted. Robust clinical trials are needed to support indications for intracranial pressure monitoring and treatment. Progress in non-invasive assessment of intracranial pressure and in signal analysis (for targeted treatment) will also be crucial.

ICP wave morphology as a screening test to exclude intracranial hypertension in brain-injured patients: a non-invasive perspective

Intracranial hypertension (IH) is a life-threating condition especially for the brain injured patient. In such cases, an external ventricular drain (EVD) or an intraparenchymal bolt are the conventional gold standard for intracranial pressure (ICPi) monitoring. However, these techniques have several limitations. Therefore, identifying an ideal screening method for IH is important to avoid the unnecessary placement of ICPi and expedite its introduction in patients who require it. A potential screening tool is the ICP wave morphology (ICPW) which changes according to the intracranial volume-pressure curve. Specifically, the P2/P1 ratio of the ICPW has shown promise as a triage test to indicate normal ICP. In this study, we propose evaluating the noninvasive ICPW (nICPW-B4C sensor) as a screening method for ICPi monitoring in patients with moderate to high probability of IH. This is a retrospective analysis of a prospective, multicenter study that recruited adult patients requiring ICPi monitoring from both Federal University of São Paulo and University of São Paulo Medical School Hospitals. ICPi values and the nICPW parameters were obtained from both the invasive and the noninvasive methods simultaneously 5 min after the closure of the EVD drainage. ICP assessment was performed using a catheter inserted into the ventricle and connected to a pressure transducer and a drainage system. The B4C sensor was positioned on the patient's scalp without the need for trichotomy, surgical incision or trepanation, and the morphology of the ICP waves acquired through a strain sensor that can detect and monitor skull bone deformations caused by changes in ICP. All patients were monitored using this noninvasive system for at least 10 min per session. The area under the curve (AUC) was used to describe discriminatory power of the P2/P1 ratio for IH, with emphasis in the Negative Predictive value (NPV), based on the Youden index, and the negative likelihood ratio [LR-]. Recruitment occurred from August 2017 to March 2020. A total of 69 patients fulfilled inclusion and exclusion criteria in the two centers and a total of 111 monitorizations were performed. The mean P2/P1 ratio value in the sample was 1.12. The mean P2/P1 value in the no IH population was 1.01 meanwhile in the IH population was 1.32 (p < 0.01). The best Youden index for the mean P2/P1 ratio was with a cut-off value of 1.13 showing a sensitivity of 93%, specificity of 60%, and a NPV of 97%, as well as an AUC of 0.83 to predict IH. With the 1.13 cut-off value for P2/P1 ratio, the LR- for IH was 0.11, corresponding to a strong performance in ruling out the condition (IH), with an approximate 45% reduction in condition probability after a negative test (ICPW). To conclude, the P2/P1 ratio of the noninvasive ICP waveform showed in this study a high Negative Predictive Value and Likelihood Ratio in different acute neurological conditions to rule out IH. As a result, this parameter may be beneficial in situations where invasive methods are not feasible or unavailable and to screen high-risk patients for potential invasive ICP monitoring.Trial registration: At clinicaltrials.gov under numbers NCT05121155 (Registered 16 November 2021-retrospectively registered) and NCT03144219 (Registered 30 September 2022-retrospectively registered).

A Narrative Review on Financial Challenges and Health Care Costs Associated with Traumatic Brain Injury in the United States

BACKGROUND

Traumatic brain injury (TBI) is a highly prevalent and potentially severe medical condition. Challenges regarding TBI management are related to accurate diagnostics, defining its severity, and establishing prompt interventions to affect outcomes. Among the health care components in the TBI handling strategy is intracranial pressure (ICP) monitoring, which is fundamental to therapy decisions. However, ICP monitoring is an Achilles tendon, imposing a significant financial burden on health care systems, particularly in middle and low-income communities. This article arises from the understanding from the authors that there is insufficient scientific evidence about the potential economic impacts from the use of noninvasive technologies in the monitoring of TBI. Based on personal experience, as well as from reading other, clinically focused studies, the thesis is that the use of such technologies could greatly affect the health care system and this article seeks to address this lack of literature, show ways in which such systems could be evaluated, and show estimations of possible results from these investigations.

OBJECTIVE

This review primarily investigates the economic burden of TBI and whether new technologies are suitable to reduce its health care costs without compromising the quality of care, according to the levels of evidence available. The objective is to stimulate more research and attention in the area.

METHODS

For this narrative review, a PubMed search was conducted for articles discussing TBI health care costs, as well as monitoring technologies (tomography, magnetic resonance imaging, optic nerve sheath diameter, transcranial Doppler, pupillometry, and noninvasive ICP waveform) and their application in managing TBI. Strategies were first evaluated from a medical noninferiority perspective before calculating the average savings of each selected strategy. All applicable studies were analyzed for quality using the Consolidated Health Economic Evaluation Reporting Standards 2022 Statement117 and this article was written to conform as much as possible with it.

RESULTS

The review included 109 references and showed a consistent potential in noninvasive technologies to reduce costs and maintain or improve the quality of care.

CONCLUSIONS

TBI prevalence has increased with a disproportionate health care burden in the last decades. Noninvasive monitoring techniques seem to be effective in reducing TBI health care costs, with few limitations, especially the need for more supporting scientific evidence. The undeniable clinical and financial potential of these techniques is compelling to further investigate their role in TBI management, as well as the creation of more comprehensive monitoring models to the understanding of complex phenomena occurring in the injured brain.

Multimodal monitoring intracranial pressure by invasive and noninvasive means

Although the placement of an intraventricular catheter remains the gold standard method for the diagnosis of intracranial hypertension (ICH), the technique has several limitations including but not limited to its invasiveness. Current noninvasive methods, however, still lack robust evidence to support their clinical use. We aimed to estimate, as an exploratory hypothesis generating analysis, the discriminative power of four noninvasive methods to diagnose ICH. We prospectively collected data from adult intensive care unit (ICU) patients with subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), and ischemic stroke (IS) in whom invasive intracranial pressure (ICP) monitoring had been placed. Measures were simultaneously collected from the following noninvasive methods: optic nerve sheath diameter (ONSD), pulsatility index (PI) using transcranial Doppler (TCD), a 5-point visual scale designed for brain Computed Tomography (CT), and two parameters (time-to-peak [TTP] and P2/P1 ratio) of a noninvasive ICP wave morphology monitor (Brain4Care[B4c]). ICH was defined as a sustained ICP > 20 mmHg for at least 5 min. We studied 18 patients (SAH = 14; ICH = 3; IS = 1) on 60 occasions with a mean age of 52 ± 14.3 years. All methods were recorded simultaneously, except for the CT, which was performed within 24 h of the other methods. The median ICP was 13 [9.8-16.2] mmHg, and intracranial hypertension was present on 18 occasions (30%). Median values from the noninvasive techniques were ONSD 4.9 [4.40-5.41] mm, PI 1.22 [1.04-1.43], CT scale 3 points [IQR: 3.0], P2/P1 ratio 1.16 [1.09-1.23], and TTP 0.215 [0.193-0.237]. There was a significant statistical correlation between all the noninvasive techniques and invasive ICP (ONSD, r = 0.29; PI, r = 0.62; CT, r = 0.21; P2/P1 ratio, r = 0.35; TTP, r = 0.35, p < 0.001 for all comparisons). The area under the curve (AUC) to estimate intracranial hypertension was 0.69 [CIs = 0.62-0.78] for the ONSD, 0.75 [95% CIs 0.69-0.83] for the PI, 0.64 [95%Cis 0.59-069] for CT, 0.79 [95% CIs 0.72-0.93] for P2/P1 ratio, and 0.69 [95% CIs 0.60-0.74] for TTP. When the various techniques were combined, an AUC of 0.86 [0.76-0.93]) was obtained. The best pair of methods was the TCD and B4cth an AUC of 0.80 (0.72-0.88). Noninvasive technique measurements correlate with ICP and have an acceptable discrimination ability in diagnosing ICH. The multimodal combination of PI (TCD) and wave morphology monitor may improve the ability of the noninvasive methods to diagnose ICH. The observed variability in non-invasive ICP estimations underscores the need for comprehensive investigations to elucidate the optimal method-application alignment across distinct clinical scenarios.

Analysis of intracranial pressure pulse waveform in studies on cerebrospinal compliance: a narrative review

Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure-volume compensation, i.e. the ability of the cerebrospinal system to buffer changes in volume without substantial increases in ICP, is considered an important factor in preventing adverse effects on the patient's condition that are associated with ICP elevation. However, existing assessment methods are poorly suited to the management of brain injured patients as they require external manipulation of intracranial volume. In the 1980s, studies suggested that spontaneous short-term variations in the ICP signal over a single cardiac cycle, called the ICP pulse waveform, may provide information on cerebrospinal compensatory reserve. In this review we discuss the approaches that have been proposed so far to derive this information, from pulse amplitude estimation and spectral techniques to most recent advances in morphological analysis based on artificial intelligence solutions. Each method is presented with focus on its clinical significance and the potential for application in standard clinical practice. Finally, we highlight the missing links that need to be addressed in future studies in order for ICP pulse waveform analysis to achieve widespread use in the neurocritical care setting.

A Deep Learning-Based Automated Framework for Subpeak Designation on Intracranial Pressure Signals

The intracranial pressure (ICP) signal, as monitored on patients in intensive care units, contains pulses of cardiac origin, where P1 and P2 subpeaks can often be observed. When calculable, the ratio of their relative amplitudes is an indicator of the patient's cerebral compliance. This characterization is particularly informative for the overall state of the cerebrospinal system. The aim of this study is to develop and assess the performances of a deep learning-based pipeline for P2/P1 ratio computation that only takes a raw ICP signal as an input. The output P2/P1 ratio signal can be discontinuous since P1 and P2 subpeaks are not always visible. The proposed pipeline performs four tasks, namely (i) heartbeat-induced pulse detection, (ii) pulse selection, (iii) P1 and P2 designation, and (iv) signal smoothing and outlier removal. For tasks (i) and (ii), the performance of a recurrent neural network is compared to that of a convolutional neural network. The final algorithm is evaluated on a 4344-pulse testing dataset sampled from 10 patient recordings. Pulse selection is achieved with an area under the curve of 0.90, whereas the subpeak designation algorithm identifies pulses with a P2/P1 ratio > 1 with 97.3% accuracy. Although it still needs to be evaluated on a larger number of labeled recordings, our automated P2/P1 ratio calculation framework appears to be a promising tool that can be easily embedded into bedside monitoring devices.