Comparison of CT black hole sign and other CT features in predicting hematoma expansion in patients with ICH

Short-term prognostic value of cranial volume in patients with cerebral hemorrhage based on propensity score matching

OBJECTIVES

The purpose of this study was to investigate whether cranial volume can improve the accuracy of prognosis, and to explore the relationship between the prognosis of patients with cerebral hemorrhage and the cranial volume and anterior and posterior diameter.

METHODS

We obtained data from patients diagnosed with spontaneous cerebral hemorrhage between 2018 and 2020 at the First Hospital of Harbin Medical University. The hematoma volume to cranial volume ratio (HVCVR) was calculated as the ratio of hematoma volume to cranial volume. Multivariate logistic regression models were developed to assess the predictive power of hematoma volume and HVCVR. Propensity score matching was employed to adjust for baseline differences in cranial volume. Multiple logistic regression models were used to explore the relationship between cranial diameter and prognosis.

RESULTS

Among 3494 patients, 1,796 (51.4%) had poor outcomes. Poor outcomes were associated with larger HVCVR values, and multivariate analysis confirmed HVCVR as an independent predictor (OR 1.722, 95 % CI 1.471-2.206, P < 0.001), outperforming hematoma volume alone (AUC 0.774 vs. 0.761, P < 0.001). Propensity-matched cohorts (n = 1199 each) revealed that larger intracranial volume correlated with better prognosis (OR 0.802, 95 % CI 0.683-0.942, P = 0.002).

CONCLUSION

Our study suggests that HVCVR provides a more accurate prediction of prognosis in spontaneous cerebral hemorrhage patients. Greater cranial volume and a more flattened cranial cavity may potentially influence positive prognoses in patients with cerebral hemorrhage.

Black Hole Sign under Anticoagulant Therapy: A Retrospective Comparison of Warfarin and Direct Oral Anticoagulants

BACKGROUND AND PURPOSE

Direct oral anticoagulants (DOAC) have rapidly replaced warfarin. Intracerebral hemorrhage (ICH) is known to be one of the most severe side effects of anticoagulant drugs. The black hole (BH) sign is reportedly a valid radiologic sign for predicting hematoma expansion in acute ICH. Here, we hypothesized that the frequency of BH signs might differ between warfarin and DOAC treatment. We critically evaluated the clinical value of the BH sign in acute ICH under warfarin versus DOAC therapy.

MATERIALS AND METHODS

Patients with acute ICH under anticoagulant therapy were enrolled. Hematoma volumes were measured by ABC/2. Radiologists blinded to the clinical information determined the presence or absence of the BH sign on CT images. This study defined a more than 12.5 mL increase in hematoma volume as cases with "expanded hematoma."

RESULTS

We analyzed 111 patients with acute ICH under anticoagulant therapy. Among them, 21 patients were treated with antagonists in this cohort. Multivariate logistic regression analysis revealed that the presence of ventricular perforation (P = .02; adjusted OR: 3.51; 95% CI: 1.32-10.2) and the BH sign (P < .01; adjusted OR: 4.86; 95% CI: 1.73-14.3) were significantly different between expanded and nonexpanded hematoma cases. Comparison of hematoma volume and the presence of the BH sign between warfarin and DOAC cases indicated significant differences in maximum hematoma volume (P = .03) and presence of the BH sign (P < .01). The increase in hematoma volume was significantly greater when the BH sign was present under warfarin therapy (P = .05). In contrast, the increase in hematoma volume did not differ between cases with and without the BH sign in patients under DOAC therapy (P = .14).

CONCLUSIONS

The BH sign is a useful radiologic signature to predict the expansion of acute ICH under anticoagulant therapy. ICH under warfarin tended to present the BH sign more frequently than that under DOAC. The results also showed that the BH sign is more reliable under warfarin than under DOAC therapy in patients with ICH.

Minimally Invasive Surgery for Spontaneous Intracerebral Hemorrhage: A Review

Background: Spontaneous intracerebral hemorrhage (ICH) accounts for approximately 20% of all strokes and is associated with high mortality and disability rates. Despite numerous trials, conventional surgical approaches have not demonstrated consistent improvements in functional outcomes. Minimally invasive surgery (MIS) for ICH evacuation has emerged as a promising alternative, with the potential to improve functional outcomes and reduce mortality. Objectives: This narrative review aims to provide a comprehensive overview of various MIS techniques and their reported impact on functional outcomes in patients with spontaneous ICH while discussing key limitations in the existing literature. Methods: We systematically searched PubMed to identify studies published from 1 January 2010 to 22 March 2024. The search strategy included the following terms: ("minimally*"[All Fields] AND "invasive*"[All Fields] AND "surgery*"[All Fields] AND "intracerebral*"[All Fields] AND "hemorrhage*"[All Fields]) AND (2010:2024[pdat]). This review focuses on randomized controlled trials (RCTs) that evaluate MIS techniques for ICH and their clinical outcomes. Results: Our search identified six RCTs conducted between January 2010 and March 2024, encompassing 2180 patients with a mean age of 58.03 ± 4.5 years. Four trials demonstrated significantly improved functional recovery (mRs ≤ 3), reduced mortality, and fewer adverse events compared with standard medical management or conventional craniotomy. All MIS techniques rely on stereotactic planning and the use of tools such as exoscopes, endoscopes, craniopuncture, or thrombolytic irrigation for precise hematoma evacuation. These approaches reduce brain tissue disruption and improve precision. However, the variability in techniques, costs, and lack of an external validation limit the generalizability of these findings. Conclusions: MIS shows potential as an alternative to conventional management strategies for ICH, offering encouraging evidence for improved functional outcomes and reduced mortality in selected studies. However, these findings remain limited by gaps in the literature, including the need for external validation, significant methodological heterogeneity, and economic challenges. Further rigorous trials are essential to confirm the generalizability and long-term impact of these approaches.

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.

Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis

PURPOSE

Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, radiomics has been gradually introduced into the early identification of hematoma enlargement. Though, radiomics has limited predictive accuracy due to variations in procedures. Therefore, we conducted a systematic review and meta-analysis to explore the value of radiomics in the early detection of HE in patients with cerebral hemorrhage.

METHODS

Eligible studies were systematically searched in PubMed, Embase, Cochrane and Web of Science from inception to April 8, 2024. English articles are considered eligible. The radiomics quality scoring (RQS) tool was used to evaluate included studies.

RESULTS

A total of 34 studies were identified with sample sizes ranging from 108 to 3016. Eleven types of models were involved, and the types of modeling contained mainly clinical, radiomic, and radiomic plus clinical features. The radiomics models seem to have better performance (0.77 and 0.73 C-index in the training cohort and validation cohort, respectively) than the clinical models (0.69 C-index in the training cohort and 0.70 C-index in the validation cohort) in discriminating HE. However, the C-index was the highest for the combined model in both the training (0.82) and validation (0.79) cohorts.

CONCLUSIONS

Machine learning based on radiomic plus clinical features has the best predictive performance for HE, followed by machine learning based on radiomic features, and can be used as a potential tool to assist clinicians in early judgment.

NCCT Markers of Intracerebral Hemorrhage Expansion Using Revised Criteria: An External Validation of Their Predictive Accuracy

BACKGROUND AND PURPOSE

Several NCCT expansion markers have been proposed to improve the prediction of hematoma expansion. We retrospectively evaluated the predictive accuracy of 9 expansion markers.

MATERIALS AND METHODS

Patients admitted for intracerebral hemorrhage within 24 hours of last seen well were retrospectively included from April 2016 to April 2020. The primary outcome was revised hematoma expansion, defined as any of a ≥6-mL or ≥33% increase in intracerebral hemorrhage volume, a ≥ 1-mL increase in intraventricular hemorrhage volume, or de novo intraventricular hemorrhage. We assessed the predictive accuracy of expansion markers and determined their association with revised hematoma expansion.

RESULTS

We included 124 patients, of whom 51 (41%) developed revised hematoma expansion. The sensitivity of each marker for the prediction of revised hematoma expansion ranged from 4% to 78%; the specificity, 37%-97%; the positive likelihood ratio, 0.41-7.16; and the negative likelihood ratio, 0.49-1.06. By means of univariable logistic regressions, 5 markers were significantly associated with revised hematoma expansion: black hole (OR = 8.66; 95% CI, 2.15-58.14; P = .007), hypodensity (OR = 3.18; 95% CI, 1.49-6.93; P = .003), blend (OR = 2.90; 95% CI, 1.08-8.38; P = .04), satellite (OR = 2.84; 95% CI, 1.29-6.61; P = .01), and Barras shape (OR = 2.41, 95% CI; 1.17-5.10; P = .02). In multivariable models, only the black hole marker remained independently associated with revised hematoma expansion (adjusted OR = 5.62; 95% CI, 1.23-40.23; P = .03).

CONCLUSIONS

No single NCCT expansion marker had both high sensitivity and specificity for the prediction of revised hematoma expansion. Improved image-based analysis is needed to tackle limitations associated with current NCCT-based expansion markers.

The comprehensive comparison of imaging sign from CT angiography and noncontrast CT for predicting intracranial hemorrhage expansion: A comparative study

Expansion of intracranial hemorrhage (ICH) is an important predictor of poor clinical outcomes. Various imaging markers on non-contrast computed tomography (NCCT) or computed tomographic angiography (CTA) have been reported as predictors of ICH expansion. We aimed to compare the associations between various CT imaging markers and ICH expansion. Patients with spontaneous ICH who underwent initial NCCT, CTA, and subsequent NCCT between January 2016 and December 2019 were retrospectively identified. ICH expansion was defined as a volume increase of > 33% or > 6 mL. We analyzed the presence of imaging markers such as the black hole sign, blend sign, island sign, or swirl sign on initial NCCT or spot sign on CTA. An alternative free-response receiver operating characteristic curve analysis was performed using a 4-point scoring system based on the consensus of the reviewers. The predictive value of each marker was assessed using univariate and multivariate logistic regression analyses. A total of 250 patients, including 60 (24.0%) with ICH expansion, qualified for the analysis. Among the patients with spontaneous ICH, 118 (47.2%) presented with a black hole sign, 52 (20.8%) with a blend sign, 93 (37.2%) with an island sign, 79 (31.6%) with a swirl sign, and 56 (22.4%) with a spot sign. In univariate logistic regression, the initial ICH volume (P = .038), initial intraventricular hemorrhage (IVH) presence (P < .001), swirl sign (P < .001), and spot sign (P < .001) were associated with ICH expansion. Multivariate analysis confirmed that the presence of initial IVH (odds ratio, 4.111; P = .002) and spot sign (odds ratio, 109.5; P < .001) were independent predictors of ICH expansion. Initial ICH volume, IVH, swirl sign, and spot sign are associated with ICH expansion. The presence of spot signs and IVH were independent predictors of ICH expansion.

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.

Non-Contrast CT-Based Radiomics Score for Predicting Hematoma Enlargement in Spontaneous Intracerebral Hemorrhage

PURPOSE

To develop a non-contrast computed tomography-(CT)-based radiomics score for predicting the risk of hematoma early enlargement in spontaneous intracerebral hemorrhage.

METHODS

A total of 258 patients from a single-center database with acute spontaneous intracerebral parenchymal hemorrhage were collected. Radiomics software was explored to segment hematomas on baseline non-contrast CT images, and the texture features were extracted. Minimal Redundancy and Maximal Relevance (mRMR) and Least Absolute Shrinkage and Selection Operator (LASSO), were used to select optimized subset of features and radiomics score was calculated. The radiomics model (radiomics score-based), radiomics nomogram (radiomics score combined with clinical factors-based) and clinical model (clinical factors-based) were built in a training cohort and validated in a test cohort. The discrimination, calibration, and clinical usefulness of the models were evaluated. Finally, a subgroup analysis was performed to assess the predictive value of radiomics score in specific hemorrhage location.

RESULTS

Radiomics score was composed of 12 radiomics features. The radiomics model and radiomics nomogram both showed good performance in predicting hematoma enlargement (area under the curve, AUC 0.83 [0.71-0.95], AUC 0.82 [0.72, 0.93]), and were both better than clinical model (AUC 0.66 [0.54-0.79]). The radiomics model and radiomics nomogram showed satisfactory calibration and clinical usefulness for detecting hematoma enlargement. For subgroup analysis, radiomics score also showed good predictive value for hematoma enlargement in different locations (AUC were 0.828, 0.940, 0.836 and 0.904, respectively, for supratentorial, subtentorial, deep and lobes).

CONCLUSION

A radiomics score based on non-contrast CT may be considered as a potential biomarker for prediction of hematoma enlargement in patients with spontaneous intracerebral hemorrhage (SICH), and it presented a high incremental value to clinical factors for hematoma enlargement prediction.

A model comprising the blend sign and black hole sign shows good performance for predicting early intracerebral haemorrhage expansion: a comprehensive evaluation of CT features

OBJECTIVE

To predict early intracerebral haemorrhage expansion (HE) by comprehensive evaluation of commonly used noncontrast computed tomography (NCCT) features.

METHODS

Two hundred eighty-eight patients who had a spontaneous intracerebral haemorrhage (ICH) were included. All of the patients had undergone baseline NCCT within 6 h after ICH symptom onset. Ten NCCT features were extracted. Univariate analysis and multivariable logistic regression analysis were used to select the features. Using the finally selected features, a logistic regression model was built with a training cohort (n = 202) and subsequently validated in an independent test cohort (n = 86). Additionally, stratification analysis was performed in cases with and without anticoagulant therapy.

RESULTS

HE was found in 78 patients (27.1%). The blend sign and black hole sign were finally selected. The logistic regression model built with the two features exhibited accuracies of 76.7% and 75.6%, specificities of 98.6% and 98.4%, and positive predictive values (PPVs) of 83.3% and 75.0% for the training and test cohorts, respectively. The model also showed specificities of 100% and 98.5% and PPVs of 100% and 76.9% for the anticoagulant and non-anticoagulant drug use groups, respectively. These performances were better than those of each of the separate features.

CONCLUSIONS

By comprehensive evaluation, the model comprising the blend sign and black hole sign showed good performance for predicting early intracerebral haemorrhage expansion, particularly for high specificity and PPV, regardless of the anticoagulant status.

KEY POINTS

• Early identification of patients who are more likely to have haematoma expansion is important for therapeutic intervention. • Many radiological features have been reported to correlate with intracerebral haemorrhage expansion. • By integrating only the blend sign and black hole sign, the logistic regression model showed good performance for predicting early intracerebral haemorrhage expansion.

Prediction of hematoma expansion in spontaneous intracerebral hemorrhage: Our institutional experience

BACKGROUND

Spontaneous intracerebral hemorrhage (sICH) is a disease process with high morbidity and mortality. In particular, hematoma expansion (HE) is a feared complication of sICH. With 15-40% of patients experiencing HE, it has become increasingly important to predict which sICH will remain stable and which will expand.

OBJECTIVE

With new treatment options being developed, it is becoming increasingly important to be able to predict which hemorrhages are at high versus low risk for expansion. The authors of this study hope to reexamine variables associated with hematoma expansion in hopes of generating newer data on risk factors for expansion.

METHODS

A retrospective analysis identified 334 patients who presented with sICH. The primary outcome was HE on follow up head CT. HE was defined as a greater than 33% increase or an absolute increase in 6 mL or more in overall volume between the two sets of CT images. Analysis was performed using unpaired t-test, Chi-square, and Fisher's exact tests, as appropriate.

RESULTS

Of the 334 patients, 247 (74.0%) did not experience an expansion of their ICH while 87 (26.0%) did. Multivariable logistic regression was performed demonstrating ICH score of 3 or greater (4.76 (95% CI 2.60-8.72, p < 0.001) , cortical location of the sICH (1.77 (95% CI 1.03-3.04, p = 0.038), and presence of a fluid level (6.46 (95% CI 2.28-18.3, p < 0.001) as significant predictors of HE.

CONCLUSIONS

Our study found that fluid-fluid levels on non-contrast CT, an ICH score 3 or greater, and lobar sICH were all more likely to expand.

Hematoma Expansion in Intracerebral Hemorrhage: An Update on Prediction and Treatment

Intracerebral hemorrhage (ICH) is the most lethal type of stroke, but there is no specific treatment. After years of effort, neurologists have found that hematoma expansion (HE) is a vital predictor of poor prognosis in ICH patients, with a not uncommon incidence ranging widely from 13 to 38%. Herein, the progress of studies on HE after ICH in recent years is updated, and the topics of definition, prevalence, risk factors, prediction score models, mechanisms, treatment, and prospects of HE are covered in this review. The risk factors and prediction score models, including clinical, imaging, and laboratory characteristics, are elaborated in detail, but limited by sensitivity, specificity, and inconvenience to clinical practice. The management of HE is also discussed from bench work to bed practice. However, the upmost problem at present is that there is no treatment for HE proven to definitely improve clinical outcomes. Further studies are needed to identify more accurate predictors and effective treatment to reduce HE.

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.

Analysis of different hematoma expansion shapes caused by different risk factors in patients with hypertensive intracerebral hemorrhage

OBJECTIVE

To elucidate the relationship between the risk factors and hematoma expansion(HE)shapes.

PATIENTS AND METHODS

From February 2013 to November 2018, 60 patients diagnosed as basal ganglia ICH were divided into the filled type hematoma expansion group (FTE group) and the expanded type hematoma expansion group (ETE group). we performed follow-up CT and three-dimensional reconstruction for the patients and compared the hematoma before and after the expansion of size and extent.

RESULTS

The regression analysis showed that the irregular sign (odds ratio, 3.64; 95 % CI, 1.46-9.12), black hole sign (odds ratio, 3.85; 95 % CI, 1.40-10.60), blend sign (odds ratio, 2.86; 95 % CI, 1.03-7.95), and early use of dehydration (odds ratio, 4.59; 95 % CI, 1.59-13.19) were possible risk factors for the ETE group, while the high systolic blood pressure (odds ratio, 1.51; 95 % CI, 1.04-2.30), early use of dehydration (odds ratio, 3.27; 95 % CI, 1.10-9.69) and low density low-density band (odds ratio, 4.52; 95 % CI, 1.54-13.28) were possible risk factors for the FTE group.

CONCLUSIONS

The irregular sign, black hole sign, blend sign and early use of dehydration may be the main risk factors for ETE, whereas early use of dehydration, high systolic blood pressure, and low density low-density band may be the main risk factors for FTE.

Interrater and Intrarater Measurement Reliability of Noncontrast Computed Tomography Predictors of Intracerebral Hemorrhage Expansion

Background and Purpose- Early hematoma expansion after intracerebral hemorrhage is a potentially modifiable predictor of outcome and a promising therapeutic target. Radiological markers seen on noncontrast computed tomography can help predict hematoma expansion and risk stratify patients presenting with intracerebral hemorrhage. Our objective was to assess the interrater and intrarater reliability of 5 commonly reported noncontrast computed tomographic markers of hematoma expansion. Methods- Four readers independently reviewed images from 40 patients from 2 intracerebral hemorrhage imaging databases (PREDICT Collaboration [Predicting Haematoma Growth and Outcome in Intracerebral Haemorrhage Using Contrast Bolus CT] and Massachusetts General Hospital). Readers were blind to all demographic and outcome data and used accepted definitions to establish the presence or absence of intrahematoma hypodensities, blend sign, fluid level, irregular hematoma morphology, and heterogeneous hematoma density. We calculated interrater and intrarater agreement and stratified kappas for the 5 imaging markers. Results- Interrater agreement was excellent for all 5 markers, ranging from 94% to 98%. Interrater kappas ranged from 0.67 to 0.91 (the lowest for fluid level). Interrater agreement had a similar pattern, ranging from 89% to 93%, with Kappas ranging from 0.60 to 0.89. Conclusions- We show that 5 commonly used noncontrast computed tomographic imaging findings all have good-to-excellent interrater and intrarater reliabilities, with the best kappa for blend sign, hypodensities, and heterogeneity.

Association Between Eosinophilic Leukocyte Count and Hematoma Expansion in Acute Spontaneous Intracerebral Hemorrhage

Background/Objective: Hematoma expansion (HE) predicts poor outcome and is an appealing treatment target in spontaneous intracerebral hemorrhage (ICH). Clinical evidence has shown an association of HE with peripheral white blood cells (WBC) count, but the individual contributions of leukocyte subtypes between literatures are described inconsistently. Our aim was to determine the relationship between admission absolute and differential leukocyte counts and HE by using different growth definitions.

Methods: We analyzed spontaneous ICH patients who underwent baseline cranial computed tomography and blood sampling within 6 h of stroke onset in our institution between September 2013 and August 2018. Hematoma volume was calculated using a semiautomated 3-dimensional reconstruction algorithm. According to commonly used absolute or relative growth definitions (>6 mL, >12.5 mL, or >33%), we defined 5 types of HE. A propensity score-matching analysis was performed to evaluate the influence of complete blood count components on HE across the various growth definitions. The receiver operating characteristic analysis assessed the predictive ability of leukocyte counts for HE.

Results: A total of 1,066 patients were included, of whom 11–21% met the 5 HE definitions. After propensity score-matching, except using the definition of >12.5 mL growth or its combination with >33% growth, both WBC and neutrophil count were independently associated with reduced risk of HE (odds ratio [OR] for 10³ cells increase; OR, 0.86–0.99; all p < 0.05) after adjusting confounders in multivariate analyses. However, monocyte count was correlated with increased risk of HE under the usage of >12.5 mL expansion definition only (OR, 1.43; p = 0.024). There was no association between lymphocyte count and HE (all p > 0.05). Regardless of the growth definition, admission eosinophil count was directly associated with the risk of HE (OR, 6.92–31.60; all p < 0.05), and was the best predictive subtype with area under the curve 0.64, sensitivity 69.5%, and specificity 58.9% at the optimal cut-off value of 45 cells/μL.

Conclusions: Growth definition affects the relationship of HE with leukocyte subtypes counting. Eosinophil count robustly predicts HE, and may be a surrogate when using an inflammatory marker to help select acute ICH patients with high expansion risk for hemostasis treatment in clinical trial and practice.

Clinical Features of Nephrotic Syndrome with Cerebral Hemorrhage

Background

Cerebral hemorrhage has been increasingly reported in patients with nephrotic syndrome (NS). However, the clinical features and pathogenesis of NS patients with cerebral hemorrhage remain unclear.

Material/Methods

From January 2007 to August 2017, continuous NS patients with cerebral hemorrhage at the First Affiliated Hospital of Guangxi Medical University were selected. The clinical manifestations, laboratory measurements, and neurological images of these patients were collected and analyzed.

Results

Acute cerebral hemorrhage was recorded in 15 of 10 461 NS patients. The average age of these 15 patients (9 males and 6 females) was 50.87±23.27 years old. Among these 15 patients, conventional vascular risk factors were identified in 8 patients, hypoalbuminemia and proteinuria were recorded in all 15 patients, coagulopathy was observed in 9 patients, increased D-dimer level was recorded in 13 patients, hyperlipidemia was recorded in 11 patients, and impaired renal function was recorded in 9 patients. The hemorrhage developed in the lobe (n=9), basal ganglia (n=3), cerebellum (n=2), and cerebral hemisphere (n=1). Eight patients were in a coma on the day the cerebral hemorrhage occurred, while 12 patients had a poor prognosis after 30 days of hemorrhage onset.

Conclusions

Poor prognosis was recorded in NS patients with cerebral hemorrhage. Although conventional vascular risk factors have only been identified in 8 patients, biochemical abnormalities (hypoalbuminemia, proteinuria, elevated D-dimer, and hyperlipidemia) were recorded in the majority of these 15 patients. Furthermore, most of the hemorrhages developed in the lobes. Coagulopathy might be the potential pathogenesis of cerebral hemorrhage in NS patients.