Treatment of intracerebral hemorrhage: Current approaches and future directions

Advancing CNS Therapeutics: Enhancing Neurological Disorders with Nanoparticle-Based Gene and Enzyme Replacement Therapies

Given the complexity of the central nervous system (CNS) and the diversity of neurological conditions, the increasing prevalence of neurological disorders poses a significant challenge to modern medicine. These disorders, ranging from neurodegenerative diseases to psychiatric conditions, not only impact individuals but also place a substantial burden on healthcare systems and society. A major obstacle in treating these conditions is the blood-brain barrier (BBB), which restricts the passage of therapeutic agents to the brain. Nanotechnology, particularly the use of nanoparticles (NPs), offers a promising solution to this challenge. NPs possess unique properties such as small size, large surface area, and modifiable surface characteristics, enabling them to cross the BBB and deliver drugs directly to the affected brain regions. This review focuses on the application of NPs in gene therapy and enzyme replacement therapy (ERT) for neurological disorders. Gene therapy involves altering or manipulating gene expression and can be enhanced by NPs designed to carry various genetic materials. Similarly, NPs can improve the efficacy of ERT for lysosomal storage disorders (LSDs) by facilitating enzyme delivery to the brain, overcoming issues like immunogenicity and instability. Taken together, this review explores the potential of NPs in revolutionizing treatment options for neurological disorders, highlighting their advantages and the future directions in this rapidly evolving field.

Risk factors of posthemorrhagic seizure in spontaneous intracerebral hemorrhage

Seizure is a relatively common neurological consequence after spontaneous intracerebral hemorrhage (SICH). This study aimed to investigate risk factors of early, late, and overall seizures in patients with SICH. Retrospective analysis was performed on all patients with SICH who completed two years of follow-up. The variables collected were obtained from demographic, clinical, radiographic and treatment data, in-hospital complications, and follow-up results. Univariate and multivariate analyzes were used to identify risk factors for post-hemorrhagic stroke seizure. Of 400 SICH patients recruited, 30 (7.5%) and 40 (10%) developed early and late seizures during the 2-year follow-up period, respectively. In the final result of the multivariate analysis, factors associated with the occurrence of the early seizure included lobar location of hematoma (p = 0.018), and GCS ≤ 12 on initial clinical presentation (p = 0.007). Factors associated with the occurrence of the late seizure included lobar location of hematoma (p = 0.001), volume of hematoma greater than 10 ml (p = 0.009), and midline shift on initial cranial CT (p = 0.036). Risk factors of the overall seizure after SICH included lobar location of hematoma (p < 0.001), volume of hematoma greater than 10 ml (p < 0.001), and craniotomy with evacuation of hematoma (p = 0.007). Furthermore, seizure was also associated with a poor functional outcome 2 years after the onset of SICH. Several factors associated with the appearance of post-ICH seizures were revealed. In patients with increased risk of post-SICH seizures, appropriate surveillance and management of seizures should be carried out.

Neuroinflammation and iron metabolism after intracerebral hemorrhage: a glial cell perspective

Intracerebral hemorrhage (ICH) is the most common subtype of hemorrhagic stroke causing significant morbidity and mortality. Previously clinical treatments for ICH have largely been based on a single pathophysiological perspective, and there remains a lack of curative interventions. Following the rupture of cerebral blood vessels, blood metabolites activate resident immune cells such as microglia and astrocytes, and infiltrate peripheral immune cells, leading to the release of a series of inflammatory mediators. Degradation of hemoglobin produces large amounts of iron ions, leading to an imbalance of iron homeostasis and the production of large quantities of harmful hydroxyl radicals. Neuroinflammation and dysregulation of brain iron metabolism are both important pathophysiological changes in ICH, and both can exacerbate secondary brain injury. There is an inseparable relationship between brain iron metabolism disorder and activated glial cells after ICH. Glial cells participate in brain iron metabolism through various mechanisms; meanwhile, iron accumulation exacerbates neuroinflammation by activating inflammatory signaling pathways modulating the functions of inflammatory cells, and so on. This review aims to explore neuroinflammation from the perspective of iron metabolism, linking the complex pathophysiological changes, delving into the exploration of treatment approaches for ICH, and offering insights that could enhance clinical management strategies.

Liangxue Tongyu prescription attenuates neuroinflammation by increasing cholecystokinin octapeptide in acute intracerebral hemorrhage rats

Inflammatory reactions after acute intracerebral hemorrhage (AICH) contribute significantly to a poor prognosis. Liangxue Tongyu Prescription (LTP) has been proven to be clinically effective in treating AICH. Numerous studies have shown that LTP suppresses brain inflammatory damage in AICH, while the internal mechanisms underlying its action remain unclear. The aim of this study was to verify the anti-inflammatory effects of LTP on an AICH rat model and investigate the potential mechanisms. The AICH rat models were created by injecting autologous blood into the right caudate nucleus. LTP markedly decreased cerebral hematoma and brain water content and recovered from neurological deficits. Meanwhile, LTP prevented microglial activation and reduced the inflammatory reaction caused by pro-inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6). Notably, the expression of cholecystokinin octapeptide (CCK-8) in the brain and intestine was increased by LTP or CCK-8 treatment. LTP further suppressed nuclear factor kappa B (NF-κB) in the brains of rats with AICH. Moreover, LTP increased the protein and mRNA expression of Occludin and Claudin-1 in the intestine and decreased the levels of lipopolysaccharide (LPS) and diamine oxidase (DAO) in serum. Furthermore, the results showed that LTP increased the protein and mRNA expression of Claudin-5 and zonula occludens-1 (ZO-1) in the brain. CCK-8 receptor antagonists increased the expression of NF-κB and the concentration of pro-inflammatory cytokines. These findings suggested that LTP attenuated neuroinflammation by increasing CCK-8 in the brain and intestine, and its mechanism might be related to alterations in the gut-brain axis (GBA).

MicroRNA-195-5p Inhibits Intracerebral Hemorrhage-Induced Inflammatory Response and Neuron Cell Apoptosis

Intracerebral hemorrhage (ICH) is a severe condition characterized by bleeding within brain tissue. Primary brain injury in ICH results from a mechanical insult caused by blood accumulation, whereas secondary injury involves inflammation, oxidative stress, and disruption of brain physiology. miR-195-5p may participate in ICH pathology by regulating cell proliferation, oxidative stress, and inflammation. Therefore, we assessed the performance of miR-195-5p in alleviating ICH-induced secondary brain injury. ICH was established in male Sprague-Dawley rats (7 weeks old, 200-250 g) via the stereotaxic intrastriatal injection of type IV bacterial collagenase, after which miR-195-5p was administered intravenously. Neurological function was assessed using corner turn and forelimb grip strength tests. Protein expression was assessed by western blotting and ELISA. The miR-195-5p treatment significantly improved neurological function; modulated macrophage polarization by promoting anti-inflammatory marker (CD206 and Arg1) production and inhibiting pro-inflammatory marker (CD68 and iNOS) production; enhanced Akt signalling, reduced oxidative stress by increasing Sirt1 and Nrf2 levels, and attenuated inflammation by decreasing NF-κB activation; inhibited apoptosis via increased Bcl-2 and decreased cleaved caspase-3 levels; and regulated synaptic plasticity by modulating NMDAR2A, NMDAR2B, BDNF, and TrkB expression and ERK and CREB phosphorylation. In conclusion, miR-195-5p exerts neuroprotective effects in ICH by reducing inflammation and oxidative stress, inhibiting apoptosis, and restoring synaptic plasticity, ultimately restoring behavioral recovery, and represents a promising therapeutic agent that warrants clinical studies.

Research Advancements on the Correlation Between Spontaneous Intracerebral Hemorrhage of Different Etiologies and Imaging Markers of Cerebral Small Vessel Disease

Objective

The purpose of this review is to identify the correlation between ICH and CSVD imaging markers under SMASH-U classification by searching and analyzing a large number of literatures in recent years, laying a theoretical foundation for future clinical research. At the same time, by collecting clinical data to evaluate patient prognosis, analyzing whether there are differences or supplements between clinical trial conclusions and previous theories, and ultimately guiding clinical diagnosis and treatment through the analysis of imaging biomarkers.

Methods

In this review, by searching CNKI, Web of Science, PubMed, FMRS and other databases, the use of "spontaneous intracerebral hemorrhage", "hypertensive hemorrhagic cerebral small vessel disease", "cerebral small vessel disease imaging", "Based cerebral small vessel diseases", "SMASH the -u classification" and their Chinese equivalents for the main search term. We focused on reading and analyzing hundreds of relevant literatures in the last decade from August 2011 to April 2020, and also included some earlier literatures with conceptual data sources. After screening and ranking the degree of relevance to this study, sixty of them were cited for analysis and elaboration.

Results

In patients with ICH, the number of cerebral microbleeds in lobes, basal ganglia, and the deep brain is positively correlated with ICH volume and independently correlated with neurological functional outcomes; white matter hyperintensity severity is positively correlated with ICH recurrence risk; multiple lacunar infarction independently predict the risk of ICH; severe brain atrophy is an independent risk factor for a poor prognosis in the long term in patients diagnosed with ICH; and the number of enlarged perivascular spaces is correlated with ICH recurrence. However, small subcortical infarct and ICH are the subject of few studies. Higher CSVD scores are independently associated with functional outcomes at 90 days in patients diagnosed with ICH.

Neutrophil-to-lymphocyte ratio, white blood cell, and C-reactive protein predicts poor outcome and increased mortality in intracerebral hemorrhage patients: a meta-analysis

Objective

Inflammation participates in the pathology and progression of secondary brain injury after intracerebral hemorrhage (ICH). This meta-analysis intended to explore the prognostic role of inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), white blood cell (WBC), and C-reactive protein (CRP) in ICH patients.

Methods

Embase, PubMed, Web of Science, and Cochrane Library were searched until June 2023. Two outcomes, including poor outcome and mortality were extracted and measured. Odds ratio (OR) and 95% confidence interval (CI) were presented for outcome assessment.

Results

Forty-six studies with 25,928 patients were included in this meta-analysis. The high level of NLR [OR (95% CI): 1.20 (1.13-1.27), p < 0.001], WBC [OR (95% CI): 1.11 (1.02-1.21), p = 0.013], and CRP [OR (95% CI): 1.29 (1.08-1.54), p = 0.005] were related to poor outcome in ICH patients. Additionally, the high level of NLR [OR (95% CI): 1.06 (1.02-1.10), p = 0.001], WBC [OR (95% CI): 1.39 (1.16-1.66), p < 0.001], and CRP [OR (95% CI): 1.02 (1.01-1.04), p = 0.009] were correlated with increased mortality in ICH patients. Nevertheless, PLR was not associated with poor outcome [OR (95% CI): 1.00 (0.99-1.01), p = 0.749] or mortality [OR (95% CI): 1.00 (0.99-1.01), p = 0.750] in ICH patients. The total score of risk of bias assessed by Newcastle-Ottawa Scale criteria ranged from 7-9, which indicated the low risk of bias in the included studies. Publication bias was low, and stability assessed by sensitivity analysis was good.

Conclusion

This meta-analysis summarizes that the high level of NLR, WBC, and CRP estimates poor outcome and higher mortality in ICH patients.

Cofilin Inhibitor Improves Neurological and Cognitive Functions after Intracerebral Hemorrhage by Suppressing Endoplasmic Reticulum Stress Related-Neuroinflammation

Neuroinflammation after intracerebral hemorrhage (ICH) is a crucial factor that determines the extent of the injury. Cofilin is a cytoskeleton-associated protein that drives neuroinflammation and microglia activation. A novel cofilin inhibitor (CI) synthesized and developed in our lab has turned out to be a potential therapeutic agent for targeting cofilin-mediated neuroinflammation in an in vitro model of ICH and traumatic brain injury. The current study aims to examine the therapeutic potential of CI in a mouse collagenase model of ICH and examine the neurobehavioral outcomes and its mechanism of action. Male mice were subjected to intrastriatal collagenase injection to induce ICH, and sham mice received needle insertion. Various concentrations (25, 50, and 100 mg/kg) of CI were administered to different cohorts of the animals as a single intravenous injection 3 h following ICH and intraperitoneally every 12 h for 3 days. The animals were tested for neurobehavioral parameters for up to 7 days and sacrificed to collect brains for hematoma volume measurement, Western blotting, and immunohistochemistry. Blood was collected for cofilin, TNF-α, and IL-1β assessments. The results indicated that 50 mg/kg CI improved neurological outcomes, reversed post-stroke cognitive impairment, accelerated hematoma resolution, mitigated cofilin rods/aggregates, and reduced microglial and astrocyte activation in mice with ICH. Microglia morphological analysis demonstrated that CI restored the homeostasis ramification pattern of microglia in mice treated with CI. CI suppressed endoplasmic reticulum stress-related neuroinflammation by inhibiting inflammasomes and cell death signaling pathways. We also showed that CI prevented synaptic loss by reviving the pre- and post-synaptic markers. Our results unveil a novel therapeutic approach to treating ICH and open a window for using CI in clinical practice.

Slain2 attenuates brain injury following subarachnoid hemorrhage by controlling axonal microtubule structure in mice

Neuronal injury is accountable for the poor outcome of SAH patients. In this study, oxyhemoglobin (oxyHb) was used to treat cultured primary neurons to simulate SAH, while the SAH model was established by vascular puncture in mice. First, proteomics analysis and western blot assays showed Slain2 as an increased factor in neurons exposed to oxyHb treatment, which has been reported to play an important role in axonal development by regulating microtubule stability. Upregulation of neuronal Slain2 was also detected in the murine SAH model compared with sham surgery. In addition, there was no sex difference in the protein level of Slain2 in either the sham-operated or SAH groups. Furthermore, Slain2 overexpression rescued SAH-induced sensorimotor impairments in mice, while Slain2 knockdown had the opposite effect. Finally, Slain2 overexpression rescued SAH-induced axonal injury both in vivo and in vitro, which was exacerbated by Slain2 knockdown. Thus, we demonstrate here that Slain2 acts as an endogenous protective factor of neuronal axonal microtubule structure, which plays a key role in the protection against SAH-induced neuronal axonal injury. Facilitated axonal microtubule structure by Slain2 overexpression may reduce SAH-induced axonal injury and neurobehavioral dysfunction.

Neuroimaging biomarkers of small vessel disease in cerebral amyloid angiopathy-related intracerebral hemorrhage

AIMS

The significance of the correlation of computed tomography (CT)-based cerebral small vessel disease (SVD) markers with the clinical outcomes in patients with cerebral amyloid angiopathy (CAA)-related intracerebral hemorrhage (ICH) remains uncertain. Thus, this study aimed to explore the relationship between SVD markers and short-term outcomes of CAA-ICH.

METHODS

A total of 183 patients with CAA-ICH admitted to the Xuanwu Hospital, and Beijing Fengtai You'anmen Hospital, from 2014 to 2021 were included. The multivariate logistic regression analysis was performed to identify the correlation between SVD markers based on CT and clinical outcomes at 7-day and 90-day.

RESULTS

Of the 183 included patients, 66 (36%) were identified with severe SVD burden. The multivariate analysis showed that the total SVD burden, white matter lesion (WML) grade, and brain atrophy indicator were independent risk factors for unfavorable outcomes at 90-day. The brain atrophy indicator was independently associated with mortality at 90-day. Severe cortical atrophy was significantly associated with early neurological deterioration.

CONCLUSIONS

The neuroimaging profiles of SVD based on CT in patients with CAA-ICH might predict the short-term outcome more effectively. Further studies are required to validate these findings and identify modifiable factors for preventing CAA-ICH development.

mRNA and lncRNA co-expression network in mice of acute intracerebral hemorrhage

Background

Intracerebral hemorrhage (ICH) is a severe subtype of stroke lacking effective pharmacological targets. Long noncoding RNA (lncRNA) has been confirmed to participate in the pathophysiological progress of various neurological disorders. However, how lncRNA affects ICH outcomes in the acute phase is not completely clear. In this study, we aimed to reveal the relationship of lncRNA-miRNA-mRNA following ICH.

Method

We conducted the autologous blood injection ICH model and extracted total RNAs on day 7. Microarray scanning was used to obtain mRNA and lncRNA profiles, which were validated by RT-qPCR. GO/KEGG analysis of differentially expressed mRNAs was performed using the Metascape platform. We calculated the Pearson correlation coefficients (PCCs) of lncRNA-mRNA for co-expression network construction. A competitive endogenous (Ce-RNA) network was established based on DIANALncBase and miRDB database. Finally, the Ce-RNA network was visualized and analyzed by Cytoscape.

Results

In total, 570 differentially expressed mRNAs and 313 differentially expressed lncRNAs were identified (FC ≥ 2 and value of p <0.05). The function of differentially expressed mRNAs was mainly enriched in immune response, inflammation, apoptosis, ferroptosis, and other typical pathways. The lncRNA-mRNA co-expression network contained 57 nodes (21 lncRNAs and 36 mRNAs) and 38 lncRNA-mRNA pairs. The ce-RNA network was generated with 303 nodes (29 lncRNAs, 163 mRNAs, and 111 miRNAs) and 906 edges. Three hub clusters were selected to indicate the most significant lncRNA-miRNA-mRNA interactions.

Conclusion

Our study suggests that the top differentially expressed RNA molecules may be the biomarker of acute ICH. Furthermore, the hub lncRNA-mRNA pairs and lncRNA-miRNA-mRNA correlations may provide new clues for ICH treatment.

Liangxue Tongyu Prescription Alleviates Brain Damage in Acute Intracerebral Hemorrhage Rats by Regulating Intestinal Mucosal Barrier Function

Background

Liangxue Tongyu prescription (LTP) is a commonly used formula for acute intracerebral hemorrhage (AICH) in clinical practice that has significant ameliorative effects on neurological deficits and gastrointestinal dysfunction, yet the mechanism remains elusive. The aim of this study was to investigate the pathway by which LTP alleviates brain damage in AICH rats.

Methods

The AICH rat models were established by autologous caudal arterial blood injection. The neurological function scores were evaluated before and after treatment. The water content and the volume of Evans blue staining in the brain were measured to reflect the degree of brain damage. RT-PCR was used to detect the inflammatory factors of the brain. Western blotting was used to detect the expression of the tight junction proteins zonula occludens 1 (ZO-1), occludin (OCLN), and claudin (CLDN) in the brain and colon, followed by mucin 2 (MUC2), secretory immunoglobulin A (SIgA), and G protein-coupled receptor 43 (GPR43) in the colon. Flow cytometry was used to detect the ratios of helper T cells 17 (Th17) and regulatory T cells (Treg) in peripheral blood, and the vagus nerve (VN) discharge signals were collected.

Results

LTP reduced the brain damage of the AICH rats. Compared with the model group, LTP significantly improved the permeability of the colonic mucosa, promoted the secretion of MUC2, SigA, and GPR43 in the colon, and regulated the immune balance of peripheral T cells. The AICH rats had significantly faster VN discharge rates and lower amplitudes than normal rats, and these abnormalities were corrected in the LTP and probiotics groups.

Conclusion

LTP can effectively reduce the degree of brain damage in AICH rats, and the mechanism may be that it can play a neuroprotective role by regulating the function of the intestinal mucosal barrier.

Prediction of Hemorrhagic Complication after Thrombolytic Therapy Based on Multimodal Data from Multiple Centers: An Approach to Machine Learning and System Implementation

Hemorrhagic complication (HC) is the most severe complication of intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS). This study aimed to build a machine learning (ML) prediction model and an application system for a personalized analysis of the risk of HC in patients undergoing IVT therapy. We included patients from Chongqing, Hainan and other centers, including Computed Tomography (CT) images, demographics, and other data, before the occurrence of HC. After feature engineering, a better feature subset was obtained, which was used to build a machine learning (ML) prediction model (Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGB)), and then evaluated with relevant indicators. Finally, a prediction model with better performance was obtained. Based on this, an application system was built using the Flask framework. A total of 517 patients were included, of which 332 were in the training cohort, 83 were in the internal validation cohort, and 102 were in the external validation cohort. After evaluation, the performance of the XGB model is better, with an AUC of 0.9454 and ACC of 0.8554 on the internal validation cohort, and 0.9142 and ACC of 0.8431 on the external validation cohort. A total of 18 features were used to construct the model, including hemoglobin and fasting blood sugar. Furthermore, the validity of the model is demonstrated through decision curves. Subsequently, a system prototype is developed to verify the test prediction effect. The clinical decision support system (CDSS) embedded with the XGB model based on clinical data and image features can better carry out personalized analysis of the risk of HC in intravenous injection patients.

3D slicer-based calculation of hematoma irregularity index for predicting hematoma expansion in intracerebral hemorrhage

BACKGROUND

Irregular hematoma is considered as a risk sign of hematoma expansion. The aim of this study was to quantify hematoma irregularity with computed tomography based on 3D Slicer.

METHODS

Patients with spontaneous intracerebral hemorrhage who underwent an initial and subsequent non-contrast computed tomography (CT) at a single medical center between January 2019 to January 2020 were retrospectively identified. The Digital Imaging and Communication in Medicine (DICOM) standard images were loaded into the 3D Slicer, and the surface area (S) and volume (V) of hematoma were calculated. The hematoma irregularity index (HII) was defined as [Formula: see text]. Logistic regression analyses and receiver operating characteristic (ROC) curve analysis were performed to assess predictive performance of HII.

RESULTS

The enrolled patients were divided into those with hematoma enlargement (n = 36) and those without the enlargement (n = 57). HII in hematoma expansion group was 130.4 (125.1-140.0), and the index in non-enlarged hematoma group was 118.6 (113.5-122.3). There was significant difference in HII between the two groups (P < 0.01). Multivariate logistic regression analysis revealed that the HII was significantly associated with hematoma expansion before (odds ratio = 1.203, 95% confidence interval [CI], 1.115-1.298; P < 0.001) and after adjustment for age, hematoma volume, Glasgow Coma Scale score (odds ratio = 1.196, 95% CI, 1.102-1.298, P < 0.001). The area under the ROC curve was 0.86 (CI, 0.78-0.93, P < 0.01), and the best cutoff of HII for predicting hematoma growth was 123.8.

CONCLUSION

As a quantitative indicator of irregular hematoma, HII can be calculated using the 3D Slicer. And the HII was independently correlated with hematoma expansion.

A symmetric prior knowledge based deep learning model for intracerebral hemorrhage lesion segmentation

Background: Accurate localization and classification of intracerebral hemorrhage (ICH) lesions are of great significance for the treatment and prognosis of patients with ICH. The purpose of this study is to develop a symmetric prior knowledge based deep learning model to segment ICH lesions in computed tomography (CT). Methods: A novel symmetric Transformer network (Sym-TransNet) is designed to segment ICH lesions in CT images. A cohort of 1,157 patients diagnosed with ICH is established to train (n = 857), validate (n = 100), and test (n = 200) the Sym-TransNet. A healthy cohort of 200 subjects is added, establishing a test set with balanced positive and negative cases (n = 400), to further evaluate the accuracy, sensitivity, and specificity of the diagnosis of ICH. The segmentation results are obtained after data pre-processing and Sym-TransNet. The DICE coefficient is used to evaluate the similarity between the segmentation results and the segmentation gold standard. Furthermore, some recent deep learning methods are reproduced to compare with Sym-TransNet, and statistical analysis is performed to prove the statistical significance of the proposed method. Ablation experiments are conducted to prove that each component in Sym-TransNet could effectively improve the DICE coefficient of ICH lesions. Results: For the segmentation of ICH lesions, the DICE coefficient of Sym-TransNet is 0.716 ± 0.031 in the test set which contains 200 CT images of ICH. The DICE coefficients of five subtypes of ICH, including intraparenchymal hemorrhage (IPH), intraventricular hemorrhage (IVH), extradural hemorrhage (EDH), subdural hemorrhage (SDH), and subarachnoid hemorrhage (SAH), are 0.784 ± 0.039, 0.680 ± 0.049, 0.359 ± 0.186, 0.534 ± 0.455, and 0.337 ± 0.044, respectively. Statistical results show that the proposed Sym-TransNet can significantly improve the DICE coefficient of ICH lesions in most cases. In addition, the accuracy, sensitivity, and specificity of Sym-TransNet in the diagnosis of ICH in 400 CT images are 91.25%, 98.50%, and 84.00%, respectively. Conclusion: Compared with recent mainstream deep learning methods, the proposed Sym-TransNet can segment and identify different types of lesions from CT images of ICH patients more effectively. Moreover, the Sym-TransNet can diagnose ICH more stably and efficiently, which has clinical application prospects.

Long-term outcome of cerebral amyloid angiopathy-related hemorrhage

OBJECT

The long-term functional outcome of cerebral amyloid angiopathy-related hemorrhage (CAAH) patients is unclear. We sought to assess the long-term functional outcome of CAAH and determine the prognostic factors associated with unfavorable outcomes.

METHODS

We enrolled consecutive CAAH patients from 2014 to 2020 in this observational study. Baseline characteristics and clinical outcomes were presented. Multivariable logistic regression analysis was performed to identify the prognostic factors associated with long-term outcome.

RESULTS

Among the 141 CAAH patients, 76 (53.9%) achieved favorable outcomes and 28 (19.9%) of them died at 1-year follow-up. For the longer-term follow-up with a median observation time of 19.0 (interquartile range, 12.0-26.5) months, 71 (50.4%) patients obtained favorable outcomes while 33 (23.4%) died. GCS on admission (OR, 0.109; 95% CI, 0.021-0.556; p = 0.008), recurrence of ICH (OR, 2923.687; 95% CI, 6.282-1360730.14; p = 0.011), WML grade 3-4 (OR, 31.007; 95% CI, 1.041-923.573; p = 0.047), severe central atrophy (OR, 4220.303; 95% CI, 9.135-1949674.84; p = 0.008) assessed by CT was identified as independent predictors for long-term outcome.

INTERPRETATION

Nearly 50% of CAAH patients achieved favorable outcomes at long-term follow-up. GCS, recurrence of ICH, WML grade and cerebral atrophy were identified as independent prognostic factors of long-term outcome.

Aprepitant attenuates NLRC4-dependent neuronal pyroptosis via NK1R/PKCδ pathway in a mouse model of intracerebral hemorrhage

BACKGROUND

Pyroptosis is a programmed cell death mediated by inflammasomes. Previous studies have reported that inhibition of neurokinin receptor 1 (NK1R) exerted neuroprotection in several neurological diseases. Herein, we have investigated the role of NK1R receptor inhibition using Aprepitant to attenuate NLRC4-dependent neuronal pyroptosis after intracerebral hemorrhage (ICH), as well as the underlying mechanism.

METHODS

A total of 182 CD-1 mice were used. ICH was induced by injection of autologous blood into the right basal ganglia. Aprepitant, a selective antagonist of NK1R, was injected intraperitoneally at 1 h after ICH. To explore the underlying mechanism, NK1R agonist, GR73632, and protein kinase C delta (PKCδ) agonist, phorbol 12-myristate 13-acetate (PMA), were injected intracerebroventricularly at 1 h after ICH induction, and small interfering ribonucleic acid (siRNA) for NLRC4 was administered via intracerebroventricular injection at 48 h before ICH induction, respectively. Neurobehavioral tests, western blot, and immunofluorescence staining were performed.

RESULTS

The expression of endogenous NK1R and NLRC 4 were gradually increased after ICH. NK1R was expressed on neurons. Aprepitant significantly improved the short- and long-term neurobehavioral deficits after ICH, which was accompanied with decreased neuronal pyroptosis, as well as decreased expression of NLRC4, Cleaved-caspase-1, GSDMD (gasdermin D), IL-1β, and IL-18. Activation of NK1R or PKCδ abolished these neuroprotective effects of Aprepitant after ICH. Similarly, knocking down NLRC4 using siRNA produced similar neuroprotective effects.

CONCLUSION

Aprepitant suppressed NLRC4-dependent neuronal pyroptosis and improved neurological function, possibly mediated by inhibition of NK1R/PKCδ signaling pathways after ICH. The NK1R may be a promising therapeutic target for the treatment of ICH.

Oxidative Stress Following Intracerebral Hemorrhage: From Molecular Mechanisms to Therapeutic Targets

Intracerebral hemorrhage (ICH) is a highly fatal disease with mortality rate of approximately 50%. Oxidative stress (OS) is a prominent cause of brain injury in ICH. Important sources of reactive oxygen species after hemorrhage are mitochondria dysfunction, degradated products of erythrocytes, excitotoxic glutamate, activated microglia and infiltrated neutrophils. OS harms the central nervous system after ICH mainly through impacting inflammation, killing brain cells and exacerbating damage of the blood brain barrier. This review discusses the sources and the possible molecular mechanisms of OS in producing brain injury in ICH, and anti-OS strategies to ameliorate the devastation of ICH.

A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

Background

We aimed to develop and validate a new nomogram for predicting the risk of intracranial hemorrhage (ICH) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT).

Methods

A retrospective study enrolled 553 patients with AIS treated with IVT. The patients were randomly divided into two cohorts: the training set (70%, n = 387) and the testing set (30%, n = 166). The factors in the predictive nomogram were filtered using multivariable logistic regression analysis. The performance of the nomogram was assessed based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).

Results

After multivariable logistic regression analysis, certain factors, such as smoking, National Institutes of Health of Stroke Scale (NIHSS) score, blood urea nitrogen-to-creatinine ratio (BUN/Cr), and neutrophil-to-lymphocyte ratio (NLR), were found to be independent predictors of ICH and were used to construct a nomogram. The AUC-ROC values of the nomogram were 0.887 (95% CI: 0.842–0.933) and 0.776 (95% CI: 0.681–0.872) in the training and testing sets, respectively. The AUC-ROC of the nomogram was higher than that of the Multicenter Stroke Survey (MSS), Glucose, Race, Age, Sex, Systolic blood Pressure, and Severity of stroke (GRASPS), and stroke prognostication using age and NIH Stroke Scale-100 positive index (SPAN-100) scores for predicting ICH in both the training and testing sets (p < 0.05). The calibration plot demonstrated good agreement in both the training and testing sets. DCA indicated that the nomogram was clinically useful.

Conclusions

The new nomogram, which included smoking, NIHSS, BUN/Cr, and NLR as variables, had the potential for predicting the risk of ICH in patients with AIS after IVT.

Lipoxin A4 Receptor Stimulation Attenuates Neuroinflammation in a Mouse Model of Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is caused by the rupture of blood vessels in the brain. The excessive activation of glial cells and the infiltration of numerous inflammatory cells are observed during bleeding. Thrombin is a key molecule that triggers neuroinflammation in the ICH brain. In this study, we focused on lipoxin A₄ (LXA₄), an arachidonic acid metabolite that has been reported to suppress inflammation and cell migration. LXA₄ and BML-111, an agonist of the LXA₄ receptor/formyl peptide receptor 2 (ALX/FPR2), suppressed microglial activation; LXA₄ strongly inhibited the migration of neutrophil-like cells in vitro. ALX/FPR2 was expressed on neutrophils in the ICH mouse brain and the daily administration of BML-111 attenuated the motor coordination dysfunction and suppressed the production of proinflammatory cytokines in the ICH mouse brain. On the other hand, BML-111 did not show a significant reduction in the number of microglia and neutrophils. These results suggest that systemic administration of ALX/FPR2 agonists may suppress the neuroinflammatory response of microglia and neutrophils without a change in cell numbers. Additionally, their combination with molecules that reduce cell numbers, such as modulators of leukotriene B₄ signaling, may be required in future studies.

Enhancing Robustness of Machine Learning Integration With Routine Laboratory Blood Tests to Predict Inpatient Mortality After Intracerebral Hemorrhage

Objective: The accurate evaluation of outcomes at a personalized level in patients with intracerebral hemorrhage (ICH) is critical clinical implications. This study aims to evaluate how machine learning integrates with routine laboratory tests and electronic health records (EHRs) data to predict inpatient mortality after ICH.

Methods: In this machine learning-based prognostic study, we included 1,835 consecutive patients with acute ICH between October 2010 and December 2018. The model building process incorporated five pre-implant ICH score variables (clinical features) and 13 out of 59 available routine laboratory parameters. We assessed model performance according to a range of learning metrics, such as the mean area under the receiver operating characteristic curve [AUROC]. We also used the Shapley additive explanation algorithm to explain the prediction model.

Results: Machine learning models using laboratory data achieved AUROCs of 0.71–0.82 in a split-by-year development/testing scheme. The non-linear eXtreme Gradient Boosting model yielded the highest prediction accuracy. In the held-out validation set of development cohort, the predictive model using comprehensive clinical and laboratory parameters outperformed those using clinical alone in predicting in-hospital mortality (AUROC [95% bootstrap confidence interval], 0.899 [0.897–0.901] vs. 0.875 [0.872–0.877]; P <0.001), with over 81% accuracy, sensitivity, and specificity. We observed similar performance in the testing set.

Conclusions: Machine learning integrated with routine laboratory tests and EHRs could significantly promote the accuracy of inpatient ICH mortality prediction. This multidimensional composite prediction strategy might become an intelligent assistive prediction for ICH risk reclassification and offer an example for precision medicine.

Small interfering RNAs based therapies for intracerebral hemorrhage: challenges and progress in drug delivery systems

Intracerebral hemorrhage (ICH) is a subtype of stroke associated with higher rates of mortality. Currently, no effective drug treatment is available for ICH. The molecular pathways following ICH are complicated and diverse. Nucleic acid therapeutics such as gene knockdown by small interfering RNAs (siRNAs) have been developed in recent years to modulate ICH’s destructive pathways and mitigate its outcomes. However, siRNAs delivery to the central nervous system is challenging and faces many roadblocks. Existing barriers to systemic delivery of siRNA limit the use of naked siRNA; therefore, siRNA-vectors developed to protect and deliver these therapies into the specific-target areas of the brain, or cell types seem quite promising. Efficient delivery of siRNA via nanoparticles emerged as a viable and effective alternative therapeutic tool for central nervous system-related diseases. This review discusses the obstacles to siRNA delivery, including the advantages and disadvantages of viral and nonviral vectors. Additionally, we provide a comprehensive overview of recent progress in nanotherapeutics areas, primarily focusing on the delivery system of siRNA for ICH treatment.

Tryptophan Metabolism in Central Nervous System Diseases: Pathophysiology and Potential Therapeutic Strategies

The metabolism of L-tryptophan (TRP) regulates homeostasis, immunity, and neuronal function. Altered TRP metabolism has been implicated in the pathophysiology of various diseases of the central nervous system. TRP is metabolized through two main pathways, the kynurenine pathway and the methoxyindole pathway. First, TRP is metabolized to kynurenine, then kynurenic acid, quinolinic acid, anthranilic acid, 3-hydroxykynurenine, and finally 3-hydroxyanthranilic acid along the kynurenine pathway. Second, TRP is metabolized to serotonin and melatonin along the methoxyindole pathway. In this review, we summarize the biological properties of key metabolites and their pathogenic functions in 12 disorders of the central nervous system: schizophrenia, bipolar disorder, major depressive disorder, spinal cord injury, traumatic brain injury, ischemic stroke, intracerebral hemorrhage, multiple sclerosis, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. Furthermore, we summarize preclinical and clinical studies, mainly since 2015, that investigated the metabolic pathway of TRP, focusing on changes in biomarkers of these neurologic disorders, their pathogenic implications, and potential therapeutic strategies targeting this metabolic pathway. This critical, comprehensive, and up-to-date review helps identify promising directions for future preclinical, clinical, and translational research on neuropsychiatric disorders.

Predicting mortality from intracranial hemorrhage in patients who undergo allogeneic hematopoietic stem cell transplantation

Intracranial hemorrhage (ICH) is a rare but fatal central nervous system complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, factors that are predictive of early mortality in patients who develop ICH after undergoing allo-HSCT have not been systemically investigated. From January 2008 to June 2020, a total of 70 allo-HSCT patients with an ICH diagnosis formed the derivation cohort. Forty-one allo-HSCT patients with an ICH diagnosis were collected from 12 other medical centers during the same period, and they comprised the external validation cohort. These 2 cohorts were used to develop and validate a grading scale that enables the prediction of 30-day mortality from ICH in all-HSCT patients. Four predictors (lactate dehydrogenase level, albumin level, white blood cell count, and disease status) were retained in the multivariable logistic regression model, and a simplified grading scale (termed the LAWS score) was developed. The LAWS score was adequately calibrated (Hosmer-Lemeshow test, P > .05) in both cohorts. It had good discrimination power in both the derivation cohort (C-statistic, 0.859; 95% confidence interval, 0.776-0.945) and the external validation cohort (C-statistic, 0.795; 95% confidence interval, 0.645-0.945). The LAWS score is the first scoring system capable of predicting 30-day mortality from ICH in allo-HSCT patients. It showed good performance in identifying allo-HSCT patients at increased risk of early mortality after ICH diagnosis. We anticipate that it would help risk stratify allo-HSCT patients with ICH and facilitate future studies on developing individualized and novel interventions for patients within different LAWS risk groups.

A Robust Deep Learning Segmentation Method for Hematoma Volumetric Detection in Intracerebral Hemorrhage

BACKGROUND AND PURPOSE

Hematoma volume (HV) is a significant diagnosis for determining the clinical stage and therapeutic approach for intracerebral hemorrhage (ICH). The aim of this study is to develop a robust deep learning segmentation method for the fast and accurate HV analysis using computed tomography.

METHODS

A novel dimension reduction UNet (DR-UNet) model was developed for computed tomography image segmentation and HV measurement. Two data sets, 512 ICH patients with 12 568 computed tomography slices in the retrospective data set and 50 ICH patients with 1257 slices in the prospective data set, were used for network training, validation, and internal and external testing. Moreover, 13 irregular hematoma cases, 11 subdural and epidural hematoma cases, and 50 different HV cases into 3 groups (<30, 30-60, and >60 mL) were selected to further evaluate the robustness of DR-UNet. The image segmentation performance of DR-UNet was compared with those of UNet, the fuzzy clustering method, and the active contour method. The HV measurement performance was compared using DR-UNet, UNet, and the Coniglobus formula method.

RESULTS

Using DR-UNet, the segmentation model achieved a performance similar to that of expert clinicians in 2 independent test data sets containing internal testing data (Dice of 0.861±0.139) and external testing data (Dice of 0.874±0.130). The HV measurement derived from DR-UNet was strongly correlated with that from manual segmentation (R²=0.9979; P<0.0001). In the irregularly shaped hematoma group and the subdural and epidural hematoma group, DR-UNet was more robust than UNet in both hematoma segmentation and HV measurement. There is no statistical significance in segmentation accuracy among 3 different HV groups.

CONCLUSIONS

DR-UNet can segment hematomas from the computed tomography scans of ICH patients and quantify the HV with better accuracy and greater efficiency than the main existing methods and with similar performance to expert clinicians. Due to robust performance and stable segmentation on different ICHs, DR-UNet could facilitate the development of deep learning systems for a variety of clinical applications.

Safety and efficacy of remote ischemic conditioning for the treatment of intracerebral hemorrhage: A proof-of-concept randomized controlled trial

BACKGROUND

Remote ischemic conditioning can promote hematoma resolution, attenuate brain edema, and improve neurological recovery in animal models of intracerebral hemorrhage.

AIMS

This study aimed to evaluate the safety and preliminary efficacy of remote ischemic conditioning in patients with intracerebral hemorrhage.

METHODS

In this multicenter, randomized, controlled trial, 40 subjects with supratentorial intracerebral hemorrhage presenting within 24-48 h of onset were randomly assigned to receive medical therapy plus remote ischemic conditioning for consecutive seven days or medical therapy alone. The primary safety outcome was neurological deterioration within seven days of enrollment, and the primary efficacy outcome was the changes of hematoma volume on CT images. Other outcomes included hematoma resolution rate at 7 days ([hematoma volume at 7 days - hematoma volume at baseline]/hematoma volume at baseline), perihematomal edema (PHE), and functional outcome at 90 days.

RESULTS

The mean age was 59.3 ± 11.7 years and hematoma volume was 13.9 ± 4.5 mL. No subjects experienced neurological deterioration within seven days of enrollment, and no subject died or experienced remote ischemic conditioning-associated adverse events during the study period. At baseline, the hematoma volumes were 14.19 ± 5.07 mL in the control group and 13.55 ± 3.99 mL in the remote ischemic conditioning group, and they were 8.54 ± 3.99 mL and 6.95 ± 2.71 mL at seven days after enrollment, respectively, which is not a significant difference (p > 0.05 each). The hematoma resolution rate in the remote ischemic conditioning group (49.25 ± 9.17%) was significantly higher than in the control group (41.92 ± 9.14%; MD, 7.3%; 95% CI, 1.51-13.16%; p = 0.015). The absolute PHE volume was 17.27 ± 8.34 mL in the control group and 12.92 ± 7.30 mL in the remote ischemic conditioning group at seven days after enrollment, which is not a significant between-group difference (p = 0.087), but the relative PHE in the remote ischemic conditioning group (1.77 ± 0.39) was significantly lower than in the control group (2.02 ± 0.27; MD, 0.25; 95% CI, 0.39-0.47; p = 0.023). At 90-day follow-up, 13 subjects (65%) in the remote ischemic conditioning group and 12 subjects (60%) in the control group achieved favorable functional outcomes (modified Rankin Scale score ≤ 3), which is not a significant between-group difference (p = 0.744).

CONCLUSIONS

Repeated daily remote ischemic conditioning for consecutive seven days was safe and well tolerated in patients with intracerebral hemorrhage, and it may be able to improve hematoma resolution rate and reduce relative PHE. However, the effects of remote ischemic conditioning on the absolute hematoma and PHE volume and functional outcomes in this patient population need further investigations.Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT03930940.

Intracranial Bleeding After Reperfusion Therapy in Acute Ischemic Stroke

Intracranial hemorrhage is one of the most feared complications following brain infarct. Ischemic tissues have a natural tendency to bleed. Moreover, the first recanalization trials using intravenous thrombolysis have shown an increase in mild to severe intracranial hemorrhage. Symptomatic intracerebral hemorrhage is strongly associated with poor outcomes and is an important factor in recanalization decisions. Stroke physicians have to weigh the potential benefit of recanalization therapies, first, with different risks of intracranial hemorrhage described in randomized controlled trials, and second with numerous risk markers that have been found to be associated with intracranial hemorrhage in retrospective series. These decisions have become quite complex with different intravenous thrombolytics and mechanical thrombectomy. This review aims to outline some elements of the pathophysiological mechanisms and classifications, describe most of the risk factors identified for each reperfusion therapy, and finally suggest future research directions that could help physicians dealing with these complications.