Abstract

Previous studies suggest that the most common cause of spontaneous intracerebral hemorrhage in children and adolescents is arteriovenous malformations (AVMs). However, an update containing recently published data on pediatric spontaneous intracranial hemorrhages is lacking. The aim of this study is to systematically analyze the published data on the etiologies and risk factors of pediatric spontaneous intracranial hemorrhage. This systematic review was performed in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A search in PubMed, Embase, Scopus, Web of Science and Cochrane Library was conducted aiming for articles published in year 2000 and later, containing data on etiology and risk factors of spontaneous intracranial hemorrhages in unselected cohorts of patients aged between 1 month and 18 years. As a result, forty studies were eligible for data extraction and final analysis. These included 7931 children and adolescents with 4009 reported etiologies and risk factors. A marked variety of reported etiologies and risk factors among studies was observed. Vascular etiologies were the most frequently reported cause of pediatric spontaneous intracranial hemorrhages (n = 1727, 43.08% of all identified etiologies or risk factors), with AVMs being the most common vascular cause (n = 1226, 70.99% of all vascular causes). Hematological and systemic causes, brain tumors, intracranial infections and cardiac causes were less commonly encountered risk factors and etiologies.

Abstract

Subarachnoid hemorrhage (SAH) and intracerebral hemorrhage (ICH) are both debilitating and life-threatening incidents calling for immediate action and treatment. This review focuses on the applicability of viscoelastic testing (rotational thromboelastometry or thromboelastography [TEG]) in the management of SAH and ICH. A systematic literature search was performed in PubMed and EMBASE. Studies including patients with SAH or ICH, in which viscoelastic testing was performed, were identified. In total, 24 studies were included for analysis, and further subdivided into studies on SAH patients investigated prior to stenting or coiling (n = 12), ICH patients (n = 8) and studies testing patients undergoing stenting or coiling, or ischemic stroke patients undergoing thrombolysis or thrombectomy and developing ICH as a complication (n = 5). SAH patients had increased clot firmness, and this was associated with a higher degree of early brain injury and higher Hunt-Hess score. SAH patients with delayed cerebral ischemia had higher clot firmness than patients not developing delayed cerebral ischemia. ICH patients showed accelerated clot formation and increased clot firmness in comparison to healthy controls. Patients with hematoma expansion had longer clot initiation and lower platelet aggregation than patients with no hematoma expansion. During stent procedures for SAH, adjustment of antiplatelet therapy according to TEG platelet mapping did not change prevalence of major bleeding, thromboembolic events, or functional outcome. Viscoelastic testing prior to thrombolysis showed conflicting results in predicting ICH as complication. In conclusion, viscoelastic testing suggests hypercoagulation following SAH and ICH. Further investigation of the predictive value of increased clot firmness in SAH seems relevant. In ICH, the prediction of hematoma expansion and ICH as a complication to thrombolysis might be clinically relevant.

Abstract

BACKGROUND Perihematomal edema (PHE) has been proposed as a radiological marker of secondary injury and therapeutic target in intracerebral hemorrhage (ICH). We conducted a systematic review and meta-analysis to assess the prognostic impact of PHE on functional outcome and mortality in patients with ICH. METHODS We searched major databases through December 2020 using predefined keywords. Any study using logistic regression to examine the association between PHE or its growth and functional outcome was included. We examined the overall pooled effect and conducted secondary analyses to explore the impact of individual PHE measures on various outcomes separately. Study quality was assessed by three independent raters using the Newcastle-Ottawa Scale. Odds ratios (per 1-unit increase in PHE) and their confidence intervals (CIs) were log transformed and entered into a DerSimonian-Laird random-effects meta-analysis to obtain pooled estimates of the effect. RESULTS Twenty studies (n = 6633 patients) were included in the analysis. The pooled effect size for overall outcome was 1.05 (95% CI 1.02-1.08; p < 0.00). For the following secondary analyses, the effect size was weak: mortality (1.01; 95% CI 0.90-1.14), functional outcome (1.04; 95% CI 1.02-1.07), both 90-day (1.06; 95% CI 1.02-1.11), and in-hospital assessments (1.04; 95% CI 1.00-1.08). The effect sizes for PHE volume and PHE growth were 1.04 (95% CI 1.01-1.07) and 1.14 (95% CI 1.04-1.25), respectively. Heterogeneity across studies was substantial except for PHE growth. CONCLUSIONS This meta-analysis demonstrates that PHE volume within the first 72 h after ictus has a weak effect on functional outcome and mortality after ICH, whereas PHE growth might have a slightly larger impact during this time frame. Definitive conclusions are limited by the large variability of PHE measures, heterogeneity, and different evaluation time points between studies.

Abstract

BACKGROUND Artificial intelligence (AI)-driven software has been developed and become commercially available within the past few years for the detection of intracranial hemorrhage (ICH) and chronic cerebral microbleeds (CMBs). However, there is currently no systematic review that summarizes all of these tools or provides pooled estimates of their performance. METHODS In this PROSPERO-registered, PRISMA compliant systematic review, we sought to compile and review all MEDLINE and EMBASE published studies that have developed and/or tested AI algorithms for ICH detection on non-contrast CT scans (NCCTs) or MRI scans and CMBs detection on MRI scans. RESULTS In total, 40 studies described AI algorithms for ICH detection in NCCTs/MRIs and 19 for CMBs detection in MRIs. The overall sensitivity, specificity, and accuracy were 92.06%, 93.54%, and 93.46%, respectively, for ICH detection and 91.6%, 93.9%, and 92.7% for CMBs detection. Some of the challenges encountered in the development of these algorithms include the laborious work of creating large, labeled and balanced datasets, the volumetric nature of the imaging examinations, the fine tuning of the algorithms, and the reduction in false positives. CONCLUSIONS Numerous AI-driven software tools have been developed over the last decade. On average, they are characterized by high performance and expert-level accuracy for the diagnosis of ICH and CMBs. As a result, implementing these tools in clinical practice may improve workflow and act as a failsafe for the detection of such lesions. REGISTRATION-URL: https://www.crd.york.ac.uk/prospero/ Unique Identifier: CRD42021246848.

Abstract

AIM: We intended to provide the clinical evidence that artificial intelligence (AI) could be used to assist doctors in the diagnosis of intracerebral hemorrhage (ICH). METHODS Studies published in 2021 were identified after the literature search of PubMed, Embase, and Cochrane. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to perform the quality assessment of studies. Data extraction of diagnosis effect included accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), area under curve (AUC), and Dice scores (Dices). The pooled effect with its 95% confidence interval (95%CI) was calculated by the random effects model. I-Square (I (2)) was used to test heterogeneity. To check the stability of the overall results, sensitivity analysis was conducted by recalculating the pooled effect of the remaining studies after omitting the study with the highest quality or the random effects model was switched to the fixed effects model. Funnel plot was used to evaluate publication bias. To reduce heterogeneity, recalculating the pooled effect of the remaining studies after omitting the study with the lowest quality or perform subgroup analysis. RESULTS Twenty-five diagnostic tests of ICH via AI and doctors with overall high quality were included. Pooled ACC, SEN, SPE, PPV, NPV, AUC, and Dices were 0.88 (0.83∼0.93), 0.85 (0.81∼0.89), 0.90 (0.88∼0.92), 0.80 (0.75∼0.85), 0.93 (0.91∼0.95), 0.84 (0.80∼0.89), and 0.90 (0.85∼0.95), respectively. There was no publication bias. All of results were stable as revealed by sensitivity analysis and were accordant as outcomes via subgroups analysis. CONCLUSION Under the background of the fourth industrial revolution, AI might be an effective and efficient tool to assist doctors in the clinical diagnosis of ICH.

Abstract

OBJECTIVES To assess whether dual-energy computed tomography (DECT), using conventional computed tomography or magnetic resonance imaging as a reference standard, is sufficiently accurate to differentiate intracerebral hemorrhage from contrast extravasation after endovascular thrombectomy for acute ischemic stroke. METHODS On January 20, 2021, we searched the PubMed Medline, Embase, Web of Science, and Cochrane Library databases. QUADAS-2 was used to assess the risk of bias and applicability. Meta-analyses were performed using a bivariate random-effects model. To explore sources of heterogeneity, meta-regression analyses were performed. Deeks' funnel plot asymmetry test was used to assess publication bias. RESULTS A total of 7 studies (269 patients, 269 focal areas) were included. The pooled mean sensitivity, specificity, and accuracy of DECT in identifying intracerebral hemorrhage from contrast extravasation after mechanical thrombectomy for acute ischemic stroke were 0.77 (95% confidence interval (CI) 0.29 to 0.96), 1 (95% CI 0.86 to 1), and 0.99 (95% CI 0.98 to 1), respectively. This evidence was of moderate certainty due to the risk of bias. Higgin's I-squared for study heterogeneity was observed for the pooled sensitivity (I(2) = 78.88%) and pooled specificity (I(2) = 82.12%). Moreover, Deeks' funnel plot asymmetry test revealed no publication bias (p = 0.38). CONCLUSION DECT shows excellent accuracy and specificity in differentiating intracerebral hemorrhage from contrast extravasation after endovascular thrombectomy for acute ischemic stroke. Nevertheless, there was substantial and moderate heterogeneity among the studies. Future large-scale, prospective cohort studies are warranted to validate our findings. KEY POINTS • Dual-energy computed tomography shows excellent accuracy and specificity in differentiating intracerebral hemorrhage from contrast extravasation after endovascular thrombectomy for acute ischemic stroke. • Via meta-regression analysis, we found various possible covariates, including the publication date, image analysis, index test time, time of follow-up imaging, and reference standard judgment, that had an important effect on the heterogeneity. • There were no concerns regarding applicability in any of the included studies.

Abstract

PURPOSE To compare the diagnostic accuracy of convolutional neural networks (CNN) with radiologists as the reference standard in the diagnosis of intracranial hemorrhages (ICH) with non contrast computed tomography of the cerebrum (NCTC). METHODS PubMed, Embase, Scopus, and Web of Science were searched for the period from 1 January 2012 to 20 July 2020; eligible studies included patients with and without ICH as the target condition undergoing NCTC, studies had deep learning algorithms based on CNNs and radiologists reports as the minimum reference standard. Pooled sensitivities, specificities and a summary receiver operating characteristics curve (SROC) were employed for meta-analysis. RESULTS 5,119 records were identified through database searching. Title-screening left 47 studies for full-text assessment and 6 studies for meta-analysis. Comparing the CNN performance to reference standards in the retrospective studies found a pooled sensitivity of 96.00% (95% CI: 93.00% to 97.00%), pooled specificity of 97.00% (95% CI: 90.00% to 99.00%) and SROC of 98.00% (95% CI: 97.00% to 99.00%), and combining retrospective and studies with external datasets found a pooled sensitivity of 95.00% (95% CI: 91.00% to 97.00%), pooled specificity of 96.00% (95% CI: 91.00% to 98.00%) and a pooled SROC of 98.00% (95% CI: 97.00% to 99.00%). CONCLUSION This review found the diagnostic performance of CNNs to be equivalent to that of radiologists for retrospective studies. Out-of-sample external validation studies pooled with retrospective studies found CNN performance to be slightly worse. There is a critical need for studies with a robust reference standard and external data-set validation.

Abstract

BACKGROUND  Remote intracerebral hemorrhage (RICH) is a severe complication following chronic subdural hematoma (cSDH) drainage, and only case reports and small case series have been reported to date. The authors present an emblematic patient affected by RICH following cSDH drainage. A systematic review of the literature on diagnosis and management of patients affected by RICH following cSDH evacuation has also been performed. METHODS  A literature search according to the PRISMA statement was conducted using PubMed and Scopus databases with the following Mesh terms: [(remote) AND (intracerebral hemorrhage or cerebral hematoma or cerebral infarction or cerebellar hemorrhage or cerebellar hematoma or cerebellar infarction) AND (chronic subdural hematoma)]. RESULTS  The literature search yielded 35 results, and 25 articles met our inclusion criteria: 22 articles were case reports and 3 were case series including three to six patients. Overall, 37 patients were included in the study. Age was reported in all 37 patients, 26 males (70.3%) and 11 females (29.7%), with a male-to-female ratio of 2.4:1. The mean age at diagnosis was 64.6 years (range: 0.25-86 years). Only in 5 cases (13.5%) did the ICH occur contralaterally to the previously drained cSDH. The rapidity of drainage can lead to several types of intracranial hemorrhages, caused by a too rapid change in the cerebral blood flow (CBF) and/or tears of bridging veins. The average time interval between cSDH drainage and neurologic deterioration was 71.05 hours (range: 0-192 hours). CONCLUSIONS  RICH following cSDH represents a rare occurrence and a serious complication, associated with elevated morbidity. Careful monitoring of drain speed after cSDH evacuation surgery is recommended, and minimally invasive techniques such as twist drill craniostomy are suggested, especially for massive cSDHs.

Abstract

The 'swirl sign' is a CT imaging finding associated with haematoma expansion and poor prognosis. We performed a systematic review and meta-analysis to determine its prognostic value. PubMed/MEDLINE and EMBASE were searched until 16/12/2020 for related articles. Articles detailing the relationship between the swirl sign and any of haematoma expansion (HE), neurological outcome in the form of Glasgow Outcome Score (GOS) or mortality were included. A meta-analysis was performed and the pooled sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were calculated for each of HE, GOS and mortality. 15 papers were assessed. Nine papers related to HE, for which the pooled sensitivity was 50% (95% CI 30-71), specificity was 77% (95%CI 67-85) and PLR was 2.16 (95%CI 1.89-2.42). There was significant heterogeneity (I(2) = 70%, Q = 26.9). Three papers related to GOS, for which the pooled sensitivity was 45% (95%CI 20-74), specificity was 78.3% (95%CI 40-95.2) and PLR was 1.77 (95%CI 1.04-2.62). Three papers related to mortality, for which the pooled sensitivity was 65% (95% CI 32-88), specificity was 75% (95%CI 42-92) and pooled PLR was 2.64 (95%CI 1.60-4.13). Our findings indicated that the swirl sign is a useful prognostic marker in the radiological evaluation of intracranial haemorrhage. However, more research is needed to assess its independence from other risk factors for haematoma expansion.

Abstract

Studies on the relationship between hospital annualized case volume and in-hospital mortality in patients with subarachnoid hemorrhage (SAH) have shown conflicting results. Therefore, we performed a meta-analysis to further examine this relationship.The authors searched the PubMed and Embase databases from inception through July 2020 to identify studies that assessed the relationship between hospital annualized SAH case volume and in-hospital SAH mortality. Studies that reported in-hospital mortality in SAH patients and an adjusted odds ratio (OR) comparing mortality between low-volume and high-volume hospitals or provided core data to calculate an adjusted OR were eligible for inclusion. No language or human subject restrictions were imposed.Five retrospective cohort studies with 46,186 patients were included for analysis. The pooled estimate revealed an inverse relationship between annualized case volume and in-hospital mortality (OR, 0.53; 95% confidence interval, 0.42-0.68, P < .0001). This relationship was consistent in almost all subgroup analyses and was robust in sensitivity analyses.This meta-analysis confirms an inverse relationship between hospital annualized SAH case volume and in-hospital SAH mortality. Higher annualized case volume was associated with lower in-hospital mortality.