Non-invasive Estimation Of Intracranial Pressure Research Articles

Evaluation of machine learning algorithms for noninvasive intracranial pressure estimation using near infrared spectroscopy as a covariate.

Intracranial pressure (ICP) is a vital parameter that is continuously monitored in patients with severe brain injury and imminent intracranial hypertension. To estimate intracranial pressure without intracranial probes based on transcutaneous near infrared spectroscopy (NIRS). We developed machine learning based approaches for noninvasive intracranial pressure (ICP) estimation using signals from transcutaneous near infrared spectroscopy (NIRS) as well as other cardiovascular and artificial ventilation parameters. In a patient cohort of 25 patients, with 22 used for model development and 3 for model testing, the best performing models were Fourier transform based Transformer ICP waveform estimation which produced a mean absolute error of 4.68 mm Hg (SD = 5.4) in estimation. We did not find a significant improvement in ICP estimation accuracy by including signals measured by transcutaneous NIRS. We expect that with higher quality and greater volume of data, noninvasive estimation of ICP will improve.

Using near-infrared spectroscopy and a random forest regressor to estimate intracranial pressure.

.SignificanceIntracranial pressure (ICP) measurements are important for patient treatment but are invasive and prone to complications. Noninvasive ICP monitoring methods exist, but they suffer from poor accuracy, lack of generalizability, or high cost.AimWe previously showed that cerebral blood flow (CBF) cardiac waveforms measured with diffuse correlation spectroscopy can be used for noninvasive ICP monitoring. Here we extend the approach to cardiac waveforms measured with near-infrared spectroscopy (NIRS).ApproachChanges in hemoglobin concentrations were measured in eight nonhuman primates, in addition to invasive ICP, arterial blood pressure, and CBF changes. Features of average cardiac waveforms in hemoglobin and CBF signals were used to train a random forest (RF) regressor.ResultsThe RF regressor achieves a cross-validated ICP estimation of , mean squared error (MSE), and 95% confidence interval (CI) of on oxyhemoglobin concentration changes; , MSE, and 95% CI of on total hemoglobin concentration changes; and , MSE, and 95% CI of on CBF changes.ConclusionsThis study provides a proof of concept for the use of NIRS in noninvasive ICP estimation.

A Review of the Methods of Non-Invasive Assessment of Intracranial Pressure through Ocular Measurement.

The monitoring of intracranial pressure (ICP) is essential for the detection and treatment of most craniocerebral diseases. Invasive methods are the most accurate approach to measure ICP; however, these methods are prone to complications and have a limited range of applications. Therefore, non-invasive ICP measurement is preferable in a range of scenarios. The current non-invasive ICP measurement methods comprise fluid dynamics, and ophthalmic, otic, electrophysiological, and other methods. This article reviews eight methods of non-invasive estimation of ICP from ocular measurements, namely optic nerve sheath diameter, flash visual evoked potentials, two-depth transorbital Doppler ultrasonography, central retinal venous pressure, optical coherence tomography, pupillometry, intraocular pressure measurement, and retinal arteriole and venule diameter ratio. We evaluated and presented the indications and main advantages and disadvantages of these methods. Although these methods cannot completely replace invasive measurement, for some specific situations and patients, non-invasive measurement of ICP still has great potential.

Linear interactions between intraocular, intracranial pressure, and retinal vascular pulse amplitude in the fourier domain

PurposeTo compare the retinal vascular pulsatile characteristics in subjects with normal (ICPn) and high (ICPh) intracranial pressure and quantify the interactions between intraocular pressure, intracranial pressure, and retinal vascular pulse amplitude in the Fourier domain.Materials and methodsTwenty-one subjects were examined using modified photoplethysmography with simultaneous ophthalmodynamometry. A harmonic regression model was fitted to each pixel in the time-series, and used to quantify the retinal vascular pulse wave parameters including the harmonic regression wave amplitude (HRWa). The pulse wave attenuation was measured under different ranges of induced intraocular pressure (IOPi), as a function of distance along the vessel (VDist). Intracranial pressure (ICP) was measured using lumbar puncture. A linear mixed-effects model was used to estimate the correlations between the Yeo-Johnson transformed harmonic regression wave amplitude (HRWa-YJt) with the predictors (IOPi, VDist and ICP). A comparison of the model coefficients was done by calculating the weighted Beta (βx) coefficients.ResultsThe median HRWa in the ICPn group was higher in the retinal veins (4.563, interquartile range (IQR) = 3.656) compared to the retinal arteries (3.475, IQR = 2.458), p<0.0001. In contrast, the ICPh group demonstrated a reduction in the median venous HRWa (3.655, IQR = 3.223) and an elevation in the median arterial HRWa (3.616, IQR = 2.715), p<0.0001. Interactions of the pulsation amplitude with ICP showed a significant disordinal interaction and the loss of a main effect of the Fourier sine coefficient (bn1) in the ICPh group, suggesting that this coefficient reflects the retinal vascular response to ICP wave. The linear mixed-effects model (LME) showed the decay in the venous (HRWa-YJt) was almost twice that in the retinal arteries (−0.067±0.002 compared to −0.028±0.0021 respectively, p<0.00001). The overall interaction models had a total explanatory power of (conditional R2) 38.7%, and 42% of which the fixed effects explained 8.8%, and 5.8% of the variance (marginal R2) for the venous and arterial models respectively. A comparison of the damping effect of VDist and ICP showed that ICP had less influence on pulse decay than distance in the retinal arteries (βICP = -0.21, se = ±0.017 compared to , se = ±0.019), whereas the mean value was equal for the retinal veins (venous , se = ±0.015, βICP = -0.42, se = ±0.019).ConclusionThe retinal vascular pulsation characteristics in the ICPh group showed high retinal arterial and low venous pulsation amplitudes. Interactions between retinal vascular pulsation amplitude and ICP suggest that the Fourier sine coefficient bn1 reflects the retinal vascular response to the ICP wave. Although a matrix of regression lines showed high linear characteristics, the low model explanatory power precludes its use as a predictor of ICP. These results may guide future predictive modelling in non-invasive estimation of ICP using modified photoplethysmography.

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.

Zero retinal vein pulsation amplitude extrapolated model in non-invasive intracranial pressure estimation

Intracranial pressure (ICP) includes the brain, optic nerve, and spinal cord pressures; it influences blood flow to those structures. Pathological elevation in ICP results in structural damage through various mechanisms, which adversely affects outcomes in traumatic brain injury and stroke. Currently, invasive procedures which tap directly into the cerebrospinal fluid are required to measure this pressure. Recent fluidic engineering modelling analogous to the ocular vascular flow suggests that retinal venous pulse amplitudes are predictably influenced by downstream pressures, suggesting that ICP could be estimated by analysing this pulse signal. We used this modelling theory and our photoplethysmographic (PPG) retinal venous pulse amplitude measurement system to measure amplitudes in 30 subjects undergoing invasive ICP measurements by lumbar puncture (LP) or external ventricular drain (EVD). We estimated ICP from these amplitudes using this modelling and found it to be accurate with a mean absolute error of 3.0 mmHg and a slope of 1.00 (r = 0.91). Ninety-four percent of differences between the PPG and invasive method were between − 5.5 and + 4.0 mmHg, which compares favourably to comparisons between LP and EVD. This type of modelling may be useful for understanding retinal vessel pulsatile fluid dynamics and may provide a method for non-invasive ICP measurement.

Introduction of a Novel, Continuous, Noninvasive Estimation of Intracranial Pressure and Cerebral Perfusion Pressure Based on Tympanic Membrane Temperature

Hydrocephalus is a common but potentially life-threatening condition. However, valve malfunction makes further diagnosis difficult. Thus, we tried to develop a noninvasive method to detect the hydrocephalus intracranial pressure (ICP) during routine follow-up. In group I, the patient was recruited because a spinal tap test was necessary for either disease diagnosis or treatment. In group II, patients were diagnosed with high ICP hydrocephalus and received shunt surgery. The tympanic membrane temperatures (TMTs) were recorded and plotted against the spinal tap pressure (STP) and shunt valve pressures. All patients in group I showed an above-normal STP (from 180 to 400 mm H2O). The STP presents with an inverted U-shaped curve when it is plotted against TMT (R2= 0.9). When the STP was 286.1 mm H2O, the TMT approached its peak value, which was 38.61°C (101.5°F). However, when ICP was in the normal range (50-200 mm H2O), the TMT correlated with ICP in a linear regression model (R2= 0.69; P < 0.001). In addition, the cerebral perfusion pressure (CPP) was calculated and plotted against TMT. The TMT-CPP was also shown as a parabola (R2= 0.74). Based on the TMT-ICP algorithm, we invented a noninvasive ICP monitor system, which performs in a manner comparable to the Codman ICP Transducer (R2= 0.9; P < 0.01). Both Y-Jiang TMT-ICP and TMT-CPP algorithms are useful to monitor the shunt outcomes and identify potential shunt failure. More importantly, these algorithms open the possibility for the rational acquisition of ICP and CPP noninvasively.

Noninvasive Estimation of Pulsatile and Static Intracranial Pressure by Optical Coherence Tomography.

PurposeTo explore the ability of optical coherence tomography (OCT) to noninvasively estimate pulsatile and static intracranial pressure (ICP).MethodsAn OCT examination was performed in patients who underwent continuous overnight monitoring of the pulsatile and static ICP for diagnostic purpose. We included two patient groups, patients with idiopathic intracranial hypertension (IIH; n = 20) and patients with no verified cerebrospinal fluid disturbances (reference; n = 12). Several OCT parameters were acquired using spectral-domain OCT (RS-3000 Advance; NIDEK, Singapore). The ICP measurements were obtained using a parenchymal sensor (Codman ICP MicroSensor; Johnson & Johnson, Raynham, MA, USA). The pulsatile ICP was determined as the mean ICP wave amplitude (MWA), and the static ICP was determined as the mean ICP.ResultsThe peripapillary Bruch's membrane angle (pBA) and the optic nerve head height (ONHH) differed between the IIH and reference groups and correlated with both MWA and mean ICP. Both OCT parameters predicted elevated MWA. Area under the curve and cutoffs were 0.82 (95% confidence interval [CI], 0.66–0.98) and -0.65° (sensitivity/specificity; 0.75/0.92) for pBA and 0.84 (95% CI, 0.70–0.99) and 405 µm (0.88/0.67) for ONHH. Adjusting for age and body mass index resulted in nonsignificant predictive values for mean ICP, whereas the predictive value for MWA remained significant.ConclusionsThis study provides evidence that the OCT parameters pBA and ONHH noninvasively can predict elevated pulsatile ICP, represented by the MWA.Translational RelevanceOCT shows promise as a method for noninvasive estimation of ICP.

Correlation Between Invasive and Noninvasive Technique of Intracranial Pressure Measurement in Children With Traumatic Brain Injury: An Observational Study

Direct measurement of intracranial pressure (ICP) is an invasive technique with potential complications, which has prompted the development of alternative, noninvasive, methods of ICP assessment. The aim of this study was to determine the relationship between noninvasive ultrasound-based measurement of optic nerve sheath diameter (ONSD), transcranial Doppler-derived pulsatility index (PI), and invasive ICP measurements in children with traumatic brain injury (TBI). Children aged 1 to 18 years undergoing invasive ICP monitoring following TBI were included in the study. Noninvasive ONSD and PI measurements were compared with simultaneous invasive ICP. In all, 406 measurements of ONSD and PI were obtained in 18 patients. ONSD and PI correlated with ICP (r=0.76 and 0.79, respectively), combining ONSD and PI resulted in an even stronger correlation with ICP (r=0.99). Formulas were derived from mixed-effect models that best fitted the data for noninvasive ICP estimation. A combination of ONSD and PI had the highest ability to detect ICP >20 mm Hg (area under the receiver operating characteristic curve=0.99, 95% confidence interval: 0.99-1.00). Optimal cutoff values for the prediction of intracranial hypertension were 5.95 mm for ONSD (sensitivity, 92%; specificity, 76%) and 1.065 for PI (sensitivity, 92%; specificity, 87%). In children with TBI, a combination of ONSD and PI strongly correlates with invasive ICP and has potential to screen for intracranial hypertension noninvasively. ONSD and PI may be useful tools for assessing ICP where invasive monitoring is unavailable or contraindicated.

Estimación no invasiva ultrasonográfica de la presión intracraneana en el paciente neurocrítico

ObjectiveTo evaluate the usefulness of transcranial Doppler (TCD) and measurement of the diameter of the optic nerve sheath (ONSD) for non-invasive estimation of intracranial pressure (ICP), through the study of its correlation with invasive monitoring. DesignA prospective, single-centre study was conducted between February 2018 and August 2019 in a 26-bed Intensive Care Unit (ICU) of the public healthcare system. ParticipantsNeurocritical patients, older than 18 years, admitted consecutively to the ICU, and requiring invasive monitoring of intracranial pressure (ICP). InterventionsNone. MeasurementsThe correlation between invasive ICP and estimated ICP by TCD was performed using the Lin's concordance correlation coefficient. The ROC curve was used to assess the diagnostic accuracy of the ONSD. In all cases, a value of p < 0.05 was adopted as the level of statistical significance. ResultsThirty records of a total of 25 patients were evaluated. No significant differences were found between the median of invasive ICP vs. that estimated by TCD (16.07 vs. 15.03) (P = 0.001). A Lin Coefficient of 0.9603 (95% CI: 0.9199 to 0.9806) was found. The ONSD had an area under the curve ROC = 0.843 (P = 0.003). The cut-off value of 5.00 mm determined a sensitivity of 80% and a specificity of 80% to predict intracranial hypertension. ConclusionsThis study shows that, for our patient population, TCD and ONSD represent methods with significant diagnostic precision for the non-invasive estimation of ICP.

Spaceflight not an eye-popping experience for astronauts.

Spaceflight not an eye-popping experience for astronauts.

Artifact rejection and missing data imputation in cerebral blood flow velocity signals via trace norm minimization

Objective: Many physiological signals are degraded by significant corruptions that limit their usefulness. One example is cerebral blood flow velocity (CBFV) signals, measured by transcranial Doppler, which are susceptible to large errors from patient motion. In this paper, we propose a method to remove artifacts and impute sections of missing data in these signals. Approach: The method exploits the low-order dynamical relationship between CBFV, arterial blood pressure and, where available, intracranial pressure. It enhances the measured signals by fitting them to a low-order dynamical model, using convex regularization terms that improve robustness to large deviations and missing data. The method is based on a convex optimization formulation and utilizes recent work in trace norm approximation and subspace system identification. Main results: Simulations demonstrate that the method successfully removes real CBFV artifacts and can impute missing data with reasonable accuracy. Performance was improved when intracranial pressure data was available. Conclusion: The methods presented can be used by researchers to remove artifacts and estimate missing sections in CBFV signals. The general approach may be applied to other biomedical signal processing settings. Significance: This low-order dynamical approach has ongoing applications in noninvasive intracranial pressure estimation.

Non-Invasive Estimation of Intracranial Pressure by Diffuse Optics: A Proof-of-Concept Study.

Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there are other less critical conditions for which ICP monitoring could still be useful; therefore, there is a need to develop non-invasive methods. We propose a new method to estimate ICP based on the analysis of the non-invasive measurement of pulsatile, microvascular cerebral blood flow with diffuse correlation spectroscopy. This is achieved by training a recurrent neural network using only the cerebral blood flow as the input. The method is validated using a 50% split sample method using the data from a proof-of-concept study. The study involved a population of infants (n = 6) with external hydrocephalus (initially diagnosed as benign enlargement of subarachnoid spaces) as well as a population of adults (n = 6) with traumatic brain injury. The algorithm was applied to each cohort individually to obtain a model and an ICP estimate. In both diverse cohorts, the non-invasive estimation of ICP was achieved with an accuracy of <4 mm Hg and a negligible small bias. Further, we have achieved a good correlation (Pearson's correlation coefficient >0.9) and good concordance (Lin's concordance correlation coefficient >0.9) in comparison with standard clinical, invasive ICP monitoring. This preliminary work paves the way for further investigations of this tool for the non-invasive, bedside assessment of ICP.

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.

A Spectral Approach to Model-Based Noninvasive Intracranial Pressure Estimation.

Intracranial pressure (ICP) normally ranges from 5 to 15mmHg. 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. 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. 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 0.4mmHg and -1.5mmHg, and a precision (standard deviation of the error) of 5.1 mmHg and 4.3mmHg, in estimating mean ICP (range of 1.3mmHg to 24.8mmHg) 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 1.3mmHg and 2.9mmHg respectively. 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.

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

In the search for a reliable, cooperation-independent, noninvasive alternative to invasive intracranial pressure (ICP) monitoring in children, various approaches have been proposed, but at the present time none are capable of providing fully automated, real-time, calibration-free, continuous and accurate ICP estimates. The authors investigated the feasibility and validity of simultaneously monitored arterial blood pressure (ABP) and middle cerebral artery (MCA) cerebral blood flow velocity (CBFV) waveforms to derive noninvasive ICP (nICP) estimates. Invasive ICP and ABP recordings were collected from 12 pediatric and young adult patients (aged 2-25 years) undergoing such monitoring as part of routine clinical care. Additionally, simultaneous transcranial Doppler (TCD) ultrasonography-based MCA CBFV waveform measurements were performed at the bedside in dedicated data collection sessions. The ABP and MCA CBFV waveforms were analyzed in the context of a mathematical model, linking them to the cerebral vasculature's biophysical properties and ICP. The authors developed and automated a waveform preprocessing, signal-quality evaluation, and waveform-synchronization "pipeline" in order to test and objectively validate the algorithm's performance. To generate one nICP estimate, 60 beats of ABP and MCA CBFV waveform data were analyzed. Moving the 60-beat data window forward by one beat at a time (overlapping data windows) resulted in 39,480 ICP-to-nICP comparisons across a total of 44 data-collection sessions (studies). Moving the 60-beat data window forward by 60 beats at a time (nonoverlapping data windows) resulted in 722 paired ICP-to-nICP comparisons. Greater than 80% of all nICP estimates fell within ± 7 mm Hg of the reference measurement. Overall performance in the nonoverlapping data window approach gave a mean error (bias) of 1.0 mm Hg, standard deviation of the error (precision) of 5.1 mm Hg, and root-mean-square error of 5.2 mm Hg. The associated mean and median absolute errors were 4.2 mm Hg and 3.3 mm Hg, respectively. These results were contingent on ensuring adequate ABP and CBFV signal quality and required accurate hydrostatic pressure correction of the measured ABP waveform in relation to the elevation of the external auditory meatus. Notably, the procedure had no failed attempts at data collection, and all patients had adequate TCD data from at least one hemisphere. Last, an analysis of using study-by-study averaged nICP estimates to detect a measured ICP > 15 mm Hg resulted in an area under the receiver operating characteristic curve of 0.83, with a sensitivity of 71% and specificity of 86% for a detection threshold of nICP = 15 mm Hg. This nICP estimation algorithm, based on ABP and bedside TCD CBFV waveform measurements, performs in a manner comparable to invasive ICP monitoring. These findings open the possibility for rational, point-of-care treatment decisions in pediatric patients with suspected raised ICP undergoing intensive care.

Real-Time Noninvasive Intracranial State Estimation Using Unscented Kalman Filter.

Intracranial pressure (ICP) monitoring is desirable as a first-line measure to assist decision-making in cases of increased ICP. Clinically, non-invasive ICP monitoring is also required to avoid infection and hemorrhage in patients. The relationships among the arterial blood pressure (ABP), ICP, cerebral blood flow, and its velocity ( [Formula: see text]) measured by transcranial Doppler ultrasound measurement have been reported. However, real-time non-invasive ICP estimation using these modalities is less well documented. This paper presents a novel algorithm for real-time and non-invasive ICP monitoring with [Formula: see text] and ABP, called direct-current (DC)-ICP. The technique was compared with invasive ICP for 10 acute-brain-injury patients admitted to Cheju Halla Hospital and Gangnam Severance Hospital from July 2017 to June 2018. The inter-subject correlation coefficient between true and estimate was 0.75 and the AUCs of the ROCs for prediction of increased ICP for the DC-ICP methods were 0.83. Thus, [Formula: see text] monitoring can facilitate reliable real-time ICP tracking with our novel DC-ICP algorithm, which can provide valuable information under clinical conditions.

Data-Augmented Modeling of Intracranial Pressure.

Precise management of patients with cerebral diseases often requires intracranial pressure (ICP) monitoring, which is highly invasive and requires a specialized ICU setting. The ability to noninvasively estimate ICP is highly compelling as an alternative to, or screening for, invasive ICP measurement. Most existing approaches for noninvasive ICP estimation aim to build a regression function that maps noninvasive measurements to an ICP estimate using statistical learning techniques. These data-based approaches have met limited success, likely because the amount of training data needed is onerous for this complex applications. In this work, we discuss an alternative strategy that aims to better utilize noninvasive measurement data by leveraging mechanistic understanding of physiology. Specifically, we developed a Bayesian framework that combines a multiscale model of intracranial physiology with noninvasive measurements of cerebral blood flow using transcranial Doppler. Virtual experiments with synthetic data are conducted to verify and analyze the proposed framework. A preliminary clinical application study on two patients is also performed in which we demonstrate the ability of this method to improve ICP prediction.

Non-Invasive Intracranial Pressure Estimation During Combined Exposure to CO₂ and Head-Down Tilt.

Exposure to carbon dioxide (CO2) and cephalad fluid shift are considered factors that affect intracranial pressure (ICP) during spaceflight. Increases in ICP were reported during cephalad fluid shift induced by head-down tilt (HDT), while little is known regarding the effect of additional CO2 during HDT on ICP. Therefore, we tested the hypothesis that this combination increases ICP more than HDT alone. There were 15 healthy male volunteers who underwent 4 types of 10-min interventions consisting of Placebo/Supine (air and supine), CO2/Supine (3% CO2 and supine, CO2 alone), Placebo/HDT (air and -10° HDT, HDT alone), and CO2/HDT (3% CO2 and -10° HDT, combination). Using arterial blood pressure (ABP) and cerebral blood flow velocity waveforms, ICP was estimated noninvasively before and during the four interventions. Two calculation methods were employed. One is based on the signal transformation from ABP to ICP with the intracranial component as a "black box" system (nICP_BB), and the other is based on the equation ICP = ABP - cerebral perfusion pressure, reflecting critical closing pressure (nICP_CrCP). Both nICP_BB and nICP_CrCP significantly increased during Placebo/HDT and CO2/HDT, although there was no statistically significant difference between the nICP indexes of these two interventions. Increases in ICP were observed during both Placebo/HDT and CO2/HDT. Contrary to our hypothesis, the combination of 3% CO2 and -10° HDT did not increase ICP remarkably compared to -10° HDT alone. Therefore, the addition of 3% CO2 is considered to have little effect on increasing ICP during cephalad fluid shift.Kurazumi T, Ogawa Y, Yanagida R, Morisaki H, Iwasaki K. Non-invasive intracranial pressure estimation during combined exposure to CO2 and head-down tilt. Aerosp Med Hum Perform. 2018; 89(4):365-370.

Effects of Prone Position and Positive End-Expiratory Pressure on Noninvasive Estimators of ICP: A Pilot Study.

Prone positioning and positive end-expiratory pressure can improve pulmonary gas exchange and respiratory mechanics. However, they may be associated with the development of intracranial hypertension. Intracranial pressure (ICP) can be noninvasively estimated from the sonographic measurement of the optic nerve sheath diameter (ONSD) and from the transcranial Doppler analysis of the pulsatility (ICPPI) and the diastolic component (ICPFVd) of the velocity waveform. The effect of the prone positioning and positive end-expiratory pressure on ONSD, ICPFVd, and ICPPI was assessed in a prospective study of 30 patients undergoing spine surgery. One-way repeated measures analysis of variance, fixed-effect multivariate regression models, and receiver operating characteristic analyses were used to analyze numerical data. The mean values of ONSD, ICPFVd, and ICPPI significantly increased after change from supine to prone position. Receiver operating characteristic analyses demonstrated that, among the noninvasive methods, the mean ONSD measure had the greatest area under the curve signifying it is the most effective in distinguishing a hypothetical change in ICP between supine and prone positioning (0.86±0.034 [0.79 to 0.92]). A cutoff of 0.43 cm was found to be a best separator of ONSD value between supine and prone with a specificity of 75.0 and a sensitivity of 86.7. Noninvasive ICP estimation may be useful in patients at risk of developing intracranial hypertension who require prone positioning.