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Background: The monitoring and analysis of quasi-periodic biological signals such as electrocardiography (ECG), intracranial pressure (ICP), and cerebral blood flow velocity (CBFV) waveforms plays an important role in the early detection of adverse patient events and contributes to improved care management in the intensive care unit (ICU). This work quantitatively evaluates existing computational frameworks for automatically extracting peaks within ICP waveforms., Methods: Peak detection techniques based on state-of-the-art machine learning models were evaluated in terms of robustness to varying noise levels. The evaluation was performed on a dataset of ICP signals assembled from 700 h of monitoring from 64 neurosurgical patients. The groundtruth of the peak locations was established manually on a subset of 13, 611 pulses. Additional evaluation was performed using a simulated dataset of ICP with controlled temporal dynamics and noise., Results: The quantitative analysis of peak detection algorithms applied to individual waveforms indicates that most techniques provide acceptable accuracy with a mean absolute error (MAE) ≤ 10 ms without noise. In the presence of a higher noise level, however, only kernel spectral regression and random forest remain below that error threshold while the performance of other techniques deteriorates. Our experiments also demonstrated that tracking methods such as Bayesian inference and long short-term memory (LSTM) can be applied continuously and provide additional robustness in situations where single pulse analysis methods fail, such as missing data., Conclusion: While machine learning-based peak detection methods require manually labeled data for training, these models outperform conventional signal processing ones based on handcrafted rules and should be considered for peak detection in modern frameworks. In particular, peak tracking methods that incorporate temporal information between successive periods of the signals have demonstrated in our experiments to provide more robustness to noise and temporary artifacts that commonly arise as part of the monitoring setup in the clinical setting., (© 2024. The Author(s).)

Optimal cerebral perfusion pressure (CPPopt)-targeted treatment of traumatic brain injury (TBI) patients requires 2-8 h multi-modal monitoring data accumulation to identify CPPopt value for individual patient. Minimizing the time required for monitoring data accumulation is needed to improve the efficacy of CPPopt-targeted therapy. A retrospective analysis of multimodal physiological monitoring data from 87 severe TBI patients was performed by separately representing cerebrovascular autoregulation (CA) indices in relation to CPP, arterial blood pressure (ABP), and intracranial pressure (ICP) to improve the existing CPPopt identification algorithms. Machine learning (ML)-based algorithms were developed for automatic identification of informative data segments that were used for reliable CPPopt, ABPopt, ICPopt and the lower/upper limits of CA (LLCA/ULCA) identification. The reference datasets of the informative data segments and, artifact-distorted segments, and the datasets of different clinical situations were used for training the ML-based algorithms, allowing us to choose the appropriate individualized CPP-, ABP- or ICP-guided management for 79% of the full monitoring time for the studied population. The developed ML-based algorithms allow us to recognize informative physiological ABP/ICP variations within 24 min intervals with an accuracy up to 79% (compared to the initial accuracy of 74%) and use these segments for timely optimal value identification or CA limits determination in CPP, ABP or ICP data. Prospective clinical studies are needed to prove the efficiency of the developed algorithms., (© 2022. The Author(s).)

The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.

Background: Postoperative cognitive dysfunction (POCD) occurs in approximately 33-83% of patients after cardiac surgery with cardiopulmonary bypass (CPB). Recent clinical data suggest that real-time, intraoperative monitoring of patient-specific cerebrovascular autoregulation (CA) may help to prevent POCD by detecting individual critical limits for mean arterial pressure (MAP) outside which CA is impaired. Objectives of the study were to detect the episodes of impaired CA during cardiac surgery with CPB, and to investigate the association between CA impairment and POCD., Methods: The observational study of non-invasive ultrasonic volumetric CA monitoring included 59 patients undergoing elective coronary artery bypass graft surgery with CPB. All patients underwent series of neuropsychological tests the day before and ten days after the surgery in order to evaluate cognitive function., Results: Twenty-two patients (37%) experienced POCD, 37 patients (63%) showed no cognitive deterioration. The duration of the single longest CA impairment event was found reliably associated with occurrence of POCD (P<0.05). The critical duration of the single longest CA impairment event was 5.03 minutes (odds ratio 14.5; CI 3.9-51.8) for studied population., Conclusions: Prospective clinical study showed that single longest CA impairment may result in post-operative deterioration of mental abilities. The duration of the single longest CA impairment event is the risk factor that is associated with POCD.

Background: This prospective study of an innovative non-invasive ultrasonic cerebrovascular autoregulation (CA) monitoring method is based on real-time measurements of intracranial blood volume (IBV) reactions following changes in arterial blood pressure. In this study, we aimed to determine the clinical applicability of a non-invasive CA monitoring method by performing a prospective comparative clinical study of simultaneous invasive and non-invasive CA monitoring on intensive care patients., Methods: CA was monitored in 61 patients with severe traumatic brain injuries invasively by calculating the pressure reactivity index (PRx) and non-invasively by calculating the volumetric reactivity index (VRx) simultaneously. The PRx was calculated as a moving correlation coefficient between intracranial pressure and arterial blood pressure slow waves. The VRx was calculated as a moving correlation coefficient between arterial blood pressure and non-invasively-measured IBV slow waves., Results: A linear regression between VRx and PRx averaged per patients' monitoring session showed a significant correlation (r = 0.843, p < 0.001; 95% confidence interval 0.751 - 0.903). The standard deviation of the difference between VRx and PRx was 0.192; bias was - 0.065., Conclusions: This prospective clinical study of the non-invasive ultrasonic volumetric reactivity index VRx monitoring, based on ultrasonic time-of-flight measurements of IBV dynamics, showed significant coincidence of non-invasive VRx index with invasive PRx index. The ultrasonic time-of-flight method reflects blood volume changes inside the acoustic path, which crosses both hemispheres of the brain. This method does not reflect locally and invasively-recorded intracranial pressure slow waves, but the autoregulatory reactions of both hemispheres of the brain. Therefore, VRx can be used as a non-invasive cerebrovascular autoregulation index in the same way as PRx and can also provide information about the CA status encompassing all intracranial hemodynamics.

Objective: To determine normal ranges for traditional transcranial Doppler (TCD) measurements for two age groups (14-19 and 20-29 years) and compare to existing literature results. The development of a normal range for TCD measurements will be required for the development of diagnostic and prognostic tests in the future., Materials and Methods: We performed TCD on the middle cerebral artery on 147 healthy subjects aged 18.9 years (SD = 2.1) and calculated mean cerebral blood flow velocity (mCBFV) and pulsatility index (PI). The study population was divided into two age populations (14-19 and 20-29 years)., Results: There was a significant decrease in PI (p = 0.015) for the older age group with no difference in mCBFV., Conclusion: Age-related, normal data are a prerequisite for TCD to continue to gain clinical acceptance. Our correlation of age-related TCD findings with previously published results as the generally accepted "gold standard" underlines the validity and sensitivity of this ultrasound method.

Purpose: The maintenance of patient-specific optimal cerebral perfusion pressure (CPPopt) is crucial for patients with traumatic brain injury (TBI). The goal of the study was to explore the influence of CPP declination from CPPopt value on the TBI patients' outcome., Methods: The CPP and cerebrovascular autoregulation (CA) monitoring of 52 TBI patients was performed. Patient-specific CPPopt has been identified and the associations between the patients' outcome and complex influence of time of CPP declination from CPPopt value, age, and the duration of CA impairment episodes has been analyzed., Results: The multiple correlation coefficient between the Glasgow outcome scale (GOS), duration of CA impairment events and percentage time, when 0<ΔCPPopt<10mmHg was r=-0.643 (P<0.001). The multiple correlation coefficients between GOS, age, and percentage time of ΔCPPopt when 0<ΔCPPopt<10mmHg was r=-0.587 (P<0.001)., Conclusion: The CPPopt-targeted patient-specific management might be useful for stabilizing CA in TBI patients as well as for improving their outcome. Better outcomes were obtained by maintaining CPP in light hyperperfusion condition (up to 10mmHg above CPPopt) when CPPopt is in the range of 60-80mmHg, and keeping CPP within the range of CPPopt +/-5mmHg when CPPopt is above 80mmHg., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Cerebrovascular autoregulation (CA) is an important hemodynamic mechanism that protects the brain against inappropriate fluctuations in cerebral blood flow in the face of changing cerebral perfusion pressure. Temporal CA failure is associated with worse outcomes in various acute neurological diseases. An integrative approach is presently used according to the existing paradigm for the association of series of temporal CA impairments with the outcomes of patients with traumatic brain injury (TBI)., Objective: To explore the influence of the duration of CA impairment events on severe TBI patient outcomes. Patient age was also included in the analysis of the prospectively collected clinical data., Methods: CA monitoring included 33 prospective severe TBI patients. The pressure reactivity index [PRx(t)] was continuously monitored to collect information on the dynamics of CA status and to analyze associations between the duration of the longest CA impairment event and patient outcomes., Results: The Glasgow outcome scale and the duration of the longest CA impairment were negatively correlated. The duration of autoregulation impairment significantly correlated with worse outcomes. Multidimensional representation of Glasgow outcome scale plots showed that better outcomes were obtained for younger patients (age < 47 years) and those whose longest CA impairment event was shorter than 40 minutes if PRx(t) was above 0.7 in the CA impairment event., Conclusion: Unfavorable outcomes for TBI patients are more significantly associated with the duration of the single longest CA impairment episode at a high PRx(t) value, rather than with averaged PRx(t) values or the average time of all CA impairment episodes., Abbreviations: ABP, arterial blood pressureABP(t), continuous reference arterial blood pressureCA, cerebrovascular autoregulationCBF, cerebral blood flowCPP, cerebral perfusion pressureGOS, Glasgow outcome scaleGOSHD, Glasgow outcome scale after hospital dischargeGOS6M, Glasgow outcome scale at 6 months after dischargeICP, intracranial pressureICP(t), continuously monitored intracranial pressureLCAI, longest CA impairmentoptCPP, optimal cerebral perfusion pressurePRx(t), pressure reactivity indexTBI, traumatic brain injury.

An innovative absolute intracranial pressure (ICP) value measurement method has been validated by multicenter comparative clinical studies. The method is based on two-depth transcranial Doppler (TCD) technology and uses intracranial and extracranial segments of the ophthalmic artery as pressure sensors. The ophthalmic artery is used as a natural pair of "scales" that compares ICP with controlled pressure Pe, which is externally applied to the orbit. To balance the scales, ICP = Pe a special two-depth TCD device was used as a pressure balance indicator. The proposed method is the only noninvasive ICP measurement method that does not need patient-specific calibration.