Transcranial Doppler combined with quantitative EEG brain function monitoring and outcome prediction in patients with severe acute intracerebral hemorrhage

The signs of computer tomography combined with artificial intelligence can indicate the correlation between status of consciousness and primary brainstem hemorrhage of patients

Background

For patients of primary brainstem hemorrhage (PBH), it is crucial to find a method that can quickly and accurately predict the correlation between status of consciousness and PBH.

Objective

To analyze the value of computer tomography (CT) signs in combination with artificial intelligence (AI) technique in predicting the correlation between status of consciousness and PBH.

Methods

A total of 120 patients with PBH were enrolled from August 2011 to March 2021 according to the criteria. Patients were divided into three groups [consciousness, minimally conscious state (MCS) and coma] based on the status of consciousness. Then, first, Mann–Whitney U test and Spearman rank correlation test were used on the factors: gender, age, stages of intracerebral hemorrhage, CT signs with AI or radiology physicians, hemorrhage involving the midbrain or ventricular system. We collected hemorrhage volumes and mean CT values with AI. Second, those significant factors were screened out by the Mann–Whitney U test and those highly or moderately correlated by Spearman’s rank correlation test, and a further ordinal multinomial logistic regression analysis was performed to find independent predictors of the status of consciousness. At last, receiver operating characteristic (ROC) curves were drawn to calculate the hemorrhage volume for predictively assessing the status of consciousness.

Results

Preliminary meaningful variables include hemorrhage involving the midbrain or ventricular system, hemorrhage volume, grade of hematoma shape and density, and CT value from Mann–Whitney U test and Spearman rank correlation test. It is further shown by ordinal multinomial logistic regression analysis that hemorrhage volume and hemorrhage involving the ventricular system are two major predictors of the status of consciousness. It showed from ROC that the hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL correspond to consciousness, MCS or coma, respectively. If the hemorrhage volume is the same, hemorrhage involving the ventricular system should be correlated with more severe disorders of consciousness (DOC).

Conclusion

CT signs combined with AI can predict the correlation between status of consciousness and PBH. Hemorrhage volume and hemorrhage involving the ventricular system are two independent factors, with hemorrhage volume in particular reaching quantitative predictions.

Theta-Alpha Variability on Admission EEG Is Associated With Outcome in Pediatric Cerebral Malaria

PURPOSE

Pediatric cerebral malaria has high rates of mortality and neurologic morbidity. Although several biomarkers, including EEG, are associated with survival or morbidity, many are resource intensive or require skilled interpretation for clinical use. Automation of quantitative interpretation of EEG may be preferable in resource-limited settings, where trained interpreters are rare. As currently used quantitative EEG factors do not adequately describe the spectrum of variability seen in studies from children with cerebral malaria, the authors developed and validated a new quantitative EEG variable, theta-alpha variability (TAV).

METHODS

The authors developed TAV, a new quantitative variable, as a composite of multiple automated EEG outputs. EEG records from 194 children (6 months to 14 years old) with cerebral malaria were analyzed. Independent EEG interpreters performed standard quantitative and qualitative analyses, with the addition of the newly created variable. The associations of TAV with other quantitative EEG factors, a qualitative assessment of variability, and outcomes were assessed.

RESULTS

Theta-alpha variability was not highly correlated with alpha, theta, or delta power and was not associated with qualitative measures of variability. Children whose EEGs had higher values of TAV had a lower risk of death (odds ratio = 0.934, 95% confidence interval = 0.902-0.966) or neurologic sequelae (odds ratio = 0.960, 95% confidence interval = 0.932-0.990) compared with those with lower values. Receiver operating characteristic analysis in predicting death at a TAV threshold of 0.244 yielded a sensitivity of 74% and specificity of 70% for an area under the receiver operating characteristic curve of 0.755.

CONCLUSIONS

Theta-alpha variability is independently associated with outcome in pediatric cerebral malaria and can predict death with high sensitivity and specificity. Automated determination of this newly created EEG factor holds promise as a potential method to increase the clinical utility of EEG in resource-limited settings by allowing interventions to be targeted to those at higher risk of death or disability.

Pathological changes of brain oscillations following ischemic stroke

Brain oscillations recorded in the extracellular space are among the most important aspects of neurophysiology data reflecting the activity and function of neurons in a population or a network. The signal strength and patterns of brain oscillations can be powerful biomarkers used for disease detection and prediction of the recovery of function. Electrophysiological signals can also serve as an index for many cutting-edge technologies aiming to interface between the nervous system and neuroprosthetic devices and to monitor the efficacy of boosting neural activity. In this review, we provided an overview of the basic knowledge regarding local field potential, electro- or magneto- encephalography signals, and their biological relevance, followed by a summary of the findings reported in various clinical and experimental stroke studies. We reviewed evidence of stroke-induced changes in hippocampal oscillations and disruption of communication between brain networks as potential mechanisms underlying post-stroke cognitive dysfunction. We also discussed the promise of brain stimulation in promoting post stroke functional recovery via restoring neural activity and enhancing brain plasticity.

Quantitative EEG parameters can improve the predictive value of the non-traumatic neurological ICU patient prognosis through the machine learning method

Background

Better outcome prediction could assist in reliable classification of the illnesses in neurological intensive care unit (ICU) severity to support clinical decision-making. We developed a multifactorial model including quantitative electroencephalography (QEEG) parameters for outcome prediction of patients in neurological ICU.

Methods

We retrospectively analyzed neurological ICU patients from November 2018 to November 2021. We used 3-month mortality as the outcome. Prediction models were created using a linear discriminant analysis (LDA) based on QEEG parameters, APACHEII score, and clinically relevant features. Additionally, we compared our best models with APACHEII score and Glasgow Coma Scale (GCS). The DeLong test was carried out to compare the ROC curves in different models.

Results

A total of 110 patients were included and divided into a training set (n=80) and a validation set (n = 30). The best performing model had an AUC of 0.85 in the training set and an AUC of 0.82 in the validation set, which were better than that of GCS (training set 0.64, validation set 0.61). Models in which we selected only the 4 best QEEG parameters had an AUC of 0.77 in the training set and an AUC of 0.71 in the validation set, which were similar to that of APACHEII (training set 0.75, validation set 0.73). The models also identified the relative importance of each feature.

Conclusion

Multifactorial machine learning models using QEEG parameters, clinical data, and APACHEII score have a better potential to predict 3-month mortality in non-traumatic patients in neurological ICU.

Noninvasive ultrasonic induction of cerebrospinal fluid flow enhances intrathecal drug delivery

Intrathecal drug delivery is routinely used in the treatment and prophylaxis of varied central nervous system conditions, as doing so allows drugs to directly bypass the blood-brain barrier. However, the utility of this route of administration is limited by poor brain and spinal cord parenchymal drug uptake from the cerebrospinal fluid. We demonstrate that a simple noninvasive transcranial ultrasound protocol can significantly increase influx of cerebrospinal fluid into the perivascular spaces of the brain, to enhance the uptake of intrathecally administered drugs. Specifically, we administered small (~1 kDa) and large (~155 kDa) molecule agents into the cisterna magna of rats and then applied low, diagnostic-intensity focused ultrasound in a scanning protocol throughout the brain. Using real-time magnetic resonance imaging and ex vivo histologic analyses, we observed significantly increased uptake of small molecule agents into the brain parenchyma, and of both small and large molecule agents into the perivascular space from the cerebrospinal fluid. Notably, there was no evidence of brain parenchymal damage following this intervention. The low intensity and noninvasive approach of transcranial ultrasound in this protocol underscores the ready path to clinical translation of this technique. In this manner, this protocol can be used to directly bypass the blood-brain barrier for whole-brain delivery of a variety of agents. Additionally, this technique can potentially be used as a means to probe the causal role of the glymphatic system in the variety of disease and physiologic processes to which it has been correlated.

Comparing the Effect of Dexmedetomidine and Midazolam in Patients with Brain Injury

BACKGROUND

Studies have shown that dexmedetomidine improves neurological function. Whether dexmedetomidine reduces mortality or improves quantitative electroencephalography (qEEG) among patients post-craniotomy remains unclear.

METHODS

This single-center randomized study was conducted prospectively from 1 January 2019 to 31 December 2020. Patients who were transferred to the ICU after craniotomy within 24 h were included. The analgesic was titrated to a Critical care Pain Observation Tool (CPOT) score ≤2, and the sedative was titrated to a Richmond Agitation-Sedation Scale (RASS) score ≤-3 for at least 24 h. The qEEG signals were collected by four electrodes (F3, T3, F4, and T4 according to the international 10/20 EEG electrode practice). The primary outcome was 28-day mortality and qEEG results on day 1 and day 3 after sedation.

RESULTS

One hundred and fifty-one patients were enrolled in this study, of whom 77 were in the dexmedetomidine group and 74 in the midazolam group. No significant difference was found between the two groups in mortality at 28 days (14.3% vs. 24.3%; p = 0.117) as well as in the theta/beta ratio (TBR), the delta/alpha ratio (DAR), and the (delta + theta)/(alpha + beta) ratio (DTABR) between the two groups on day 1 or day 3. However, both the TBR and the DTABR were significantly increased in the dexmedetomidine group. The DTABR in the midazolam group was significantly increased. The DAR was significantly increased on the right side in the dexmedetomidine group (20.4 (11.6-43.3) vs. 35.1 (16.7-65.0), p = 0.006) as well as on both sides in the midazolam group (Left: 19.5 (10.1-35.8) vs. 37.3 (19.3-75.7), p = 0.006; Right: 18.9 (10.1-52.3) vs. 39.8 (17.5-99.9), p = 0.002).

CONCLUSION

Compared with midazolam, dexmedetomidine did not lead to a lower 28-day mortality or better qEEG results in brain injury patients after a craniotomy.

Surface electroencephalography (EEG) during the acute phase of stroke to assist with diagnosis and prediction of prognosis: a scoping review

BACKGROUND

Stroke is a common medical emergency responsible for significant mortality and disability. Early identification improves outcomes by promoting access to time-critical treatments such as thrombectomy for large vessel occlusion (LVO), whilst accurate prognosis could inform many acute management decisions. Surface electroencephalography (EEG) shows promise for stroke identification and outcome prediction, but evaluations have varied in technology, setting, population and purpose. This scoping review aimed to summarise published literature addressing the following questions: 1. Can EEG during acute clinical assessment identify: a) Stroke versus non-stroke mimic conditions. b) Ischaemic versus haemorrhagic stroke. c) Ischaemic stroke due to LVO. 2. Can these states be identified if EEG is applied < 6 h since onset. 3. Does EEG during acute assessment predict clinical recovery following confirmed stroke.

METHODS

We performed a systematic search of five bibliographic databases ending 19/10/2020. Two reviewers assessed eligibility of articles describing diagnostic and/or prognostic EEG application < 72 h since suspected or confirmed stroke.

RESULTS

From 5892 abstracts, 210 full text articles were screened and 39 retained. Studies were small and heterogeneous. Amongst 21 reports of diagnostic data, consistent associations were reported between stroke, greater delta power, reduced alpha/beta power, corresponding ratios and greater brain asymmetry. When reported, the area under the curve (AUC) was at least good (0.81-1.00). Only one study combined clinical and EEG data (AUC 0.88). There was little data found describing whether EEG could identify ischaemic versus haemorrhagic stroke. Radiological changes suggestive of LVO were also associated with increased slow and decreased fast waves. The only study with angiographic proof of LVO reported AUC 0.86 for detection < 24 h since onset. Amongst 26 reports of prognostic data, increased slow and reduced fast wave EEG changes were associated with future dependency, neurological impairment, mortality and poor cognition, but there was little evidence that EEG enhanced outcome prediction relative to clinical and/or radiological variables. Only one study focussed solely on patients < 6 h since onset for predicting neurological prognosis post-thrombolysis, with more favourable outcomes associated with greater hemispheric symmetry and a greater ratio of fast to slow waves.

CONCLUSIONS

Although studies report important associations with EEG biomarkers, further technological development and adequately powered real-world studies are required before recommendations can be made regarding application during acute stroke assessment.

Multimodal Monitoring in Large Hemispheric Infarction: Quantitative Electroencephalography Combined With Transcranial Doppler for Prognosis Prediction

Background: We aimed to explore whether transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) can improve prognosis evaluation in patients with a large hemispheric infarction (LHI) and to establish an accurate prognosis prediction model.

Methods: We prospectively assessed 90-day mortality in patients with LHI. Brain function was monitored using TCD-QEEG at the bedside of the patient.

Results: Of the 59 (55.3 ± 10.6 years; 17 men) enrolled patients, 37 (67.3%) patients died within 90 days. The Cox regression analyses revealed that the Glasgow Coma Scale (GCS) score ≤ 8 [hazard ratio (HR), 3.228; 95% CI, 1.335–7.801; p = 0.009], TCD-terminal internal carotid artery as the offending vessel (HR, 3.830; 95% CI, 1.301–11.271; p = 0.015), and QEEG-a (delta + theta)/(alpha + beta) ratio ≥ 3 (HR, 3.647; 95% CI, 1.170–11.373; p = 0.026) independently predicted survival duration. Combining these three factors yielded an area under the receiver operating characteristic curve of 0.905 and had better predictive accuracy than those of individual variables (p < 0.05).

Conclusion: TCD and QEEG complement the GCS score to create a reliable multimodal method for monitoring prognosis in patients with LHI.

Nomogram Prediction of Short-Term Outcome After Intracerebral Hemorrhage

Background

The early symptoms of patients with elevated intracranial pressure (ICP) after intracerebral hemorrhage (ICH) are easily overlooked, which will result in missing the optimal opportunity for clinical intervention. However, it is difficult for ICH patients admitted to the neurology department to receive invasive ICP monitoring, although it is crucial for the early identification of neurologic deterioration (ND).

Objective

The aim of this study is to investigate the association between the changes of transcranial Doppler (TCD) variables and ND after onset and establish a nomogram for predicting the short-term outcome of ICH.

Methods

A total of 297 patients were recruited and their clinical characteristics and the changes of TCD variables were recorded. The independent prognostic factors for the ND after onset in the ICH patients were screened from multivariate Logistic regression analysis, which were served as inputs for the nomogram construction. Discrimination and calibration validations were performed to assess the performance of the nomogram [concordance index (C-index) for discrimination and Hosmer–Lemeshow (HL) test for calibration] and the decision curve analysis was applied to assess the clinical suitability.

Results

ΔaPI [defined as the change of pulsatility index (PI) between the 1st and 3rd day after onset for affected hemisphere] was independently associated with the ND after onset. Moreover, hematoma volume, presence of intraventricular hemorrhage, and Glasgow coma scale were also the independent prognostic factors of ND. The developed nomogram incorporating ΔaPI showed good discrimination (C-index: 0.916 after 1000 bootstrapping) and calibration (P=0.412, HL test) and yielded net benefits.

Conclusion

The nomogram incorporating ΔaPI might be useful in predicting the risk of ND within 14 days after onset, which might help identify patients in the neurology department in need of further care.

Transcranial Doppler Combined With Quantitative Electroencephalography Brain Function Monitoring for Estimating the Prognosis of Patients With Posterior Circulation Cerebral Infarction

Posterior circulation cerebral infarction (PCCI) can lead to deceased infratentorial cerebral blood flow (CBF) and metabolism. Neural activity is closely related to regional cerebral blood flow both spatially and temporally. Transcranial Doppler (TCD) combined with quantitative electroencephalography (QEEG) is a technique that evaluates neurovascular coupling and involves synergy between the metabolic and vascular systems. This study aimed to monitor brain function using TCD-QEEG and estimate the efficacy of TCD-QEEG for predicting the prognosis of patients with PCCI. We used a TCD-QEEG recording system to perform quantitative brain function monitoring; we recorded the related clinical variables simultaneously. The data were analyzed using a Cox proportional hazards regression model. Receiver-operating characteristic (ROC) curve analysis was used to evaluate the cut-off for the diastolic flow velocity (VD) and (delta + theta)/(alpha + beta) ratio (DTABR). The area under the ROC curve (AUROC) was calculated to assess the predictive validity of the study variables. Forty patients (aged 63.7 ± 9.9 years; 30 men) were assessed. Mortality at 90 days was 40%. The TCD indicators of VD [hazard ratio (HR) 0.168, confidence interval (CI) 0.047-0.597, p = 0.006] and QEEG indicators of DTABR (HR 12.527, CI 1.637-95.846, p = 0.015) were the independent predictors of the clinical outcomes. The AUROC after combination of VD and DTABR was 0.896 and showed better predictive accuracy than the Glasgow Coma Scale score (0.75), VD (0.76), and DTABR (0.781; all p < 0.05). TCD-QEEG provides a good understanding of the coupling mechanisms in the brain and can improve our ability to predict the prognosis of patients with PCCI.

Multi-Center Validation Study of Automated Classification of Pathological Slowing in Adult Scalp Electroencephalograms Via Frequency Features

Pathological slowing in the electroencephalogram (EEG) is widely investigated for the diagnosis of neurological disorders. Currently, the gold standard for slowing detection is the visual inspection of the EEG by experts, which is time-consuming and subjective. To address those issues, we propose three automated approaches to detect slowing in EEG: Threshold-based Detection System (TDS), Shallow Learning-based Detection System (SLDS), and Deep Learning-based Detection System (DLDS). These systems are evaluated on channel-, segment-, and EEG-level. The three systems perform prediction via detecting slowing at individual channels, and those detections are arranged in histograms for detection of slowing at the segment- and EEG-level. We evaluate the systems through Leave-One-Subject-Out (LOSO) cross-validation (CV) and Leave-One-Institution-Out (LOIO) CV on four datasets from the US, Singapore, and India. The DLDS achieved the best overall results: LOIO CV mean balanced accuracy (BAC) of 71.9%, 75.5%, and 82.0% at channel-, segment- and EEG-level, and LOSO CV mean BAC of 73.6%, 77.2%, and 81.8% at channel-, segment-, and EEG-level. The channel- and segment-level performance is comparable to the intra-rater agreement (IRA) of an expert of 72.4% and 82%. The DLDS can process a 30 min EEG in 4 s and can be deployed to assist clinicians in interpreting EEGs.

Monitoring of patients with brainstem hemorrhage: A simultaneous study of quantitative electroencephalography and transcranial Doppler

OBJECTIVE

To explore whether quantitative electroencephalography (QEEG) and transcranial Doppler (TCD) can be used to evaluate patients with acute severe brainstem hemorrhage (ASBH).

METHODS

We prospectively enrolled patients with ASBH and assessed their mortality at the 90-day follow-up. The patients' demographic data, serological data, and clinical factors were recorded. Quantitative brain function monitoring was performed using a TCD-QEEG recording system attached to the patient's bedside.

RESULTS

Thirty-one patients (55.3 ± 10.6 years; 17 men) were studied. Mortality at 90 days was at 61.3%. There was no significant difference in TCD-related parameters between the survival group and the death group (p > 0.05). Among the QEEG-related indexes, only the (delta + theta)/(alpha + beta) ratio (DTABR) (odds ratio 11.555, 95%confidence interval 1.413-94.503, p = 0.022) was an independent predictor of clinical outcome; the area under the ROC curve of DTABR was 0.921, cut-off point was 3.88, sensitivity was 79%, and specificity was 100%.

CONCLUSIONS

In patients with ASBH, QEEG can effectively inform the clinical prognosis regarding 90-day mortality, while TCD cannot.

SIGNIFICANCE

QEEG shows promise for informing the mortality prognosis of patients with ASBH.

Causal relationship between neuronal activity and cerebral hemodynamics in patients with ischemic stroke

OBJECTIVE

Neurovascular coupling enables rapid adaptation of cerebral blood flow (CBF) to support neuronal activity. Modern techniques enable the simultaneous recording of neuronal activities and hemodynamic parameters. However, the causal relationship between electrical brain activity and CBF is still unclarified. In this study, we investigated the causal relationship between surface electroencephalogram (EEG) and cerebral blood flow velocity (FV) from transcranial Doppler using Granger causality (GC) analysis.

APPROACH

Twenty simultaneous recordings of EEG and FV from 17 acute ischemic stroke patients were studied. Each patient had simultaneous, continuous monitoring of EEG and bilateral FVs in either the middle cerebral arteries or posterior cerebral arteries. The causal interactions between FV (0.006-0.4 Hz) and EEG (delta, theta, alpha, beta and gamma bands) were investigated through GC index (GCI). In order to make the GCIs comparable, the proportion of GCI (PGCI) values where G-causality is statistically significant were calculated. Scores on the NIH Stroke Scale (NIHSS) and the modified Rankin Scale (mRS) for neurologic disability were recorded respectively at discharge. Patients were divided into a deceased (mRS = 6) and a survival group (mRS = 1 to 5), and a favorable (mRS: 1 to 2) and unfavorable outcome group (mRS: 3 ~ 6).

MAIN RESULTS

This study identified a causal relationship from EEG→FV, indicating EEG contained information that can be used for FV prediction. PGCI was negatively related with mRS (p < 0.05), indicating that stronger causalities between EEG and FV exist in patients with better outcome. The NIHSS was negatively related with the asymmetry of the two-side PGCI, calculated as the difference between the lesional side and non-lesional side PGCI.

SIGNIFICANCE

A causal relationship from EEG→FV may exist in patients with ischemic stroke. The strength of G-causality may be related to stroke severity at discharge.

Global brain inflammation in stroke

Stroke, including acute ischaemic stroke and intracerebral haemorrhage, results in neuronal cell death and the release of factors such as damage-associated molecular patterns (DAMPs) that elicit localised inflammation in the injured brain region. Such focal brain inflammation aggravates secondary brain injury by exacerbating blood-brain barrier damage, microvascular failure, brain oedema, oxidative stress, and by directly inducing neuronal cell death. In addition to inflammation localised to the injured brain region, a growing body of evidence suggests that inflammatory responses after a stroke occur and persist throughout the entire brain. Global brain inflammation might continuously shape the evolving pathology after a stroke and affect the patients' long-term neurological outcome. Future efforts towards understanding the mechanisms governing the emergence of so-called global brain inflammation would facilitate modulation of this inflammation as a potential therapeutic strategy for stroke.

Advancements in Managing Intracerebral Hemorrhage: Transition from Nihilism to Optimism

There have been significant advancements in the management of intracerebral hemorrhage (ICH) stemming from new knowledge on its pathogenesis. Major clinical trials, such as Surgical Trial in Lobar Intracerebral Hemorrhage (STICH I and II), have shown only a small, albeit clinically relevant, advantage of surgical interventions in specific subsets of patients suffering from ICH. Currently, the aim is to use a minimally invasive and safe trajectory in removing significant brain hematomas with the aid of neuro-endoscopy or precise guidance through neuro-navigation, thereby avoiding a collateral damage to the surrounding normal brain tissue. A fundamental rational to such approach is to safely remove hematoma, preventing the ongoing mass effect resulting in brain herniation, and to minimize deleterious effects of iron released from hematoma to brain cells. The clot lysis process is facilitated with the adjunctive use of recombinant tissue plasminogen activator and sonolysis. Revised recommendations for the management of ICH focus on a holistic approach, with special emphasis on early patient mobilization and graded rehabilitative process. There has been a paradigm shift in the management algorithm, putting emphasis on early and safe removal of brain hematoma and then focusing on the improvement of patients' quality of life. We have made significant progress in transition from nihilism toward optimism, based on evidence-based management of such a severe global health scourge as intracranial hemorrhage.