Intracerebral Hemorrhage Expansion Research Articles

Effects of Achieving Rapid, Intensive, and Sustained Blood Pressure Reduction in Intracerebral Hemorrhage Expansion and Functional Outcome.

The time taken to achieve blood pressure (BP) control could be pivotal in the benefits of reducing BP in acute intracerebral hemorrhage (ICH). We aimed to assess the relationship between the rapid achievement and sustained maintenance of an intensive systolic BP (SBP) target with radiologic, clinical, and functional outcomes. Rapid, Intensive, and Sustained BP lowering in Acute ICH (RAINS) was a multicenter, prospective, observational cohort study of adult patients with ICH <6 hours and SBP ≥150 mm Hg at 4 Comprehensive Stroke Centers during a 4.5-year period. Patients underwent baseline and 24-hour CT scans and 24-hour noninvasive BP monitoring. BP was managed under a rapid (target achievement ≤60 minutes), intensive (target SBP <140 mm Hg), and sustained (target stability for 24 hours) BP protocol. SBP target achievement ≤60 minutes and 24-hour SBP variability were recorded. Outcomes included hematoma expansion (>6 mL or >33%) at 24 hours (primary outcome), early neurologic deterioration (END, 24-hour increase in NIH Stroke Scale score ≥4), and 90-day ordinal modified Rankin scale (mRS) score. Analyses were adjusted by age, sex, anticoagulation, onset-to-imaging time, ICH volume, and intraventricular extension. We included 312 patients (mean age 70.2 ± 13.3 years, 202 [64.7%] male). Hematoma expansion occurred in 70/274 (25.6%) patients, END in 58/291 (19.9%), and the median 90-day mRS score was 4 (interquartile range, 2-5). SBP target achievement ≤60 minutes (178/312 [57.1%]) associated with a lower risk of hematoma expansion (adjusted odds ratio [aOR] 0.43, 95% confidence interval [CI] 0.23-0.77), lower END rate (aOR 0.43, 95% CI 0.23-0.80), and lower 90-day mRS scores (aOR 0.48, 95% CI 0.32-0.74). The mean 24-hour SBP variability was 21.0 ± 7.6 mm Hg. Higher 24-hour SBP variability was not related to expansion (aOR 0.99, 95% CI 0.95-1.04) but associated with higher END rate (aOR 1.15, 95% CI 1.09-1.21) and 90-day mRS scores (aOR 1.06, 95% CI 1.04-1.10). Among patients with acute ICH, achieving an intensive SBP target within 60 minutes was associated with lower hematoma expansion risk. Rapid SBP reduction and stable sustention within 24 hours were related to improved clinical and functional outcomes. These findings warrant the design of randomized clinical trials examining the impact of effectively achieving rapid, intensive, and sustained BP control on hematoma expansion. This study provides Class III evidence that in adults with spontaneous ICH and initial SBP ≥150 mm Hg, lowering SBP to <140 mm Hg within the first hour and maintaining this for 24 hours is associated with decreased hematoma expansion.

Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach.

Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its proper treatment are of great significance in curbing the deterioration and improving the prognosis of patients with ICH. This study aimed to develop an automated hybrid approach to predict hematoma expansion in ICH. The transfer learning method was applied to build a hybrid model based on a convolutional neural network (CNN) to predict the expansion of hematoma. The model integrated (1) a CNN for automated hematoma segmentation and (2) a CNN-based classifier for hematoma expansion prediction that incorporated both 2-dimensional images and the radiomics features of the 3-dimensional hematoma shape. The radiomics feature module had the highest area under the receiver operating characteristic curve (AUC) of 0.58, a precision of 0, a recall of 0, and an average precision (AP) of 0.26. The ResNet50 and Inception_v3 modules had AUCs of 0.79 and 0.93, a precision of 0.56 and 0.86, a recall of 0.42 and 0.75, and an AP of 0.51 and 0.85, respectively. Radiomic with Inception_v3 and Radiomic with ResNet50 had AUCs of 0.95 and 0.81, a precision of 0.90 and 0.57, a recall of 0.79 and 0.17, and an AP of 0.87 and 0.69, respectively. A model using deep learning and radiomics was successfully developed. This model can reliably predict the hematoma expansion of ICH with a fully automated process based on non-contrast computed tomography imaging. Furthermore, the radiomics fusion with the Inception_v3 model had the highest accuracy.

Predictors of severe intracerebral hemorrhage expansion

Predictors of severe intracerebral hemorrhage expansion

CT-based radiomics models predict spontaneous intracerebral hemorrhage expansion and are comparable with CT angiography spot sign.

This study aimed to investigate the efficacy of radiomics, based on non-contrast computed tomography (NCCT) and computed tomography angiography (CTA) images, in predicting early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (SICH). Additionally, the predictive performance of these models was compared with that of the established CTA spot sign. A retrospective analysis was conducted using CT images from 182 patients with SICH. Data from the patients were divided into a training set (145 cases) and a testing set (37 cases) using random stratified sampling. Two radiomics models were constructed by combining quantitative features extracted from NCCT images (the NCCT model) and CTA images (the CTA model) using a logistic regression (LR) classifier. Additionally, a univariate LR model based on the CTA spot sign (the spot sign model) was established. The predictive performance of the two radiomics models and the spot sign model was compared according to the area under the receiver operating characteristic (ROC) curve (AUC). For the training set, the AUCs of the NCCT, CTA, and spot sign models were 0.938, 0.904, and 0.726, respectively. Both the NCCT and CTA models demonstrated superior predictive performance compared to the spot sign model (all P < 0.001), with the performance of the two radiomics models being comparable (P = 0.068). For the testing set, the AUCs of the NCCT, CTA, and spot sign models were 0.925, 0.873, and 0.720, respectively, with only the NCCT model exhibiting significantly greater predictive value than the spot sign model (P = 0.041). Radiomics models based on NCCT and CTA images effectively predicted HE in patients with SICH. The predictive performances of the NCCT and CTA models were similar, with the NCCT model outperforming the spot sign model. These findings suggest that this approach has the potential to reduce the need for CTA examinations, thereby reducing radiation exposure and the use of contrast agents in future practice for the purpose of predicting hematoma expansion.

Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan

Hematoma expansion (HE) is a modifiable risk factor and a potential treatment target in patients with intracerebral hemorrhage (ICH). We aimed to train and validate deep-learning models for high-confidence prediction of supratentorial ICH expansion, based on admission non-contrast head Computed Tomography (CT). Applying Monte Carlo dropout and entropy of deep-learning model predictions, we estimated the model uncertainty and identified patients at high risk of HE with high confidence. Using the receiver operating characteristics area under the curve (AUC), we compared the deep-learning model prediction performance with multivariable models based on visual markers of HE determined by expert reviewers. We randomly split a multicentric dataset of patients (4-to-1) into training/cross-validation (n = 634) versus test (n = 159) cohorts. We trained and tested separate models for prediction of ≥6 mL and ≥3 mL ICH expansion. The deep-learning models achieved an AUC = 0.81 for high-confidence prediction of HE≥6 mL and AUC = 0.80 for prediction of HE≥3 mL, which were higher than visual maker models AUC = 0.69 for HE≥6 mL (p = 0.036) and AUC = 0.68 for HE≥3 mL (p = 0.043). Our results show that fully automated deep-learning models can identify patients at risk of supratentorial ICH expansion based on admission non-contrast head CT, with high confidence, and more accurately than benchmark visual markers.

Abstract TMP81: Effect of Post Thrombolytic Intracerebral Hemorrhage Volume on 90-day Outcomes in Acute Ischemic Stroke Patients

Background and Purpose: Post thrombolytic intracerebral hemorrhage (ICH) is associated with higher rate of death or disability in acute ischemic stroke patients. We investigated the relationship between post thrombolytic ICH volume and change in volume and death or disability at 90 days in acute ischemic stroke patients. Methods: We analyzed 110 patents recruited in the Safety Evaluation of 3K3A-APC in Ischemic Stroke (RHAPSODY) trial who received intravenous tissue plasminogen activator (tPA) followed by mechanical thrombectomy (if indicated) and 3K3A-APC or placebo. ICH volume was measured at Day 2 and Day 7 using susceptibility weighted sequence (SWI) on magnetic resonance imaging (MRI). We also calculated the post thrombolytic ICH volume change between Day 2 and Day 7. Outcomes were determined by using utility weighted modified Rankin scale (UW-mRs) at 90-days. We adjusted for age, gender, National Institute of Health Stroke Scale (NIHSS) score (&lt;10,10-19 and ≥20), location of hemorrhage (single basal ganglia hemorrhage, single lobar, single cerebellum, and multiple sites hemorrhage) in multivariate regression analysis. Results: A total of 88 (80%) of 110 patients had post thrombolytic ICH (mean volume 28.3 ml ± SD 62ml). The strata of ICH volume were not associated with UW-mRs at 90 days: &lt;20 cc (regression coefficient-0.05, p= 0.58), 20-39 cc (-0.23, p=0.15), or 40 cc (-0.33, p= 0.086) compared with no ICH after adjusting for potential confounders. Change in ICH volume mean volume 27.43ml ±59.01, 52 had increase in volume) between Day 2 and day 7 was not associated with UW-mRS at 90 days (regression coefficient -11.87, p= 0.796). Conclusions: We did not observe any independent effect of post thrombolytic ICH volume on death or disability in acute ischemic stroke patients. Strategies to prevent ICH expansion such as antifibrinolytic medications and reduction in ICH volume such as surgical evacuation may not reduce death or disability in acute ischemic stroke patients with post thrombolytic ICH.

Is the frequency of imaging markers still a predictor for revised intracerebral hemorrhage expansion?

Frequency of imaging markers (FIM) has been described as a novel predictor for hematoma expansion after intracerebral hemorrhage (ICH). A revised definition of hematoma expansion that incorporates intraventricular hemorrhage (IVH) growth, that is, revised hematoma expansion (RHE), has also been proposed. Nevertheless, the associations between FIM and IVH growth or RHE remains unexplored. The objective of this study was to assess the influence and performance of the FIM on two types. Patient selection and variables were based on our published protocol. FIM was defined as the ratio of the number of imaging markers to the onset-to-neuroimaging time. The association between FIM and two definitions was tested by multivariate analysis. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the FIM on two definitions were also evaluated. There were 303 (20.36%) and 583 (39.18%) subjects in the IVH growth and RHE, respectively. Multivariate analysis demonstrated that FIM was associated with both IVH growth and RHE (odds ratio [OR] = 1.96, 95% confidence interval [CI] = 1.60-2.39; OR = 15.01, 95% CI = 10.51-21.43, respectively). The optimal cutoff points for FIM to predict IVH growth and RHE were 0.63 and 0.62, with AUC, sensitivity, specificity, PPV, and NPV of 0.66, 0.50, 0.78, 0.36, and 0.86 versus 0.80, 0.60, 0.93, 0.84, and 0.78, respectively. FIM was not only a predictor of IVH growth, but also of RHE. These findings may have important clinical implications for decision-making based on risk stratification of patients with ICH.

Analysis of the diagnostic informativity of non-contrast computed tomography markers of intracerebral hemorrhage expansion in assessment of the individual risk of early neurological deterioration in patients with hemorrhagic hemispheric stroke

The aim of the study was to evaluate the diagnostic informativity of non-contrast computed tomography (NCCT) markers of intracerebral hemorrhage (ICH) expansion in assessment of the individual risk of early neurological deterioration (END) in patients with hemorrhagic hemispheric stroke (HHS). Materials and methods. A prospective, cohort study was conducted involving 333 patients in the acute period of hypertensive spontaneous supratentorial ICH on the background of conservative therapy. The level of neurological deficit was assessed using the Full Outline of Unresponsiveness (FOUR) coma scale and the National Institute of Health Stroke Scale (NIHSS). The computed tomography of the brain was used to verify the ICH volume, the midline shift (MS), the secondary intraventricular hemorrhage volume (IVHV) and NCCT markers of intracerebral hemorrhage expansion. As a combined clinical endpoint, END was considered (decrease of the FOUR scale score ≥2 or/and increase of the NIHSS score ≥4 or/and lethal outcome within 48 hours of hospitalization). Results. Early neurological deterioration was registered in 112 patients. On the basis of a comparative analysis, it was established that the specific weight of END was significantly higher in subcohorts of patients with individual NCCT markers of intracerebral hemorrhage expansion, than it was in subcohorts of patients without corresponding NCCT signs (p ˂ 0.0001). It was established that the following NCCT markers of ICH expansion are the most sensitive predictors of END: hypodensity, swirl sign and irregular shape (sensitivity &gt;90.0 %). The most specific NCCT markers were island sign, black hole sign, blend sign, satellite sign and heterogeneous density (specificity &gt;87.0 %). In accordance with the multiple logistic regression analysis, hypodensity (OR (95 % CI) = 13.56 (4.54–40.49), p &lt; 0.0001) and island sign (OR (95 % CI) = 5.94 (2.05–17.16), p = 0.0010) are independently associated with the risk of END. A highly sensitive multi-prediction logistic regression model was elaborated in order to predict END in patients with HHS which takes into account the most informative NCCT markers of ICH expansion (hypodensity, island sign) and quantitative neuroimaging indicators (MS, IVHV) (AUC ± SE (95 % CI) = 0.92 ± 0.02 (0.89–0.95), р ˂ 0.0001). Conclusions. Non-contrast computed tomography markers of ICH expansion are associated with increased risk of END in patients with HHS. Hypodensity and island sign are independent predictors of END. The integration of NCCT markers of ICH expansion with quantitative neuroimaging indicators (MS, IVHV) in the structure of the multi-prediction logistic regression model allows to assess the individual risk of END with an accuracy of &gt;85.0 %.

Glibenclamide pretreatment attenuates early hematoma expansion of warfarin-associated intracerebral hemorrhage in rats by alleviating perihematomal blood–brain barrier dysfunction

BackgroundHematoma expansion is a determinant of poor outcome of intracerebral hemorrhage but occurs frequently, especially in warfarin-associated intracerebral hemorrhage (W-ICH). In the present study, we employ the warfarin-associated intracerebral hemorrhage (W-ICH) rat model, to explore the efficacy and potential mechanism of glibenclamide pretreatment on hematoma expansion after intracerebral hemorrhage, hoping to provide proof of concept that glibenclamide in stroke primary and secondary prevention is also potentially beneficial for intracerebral hemorrhage patients at early stage.MethodsIn the present study, we tested whether glibenclamide, a common hypoglycemic drug, could attenuate hematoma expansion in a rat model of W-ICH. Hematoma expansion was evaluated using magnetic resonance imaging; brain injury was evaluated by brain edema and neuronal death; and functional outcome was evaluated by neurological scores. Then blood–brain barrier integrity was assessed using Evans blue extravasation and tight junction-related protein.ResultsThe data indicated that glibenclamide pretreatment significantly attenuated hematoma expansion at 24 h after W-ICH, thus mitigating brain edema and neuronal death and promoting neurological function recovery, which may benefit from alleviating blood–brain barrier disruption by suppressing matrix metallopeptidase-9.ConclusionsThe results indicate that glibenclamide pretreatment in stroke primary and secondary prevention might be a promising therapy for hematoma expansion at the early stage of W-ICH.

Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomography.

Aimed to develop a nomogram model based on deep learning features and radiomics features for the prediction of early hematoma expansion. A total of 561 cases of spontaneous intracerebral hemorrhage (sICH) with baseline Noncontrast Computed Tomography (NCCT) were included. The metrics of hematoma detection were evaluated by Intersection over Union (IoU), Dice coefficient (Dice), and accuracy (ACC). The semantic features of sICH were judged by EfficientNet-B0 classification model. Radiomics analysis was performed based on the region of interest which was automatically segmented by deep learning. A combined model was constructed in order to predict the early expansion of hematoma using multivariate binary logistic regression, and a nomogram and calibration curve were drawn to verify its predictive efficacy by ROC analysis. The accuracy of hematoma detection by segmentation model was 98.2% for IoU greater than 0.6 and 76.5% for IoU greater than 0.8 in the training cohort. In the validation cohort, the accuracy was 86.6% for IoU greater than 0.6 and 70.0% for IoU greater than 0.8. The AUCs of the deep learning model to judge semantic features were 0.95 to 0.99 in the training cohort, while in the validation cohort, the values were 0.71 to 0.83. The deep learning radiomics model showed a better performance with higher AUC in training cohort (0.87), internal validation cohort (0.83), and external validation cohort (0.82) than either semantic features or Radscore. The combined model based on deep learning features and radiomics features has certain efficiency for judging the risk grade of hematoma. Our study revealed that the deep learning model can significantly improve the work efficiency of segmentation and semantic feature classification of spontaneous intracerebral hemorrhage. The combined model has a good prediction efficiency for early hematoma expansion. • We employ a deep learning algorithm to perform segmentation and semantic feature classification of spontaneous intracerebral hemorrhage and construct a prediction model for early hematoma expansion. • The deep learning radiomics model shows a favorable performance for the prediction of early hematoma expansion. • The combined model holds the potential to be used as a tool in judging the risk grade of hematoma.

Activated Prothrombin Complex Concentrates for the Treatment of Factor Xa Inhibitor-Associated Spontaneous Intracerebral Hemorrhage

Background: Anticoagulant-associated intracerebral hemorrhage (ICH) is a significant cause of morbidity and mortality. Despite approval of a specific reversal agent for factor Xa inhibitors, there is still much interest in nonspecific reversal agents, such as activated prothrombin complex concentrates (aPCCs). Objective: The objective of this study was to describe ICH expansion in a cohort of patients with factor Xa inhibitor-associated ICH who were treated with aPCC. Methods: This was a retrospective cohort study conducted at an academic medical center designated as a comprehensive stroke center. Consecutive patients admitted for ICH who reported use of apixaban or rivaroxaban prior to admission were considered for inclusion in the study. Patients were treated with 25 to 50 units/kg of aPCC. Intracerebral hemorrhage volume was measured before administration of aPCC and then again within 36 hours of aPCC administration. Results: A total of 40 patients were included in the final analysis. Overall, the cohort was predominantly male (24 [60%]), white (27 [67.5%]), and the mean age was 75.3 ± 10.5 years. Most patients reported taking apixaban prior to admission (31 [77.5%]) and a large proportion were also taking aspirin (13 [32.5%]). The mean change in ICH volume was 1.12 ± 6.03 mL ( P = 0.2475). Conclusions and Relevance: There was a nonsignificant change in mean ICH volume and no reported cases of thromboembolism. Due to the relatively high proportion of patients with significant hematoma expansion, more studies are needed on which patient population would best benefit from treatment with aPCC.

Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers.

To devise and validate radiomic signatures of impending hematoma expansion (HE) based on admission non-contrast head computed tomography (CT) of patients with intracerebral hemorrhage (ICH). Utilizing a large multicentric clinical trial dataset of hypertensive patients with spontaneous supratentorial ICH, we developed signatures predictive of HE in a discovery cohort (n = 449) and confirmed their performance in an independent validation cohort (n = 448). In addition to n = 1,130 radiomic features, n = 6 clinical variables associated with HE, n = 8 previously defined visual markers of HE, the BAT score, and combinations thereof served as candidate variable sets for signatures. The area under the receiver operating characteristic curve (AUC) quantified signatures' performance. A signature combining select radiomic features and clinical variables attained the highest AUC (95% confidence interval) of 0.67 (0.61-0.72) and 0.64 (0.59-0.70) in the discovery and independent validation cohort, respectively, significantly outperforming the clinical (pdiscovery = 0.02, pvalidation = 0.01) and visual signature (pdiscovery = 0.03, pvalidation = 0.01) as well as the BAT score (pdiscovery < 0.001, pvalidation < 0.001). Adding visual markers to radiomic features failed to improve prediction performance. All signatures were significantly (p < 0.001) correlated with functional outcome at 3-months, underlining their prognostic relevance. Radiomic features of ICH on admission non-contrast head CT can predict impending HE with stable generalizability; and combining radiomic with clinical predictors yielded the highest predictive value. By enabling selective anti-expansion treatment of patients at elevated risk of HE in future clinical trials, the proposed markers may increase therapeutic efficacy, and ultimately improve outcomes.

Predictors Of Outcome In ICH Patients Initially Admitted To The ICU Who Are Transferred To Inpatient Rehab (P5-7.002)

<h3>Objective:</h3> Assess factors associated with good functional outcomes after ICH requiring ICU admission. <h3>Background:</h3> Intracerebral hemorrhage (ICH) is associated with high mortality, with patients requiring intensive care unit (ICU) admission having worse outcomes. However, current scores are limited in their ability to predict functional outcomes. <h3>Design/Methods:</h3> We collected data using a prospectively maintained registry of stroke patients admitted to 5 inpatient rehabs (IR)s in our hospital system between 1/2018 to 6/2019. We performed predictive modeling with RIDGE regression analysis to predict the rehab discharge motor functional independence measure (FIM). Variables used to perform predictive modeling included age, ICU length of stay (LOS), concurrent IVH, ICH expansion, decompressive surgery, laterality of ICH, symptom onset to rehab admission, rehab admission motor FIM score, initial NIHSS, and total therapy days. <h3>Results:</h3> We identified 166 patients with ICH admitted to IR, of which a significant number (51%) were initially admitted to the ICU. After excluding patients with incomplete variables, 61 patients were included in the model. The median age was 59[47–71] years, and 44% were female. The median initial NIHSS was 12 [5–18], and the length of stay in the ICU was 6 [3–10] days. 34 (55.7%) of the patient had IVH, and 7 (11.5%) had hematoma expansion. 7 (11.5%) needed decompressive surgery. The median admit motor FIM score was 24 [17–36], and after a median of 14 [14–14] days in IR, the median discharge motor FIM score more than doubled to 58 [46–69]. Our predictive model had an r-squared of 0.65. Decompressive surgery patients had better scores by 4 points than patients without decompressive surgery. As therapy days increase by one day, discharge motor FIM scores increase by approximately 2 points. <h3>Conclusions:</h3> Our model can satisfactorily predict rehab discharge motor FIM. However, additional factors involved in the process will be explored to improve the model. <b>Disclosure:</b> Dr. Ahmad has nothing to disclose. Dr. Tariq has nothing to disclose. Christin Silos has nothing to disclose. Ms. Hernandez has nothing to disclose. Ms. Contreras has nothing to disclose. Dr. Savitz has nothing to disclose.

Derivation and validation of three intracerebral hemorrhage expansion scores using different CT modalities.

To derivate and validate three scores for the prediction of intracerebral hemorrhage (ICH) expansion depending on the use of non-contrast CT (NCCT), single-phase CTA, or multiphase CTA markers of hematoma expansion, and to evaluate the added value of single-phase and multiphase CTA over NCCT. After prospectively deriving NCCT, single-phase CTA, and multiphase CTA hematoma expansion scores in 156 patients with ICH < 6h, we validated them in 120 different patients. Discrimination and calibration of the three scores was assessed. Primary outcome was substantial hematoma expansion > 6mL or > 33% at 24h. The evaluation of single-phase and multiphase CTA markers gave a steadily increase in discrimination for substantial hematoma expansion over NCCT markers. The C-index (95% confidence interval) in derivation and validation cohorts was 0.69 (0.58-0.80) and 0.59 (0.46-0.72) for NCCT score, significantly lower than 0.75 ([0.64-0.87], p = 0.038) and 0.72 ([0.59-0.84], p = 0.016) for single-phase CTA score, and than 0.79 ([0.68-0.89], p = 0.033) and 0.73 ([0.62-0.85], p = 0.031) for multiphase CTA score, respectively. The three scores showed good calibration in both derivation and validation cohorts: NCCT (χ2 statistic 0.389, p = 0.533; and χ2 statistic 0.352, p = 0.553), single-phase CTA (χ2 statistic 2.052, p = 0.359; and χ2 statistic 2.230, p = 0.328), and multiphase CTA (χ2 statistic 0.559, p = 0.455; and χ2 statistic 0.020, p = 0.887) scores, respectively. This study shows the added prognostic value of more advanced CT modalities in acute ICH evaluation. NCCT, single-phase CTA, and multiphase CTA scores may help to refine the selection of patients at risk of expansion in different decision-making scenarios. • This study shows the added prognostic value of more advanced CT modalities in acute intracerebral hemorrhage evaluation. • The evaluation of single-phase and multiphase CTA markers provides a steadily increase in discrimination for intracerebral hemorrhage expansion over non-contrast CT markers. • Non-contrast CT, single-phase CTA, and multiphase CTA scores may help clinicians and researchers to refine the selection of patients at risk of intracerebral hemorrhage expansion in different decision-making scenarios.

Abstract HUP19: Sex Differences In Incidence Of Intraventricular Hemorrhage And Hydrocephalus In Patients With Non-traumatic Intracerebral Hemorrhage

Introduction: Non-traumatic Intracerebral Hemorrhage (ICH) accounts for 2 million strokes annually worldwide. This stroke burden disproportionately impacts minorities, and results in severe neurological deficits. Sex differences in brain structure and function, such as a larger mean length of frontal horn in males and increased global cerebral blood flow in women, can contribute to hematoma volume and expansion of ICH into nearby structures. No studies have yet to investigate sex differences in the incidence of Intraventricular Hemorrhage (IVH) and hydrocephalus as sequelae of ICH, both or which correlate with poor long-term outcomes. Methods: A retrospective review of a comprehensive stroke center spontaneous ICH database from 2019-2022 was performed, including patient characteristics such as history of diabetes mellitus, hypertension, coronary artery disease, tobacco use, and anticoagulant use in addition to ICH characteristics such as hematoma location volume, expansion, incidence of IVH and hydrocephalus. A logistic regression model controlling for these covariates was built to investigate sex differences in incidence of IVH and hydrocephalus. Results: This cohort had 100 patients with spontaneous, non-traumatic ICH, of which 39% were female. Overall, 52/100 (52%) patients had IVH and 21/100 (21%) patients developed hydrocephalus. Among males, 29/61(48%) had IVH as opposed to 23/39 (59%) in females, p = 0.264. There was similar development of hydrocephalus in both males 13/61(21%) and females 8/39 (21%). Logistic regression showed females had higher odds of IVH. Higher diastolic blood pressure and anticoagulant use on admission also had higher odds of IVH. Conclusion: This pilot study demonstrates a trend towards higher incidence of IVH among females when controlling for history of diabetes mellitus, hypertension, coronary artery disease, tobacco use, and anticoagulant use. Higher odds of IVH in patients with higher diastolic blood pressure on admission adds to the previously investigated association between systolic blood pressure and ICH hematoma volume. Our sample validated the higher odds of IVH in patients with anticoagulant use on admission.

Abstract TP120: Noncontrast Ct, Single-phase Cta, And Multiphase Cta Intracerebral Hemorrhage Expansion Scores

Background: Several noncontrast computed tomography (NCCT), single-phase computed tomography angiography (CTA), and multiphase CTA markers of intracerebral hemorrhage (ICH) expansion have been previously proposed. We derived and validated three scores for the prediction of hematoma expansion depending on the use of NCCT, single-phase CTA, or multiphase CTA markers of hematoma expansion. Methods: We prospective studied 276 consecutive patients with ICH within 6 hours from symptom onset. After deriving NCCT, single-phase CTA, and multiphase CTA scores in a 5-year period population (n=156), we validated them in a different 3-year period population (n=120). Outcome parameters included substantial hematoma expansion &gt;6 mL or &gt;33% at 24 hours (primary outcome) and poor outcome (mRS score &gt;2) at 90 days. Results: The most accurate marker of hematoma expansion was spot sign in phase 1 of multiphase CTA (80.3%). The four independent predictors of substantial hematoma expansion included in the different scores were ultraearly hematoma growth (uHG) &gt;5 mL/h, heterogeneous density, spot sign in phase 1 of multiphase CTA, and spot sign in any phase of multiphase CTA (Table). On each of the three scores, the proportion of patients that experienced substantial hematoma expansion increased with each point increase. C-index for both substantial hematoma expansion and poor outcome in the derivation and validation cohort was lower in NCCT expansion score than in single-phase CTA expansion score which, in turn, was lower than in multiphase CTA expansion score (Table). Conclusions: This study demonstrates the added prognostic value of more advanced CT modalities in acute ICH evaluation. Single-phase CTA score and, especially, multiphase CTA score, are more robust than NCCT score in the prediction of hematoma expansion and poor outcome. These scores may help to refine the selection of patients at risk of expansion and poorest outcomes in different decision-making scenarios.

Using Noncontrast Computed Tomography to Improve Prediction of Intracerebral Hemorrhage Expansion.

Noncontrast computed tomography hypodensities are a validated predictor of hematoma expansion (HE) in intracerebral hemorrhage and a possible alternative to the computed tomography angiography (CTA) spot sign but their added value to available prediction models remains unclear. We investigated whether the inclusion of hypodensities improves prediction of HE and compared their added value over the spot sign. Retrospective analysis of patients admitted for primary spontaneous intracerebral hemorrhage at the following 8 university hospitals in Boston, US (1994-2015, prospective), Hamilton, Canada (2010-2016, retrospective), Berlin, Germany (2014-2019, retrospective), Chongqing, China (2011-2015, retrospective), Pavia, Italy (2017-2019, prospective), Ferrara, Italy (2010-2019, retrospective), Brescia, Italy (2020-2021, retrospective), and Bologna, Italy (2015-2019, retrospective). Predictors of HE (hematoma growth >6 mL and/or >33% from baseline to follow-up imaging) were explored with logistic regression. We compared the discrimination of a simple prediction model for HE based on 4 predictors (antitplatelet and anticoagulant treatment, baseline intracerebral hemorrhage volume, and onset-to-imaging time) before and after the inclusion of noncontrast computed tomography hypodensities, using receiver operating characteristic curve and De Long test for area under the curve comparison. A total of 2465 subjects were included, of whom 664 (26.9%) had HE and 1085 (44.0%) had hypodensities. Hypodensities were independently associated with HE after adjustment for confounders in logistic regression (odds ratio, 3.11 [95% CI, 2.55-3.80]; P<0.001). The inclusion of noncontrast computed tomography hypodensities improved the discrimination of the 4 predictors model (area under the curve, 0.67 [95% CI, 0.64-0.69] versus 0.71 [95% CI, 0.69-0.74]; P=0.025). In the subgroup of patients with a CTA available (n=895, 36.3%), the added value of hypodensities remained statistically significant (area under the curve, 0.68 [95% CI, 0.64-0.73] versus 0.74 [95% CI, 0.70-0.78]; P=0.041) whereas the addition of the CTA spot sign did not provide significant discrimination improvement (area under the curve, 0.74 [95% CI, 0.70-0.78]). Noncontrast computed tomography hypodensities provided a significant added value in the prediction of HE and appear a valuable alternative to the CTA spot sign. Our findings might inform future studies and suggest the possibility to stratify the risk of HE with good discrimination without CTA.

Surface regularity: A new factor for predicting the expansion of intracerebral hemorrhage?

BackgroundThe radiology features of CT can be used to predict the development of hemorrhage. Purpose: To explore the relationship between regularity and the expansion of hematoma by using a novel factor: surface regulation. Methods: This is a retrospective study, where 213 patients (71 females, 33.3 %) are retrospectively analyzed. The inclusion criteria are as follows. The diagnosis of spontaneous supratentorial hemorrhage, admission CT scan and a cranial CT scan obtained within 9 h are required, with other potential causes of intracerebral hemorrhage excluded during hospitalization. The exclusion criteria are as follows. Any patients having operative treatment before the cranial CT scan are excluded. Then, they are divided into the hematoma expansion group based on expanded hematoma (relative growth ≥ 33 % or absolute growth ≥ 6 ml) and the non-hematoma expansion group. After other factors are balanced through a 1:2 PS match, 82 samples (31 females, 37.8 %) are modeled to calculate their surface area and volume by using 3D Slicer and their surface regularity [SR=6√πvolume√surfacearea3]. Results: The mean ± SD SR value of Group-HE is calculated to be 0.557 ± 0.131, while that of Group-NHE is calculated to be 0.631 ± 0.101. The effect of surface regulation on the expansion of intracerebral hemorrhage hematoma is found to be statistically significant (OR 0.004, 95 %CI 0.00–0.27, P = 0.011). Conclusions: There is a link between surface regularity and hematoma expansion during the early stages of intracerebral hemorrhage.

The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage.

Among patients undergoing head computed tomography (CT) scans within 3 h of spontaneous intracerebral hemorrhage (sICH), 28% to 38% have hematoma expansion (HE) on follow-up CT. This study aimed to predict HE using radiomics analysis and investigate the impact of intraventricular hemorrhage (IVH) compared with the conventional approach based on intraparenchymal hemorrhage (IPH) alone. This retrospective study enrolled 127 patients with baseline and follow-up non-contrast CT (NCCT) within 4~72 h of sICH. IPH and IVH were outlined separately for performing radiomics analysis. HE was defined as an absolute hematoma growth &gt; 6 mL or percentage growth &gt; 33% of either IPH (HEP) or a combination of IPH and IVH (HEP+V) at follow-up. Radiomic features were extracted using PyRadiomics, and then the support vector machine (SVM) was used to build the classification model. For each case, a radiomics score was generated to indicate the probability of HE. There were 57 (44.9%) HEP and 70 (55.1%) non-HEP based on IPH alone, and 58 (45.7%) HEP+V and 69 (54.3%) non-HEP+V based on IPH + IVH. The majority (&gt;94%) of HE patients had poor early outcomes (death or modified Rankin Scale &gt; 3 at discharge). The radiomics model built using baseline IPH to predict HEP (RMP) showed 76.4% accuracy and 0.73 area under the ROC curve (AUC). The other model using IPH + IVH to predict HEP+V (RMP+V) had higher accuracy (81.9%) with AUC = 0.80, and this model could predict poor outcomes. The sensitivity/specificity of RMP and RMP+V for HE prediction were 71.9%/80.0% and 79.3%/84.1%, respectively. The proposed radiomics approach with additional IVH information can improve the accuracy in prediction of HE, which is associated with poor clinical outcomes. A reliable radiomics model may provide a robust tool to help manage ICH patients and to enroll high-risk ICH cases into anti-expansion or neuroprotection drug trials.

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.

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. 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 24h 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. 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). 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.