Neurocritical care for intracranial haemorrhage: a systematic review of recent studies

Rapid chest compression effects on intracranial pressure in patients with acute cerebral injury

BACKGROUND

Patients with acute brain injury often require invasive mechanical ventilation, increasing the risk of developing complications such as respiratory secretions retention. Rapid chest compression is a manual chest physiotherapy technique that aims to improve clearance of secretions in these patients. However, the rapid chest compression technique has been suggested to be associated with increased intracranial pressure in patients with acute brain injury. The aim of this work is to elucidate the effects of the technique on intracranial pressure in mechanically ventilated patients with acute brain injury. Furthermore, the effects of the technique in different volumes and flows recorded by the ventilator and the relationship between the pressure applied in the intervention group and the different variables will also be studied.

METHODS

Randomized clinical trial, double-blinded. Patients with acute brain injury on invasive mechanical ventilation > 48 h will be included and randomized in two groups. In the control group, a technique of passive hallux mobilization will be applied, and in the intervention group, it will be performed using the rapid chest compression technique. Intracranial pressure (main variable) will be collected with an intracranial pressure monitoring system placed at the lateral ventricles (Integra Camino).

DISCUSSION

The safety of chest physiotherapy techniques in patients at risk of intracranial hyperpressure is still uncertain. The aim of this study is to identify if the rapid manual chest compression technique is safe in ventilated patients with acute brain injury.

TRIAL REGISTRATION

NCT03609866 . Registered on 08/01/2018.

Pulmonary complications and respiratory management in neurocritical care: a narrative review

ABSTRACT

Neurocritical care (NCC) is not only generally guided by principles of general intensive care, but also directed by specific goals and methods. This review summarizes the common pulmonary diseases and pathophysiology affecting NCC patients and the progress made in strategies of respiratory support in NCC. This review highlights the possible interactions and pathways that have been revealed between neurological injuries and respiratory diseases, including the catecholamine pathway, systemic inflammatory reactions, adrenergic hypersensitivity, and dopaminergic signaling. Pulmonary complications of neurocritical patients include pneumonia, neurological pulmonary edema, and respiratory distress. Specific aspects of respiratory management include prioritizing the protection of the brain, and the goal of respiratory management is to avoid inappropriate blood gas composition levels and intracranial hypertension. Compared with the traditional mode of protective mechanical ventilation with low tidal volume (Vt), high positive end-expiratory pressure (PEEP), and recruitment maneuvers, low PEEP might yield a potential benefit in closing and protecting the lung tissue. Multimodal neuromonitoring can ensure the safety of respiratory maneuvers in clinical and scientific practice. Future studies are required to develop guidelines for respiratory management in NCC.

Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques

Traumatic Brain Injury (TBI) is a devastating and life-threatening medical condition that can result in long-term physical and mental disabilities and even death. Early and accurate detection of Intracranial Hemorrhage (ICH) in TBI is crucial for analysis and treatment, as the condition can deteriorate significantly with time. Hence, a rapid, reliable, and cost-effective computer-aided approach that can initially capture the hematoma features is highly relevant for real-time clinical diagnostics. In this study, the Gray Level Occurrence Matrix (GLCM), the Gray Level Run Length Matrix (GLRLM), and Hu moments are used to generate the texture features. The best set of discriminating features are obtained using various meta-heuristic algorithms, and these optimal features are subjected to different classifiers. The synthetic samples are generated using ADASYN to compensate for the data imbalance. The proposed CAD system attained 95.74% accuracy, 96.93% sensitivity, and 94.67% specificity using statistical and GLRLM features along with KNN classifier. Thus, the developed automated system can enhance the accuracy of hematoma detection, aid clinicians in the fast interpretation of CT images, and streamline triage workflow.

Perioperative Management of Polytrauma Patients with Severe Traumatic Brain Injury Undergoing Emergency Extracranial Surgery: A Narrative Review

Managing the acute phase after a severe traumatic brain injury (TBI) with polytrauma represents a challenging situation for every trauma team member. A worldwide variability in the management of these complex patients has been reported in recent studies. Moreover, limited evidence regarding this topic is available, mainly due to the lack of well-designed studies. Anesthesiologists, as trauma team members, should be familiar with all the issues related to the management of these patients. In this narrative review, we summarize the available evidence in this setting, focusing on perioperative brain protection, cardiorespiratory optimization, and preservation of the coagulative function. An overview on simultaneous multisystem surgery (SMS) is also presented.

Effects of Hemodialysis on Prognosis in Individuals with Comorbid ERSD and ICH: A Retrospective Single-Center Study

OBJECTIVES

End-stage renal disease (ESRD) is one of the most critical risk factors of intracerebral hemorrhage (ICH). We aimed to investigate the effects of maintenance hemodialysis on hematoma volume, edema volume, and prognosis in patients with comorbid ESRD and ICH.

MATERIALS AND METHODS

Patients with comorbid ESRD and ICH were divided into two groups based on whether receiving maintenance hemodialysis. Hematoma and perihemorrhagic edema (PHE) volumes and relative edema ratio after admission were assessed on head computed tomography scans.

RESULTS

During the initial diagnosis, the dialysis group had lower PHE volume (16.41 vs 35.90 mL, P = 0.010), total volume of hematoma and edema (31.58 vs 54.58 mL, P = 0.013), and relative edema ratio (0.57 vs 0.92, P = 0.033) than the non-dialysis group. In addition, the peak PHE volume (36.68 vs 84.30 mL, P < 0.001), peak total volume of hematoma and edema (53.45 vs 127.69 mL, P = 0.011), and peak relative edema ratio (1.12 vs 1.92, P = 0.001) within one week after onset were lower in the dialysis group than in the non-dialysis group. The dialysis group had a higher in-hospital mortality rate than the non-dialysis group (40% vs 10%, P = 0.007). At 1-year follow-up, the two groups had similar 1-year-mortality rates and modified Rankin Scale.

CONCLUSIONS

Hemodialysis can prevent the enlargement of edema and reduce PHE volume shortly after onset. Although dialyzed patients had a higher in-hospital mortality rate, hemodialysis did not affect 1-year survival rate and functional neurologic scales.

A simplified framework for the detection of intracranial hemorrhage in CT brain images using deep learning

BACKGROUND

The need for accurate and timely detection of Intracranial hemorrhage (ICH) is utmost important to avoid untoward incidents that may even lead to death.Hence, this presented work leverages the ability of a pretrained deep convolutional neural network (CNN) for the detection of ICH in computed tomography (CT) brain images.

METHODS

Different frameworks have been analyzed for their effectiveness for the classification of CT brain images into hemorrhage or non-hemorrhage conditions. All these frameworks were investigated on CQ500 dataset. Furthermore, an exclusive preprocessing pipeline was designed for both normal and ICH CT images. Firstly, a framework involving the pretrained deep CNN, AlexNet, has been exploited for both feature extraction and classification using the transfer learning method, secondly, a modified AlexNet-Support vector machine (SVM) classifier is explored and finally, a feature selection method, Principal Component Analysis (PCA) has been introduced in the AlexNet-SVM classifier model and its efficacy is explored.These models were trained and tested on two different sets of CT images, one containing the original images without preprocessing and another set consisting of preprocessed images.

RESULTS

The modified AlexNet-SVM classifier has shown an improved performance in comparison to the other investigated frameworks and has achieved a classification accuracy of 99.86%, sensitivity and specificity of 0.9986 for the detection of ICH in brain CT images.

CONCLUSION

This research has given an overview of a simple and efficient framework for the classification of hemorrhage and non-hemorrhage images. Also, the proposed simplified deep learning framework manifests its ability as a screening tool to assist the radiological trainees for the accurate detection of ICH.

MicroNAR-194-5p hinders the activation of NLRP3 inflammasomes and alleviates neuroinflammation during intracerebral hemorrhage by blocking the interaction between TRAF6 and NLRP3

The possible role of miR-194-5p in brain and neurodegenerative diseases has been reported, but its role in intracerebral hemorrhage (ICH) has not been studied. This study estimated the mechanism of miR-194-5p in ICH. ICH rat model was established by injecting collagenase type VII. miR-194-5p expression in brain tissue of ICH rats was overexpressed by injection of miR-194-5p agomir. Then neurological function score and brain water content were measured. The morphological changes of brain tissue and neuronal apoptosis were evaluated by histological staining. Levels of NLRP3 inflammasomes, IL-1β and IL-18 were measured. The target relation between miR-194-5p and TRAF6 was verified and the binding of TRAF6 to NLRP3 was explored. miR-194-5p was decreased in ICH rats. After overexpression of miR-194-5p, the neuropathological injury in ICH rats was significantly reduced, and NLRP3-mediated inflammatory injury was inhibited. miR-194-5p targeted TRAF6. TRAF6 interacted with NLRP3 to promote the activation of NLRP3 inflammasomes. Overexpression of miR-194-5p reduced the interaction between TRAF6 and NLRP3, thereby alleviating the neuroinflammation. Collectively, overexpression of miR-194-5p reduced the TRAF6/NLRP3 interaction, thus inhibiting the activation of NLRP3 inflammasomes and reducing neuroinflammation during ICH. This study may shed new light on ICH treatment.

Surgical Interventions for Supratentorial Intracranial Hemorrhage: The Past, Present, and Future

Spontaneous supratentorial intracranial hemorrhage is extremely disabling and is associated with high mortality. Primary treatment for patients with this disease process is maximal medical management with blood pressure control and correction of clotting disorders due to comorbid conditions or medications. Over the past decade, significant strides have been made in understanding the benefits of surgical intervention in the treatment of intracranial hemorrhage through multiple clinical trials. In this article, we review the evolution of surgical treatments beginning with the STICH trials, discuss new developments with minimally invasive surgical strategies, and provide a brief update regarding ongoing trials and future directions in the treatment of spontaneous supratentorial intracranial hemorrhage.

Proteomic Analysis of Perihematoma Tissue from Patients with Intracerebral Hemorrhage Using iTRAQ-Based Quantitative Proteomics

Intracerebral hemorrhage is a complicated disorder with limited proven prognostic and therapeutic targets and elusive mechanisms. With proteomic methods, we aimed to explore the global protein expression profile of perihematomal tissue from ICH patients and identify potential pathophysiological pathways and protein markers. Using iTRAQ-labeling quantitative proteomics technology, four ICH brain sample and four non-ICH brain samples were analyzed. Among the 3740 quantifiable proteins, 884 were dysregulated in the patients compared to those in the controls (p < 0.05). After bioinformatics analysis, the differentially expressed proteins were found to be mostly involved in hemostatic processes, nutrient metabolism signaling pathways, and antioxidation pathways. Moreover, fibronectin 1 was revealed to be at the center of the protein-protein interaction networks. In summary, the potential pathways and brain protein markers that could potentially be used to predict the prognosis of ICH were obtained from the altered proteomic profile of perihematomal tissue. Thus, these data may yield novel insights into the mechanisms of ICH-induced secondary brain injury.

Temperature management in acute brain injury: A systematic review of clinical evidence

Temperature alterations in neurocritical care settings are common and have a striking effect on brain metabolism leading to or exacerbating neuronal injury. Hyperthermia worsens acute brain injury (ABI) patients outcome. However conclusive evidence linking control of temperature to improved outcome is still lacking. This review article report an update -results from clinical studies published between March 2006 and March 2020- on the relationship between hyperthermia or Target Temperature Management and functional outcome or mortality in ABI patients.

MATERIALS AND METHODS

A systematic search of articles in PubMed and EMBASE database was accomplished. Only complete studies, published in English in peer-reviewed journals were included.

RESULTS

A total of 63 articles into 5 subchapters are presented: acute ischemic stroke (17), subarachnoid hemorrhage (14), brain trauma (14), intracranial hemorrhage (8), and mixed acute brain injury (10). This evidence confirm and extend the negative impact of hyperthermia in ABI patients on worse functional outcome and higher mortality. In particular "early hyperthermia" in AIS patients seems to have a protective role have as promoting factor of clot lysis but no conclusive evidence is available. Normothermic TTM seems to have a positive effect on TBI patients in a reduced mortality rate compared to hypothermic TTM.

CONCLUSIONS

Hyperthermia in ABI patients is associated with worse functional outcome and higher mortality. The use of normothermic TTM has an established indication only in TBI; further studies are needed to define the role and the indications of normothermic TTM in ABI patients.

Abilities of a Densitometric Analysis of Computed Tomography Images and Hemorrhagic Parameters to Predict Outcome Favorability in Patients With Intracerebral Hemorrhage

BACKGROUND

Intracerebral hemorrhage (ICH) is one of the most devastating subtypes of stroke. A rapid assessment of ICH severity involves the use of computed tomography (CT) and derivation of the hemorrhage volume, which is often estimated using the ABC/2 method. However, these estimates are highly inaccurate and may not be feasible for anticipating outcome favorability.

OBJECTIVE

To predict patient outcomes via a quantitative, densitometric analysis of CT images, and to compare the predictive power of these densitometric parameters with the conventional ABC/2 volumetric parameter and segmented hemorrhage volumes.

METHODS

Noncontrast CT images of 87 adult patients with ICH (favorable outcomes = 69, unfavorable outcomes = 12, and deceased = 6) were analyzed. In-house software was used to calculate the segmented hemorrhage volumes, ABC/2 and densitometric parameters, including the skewness and kurtosis of the density distribution, interquartile ranges, and proportions of specific pixels in sets of CT images. Nonparametric statistical analyses were conducted.

RESULTS

The densitometric parameter interquartile range exhibited greatest accuracy (82.7%) in predicting favorable outcomes. The combination of skewness and the interquartile range effectively predicted mortality (accuracy = 83.3%). The actual volume of the ICH exhibited good coherence with ABC/2 (R = 0.79). Both parameters predicted mortality with moderate accuracy (<78%) but were less effective in predicting unfavorable outcomes.

CONCLUSION

Hemorrhage volume was rapidly estimated and effectively predicted mortality in patients with ICH; however, this value may not be useful for predicting favorable outcomes. The densitometric analysis exhibited significantly higher power in predicting mortality and favorable outcomes in patients with ICH.

Application of Deep Learning in Neuroradiology: Brain Haemorrhage Classification Using Transfer Learning

In this paper, we address the problem of identifying brain haemorrhage which is considered as a tedious task for radiologists, especially in the early stages of the haemorrhage. The problem is solved using a deep learning approach where a convolutional neural network (CNN), the well-known AlexNet neural network, and also a modified novel version of AlexNet with support vector machine (AlexNet-SVM) classifier are trained to classify the brain computer tomography (CT) images into haemorrhage or nonhaemorrhage images. The aim of employing the deep learning model is to address the primary question in medical image analysis and classification: can a sufficient fine-tuning of a pretrained model (transfer learning) eliminate the need of building a CNN from scratch? Moreover, this study also aims to investigate the advantages of using SVM as a classifier instead of a three-layer neural network. We apply the same classification task to three deep networks; one is created from scratch, another is a pretrained model that was fine-tuned to the brain CT haemorrhage classification task, and our modified novel AlexNet model which uses the SVM classifier. The three networks were trained using the same number of brain CT images available. The experiments show that the transfer of knowledge from natural images to medical images classification is possible. In addition, our results proved that the proposed modified pretrained model "AlexNet-SVM" can outperform a convolutional neural network created from scratch and the original AlexNet in identifying the brain haemorrhage.

Programmed Cell Death after Intracerebral Hemorrhage

Background:

Intracerebral hemorrhage (ICH) accounts for up to 15% of all strokes and is characterized by high rates of mortality and morbidity. The post-ICH brain injury can be distinguished in 1) primary, which are caused by disrup-tion and mechanical deformation of brain tissue due to hematoma growth and 2) secondary, which are induced by microglia activation, mitochondrial dysfunction, neurotransmitter and inflammatory mediator release. Although these events typically lead to necrosis, the occurrence of programmed cell death has also been reported after ICH.

Methods:

We reviewed recent publications describing advance in pre- and clinic ICH research.

Results:

At present, treatment of ICH patients is based on oral anticoagulant reversal, management of blood pressure and other medical complications. Several pre-clinical studies showed promising results and demonstrated that anti-oxidative and anti-inflammatory treatments reduced neuronal cell death, however, to date, all of these attempts have failed in randomized controlled clinical trials. Yet, the time frame of administration may be crucial in translation from animal to clinical studies. Furthermore, the latest pre-clinical research points toward the existence of other, apoptosis-unrelated forms kinds of pro-grammed cell death.

Conclusion:

Our review summarizes current knowledge of pathways leading to programmed cell death after ICH in addition to data from clinical trials. Some of the pre-clinical results have not yet demonstrated clinical confirmation, however they sig-nificantly contribute to our understanding of post-ICH pathology and can contribute to development of new therapeutic ap-proaches, decreasing mortality and improving ICH patients’ quality of life.