Island Sign Predicts Hematoma Expansion and Poor Outcome After Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis

Research advances in predicting the expansion of hypertensive intracerebral hemorrhage based on CT images: an overview

Hematoma expansion (HE) is an important risk factor for death or poor prognosis in patients with hypertensive intracerebral hemorrhage (HICH). Accurately predicting the risk of HE in patients with HICH is of great clinical significance for timely intervention and improving patient prognosis. Many imaging signs reported in literatures showed the important clinical value for predicting HE. In recent years, the development of radiomics and artificial intelligence has provided new methods for HE prediction with high accuracy. Therefore, this article reviews the latest research progress in CT imaging, radiomics, and artificial intelligence of HE, in order to help identify high-risk patients for HE in clinical practice.

Efficacy of non-enhanced computer tomography-based radiomics for predicting hematoma expansion: A meta-analysis

Background

This meta-analysis aimed to assess the efficacy of radiomics using non-enhanced computed tomography (NCCT) for predicting hematoma expansion in patients with spontaneous intracerebral hemorrhage.

Methods

Throughout the inception of the project to April 11, 2022, a comprehensive search was conducted on PubMed, Embase, and Cochrane Central Register of Controlled Trials. The methodological quality of studies in this analysis was assessed by the radiomics quality scoring system (RQS). A meta-analysis of radiomic studies based on NCCT for predicting hematoma expansion in patients with intracerebral hemorrhage was performed. The efficacy of the radiomics approach and non-contrast CT markers was compared using network meta-analysis (NMA).

Results

Ten articles comprising a total of 1525 patients were quantitatively analyzed for hematoma expansion after cerebral hemorrhage using radiomics. Based on the included studies, the mean RQS was 14.4. The AUC value (95% confidence interval) of the radiomics model was 0.80 (0.76-0.83). Five articles comprising 846 patients were included in the NMA. The results synthesized according to Bayesian NMA revealed that the predictive ability of the radiomics model outperformed most of the NCCT biomarkers.

Conclusions

The NCCT-based radiomics approach has the potential to predict hematoma expansion. Compared to NCCT biomarkers, we recommend a radiomics approach. Standardization of the radiomics approach is required for further clinical implementation.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=324034, identifier [CRD42022324034].

Computed tomography in acute intracerebral hemorrhage: neuroimaging predictors of hematoma expansion and outcome

Intracerebral hemorrhage (ICH) accounts for 10–20% of all strokes worldwide and is associated with serious outcomes, including a 30-day mortality rate of up to 40%. Neuroimaging is pivotal in diagnosing ICH as early detection and determination of underlying cause, and risk for expansion/rebleeding is essential in providing the correct treatment. Non-contrast computed tomography (NCCT) is the most used modality for detection of ICH, identification of prognostic markers and measurements of hematoma volume, all of which are of major importance to predict outcome. The strongest predictors of 30-day mortality and functional outcome for ICH patients are baseline hematoma volume and hematoma expansion. Even so, exact hematoma measurement is rare in clinical routine practice, primarily due to a lack of tools available for fast, effective, and reliable volumetric tools. In this educational review, we discuss neuroimaging findings for ICH from NCCT images, and their prognostic value, as well as the use of semi-automatic and fully automated hematoma volumetric methods and assessment of hematoma expansion in prognostic studies.

Intracerebral hemorrhage markers on non-contrast computed tomography as predictors of the dynamic spot sign on CT perfusion and associations with hematoma expansion and outcome

PURPOSE

To assess the association between non-contrast computed tomography (NCCT) hematoma markers and the dynamic spot sign on computed tomography perfusion (CTP), and their associations with hematoma expansion, clinical outcome, and in-hospital mortality.

METHODS

Patients who presented with intracerebral hemorrhage (ICH) to a stroke center over an 18-month period and underwent baseline NCCT and CTP, and a follow-up NCCT within 24 h after the baseline scan were included. The initial and follow-up hematoma volumes were calculated. Two raters independently assessed the baseline NCCT for hematoma markers and concurrently assessed the CTP for the dynamic spot sign. Univariate and multivariate logistic regression analyses were performed to assess the association between the hematoma markers and the dynamic spot sign, adjusting for known ICH expansion predictors.

RESULTS

Eighty-five patients were included in our study and 55 patients were suitable for expansion analysis. Heterogeneous density was the only NCCT hematoma marker to be associated with the dynamic spot sign after multivariate analysis (odds ratio, 58.61; 95% confidence interval, 9.13-376.05; P < 0.001). The dynamic spot sign was present in 22 patients (26%) and significantly predicted hematoma expansion (odds ratio, 36.6; 95% confidence interval, 2.51-534.2; P = 0.008). All patients with a spot sign had a swirl sign. A co-located hypodensity and spot sign was significantly associated with in-hospital mortality (odds ratio, 6.17; 95% confidence interval, 1.09-34.78; P = 0.039).

CONCLUSION

Heterogeneous density and swirl sign are associated with the dynamic spot sign. The dynamic spot sign is a stronger predictor than NCCT hematoma markers of significant hematoma expansion. A co-located spot sign and hypodensity predicts in-hospital mortality.

Predicting Hematoma Expansion after Spontaneous Intracranial Hemorrhage Through a Radiomics Based Model

PURPOSE

Intracranial hemorrhage (ICH) is characterized as bleeding into the brain tissue, intracranial space, and ventricles and is the second most disabling form of stroke. Hematoma expansion (HE) following ICH has been correlated with significant neurological decline and death. For early detection of patients at risk, deep learning prediction models were developed to predict whether hematoma due to ICH will expand. This study aimed to explore the feasibility of HE prediction using a radiomic approach to help clinicians better stratify HE patients and tailor intensive therapies timely and effectively.

MATERIALS AND METHODS

Two hundred ICH patients with known hematoma evolution, were enrolled in this study. An open-source python package was utilized for the extraction of radiomic features from both non-contrast computed tomography (NCCT) and magnetic resonance imaging (MRI) scans through characterization algorithms. A total of 99 radiomic features were extracted and different features were selected for network inputs for the NCCT and MR models. Seven supervised classifiers: Support Vector Machine, Naïve Bayes, Decision Tree, Random Forest, Logistic Regression, K-Nearest Neighbor and Multilayer Perceptron were used to build the models. A training:testing split of 80:20 and 20 iterations of Monte Carlo cross validation were performed to prevent overfitting and assess the variability of the networks, respectively. The models were fed training datasets from which they learned to classify the data based on pre-determined radiomic categories.

RESULTS

The highest sensitivity among the NCCT classifier models was seen with the support vector machine (SVM) and logistic regression (LR) of 72 ± 0.3% and 73 ± 0.5%, respectively. The MRI classifier models had the highest sensitivity of 68 ± 0.5% and 72 ± 0.5% for the SVM and LR models, respectively.

CONCLUSIONS

This study indicates that the NCCT radiomics model is a better predictor of HE and that SVM and LR classifiers are better predictors of HE due to their more cautious approach indicated by a higher sensitivity metric.

Minimally Invasive Intracerebral Hemorrhage Evacuation Techniques: A Review

Intracerebral hemorrhage (ICH) continues to have high morbidity and mortality. Improving ICH outcomes likely requires rapid removal of blood from the parenchyma and restraining edema formation while also limiting further neuronal damage due to the surgical intervention. Minimally invasive surgery (MIS) approaches promise to provide these benefits and have become alluring options for management of ICH. This review describes six MIS techniques for ICH evacuation including craniopuncture, stereotactic aspiration with thrombolysis, endoport-mediated evacuation, endoscope-assisted evacuation, adjunctive aspiration devices, and the surgiscope. The efficacy of each modality is discussed based on current literature. The largest clinical trials have yet to demonstrate definitive effects of MIS intervention on mortality and functional outcomes for ICH. Thus, there is a significant need for further innovation for ICH treatment. Multiple ongoing trials promise to better clarify the potential of the newer, non-thrombolytic MIS techniques.

Computed Tomography Imaging Predictors of Intracerebral Hemorrhage Expansion

PURPOSE OF REVIEW

Hematoma expansion (HE) is strongly associated with poor clinical outcome and is a compelling target for improving outcome after intracerebral hemorrhage (ICH). Non-contrast computed tomography (NCCT) is widely used in clinical practice due to its faster acquisition at the presence of acute stroke. Recently, imaging markers on NCCT are increasingly used for predicting HE. We comprehensively review the current evidence on HE prediction using NCCT and provide a summary for assessment of these markers in future research studies.

RECENT FINDINGS

Predictors of HE on NCCT have been described in reports of several studies. The proposed markers, including swirl sign, blend sign, black hole sign, island sign, satellite sign, and subarachnoid extension, were all significantly associated with HE and poor outcome in their small sample studies after ICH. In summary, the optimal management of ICH remains a therapeutic dilemma. Therefore, using NCCT markers to select patients at high risk of HE is urgently needed. These markers may allow rapid identification and provide potential targets for anti-HE treatments in patients with acute ICH.

A Meta-analysis of the Predictive Significance of the Island Sign for Hematoma Expansion in Intracerebral Hemorrhage

BACKGROUND

The island sign of non-contrast computed tomography is a risk factor for hematoma expansion (HE) after spontaneous intracerebral hemorrhage, but has inconsistent conclusions. A meta-analysis was performed to investigate the predictive accuracy of island sign for HE.

METHODS

A systematic review of published literature on island sign and hematoma expansion was conducted. The pooled sensitivity, specificity, and summary receiver operating characteristics curve (SROC) were generated. The publication bias was assessed by Deeks' funnel plot asymmetry test.

RESULTS

Nine studies with a total of 2939 patients were included in the present study. The pooled sensitivity and specificity of island sign for predicting hematoma expansion was 0.50 and 0.89, respectively. The area under the curve was 0.73 in the SROC curve. There was no significant publication bias.

CONCLUSIONS

This meta-analysis suggests that island sign of non-contrast computed tomography has a good predictive accuracy for hematoma enlargement in intracerebral hemorrhage.