Blend sign predicts poor outcome in patients with intracerebral hemorrhage

Early NCCT imaging signs for prognostication in intracerebral hemorrhage: a retrospective cohort study with long follow up results

OBJECTIVE

This study intends to investigate the connection between non-contrast computed tomography (NCCT) imaging findings and neurological function scores in patients with intracerebral hemorrhage (ICH) in a long follow up of 451 patients.

METHODS

Between January 2020 and October 2021, a retrospective review was undertaken on patients with ICH. The NCCT imaging results within 24 h of symptom onset, clinical information, biochemical markers and the one-year outcome post-discharge were collected and analyzed. Subsequently, a prognostic model was devised to predict poor outcomes.

RESULTS

A cohort of 451 patients diagnosed with ICH was analyzed in this study. Adverse prognostic outcomes at three months were found to be independently associated with several factors, including the presence of the swirl sign (P = 0.010), advanced age (P = 0.003), post-ICH modified Rankin Scale (mRS) score (P = 0.003,), time elapsed from symptom onset to NCCT scan (P = 0.018), and the presence of ventricular hemorrhage (P = 0.003). Unfavorable prognosis at 12 months was independently associated with the presence of the island sign (P = 0.001), older age (P = 0.003), post-ICH mRS score (P = 0.003), and HE (P = 0.014). Additionally, the integration of NCCT imaging signs into the predictive model significantly improved its accuracy in predicting adverse outcomes at both three months (AUC = 0.817 vs. 0.782 in the model without NCCT, NRI = 0.219, P = 0.033, IDI = 0.080, P = 0.006) and 12 months (AUC = 0.829 vs. 0.797 in the model without NCCT, NRI = 0.235, P = 0.028, IDI = 0.096, P = 0.003).

CONCLUSIONS

The early imaging features of patients suffering from ICH can provide a more precise prognosis from the analysis of the 12-month follow up results.

Enhancing mortality prediction in patients with spontaneous intracerebral hemorrhage: Radiomics and supervised machine learning on non-contrast computed tomography

Purpose

This study aims to develop a Radiomics-based Supervised Machine-Learning model to predict mortality in patients with spontaneous intracerebral hemorrhage (sICH).

Methods

Retrospective analysis of a prospectively collected clinical registry of patients with sICH consecutively admitted at a single academic comprehensive stroke center between January-2016 and April-2018. We conducted an in-depth analysis of 105 radiomic features extracted from 105 patients. Following the identification and handling of missing values, radiomics values were scaled to 0-1 to train different classifiers. The sample was split into 80-20 % training-test and validation cohort in a stratified fashion. Random Forest(RF), K-Nearest Neighbor(KNN), and Support Vector Machine(SVM) classifiers were evaluated, along with several feature selection methods and hyperparameter optimization strategies, to classify the binary outcome of mortality or survival during hospital admission. A tenfold stratified cross-validation method was used to train the models, and average metrics were calculated.

Results

RF, KNN, and SVM, with the "DropOut+SelectKBest" feature selection strategy and no hyperparameter optimization, demonstrated the best performances with the least number of radiomic features and the most simplified models, achieving a sensitivity range between 0.90 and 0.95 and AUC range from 0.97 to 1 on the validation dataset. Regarding the confusion matrix, the SVM model did not predict any false negative test (negative predicted value 1).

Conclusion

Radiomics-based Supervised Machine Learning models can predict mortality during admission in patients with sICH. SVM with the "DropOut+SelectKBest" feature selection strategy and no hyperparameter optimization was the best simplified model to detect mortality during admission in patients with sICH.

A machine learning model based on results of a comprehensive radiological evaluation can predict the prognosis of basal ganglia cerebral hemorrhage treated with neuroendoscopy

Introduction

Spontaneous intracerebral hemorrhage is the second most common subtype of stroke. Therefore, this study aimed to investigate the risk factors affecting the prognosis of patients with basal ganglia cerebral hemorrhage after neuroendoscopy.

Methods

Between January 2020 and January 2024, 130 patients with basal ganglia cerebral hemorrhage who underwent neuroendoscopy were recruited from two independent centers. We split this dataset into training (n = 79), internal validation (n = 22), and external validation (n = 29) sets. The least absolute shrinkage and selection operator-regression algorithm was used to select the top 10 important radiomic features of different regions (perioperative hemorrhage area [PRH], perioperative surround area [PRS], postoperative hemorrhage area [PSH], and postoperative edema area [PSE]). The black hole, island, blend, and swirl signs were evaluated. The top 10 radiomic features and 4 radiological features were combined to construct the k-nearest neighbor classification (KNN), logistic regression (LR), and support vector machine (SVM) models. Finally, the performance of the perioperative hemorrhage and postoperative edema machine learning models was validated using another independent dataset (n = 29). The primary outcome is mRS at 6 months after discharge. The mRS score greater than 3 defined as functional independence.

Results

A total of 12 models were built: PRH-KNN, PRH-LR, PRH-SVM, PRS-KNN, PRS-LR, PRS-SVM, PSH-KNN, PSH-LR, PSH-SVM, PSE-KNN, PSE-LR, and PSE-SVM, with corresponding areas under the curve (AUC) values in the internal validation set of 0.95, 0.91, 0.94, 0.52, 0.91, 0.54, 0.67, 0.9, 0.72, 0.92, 0.92, and 0.95, respectively. The AUC values of the PRH-KNN, PRH-LR, PRH-SVM, PSE-KNN, PSE-LR, and PSE-SVM in the external validation were 0.9, 0.92, 0.89, 0.91, 0.92, and 0.88, respectively.

Conclusion

The model built based on computed tomography images of different regions accurately predicted the prognosis of patients with basal ganglia cerebral hemorrhage treated with neuroendoscopy. The models built based on the preoperative hematoma area and postoperative edema area showed excellent predictive efficacy in external verification, which has important clinical significance.

Added Value of Frequency of Imaging Markers for Prediction of Outcome After Intracerebral Hemorrhage: A Secondary Analysis of Existing Data

BACKGROUND

Frequency of imaging markers (FIM) has been identified as an independent predictor of hematoma expansion in patients with intracerebral hemorrhage (ICH), but its impact on clinical outcome of ICH is yet to be determined. The aim of the present study was to investigate this association.

METHODS

This study was a secondary analysis of our prior research. The data for this study were derived from six retrospective cohorts of ICH from January 2018 to August 2022. All consecutive study participants were examined within 6 h of stroke onset on neuroimaging. FIM was defined as the ratio of the number of imaging markers on noncontrast head tomography (i.e., hypodensities, blend sign, and island sign) to onset-to-neuroimaging time. The primary poor outcome was defined as a modified Rankin Scale score of 3-6 at 3 months.

RESULTS

A total of 1253 patients with ICH were included for final analysis. Among those with available follow-up results, 713 (56.90%) exhibited a poor neurologic outcome at 3 months. In a univariate analysis, FIM was associated with poor prognosis (odds ratio 4.36; 95% confidence interval 3.31-5.74; p < 0.001). After adjustment for age, Glasgow Coma Scale score, systolic blood pressure, hematoma volume, and intraventricular hemorrhage, FIM was still an independent predictor of worse prognosis (odds ratio 3.26; 95% confidence interval 2.37-4.48; p < 0.001). Based on receiver operating characteristic curve analysis, a cutoff value of 0.28 for FIM was associated with 0.69 sensitivity, 0.66 specificity, 0.73 positive predictive value, 0.62 negative predictive value, and 0.71 area under the curve for the diagnosis of poor outcome.

CONCLUSIONS

The metric of FIM is associated with 3-month poor outcome after ICH. The novel indicator that helps identify patients who are likely within the 6-h time window at risk for worse outcome would be a valuable addition to the clinical management of ICH.

The clinical potential of radiomics to predict hematoma expansion in spontaneous intracerebral hemorrhage: a narrative review

Spontaneous intracerebral hemorrhage (sICH) is associated with significant morbidity and mortality, with subsequent hematoma expansion (HE) linked to worse neurologic outcomes. Accurate, real-time predictions of the risk of HE could enable tailoring management-including blood pressure control or surgery-based on individual patient risk. Although multiple radiographic markers of HE have been proposed based on standard imaging, their clinical utility remains limited by a reliance on subjective interpretation of often ambiguous findings and a poor overall predictive power. Radiomics refers to the quantitative analysis of medical images that can be combined with machine-learning algorithms to identify predictive features for a chosen clinical outcome with a granularity beyond human limitations. Emerging data have supported the potential utility of radiomics in the prediction of HE after sICH. In this review, we discuss the current clinical management of sICH, the impact of HE and standard imaging predictors, and finally, the current data and potential future role of radiomics in HE prediction and management of patients with sICH.

Difference of mean Hounsfield units (dHU) between follow-up and initial noncontrast CT scan predicts 90-day poor outcome in spontaneous supratentorial acute intracerebral hemorrhage with deep convolutional neural networks

OBJECTIVES

This study aimed to investigate the usefulness of a new non-contrast CT scan (NCCT) sign called the dHU, which represented the difference in mean Hounsfield unit values between follow-up and the initial NCCT for predicting 90-day poor functional outcomes in acute supratentorial spontaneous intracerebral hemorrhage(sICH) using deep convolutional neural networks.

METHODS

A total of 377 consecutive patients with sICH from center 1 and 91 patients from center 2 (external validation set) were included. A receiver operating characteristic (ROC) analysis was performed to determine the critical value of dHU for predicting poor outcome at 90 days. Modified Rankin score (mRS) >3 or >2 was defined as the primary and secondary poor outcome, respectively. Two multivariate models were developed to test whether dHU was an independent predictor of the two unfavorable functional outcomes.

RESULTS

The ROC analysis showed that a dHU >2.5 was a critical value to predict the poor outcomes (mRS >3) in sICH. The sensitivity, specificity, and accuracy of dHU >2.5 for poor outcome prediction were 37.5%, 86.0%, and 70.6%, respectively. In multivariate models developed after adjusting for all elements of the ICH score and hematoma expansion, dHU >2.5 was an independent predictor of both primary and secondary poor outcomes (OR = 2.61, 95% CI [1.32,5.13], P = 0.006; OR = 2.63, 95% CI [1.36,5.10], P = 0.004, respectively). After adjustment for all possible significant predictors (p < 0.05) by univariate analysis, dHU >2.5 had a positive association with primary and secondary poor outcomes (OR = 3.25, 95% CI [1.52,6.98], P = 0.002; OR = 3.42, 95% CI [1.64,7.15], P = 0.001).

CONCLUSIONS

The dHU of hematoma based on serial CT scans is independently associated with poor outcomes after acute sICH, which may help predict clinical evolution and guide therapy for sICH patients.

Prior knowledge-based precise diagnosis of blend sign from head computed tomography

Introduction

Automated diagnosis of intracranial hemorrhage on head computed tomography (CT) plays a decisive role in clinical management. This paper presents a prior knowledge-based precise diagnosis of blend sign network from head CT scans.

Method

We employ the object detection task as an auxiliary task in addition to the classification task, which could incorporate the hemorrhage location as prior knowledge into the detection framework. The auxiliary task could help the model pay more attention to the regions with hemorrhage, which is beneficial for distinguishing the blend sign. Furthermore, we propose a self-knowledge distillation strategy to deal with inaccuracy annotations.

Results

In the experiment, we retrospectively collected 1749 anonymous non-contrast head CT scans from the First Affiliated Hospital of China Medical University. The dataset contains three categories: no intracranial hemorrhage (non-ICH), normal intracranial hemorrhage (normal ICH), and blend sign. The experimental results demonstrate that our method performs better than other methods.

Discussion

Our method has the potential to assist less-experienced head CT interpreters, reduce radiologists' workload, and improve efficiency in natural clinical settings.

Frontal Lobe Hemorrhage With Surrounding Edema and Subarachnoid Hemorrhage

We report the case of an 81-year-old woman who presented with a left hemineglect, a rightward gaze preference, and baseline disorientation. Her National Institutes of Health Stroke Score was 4. Her medical history was significant for dementia, osteoporosis, dyslipidemia, and a previous stroke. CT revealed a right-sided frontal lobe hemorrhage with surrounding edema and subarachnoid hemorrhage. Laboratory evaluation was significant for leukocytosis. The etiologies, clinical presentation, and diagnosis of this often devastating type of stroke are presented. While she did have a significant neurologic deficit (neglect), she was able to remain alert and protect her airway. Her hospital course consisted of observation in the ICU and blood pressure management. The case illustrates that intracerebral hemorrhage (ICH) can sometimes present indolently and does not always require surgical intervention.

The new Hematoma Maturity Score is highly associated with poor clinical outcome in spontaneous intracerebral hemorrhage

OBJECTIVES

The purpose of this study was to analyze the new combined indicators on noncontrast computed tomography (NCCT) to predict functional outcome at discharge, compared to previously individual radiological NCCT signs.

METHODS

Patients with spontaneous intracerebral hemorrhage (ICH) who underwent baseline CT scan were retrospectively analyzed. Black hole (BH) sign, blend sign (BS), island sign (IS), swirl sign (SwS), Barras classification, any hypodensity, any irregularity, and two combined novel indicators-Combined Barras Total Score (CBTS) and Hematoma Maturity Score-were assessed independently by two radiologists blinded to clinical information. Patients were trichotomized depending on the disability or dependency at discharge according to the Modified Rankin Scale (mRS): no symptoms or no significant/mild disability (mRS 0-2); moderate or severe disability (mRS 3-5); and mortality (mRS 6).

RESULTS

One hundred fourteen patients with spontaneous ICH confirmed by NCCT were included in the analysis. Multivariable statistical analysis was adjusted for anticoagulation, hematoma volume, ventricular expansion, hypertension, blood glucose level at admission, age, and history of atrial fibrillation and demonstrated that any hypodensity (OR 4.768, p 0.006), any irregularity (OR 4.768, p 0.006), CBTS ≥ 4 (OR 3.205, p 0.025), and the new Hematoma Maturity Score (Immature) (OR 5.872, p 0.006) are independent predictors of functional outcome at discharge.

CONCLUSIONS

The new concept of the Hematoma Maturity Score was the radiological sign on NCCT with the highest impact on clinical outcome in comparison with the rest of the evaluated radiological signs.

KEY POINTS

• This is the first manuscript where density and shape characteristics of the ICH had been evaluated together and integrated in a new Hematoma Maturity Score. • The new Hematoma Maturity Score is the radiological sign on NCCT with the highest impact on clinical outcome at discharge.

New Prediction Models of Functional Outcome in Acute Intracerebral Hemorrhage: The dICH Score and uICH Score

Objectives: The original intracerebral hemorrhage (oICH) score is the severity score most commonly used in clinical intracerebral hemorrhage (ICH) research but may be influenced by hematoma expansion or intraventricular hemorrhage (IVH) growth in acute ICH. Here, we aimed to develop new clinical scores to improve the prediction of functional outcomes in patients with ICH.

Methods: Patients admitted to the First Affiliated Hospital of Chongqing Medical University with primary ICH were prospectively enrolled in this study. Hematoma volume was measured using a semiautomated, computer-assisted technique. The dynamic ICH (dICH) score was developed by incorporating hematoma expansion and IVH growth into the oICH score. The ultra-early ICH (uICH) score was developed by adding the independent non-contrast CT markers to the oICH score. Receiver operating characteristic curve analysis was used to compare performance among the oICH score, dICH score, and uICH score.

Results: There were 310 patients in this study which included 72 patients (23.2%) with hematoma expansion and 58 patients (18.7%) with IVH growth. Of 31 patients with two or more non-contrast computed tomography markers, 61.3% died, and 96.8% had poor outcomes at 90 days. After adjustment for potential confounding variables, we found that age, baseline Glasgow Coma Scale score, presence of IVH on initial CT, baseline ICH volume, infratentorial hemorrhage, hematoma expansion, IVH growth, blend sign, black hole sign, and island sign could independently predict poor outcomes in multivariate analysis. In comparison with the oICH score, the dICH score and uICH score exhibited better performance in the prediction of poor functional outcomes.

Conclusions: The dICH score and uICH score were useful clinical assessment tools that could be used for risk stratification concerning functional outcomes and provide guidance in clinical decision-making in acute ICH.

The initial CT blend sign is not associated with poor patient outcomes after stereotactic minimally invasive surgery

Background

The initial CT blend sign is an imaging marker that has been used to predict haematoma expansion and poor outcomes in patients with small-volume intracerebral haemorrhage (ICH). However, the association of the blend sign with the outcomes of patients undergoing surgery remains unclear. The present study aimed to retrospectively evaluate the influence of the initial CT blend sign on short-term outcomes in patients with hypertensive ICH after stereotactic minimally invasive surgery (sMIS).

Methods

We enrolled 242 patients with spontaneous ICH. The patients were assigned to the blend sign group (91 patients) or non-blend sign (control) group (151 patients) based on the initial CT features. The NIHSS, GCS and mRS were used to assess the effects of sMIS. The rates of severe pulmonary infection and cardiac complications were also compared between the two groups.

Results

Statistically significant differences in the NIHSS and GCS scores were not observed between the blend sign group and the control group. No significant differences in the proportion of patients with good outcomes during the follow-up period were observed between the two groups. A higher rate of re-haemorrhage was noted in the blend sign group. Significant differences in the rates of severe pulmonary infection and cardiac complications were not observed between the two groups.

Conclusions

The initial CT blend sign is not associated with poor outcomes in patients with hypertensive ICH after sMIS. ICH patients with the CT blend sign should undergo sMIS if they are suitable candidates for surgery.

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.

A clinical-radiomics nomogram may provide a personalized 90-day functional outcome assessment for spontaneous intracerebral hemorrhage

OBJECTIVES

To develop and validate a noncontrast computed tomography (NCCT)-based clinical-radiomics nomogram to identify spontaneous intracerebral hemorrhage (sICH) patients with a poor 90-day prognosis on admission.

METHODS

In this double-center retrospective study, data from 435 patients with sICH (training cohort: n = 244; internal validation cohort: n = 104; external validation cohort: n = 87) were reviewed. The radiomics score (Rad-score) was calculated based on the coefficients of the selected radiomics features. A clinical-radiomics nomogram was developed by using independent predictors of poor outcome at 90 days through multivariate logistic regression analysis in the training cohort and was validated in the internal and external cohorts.

RESULTS

At 90 days, 200 of 435 (46.0%) patients had a poor prognosis. The clinical-radiomics nomogram was developed by six independent predictors namely midline shift, NCCT time from sICH onset, Glasgow Coma Scale score, serum glucose, uric acid, and Rad-score. In identifying patients with poor prognosis, the clinical-radiomics nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.81 in the training cohort, an AUC of 0.78 in the internal validation cohort, and an AUC of 0.73 in the external validation cohort. The calibration curve revealed that the clinical-radiomics nomogram showed satisfactory calibration in the training and internal validation cohorts (both p > 0.05), but slightly poor agreement in the external validation cohort (p < 0.05).

CONCLUSIONS

The clinical-radiomics nomogram is a valid computer-aided tool that may provide personalized risk assessment of 90-day functional outcome for sICH patients.

KEY POINTS

• The proposed Rad-score was significantly associated with 90-day poor functional outcome in patients with sICH. • The clinical-radiomics nomogram showed satisfactory calibration and the most net benefit for discriminating 90-day poor outcome. • The clinical-radiomics nomogram may provide personalized risk assessment of 90-day functional outcome for sICH patients.

Expanding indications for endovascular thrombectomy-how to leave no patient behind

Endovascular thrombectomy (EVT) has become standard of care for large vessel occlusion strokes but current guidelines exclude a large proportion of patients from this highly effective treatment. This review therefore focuses on expanding indications for EVT in several borderline indications such as patients in the extended time window, patients with extensive signs of infarction on admission imaging, elderly patients and patients with pre-existing deficits. It also discusses the current knowledge on intravenous thrombolysis as an adjunct to EVT and EVT as primary therapy for distal vessel occlusions, for tandem occlusions, for basilar artery occlusions and in pediatric patients. We provide clear recommendations based on current guidelines and further literature.

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 Triage Model for Interhospital Transfers of Low Risk Intracerebral Hemorrhage Patients

OBJECTIVES

Intracerebral hemorrhage comprises a large proportion of inter-hospital transfers to comprehensive stroke centers from centers without comprehensive stroke center resources despite lack of mortality benefit and low comprehensive stroke center resource utilization. The subset of patients who derive the most benefit from inter-hospital transfers is unclear. Here, we create a triage model to identify patients who can safely avoid transfer to a comprehensive stroke center.

MATERIALS AND METHODS

A retrospective cohort of spontaneous intracerebral hemorrhage patients transferred to our comprehensive stroke center from surrounding centers was used. Patients with early discharge from the Neuroscience Intensive Care Unit without use of comprehensive stroke center resources were identified as low risk, non-utilizers. Variables associated with this designation were used to develop and validate a triage model.

RESULTS

The development and replication cohorts comprised 358 and 99 patients respectively, of whom 78 (22%) and 26 (26%) were low risk, non-utilizers. Initial Glasgow Coma Scale and baseline hemorrhage volume were associated with low risk, non-utilizers in multivariate analysis. Initial Glasgow Coma Scale >13, intracerebral hemorrhage volume <15ml, absence of intraventricular hemorrhage, and supratentorial location had an area under curve, specificity, and sensitivity of 0.72, 91.4%, 52.6%, respectively, for identifying low risk, non-utilizers, and 0.75, 84.9%, 65.4%, respectively, in the replication cohort.

CONCLUSIONS

Spontaneous intracerebral hemorrhage patients with Glasgow Coma Scale >13, intracerebral hemorrhage volume <15 ml, absence of intraventricular hemorrhage, and supratentorial location might safely avoid inter-hospital transfer to a comprehensive stroke center. Validation in a prospective, multicenter cohort is warranted.

An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage

Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolutional neural networks for managing hemorrhagic stroke. Such a capability may be used to alert appropriate care teams, make decisions about patient transport from a primary care center to a comprehensive stroke center, and assist in treatment selection. This article reviews artificial intelligence algorithms for intracranial hemorrhage detection, quantification, and prognostication. Multiple algorithms currently being explored are described and illustrated with the help of examples.

Prediction of Poor Outcome in Intracerebral Hemorrhage Based on Computed Tomography Markers

INTRODUCTION

Intracerebral hemorrhage (ICH) is the most fatal type of stroke worldwide. Herein, we aim to develop a predictive model based on computed tomography (CT) markers in an ICH cohort and validate it in another cohort.

METHODS

This retrospective observational cohort study was conducted in 3 medical centers in China. The values of CT markers, including hypodensities, hematoma density, blend sign, black hole sign, island sign, midline shift, baseline hematoma volume, and satellite sign, in predicting poor outcome were analyzed by logistic regression analysis. A nomogram was developed based on the results of multivariate logistic regression analysis in development cohort. Area under curve (AUC) and calibration plot were used to assess the accuracy of nomogram in this development cohort and validate in another cohort.

RESULTS

A total of 1,498 patients were included in this study. Multivariate logistic regression analysis indicated that hypodensities, black hole sign, island sign, midline shift, and baseline hematoma volume were independently associated with poor outcome in development cohort. The AUC was 0.75 (95% confidence interval [CI]: 0.73-0.76) in the internal validation with development cohort and 0.74 (95% CI: 0.72-0.75) in the external validation with validation cohort. The calibration plot in development and validation cohort indicated that the nomogram was well calibrated.

CONCLUSIONS

CT markers of hypodensities, black hole sign, and island sign might predict poor outcome of ICH patients within 90 days.

The predictive accuracy of satellite sign for hematoma expansion in intracerebral hemorrhage: A meta-analysis

BACKGROUND AND PURPOSE

Satellite sign is a novel neuroimaging marker for predicting hematoma expansion (HE), which is closely related to unfavorable prognosis in patients with spontaneous intracerebral hemorrhage (ICH). However, the predictive value of satellite sign varied according to previous studies. Thus, we conduct this meta-analysis to systematically review the application value of satellite sign in related studies.

METHODS

We searched the literature in PubMed, Embase, and Web of Science from inception to April 10, 2020. Effect values, including sensitivity, specificity, and positive and negative likelihood ratio were pooled to assess the diagnostic value of satellite sign for HE in patients with ICH.

RESULTS

The meta-analysis included five studies with a total of 1493 patients. Results showed that the pooled diagnostic sensitivity and specificity were 0.50 (95 % CI, 0.31-0.70) and 0.71 (95 % CI, 0.56-0.83), respectively. In addition, the pooled positive and negative likelihood ratios were 1.7 (95 % CI, 1.5-2.1) and 0.70 (95 % CI, 0.54-0.89), respectively. No significant publication bias was found.

CONCLUSION

Satellite sign exhibited moderate sensitivity and specificity for predicting HE in patients with ICH. Further studies are needed to explore its value in clinical application.

Benign Intracerebral Hemorrhage: A Population at Low Risk for Hematoma Growth and Poor Outcome

Background

To define benign intracerebral hemorrhage (ICH) and to investigate the association between benign ICH, hematoma expansion, and functional outcome.

Methods and Results

We analyzed a prospectively collected cohort of patients with ICH, who presented within 6 hours of symptom onset between July 2011 and February 2017 to a tertiary teaching hospital. Follow‐up computed tomographic scanning was performed within 36 hours after initial computed tomographic scanning. Benign ICH was operationally defined as homogeneous and regularly shaped small ICH. The presence of benign ICH was judged by 2 independent reviewers (Q.L., W.Y.) on the basis of the admission computed tomographic scan. Functional independence was defined as a modified Rankin Scale score of 0 to 2 at 3 months. The associations between benign ICH, hematoma expansion, and functional outcome were assessed by using multivariable logistic regression analyses. A total of 288 patients with ICH were included. Benign ICH was found in 48 patients (16.7%). None of the patients with benign ICH had early hematoma expansion. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of benign ICH for predicting functional independence at 3 months were 30.7%, 96.6%, 90.0%, 60.0%, and 0.637, respectively.

Conclusions

Patients with benign ICH are at low risk of hematoma expansion and poor outcome. These patients may be safe for less intensive monitoring and are unlikely to benefit from therapies aimed at preventing ICH expansion.

Regular-Shaped Hematomas Predict a Favorable Outcome in Patients with Hypertensive Intracerebral Hemorrhage Following Stereotactic Minimally Invasive Surgery

BACKGROUND

Stereotactic minimally invasive surgery (sMIS) has been used in the treatment of intracerebral hemorrhage (ICH) in recent years and has obtained promising results. However, the outcomes of patients are associated with many factors. The aim of the present study was to retrospectively observe the relationship between hematoma shape features and the outcome of patients with spontaneous ICH following sMIS.

METHODS

One hundred eighty-three patients with hypertensive ICH who underwent sMIS were enrolled. Based on hematoma shape features, the patients were assigned to a regular-shaped hematoma group (RSH group, including 121 patients) or an irregular-shaped hematoma group (ISH group, including 62 patients). The Glasgow Coma Scale (GCS) score and the National Institutes of Health Stroke Scale (NIHSS) score were assessed on admission and at 1 week and 2 weeks after surgery. The rates of severe pulmonary infection, cardiac complications, and postoperative rebleeding during the hospital stay were also recorded for comparison. The functional outcome assessed by using the modified Rankin scale score was determined at discharge. A multivariate logistic regression analysis was performed for predictors of good outcome in patients with ICH who underwent sMIS. A receiver operating characteristic curve was also used to confirm the results.

RESULTS

Compared to the ISH group, the RSH group showed increased median GCS scores at one week and two weeks after surgery. The RSH group showed significantly decreased NIHSS scores at one week and two weeks after surgery compared with the ISH group at the same time point. Significant differences in the GCS score and the NIHSS score at 1 week (P < 0.05) and 2 weeks (P < 0.05) after surgery were observed between the RSH group and the ISH group. The RSH group showed lower rates of severe pulmonary infection, heart failure, and postoperative rehemorrhage than the ISH group (P < 0.05). Of the total patients with good outcomes, the RSH group accounted for 84.6%, and just 15.4% were from the ISH group. The multivariate logistic regression analysis demonstrated that regular-shaped hematoma (P < 0.0001) was an independent predictor of good outcome. The postoperative residual hematoma volume (P < 0.05) predicted a poor outcome. The sensitivity, specificity, and positive and negative predictive values of regular-shaped hematomas for the prediction of a favorable outcome in patients were 0.667, 0.846, 0.917, and 0.542, respectively. Additionally, the Youden index was 0.513.

CONCLUSIONS

Patients with regular-shaped hematomas exhibited more favorable outcomes. Irregular-shaped hematomas and postoperative residual hematoma volume predicted a poor outcome in patients with ICH following sMIS.

Blend Sign Is a Strong Predictor of the Extent of Early Hematoma Expansion in Spontaneous Intracerebral Hemorrhage

Background and Purpose: It is unclear which imaging marker is optimal for predicting the extent of hematoma expansion (EHE). We aimed to compare the usefulness of the blend sign (BS) with that of other non-contrast computed tomography (NCCT) markers for predicting the EHE in patients with spontaneous intracerebral hemorrhage (sICH). Methods: Patients with sICH admitted to our Neurology Emergency Department between September 2013 and January 2019 were enrolled. The EHE was calculated as the absolute increase in hematoma volume between baseline and follow-up CT (within 72 h). The EHE was categorized into four groups: "no growth," "minimal change" (≤5.1 ml), "moderate change" (5.1-12.5 ml), and "massive change" (>12.5 ml). Univariate and multivariate analyses were performed to investigate the relationship between the NCCT markers [BS, black hole sign (BHS), satellite sign, and island sign] and the EHE. Results: A total of 1,111 sICH patients were included (median age: 60 years; 66.5% males). Multiple linear regression analysis showed that the presence of the BS and BHS was independently associated with the EHE, after adjusting for confounders (P < 0.001 and P = 0.003, respectively). The presence of the BS and BHS was positively correlated with growth category (r = 0.285 and r = 0.199, both Ps < 0.001). The BS demonstrated a better predictive performance for the EHE than did the BHS [area under the curve (AUC): 0.67 vs. 0.57; both Ps < 0.001]. Conclusions: In patients with acute sICH, the BS showed a better performance in predicting the EHE compared with other NCCT markers. This imaging marker may help identify patients at a high risk of significant hematoma expansion and may facilitate its early management.

Expansion-Prone Hematoma: Defining a Population at High Risk of Hematoma Growth and Poor Outcome

BACKGROUND

Noncontrast computed tomography (CT) markers are increasingly used for predicting hematoma expansion. The aim of our study was to investigate the predictive value of expansion-prone hematoma in predicting hematoma expansion and outcome in patients with intracerebral hemorrhage (ICH).

METHODS

Between July 2011 and January 2017, ICH patients who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. Expansion-prone hematoma was defined as the presence of one or more of the following imaging markers: blend sign, black hole sign, or island sign. The diagnostic performance of blend sign, black hole sign, island sign, and expansion-prone hematoma in predicting hematoma expansion was assessed. Predictors of hematoma growth and poor outcome were analyzed using multivariable logistical regression analysis.

RESULTS

A total of 282 patients were included in our final analysis. Of 88 patients with early hematoma growth, 69 (78.4%) had expansion-prone hematoma. Expansion-prone hematoma had a higher sensitivity and accuracy for predicting hematoma expansion and poor outcome when compared with any single imaging marker. After adjustment for potential confounders, expansion-prone hematoma independently predicted hematoma expansion (OR 28.33; 95% CI 12.95-61.98) and poor outcome (OR 5.67; 95% CI 2.82-11.40) in multivariable logistic model.

CONCLUSION

Expansion-prone hematoma seems to be a better predictor than any single noncontrast CT marker for predicting hematoma expansion and poor outcome. Considering the high risk of hematoma expansion in these patients, expansion-prone hematoma may be a potential therapeutic target for anti-expansion treatment in future clinical studies.

Combination of Ultraearly Hematoma Growth and Hypodensities for Outcome Prediction after Intracerebral Hemorrhage

BACKGROUND

Noncontrast computed tomography hypodensities (HD) and ultraearly hematoma growth (uHG) are reliable markers for outcome prediction in patients with spontaneous intracerebral hemorrhage (sICH). The present study aimed to assess whether the combination of these 2 markers could improve the prognostic value for sICH.

METHODS

We recruited 242 patients with sICH who had been admitted within 6 hours from the onset of symptoms. HD was assessed by 2 independent blinded readers, and uHG was calculated as baseline ICH volume/onset-to-imaging time. We divided the study population into 4 groups: uHG(L) HD(-) (uHG <6.16 mL/hour and HD negative), uHG(L) HD(+) (uHG<6.16 mL/hour and HD positive), uHG(H) HD(-) (uHG ≥6.16 mL/hour and HD negative), and uHG(H) HD(+) (uHG ≥6.16 mL/h and HD positive). The outcome at 90 days was evaluated by the modified Rankin Scale (mRS) score and was dichotomized as good (mRS score 0-3) and poor (mRS score 4-6). The association between the combined indicators and unfavorable outcome was investigated using multivariable logistic regression models.

RESULTS

Patients with poor outcomes were more likely to have HD and higher uHG in univariate analysis. In multivariate logistic regression analysis, uHG(H) HD(+) had a higher risk of unfavorable outcomes compared with uHG(L) HD(-) (odds ratio [OR], 5.710; P < 0.001). In addition, the risk of unfavorable outcomes was increased in uHG(H) HD(-) (OR, 2.957, P = 0.044) and uHG(L) HD(+) (OR, 1.924; P = 0.232). The proportions of unfavorable prognoses were 32.6% in uHG(L) HD(-), 48.3% in uHG(L) HD(+), 72.2% in uHG(H) HD(-), and 87.5% in uHG(H) HD(+) (P < 0.001).

CONCLUSIONS

The combination of uHG and HD improves the stratification of unfavorable prognoses in patients with sICH.

Comparison of Ultra-Early Hematoma Growth and Common Noncontrast Computed Tomography Features in Predicting Hematoma Enlargement in Patients with Spontaneous Intracerebral Hemorrhage

OBJECTIVE

Ultra-early hematoma growth (uHG), the black hole sign, and the blend sign are common predictors of hematoma enlargement (HE). This study aimed to develop a new diagnostic criterion for predicting HE using uHG and to compare the accuracy of uHG, the black hole sign, and the blend sign in predicting HE in patients with spontaneous intracerebral hemorrhage (sICH).

METHODS

We retrospectively analyzed data of 920 patients with sICH from August 2013 to January 2018. Receiver operating characteristic curves were plotted to determine the optimal threshold values of uHG to predict HE. The effects of the black hole sign, blend sign, and uHG on HE were assessed using univariate and multivariate logistic regression models, and their prediction accuracies were analyzed using receiver operator analyses.

RESULTS

The black hole sign was identified in 131 patients, the blend sign in 163 patients, and uHG >6.46 mL/h in 441 patients. Logistic analysis showed that the black hole sign, blend sign, and uHG >6.46 mL/h were independent predictors of HE. The sensitivity values of uHG >6.46 mL/h, the black hole sign, and the blend sign were 70.43%, 24.19%, and 36.56%, respectively, and specificity values were 57.77%, 88.28%, and 87.06%, respectively. uHG had the greatest area under the curve. The black hole and blend signs were more commonly found in patients with uHG >6.46 mL/h (P < 0.001).

CONCLUSIONS

uHG >6.46 mL/h was the optimal predictor used for identifying patients at high risk of developing HE. A greater uHG value was associated with an increased prevalence of the black hole and blend signs.

Triage of 5 Noncontrast Computed Tomography Markers and Spot Sign for Outcome Prediction After Intracerebral Hemorrhage

Background and Purpose- Besides the established spot sign (SS) in computed tomography angiography (CTA), there is growing evidence that different imaging markers in noncontrast CT offer great value for outcome prediction in patients with intracerebral hemorrhage (ICH). However, it is unclear how the concurrent presence of each sign independently contributes to the predictive power of poor outcome. We, therefore, aimed to clarify the predictive value of 5 recently published noncontrast CT parameters (blend sign, black hole sign, island sign, hematoma heterogeneity, and hypodensities) and the established SS in 1 consecutive series of patients with ICH. Methods- Retrospective study of patients with ICH at 2 German tertiary stroke centers; inclusion criteria were (1) spontaneous ICH and (2) noncontrast CT and CTA performed on admission within 6 hours after onset of symptoms. We defined a binary outcome (good outcome [modified Rankin Scale score of ≤3] versus poor outcome [modified Rankin Scale score of >3]) at discharge. The predictive value of each sign was assessed in univariate and multivariable logistic regression models. Results- Of 201 patients with spontaneous ICH, 28 (13.9%) presented with black hole sign, 38 (18.9%) with blend sign, 120 (59.7%) with hypodensities, 97 (48.3%) with heterogeneous densities, 53 with island sign (26.4%), and 45 (22.4%) with SS. In univariable logistic regression, higher hematoma volume ( P<0.001), intraventricular hemorrhage ( P=0.002), and the presence of black hole sign/blend sign/hypodensities/island sign/SS/heterogeneous density (all P<0.001) on admission CT were associated with poor outcome. Multivariable analysis confirmed intraventricular hemorrhage (odds ratio, 2.20; P=0.025), higher hematoma volume (odds ratio, 1.02 per mL; P<0.019), the presence of hypodensities (odds ratio, 2.47; P=0.018), and SS (odds ratio, 12.22; P<0.001) as independent predictors of poor outcome. Conclusions- This study demonstrates the degree of interaction between 5 recent noncontrast CT imaging markers and SS and their individual contribution for outcome prediction in patients with ICH. Of the CT variables indicating poor outcome SS on CTA and hypodensities were the most reliable outcome predictors.

Standards for Detecting, Interpreting, and Reporting Noncontrast Computed Tomographic Markers of Intracerebral Hemorrhage Expansion

Significant hematoma expansion (HE) affects one-fifth of people within 24 hours after acute intracerebral hemorrhage (ICH), and its prevention is an appealing treatment target. Although the computed tomography (CT)-angiography spot sign predicts HE, only a minority of ICH patients receive contrast injection. Conversely, noncontrast CT (NCCT) is used to diagnose nearly all ICH, so NCCT markers represent a widely available alternative for prediction of HE. However, different NCCT signs describe similar features, with lack of consensus on the optimal image acquisition protocol, assessment, terminology, and diagnostic criteria. In this review, we propose practical guidelines for detecting, interpreting, and reporting NCCT predictors of HE. ANN NEUROL 2019;86:480-492.

Hematoma location and morphology of anticoagulation-associated intracerebral hemorrhage

OBJECTIVE

To study hematoma location and morphology of intracerebral hemorrhage (ICH) associated with oral anticoagulants (OAC) and delineate causes and mechanism.

METHODS

We performed a systematic literature research and meta-analysis of studies comparing neuroimaging findings in patients with OAC-ICH compared to those with ICH not associated with OAC (non-OAC ICH). We calculated pooled risk ratios (RRs) for ICH location using the Mantel-Haenszel random-effects method and corresponding 95% confidence intervals (95% CI).

RESULTS

We identified 8 studies including 6,259 patients (OAC-ICH n = 1,107, pooled OAC-ICH population 17.7%). There was some evidence for deep ICH location (defined as ICH in the thalamus, basal ganglia, internal capsule, or brainstem) being less frequent in patients with OAC-ICH (OAC-ICH: 450 of 1,102/40.8% vs non-OAC ICH: 2,656 of 4,819/55.1%; RR 0.94, 95% CI 0.88-1.00, p = 0.05, I ² = 0%) while cerebellar ICH location was significantly more common in OAC-ICH (OAC-ICH: 111 of 1,069/10.4% vs non-OAC ICH: 326 of 4,787/6.8%; RR 1.45, 95% CI 1.12-1.89, p = 0.005, I ² = 21%) compared to non-OAC ICH. There was no statistically significant relationship to OAC use for lobar (OAC-ICH: 423 of 1,107/38.2% vs non-OAC ICH: 1,884 of 5,152/36.6%; RR 1.02, 95% CI 0.89-1.17, p = 0.75, I ² = 53%, p for heterogeneity = 0.04) or brainstem ICH (OAC-ICH: 36 of 546/6.6% vs non-OAC ICH: 172 of 2,626/6.5%; RR 1.04, 95% CI 0.58-1.87, p = 0.89, I ² = 59%, p for heterogeneity = 0.04). The risk for intraventricular extension (OAC-ICH: 436 of 840/51.9% vs non-OAC ICH: 1,429 of 3,508/40.7%; RR 1.26, 95% CI 1.16-1.36, p < 0.001, I ² = 0%) was significantly increased in patients with OAC-ICH. We found few data on ICH morphology in OAC-ICH vs non-OAC ICH.

CONCLUSION

The overrepresentation of cerebellar ICH location and intraventricular extension in OAC-ICH might have mechanistic relevance for the underlying arteriopathy, pathophysiology, or bleeding pattern of OAC-ICH, and should be investigated further.

Intracerebral haemorrhage: current approaches to acute management

Acute spontaneous intracerebral haemorrhage is a life-threatening illness of global importance, with a poor prognosis and few proven treatments. As a heterogeneous disease, certain clinical and imaging features help identify the cause, prognosis, and how to manage the disease. Survival and recovery from intracerebral haemorrhage are related to the site, mass effect, and intracranial pressure from the underlying haematoma, and by subsequent cerebral oedema from perihaematomal neurotoxicity or inflammation and complications from prolonged neurological dysfunction. A moderate level of evidence supports there being beneficial effects of active management goals with avoidance of early palliative care orders, well-coordinated specialist stroke unit care, targeted neurointensive and surgical interventions, early control of elevated blood pressure, and rapid reversal of abnormal coagulation.

Imaging-based outcome prediction in patients with intracerebral hemorrhage

Besides the established spot sign in computed tomography angiography (CTA), recently investigated imaging predictors of hematoma growth in noncontrast computed tomography (NCCT) suggest great potential for outcome prediction in patients with intracerebral hemorrhage (ICH). Secondary hematoma growth is an appealing target for therapeutic interventions because in contrast to other determined factors, it is potentially modifiable. Even more initial therapy studies failed to demonstrate clear therapeutic benefits, there is a need for an effective patient selection using imaging markers to identify patients at risk for poor outcome and thereby tailor individual treatments for every patient. Hence, this review gives an overview about the current literature on NCCT imaging markers for neurological outcome prediction and aims to clarify the association with the established spot sign. Moreover, it demonstrates the clinical impact of these parameters and gives a roadmap for future imaging research in patients with intracerebral hemorrhage.