Background and objectivesThis study investigates whether ultra-early follow-up imaging can reliably identify patients at risk for hematoma expansion (HE) in acute intracerebral hemorrhage (ICH).MethodsIn this multicenter study, we analyzed data from patients with primary ICH who underwent at least two non-contrast cranial computed tomography (NCCT) scans within 7 days of symptom onset or last known well. To define the optimal time window, hematoma growth dynamics were retrospectively assessed in a large cohort (n = 1,663). Based on these findings, a prospective sub-study included patients with repeated imaging within 200 min (n = 46). HE was defined as >6 mL or >33% volume increase between the admission and the second follow-up scan. The diagnostic performance of early volume increase was evaluated using receiver operating characteristic (ROC) analysis.ResultsThe highest proportion of patients with active hemorrhage was detected within the first 200 min in the initial phase of this study. In the prospective sub-study, percentage volume increase between admission and early follow-up imaging demonstrated excellent diagnostic performance for HE (AUC = 0.819). At an optimized cutoff, the model yielded a sensitivity of 0.885 and a positive predictive value (PPV) of 74%. Among patients with early expansion already visible at follow-up, 50% showed further volume increase on the final scan. A separate analysis limited to follow-up imaging within the first 120 min after symptom onset (n = 27) revealed a higher diagnostic accuracy, with an AUC of 0.846 (sensitivity 0.857; PPV 71%).ConclusionICH evolves rapidly in the first hours after onset. Follow-up imaging within the first 200 min can diagnose hematoma growth with high sensitivity and good accuracy. However, the inability to distinguish between ongoing and completed expansion underscores the need for additional imaging or clinical markers to support clinical decisions.

Background:The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is widely established to assess early ischemic changes on non-contrast computed tomography (NCCT) and guide treatment decisions in acute stroke. While automated ASPECTS tools are increasingly available, independent validation and the potential influence on human ratings remain important. The aim of this study was to evaluate agreement between an automated ASPECTS scoring system and expert readers and to examine whether software assistance was associated with a systematic shift in human ASPECTS scoring. Methods:We implemented an automated ASPECTS scoring system, incorporating image normalization, anatomical registration, and regional intensity analysis through hemispheric comparisons of net water uptake (NWU) values. A total of 224 cases were retrospectively analyzed. We included two expert unassisted readers (U1-2; reference reader group) and four software-assisted readers (A1-4). Agreement was assessed using intraclass correlation coefficient (ICC), mean difference (MD), mean absolute difference (MAD), and the distribution of absolute score differences (Δ=0/1/2/≥3). Unassisted vs assisted scores were compared using a Wilcoxon rank-sum test. Analyses were performed using two bootstrapped stratifications (approximately uniform and clinically representative). Results:Inter-rater agreement within the unassisted and assisted reader groups was high (uniform: unassisted ICC 0.96, MAD 0.65; assisted ICC 0.95, MAD 0.66; clinical: unassisted ICC 0.91, MAD 0.83; assisted ICC 0.88, MAD 0.89). Agreement between unassisted and assisted readings was similarly high (uniform: ICC 0.96, MAD 0.60, MD -0.02; clinical: ICC 0.90, MAD 0.80, MD -0.05), with no significant differences between unassisted and assisted scores (Wilcoxon: uniform P=0.82, clinical P=0.61). The automated output showed good agreement with human ratings, though consistently lower than inter-reader agreement (uniform: ICC 0.89, MAD 0.97-1.01, MD -0.20 to -0.22; clinical: ICC 0.76-0.77, MAD 1.18-1.27, MD -0.16 to -0.21). Sensitivity analyses supported an NWU threshold of approximately 7%. Conclusions:The automated system demonstrated good-to-moderate agreement with expert ratings and was not associated with a systematic group-level shift in ASPECTS scoring. It may support more standardized ASPECTS evaluation, particularly in settings with limited access to expert readers, while maintaining the autonomy of clinical judgment.

Background/Objectives: This study aimed to research the potential association between brain atrophy and hematoma expansion (HE) in intracerebral hemorrhage (ICH). Methods: A retrospective analysis was conducted using data from patients with primary ICH in our stroke database. ICH volumes from initial and follow-up CT scans were manually segmented. Total brain and intracranial volumes were quantified using an automated head CT segmentation method. Normalized brain volume (NBV) was calculated by dividing the total brain volume by the total intracranial volume to account for individual head size differences. The relationship between the NBV and hematoma expansion was assessed using linear regression, adjusting for other variables influencing hematoma expansion. Results: Our final analysis included 420 patients. Brain atrophy (lower NBV) was associated with hematoma growth (>0 mL) in patients not on oral anticoagulants (β = -0.159, p = 0.032). A strong association was observed in patients using vitamin K antagonists (β = -0.667, p = 0.006) but not in those on direct oral anticoagulants (DOACs; (β = -0.159, p = 0.436)). Results remained significant in patients not on oral anticoagulants and in those on VKAs when hematoma expansion was defined as a volume increase >6 mL or >33%. Conclusions: This research provides initial evidence that brain atrophy is a risk factor for hematoma expansion, depending on the patient's coagulation status. These findings could enhance risk stratification for acute clinical management and deepen understanding of the biological mechanisms behind hematoma expansion.

Background:Precise volume quantification of intracerebral hemorrhage (ICH), intraventricular hemorrhage (IVH), and perihematomal edema (PHE) is a critical parameter for guiding therapy decisions, monitoring therapeutic effects over time, and predicting patient outcomes. Purpose:To evaluate a nnU-Net-based deep learning model for automated, multilesion segmentation on non-contrast CT. Materials and Methods:Retrospective data from acute spontaneous ICH patients admitted to 4 stroke centers (2015-2022) and controls (2022-2023) were analyzed. Manual segmentations served as ground truth with repeated segmentations as reference standard. nnU-Net was trained (n = 775) using 5-fold cross-validation and tested on a holdout set (n = 189). Lesion detection, segmentation, and volumetric accuracy were evaluated using the Dice similarity coefficient (DSC) and Pearson correlation coefficients (r), with subanalyses for anatomical location and impact of other hemorrhage types (subarachnoid, subdural, or epidural hematoma). The model was validated on internal (n = 121) and external (n = 169) datasets. Processing time was compared to manual segmentation. Results:Test set sensitivity was 99% for ICH and PHE and 97% for IVH. Segmentation achieved a DSC of 0.91 (ICH), 0.71 (PHE), and 0.76 (IVH), with r = 0.99 (ICH, IVH) and r = 0.92 (PHE). DSC for lobar and deep hemorrhages were 0.90 and 0.92, respectively, and 0.70 in the brainstem, with other hemorrhage types showing no significant impact on segmentation accuracy, P > .05. For internal validation, DSC was 0.88 (ICH), 0.66 (PHE), and 0.80 (IVH), with r of 0.98, 0.88, and 0.98, respectively. External validation yielded DSC values of 0.85 (ICH), 0.61 (PHE), and 0.80 (IVH), with r values of 0.97, 0.85, and 0.96. Mean processing time was 18.2 s (±5 SD), compared to 18.01 min (±20.47 SD) for manual segmentations. Conclusion:nnU-Net enables reliable, time-efficient segmentation of ICH, PHE, and IVH, validated across multicenter, multivendor datasets of spontaneous ICH, showing potential to enhance clinical workflows.

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.

BACKGROUND:The prognostic impact of intracerebral hemorrhage (ICH) volume varies according to location, with smaller volume tolerance in deep ICH, and hematoma expansion (HE) contributes to final ICH volume. We tested the hypothesis that HE influences outcome only when the final ICH volume achieves a critical threshold that differs according to ICH location. METHODS:Retrospective analysis of patients with supratentorial ICH admitted at 10 centers in North America and China (development cohort) and Europe (replication cohort). HE was defined as growth >33% and/or >6 mL. Location-specific (lobar versus deep) volume cutoffs for the prediction of poor outcomes were derived using receiver operating characteristic curves and the Youden index. The prognostic impact of HE stratified by location and final volume was explored with logistic regression (poor outcome: 90-day modified Rankin Scale score of 4-6), accounting for age, Glasgow Coma Scale, baseline volume, intraventricular hemorrhage, and admission center. RESULTS:We identified 1774 patients with ICH in the development cohort and 1746 in the replication cohort. A total of 1058 (mean age, 68 years; 47.8% men) and 1423 (mean age, 71 years; 44.7% men) subjects met the inclusion criteria, respectively. The optimal final ICH volume cutoff for poor outcome differed by location: ≥36 mL for lobar and ≥17 mL for deep ICH. HE with final volume below the cutoff was not associated with higher odds of poor outcome compared with patients without HE (adjusted odds ratio, 1.85 [95% CI, 0.78-4.38]; P=0.163 in lobar ICH; adjusted odds ratio, 0.85 [95% CI, 0.38-1.89]; P=0.685 in deep ICH). The combination of HE and final volume over the critical threshold was, however, significantly associated with poor prognosis, and the magnitude of this effect was substantial (adjusted odds ratio, 8.55 [95% CI, 2.87-25.48]; P<0.001 in lobar ICH; adjusted odds ratio, 10.34 [95% CI, 2.86-37.44]; P<0.001 in deep ICH). These findings were confirmed in the replication cohort. CONCLUSIONS:HE significantly impacts severe outcomes only when the final ICH volume exceeds a critical target threshold, and this threshold is lower in deep versus lobar ICH. These findings might inform clinical practice and future trials.

Hematoma volume is a major pathophysiological hallmark of acute intracerebral hemorrhage (ICH). We investigated how the variance in functional outcome induced by the ICH volume is explained by neurological deficits at admission using a mediation model. Patients with acute ICH treated in three tertiary stroke centers between January 2010 and April 2019 were retrospectively analyzed. Mediation analysis was performed to investigate the effect of ICH volume (0.8 ml (5

Introduction: Most intracerebral hemorrhage (ICH) trials assessed outcome at 3 months but the recovery trajectory of ICH survivors may continue up to 1 year after the index event. We aimed to describe the predictors of functional outcome improvement from 3 to 12 months after ICH.Materials and Methods: Retrospective analysis of patients admitted to six European Stroke Centers for supratentorial ICH. Functional outcome was measured with the modified Rankin Scale (mRS) at 3 and 12 months. Predictors of functional outcome improvement were explored with binary logistic regression.Results: We included 703 patients, of whom 245 (34.9%) died within 3 months. Among survivors, 131 (28.6%) had an mRS improvement, 78 (17.0%) had a worse mRS and 249 (54.4%) had a stable functional status at 12 months. Older age and the presence of baseline disability (defined as pre-stroke mRS > 1), were associated with lower odds of functional outcome improvement (Odds Ratio (OR) 0.98 per year increase, 95% Confidence Interval (CI) 0.96-1.00, p = 0.017 and OR 0.45, 95% CI 0.25-0.81, p = 0.008 respectively). Conversely, deep ICH location increased the probability of long term mRS improvement (OR 1.67, 95% CI, 1.07-2.61, p = 0.023). Patients with mild-moderate disability at 3 months (mRS 2-3) had the highest odds of improvement at 12 months (OR 8.76, 95% CI 3.68-20.86, p < 0.001).Discussion and Conclusion: Long term recovery is common after ICH and associated with age, baseline functional status, mRS at 3 months and hematoma location. Our findings might inform future trials and improve long-term prognostication in clinical practice.

INTRODUCTION:In patients with acute intracerebral haemorrhage (ICH) and elevated systolic blood pressure (BP), guidelines suggest that systolic BP reduction to <140 mmHg should be rapidly initiated. Compared with conventional care, Mobile Stroke Units (MSUs) allow for earlier ICH diagnosis through prehospital imaging and earlier BP lowering. PATIENTS AND METHODS:ICH patients were prospectively evaluated as a cohort of the controlled B_PROUD-study in which MSU availability alone determined MSU dispatch in addition to conventional ambulance. We used inverse probability of treatment weighting to adjust for confounding to estimate the effect of additional MSU dispatch in ICH patients. Outcomes of interest were 7-day mortality (primary), systolic BP (sBP) at hospital arrival, dispatch-to-imaging time, largest haematoma volume, anticoagulation reversal, length of in-hospital stay, 3-month functional outcome. RESULTS:Between February 2017 and May 2019, MSUs were dispatched to 95 (mean age: 72 ± 13 years, 45% female) and only conventional ambulances to 78 ICH patients (mean age: 71 ± 12 years, 44% female). After adjusting for confounding, we found shorter dispatch-to-imaging time (mean difference: -17.75 min, 95% CI: -27.16 to -8.21 min) and lower sBP at hospital arrival (mean difference = -16.31 mmHg, 95% CI: -30.64 to -6.19 mmHg) in the MSU group. We found no statistically significant difference for the other outcomes, including 7-day mortality (adjusted odds ratio: 1.43, 95% CI: 0.68 to 3.31) or favourable outcome (adjusted odds ratio = 0.67, 95% CI: 0.27 to 1.67). CONCLUSIONS:Although MSU dispatch led to sBP reduction and lower dispatch-to-imaging time compared to conventional ambulance care, we found no evidence of better outcomes in the MSU dispatch group.

Purpose: To evaluate a nnU-Net-based deep learning for automated segmentation of intracerebral hemorrhage (ICH), intraventricular hemorrhage (IVH), and perihematomal edema (PHE) on noncontrast CT scans. Materials and Methods: Retrospective data from acute ICH patients admitted at four European stroke centers (2017-2019), along healthy controls (2022-2023), were analyzed. nnU-Net was trained (n=775) using a 5-fold cross-valiadtion approach, tested (n=189), and seperatly validated on internal (n=121), external (n=169), and diverse ICH etiologies (n=175) datasets. Interrater-validated ground truth served as the reference standard. Lesion detection, segmentation, and volumetric accuracy were measured, alongside time efficiency versus manual segmentation. Results: Test set results revealed high nnU-Net accuracy (median Dice Similartiy Coefficient (DSC): ICH 0.91, IVH 0.76, PHE 0.71) and volumetric correlation (ICH, IVH: r=0.99; PHE: r=0.92). Sensitivities were high (ICH, PHE: 99%; IVH: 97%), with IVH detection specificities and sensitivities >90% for volumes up to 0.2 ml. Anatomical-specific metrics showed higher performance for lobar and deep hemorrhages (median DSC 0.90 and 0.92, respectively) and lower for brainstem (median DSC 0.70). Concurrent hemorrhages did not affect accuracy, p> 0.05. Across validation sets, segmentation precision was consistent, especially for ICH (median DSC 0.85-0.90), with PHE slightly lower (median DSC 0.61-0.66) and IVH best in the second and third set (median DSC 0.80). Average processing time was 18.2 seconds versus 18.01 minutes manually. Conclusion: The nnU-Net provides reliable, time-efficient ICH, IVH, and PHE segmentation, validated across various clinical settings, with excellent anatomical-specific performance for lobar and deep hemorrhages. It shows promise for enhancing clinical workflow and research initiatives. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This retrospective multicenter study received approval from the ethics committees of Charite Berlin, Germany (protocol number EA1/035/20), University Medical-Center Hamburg, Germany (protocol number WF-054/19), University Hospital Munster, Germany [2017-233-f-S], and and IRCCS Mondino Foundation Pavia, Italy (protocol number 20190099462). The institutional review boards waived the requirement for written informed consent. All protocols and procedures adhered to the Declaration of Helsinki. Given the study's retrospective nature, patient consent was not required. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The datasets that support the findings of our study are available upon reasonable request from the corresponding author. However prior approval of proposals may apply by our institution's data security management and a signed data sharing agreement will then be approved.

Background: Severe hematoma expansion (sHE) has the strongest impact on intracerebral hemorrhage (ICH) outcome. We investigated the predictors of sHE. Methods: Retrospective analysis of ICH patients admitted at nine sites in Italy, Germany, China, and Canada. The following imaging features were analyzed: non-contrast CT (NCCT) hypodensities, heterogeneous density, blend sign, irregular shape, and CT angiography (CTA) spot sign. The outcome of interest was sHE, defined as volume increase >66% and/or >12.5 from baseline to follow-up NCCT. Predictors of sHE were explored with logistic regression. Results: A total of 1472 patients were included (median age 73, 56.6% males) of whom 223 (15.2%) had sHE. Age (odds ratio (OR) per year, 95% confidence interval (CI), 1.02 (1.01-1.04)), Anticoagulant treatment (OR 3.00, 95% CI 2.09-4.31), Glasgow Coma Scale (OR 0.93, 95% CI 0.89-0.98), time from onset/last known well to imaging, (OR per h 0.96, 95% CI 0.93-0.99), and baseline ICH volume, (OR per mL 1.02, 95% CI 1.02-1.03) were independently associated with sHE. Ultra-early hematoma growth (baseline volume/baseline imaging time) was also a predictor of sHE (OR per mL/h 1.01, 95% CI 1.00-1.02). All NCCT and CTA imaging markers were also predictors of sHE. Amongst imaging features NCCT hypodensities had the highest sensitivity (0.79) whereas the CTA spot sign had the highest positive predictive value (0.51). Conclusions: sHE is common in the natural history of ICH and can be predicted with few clinical and imaging variables. These findings might inform clinical practice and future trials targeting active bleeding in ICH.

Non-contrast computed tomography (NCCT) markers are robust predictors of parenchymal hematoma expansion in intracerebral hemorrhage (ICH). We investigated whether NCCT features can also identify ICH patients at risk of intraventricular hemorrhage (IVH) growth. Patients with acute spontaneous ICH admitted at four tertiary centers in Germany and Italy were retrospectively included from January 2017 to June 2020. NCCT markers were rated by two investigators for heterogeneous density, hypodensity, black hole sign, swirl sign, blend sign, fluid level, island sign, satellite sign, and irregular shape. ICH and IVH volumes were semi-manually segmented. IVH growth was defined as IVH expansion > 1 mL (eIVH) or any delayed IVH (dIVH) on follow-up imaging. Predictors of eIVH and dIVH were explored with multivariable logistic regression. Hypothesized moderators and mediators were independently assessed in PROCESS macro models. A total of 731 patients were included, of whom 185 (25.31 • NCCT features identified ICH patients at a high risk of IVH growth with subtype-specific differences. • The effect of NCCT features was not moderated by time and location or indirectly mediated by hematoma expansion. • Our findings may assist in the risk stratification of IVH growth with baseline NCCT and might inform ongoing and future studies.

Background and Objectives Hematoma expansion (HE) is a major determinant of neurologic deterioration and poor outcome in intracerebral hemorrhage (ICH) and represents an appealing therapeutic target. We analyzed the prognostic effect of different degrees of HE. Methods This was a retrospective analysis of patients with ICH admitted at 8 academic institutions in Italy, Germany, Canada, China, and the United States. All patients underwent baseline and follow-up imaging for HE assessment. Relative HE (rHE) was classified as follows: none (<0%), mild (0%–33%), moderate (33.1%–66%), and severe (>66%). Absolute HE (aHE) was classified as none (<0 mL), mild (0–6.0 mL), moderate (6.1–12.5 mL), and severe (>12.5 mL). Predictors of poor functional outcome (90 days modified Rankin Scale 4–6) were explored with logistic regression. Results We included 2,163 patients, of whom 1,211 (56.0%) had poor outcome. The occurrence of severe aHE or rHE was more common in patients with unfavorable outcome (13.9% vs 6.5%, p < 0.001 and 18.3% vs 7.2%, p < 0.001 respectively). This association was confirmed in logistic regression (rHE odds ratio [OR] 1.98, 95% CI 1.38–2.82, p < 0.001; aHE OR 1.73, 95% CI 1.23–2.45, p = 0.002) while there was no association between mild or moderate HE and poor outcome. The association between severe HE and poor outcome was significant only in patients with baseline ICH volume below 30 mL. Discussion The strongest association between HE and outcome was observed in patients with smaller initial volume experiencing severe HE. These findings may inform clinical trial design and guide clinicians in selecting patients for antiexpansion therapies.

Background and Purpose: Fully automated methods for segmentation and volume quantification of intraparenchymal hemorrhage (ICH), intraventricular hemorrhage extension (IVH), and perihematomal edema (PHE) are gaining increasing interest. Yet, reliabilities demonstrate considerable variances amongst each other. Our aim was therefore to evaluate both the intra- and interrater reliability of ICH, IVH and PHE on ground-truth segmentation masks. Methods: Patients with primary spontaneous ICH were retrospectively included from a German tertiary stroke center (Charité Berlin; January 2016–June 2020). Baseline and follow-up non-contrast Computed Tomography (NCCT) scans were analyzed for ICH, IVH, and PHE volume quantification by two radiology residents. Raters were blinded to all demographic and outcome data. Inter- and intrarater agreements were determined by calculating the Intraclass Correlation Coefficient (ICC) for a randomly selected set of patients with ICH, IVH, and PHE. Results: 100 out of 670 patients were included in the analysis. Interrater agreements ranged from an ICC of 0.998 for ICH (95% CI [0.993; 0.997]), to an ICC of 0.979 for IVH (95% CI [0.984; 0.993]), and an ICC of 0.886 for PHE (95% CI [0.760; 0.938]), all p-values < 0.001. Intrarater agreements ranged from an ICC of 0.997 for ICH (95% CI [0.996; 0.998]), to an ICC of 0.995 for IVH (95% CI [0.992; 0.996]), and an ICC of 0.980 for PHE (95% CI [0.971; 0.987]), all p-values < 0.001. Conclusion Manual segmentations of ICH, IVH, and PHE demonstrate good-to-excellent inter- and intrarater reliabilities, with the highest agreement for ICH and IVH and lowest for PHE. Therefore, the degree of variances reported in fully automated quantification methods might be related amongst others to variances in ground-truth masks.

BACKGROUND: Spreading depolarizations (SDs) occur in all types of brain injury and may be associated with detrimental effects in ischemic stroke and subarachnoid hemorrhage. While rapid hematoma growth during intracerebral hemorrhage triggers SDs, their role in intracerebral hemorrhage is unknown. METHODS: We used intrinsic optical signal and laser speckle imaging, combined with electrocorticography, to investigate the effects of SD on hematoma growth during the hyperacute phase (0–4 hours) after intracortical collagenase injection in mice. Hematoma expansion, SDs, and cerebral blood flow were simultaneously monitored under normotensive and hypertensive conditions. RESULTS: Spontaneous SDs erupted from the vicinity of the hematoma during rapid hematoma growth. We found that hematoma growth slowed down by >60% immediately after an SD. This effect was even stronger in hypertensive animals with faster hematoma growth. To establish causation, we exogenously induced SDs (every 30 minutes) at a remote site by topical potassium chloride application and found reduced hematoma growth rate and final hemorrhage volume (18.2±5.8 versus 10.7±4.1 mm 3 ). Analysis of cerebral blood flow using laser speckle flowmetry revealed that suppression of hematoma growth by spontaneous or induced SDs coincided and correlated with the characteristic oligemia in the wake of SD, implicating the vasoconstrictive effect of SD as one potential mechanism of action. CONCLUSIONS: Our findings reveal that SDs limit hematoma growth during the early hours of intracerebral hemorrhage and decrease final hematoma volume.

Background: 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. Methods: 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. Results: 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]). Conclusions: 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.

Hematoma expansion (HE) is common and predicts poor outcome in patients with supratentorial intracerebral hemorrhage (ICH). We investigated the predictors and prognostic impact of HE in infratentorial ICH. We conducted a retrospective analysis of patients with brainstem and cerebellar ICH admitted at seven sites. Noncontrast computed tomography images were analyzed for the presence of hypodensities according to validated criteria, defined as any hypodense region strictly encapsulated within the hemorrhage with any shape, size, and density. Occurrence of HE (defined as > 33

Background: Hematoma expansion (HE) is an appealing therapeutic target in intracerebral hemorrhage (ICH) and non-contrast computed tomography (NCCT) features are promising predictors of HE. Aims: We investigated whether onset-to-CT time influences the diagnostic performance of NCCT markers for HE. Methods: Retrospective multicentre analysis of patients with primary ICH. The following NCCT markers were analyzed: hypodensities, heterogeneous density, blend sign, and irregular shape. HE was defined as growth ⩾6 mL and/or ⩾33%. We calculated the sensitivity, specificity, positive, and negative predictive values (PPVs and NPVs) of NCCT markers for HE, stratified by onset-to-CT time (<2 h, 2–4 h, 4–6 h, >6 h). Results: We included 1135 patients (median age 69, 53% males), of whom 307 (27%) experienced HE. Overall hypodensities had the highest sensitivity (0.68) and blend sign the highest specificity (0.87) for HE. Hypodensities were more common and had higher sensitivity (0.80) in patients with imaging within 2 h. The same result was observed for heterogeneous density, whereas irregular shape had a similar prevalence across time strata and higher sensitivity (0.79) beyond 6 h from onset. The frequency of blend sign increased with longer onset-to-CT time, whereas its specificity declined after 6 h from onset. Conclusion: The diagnostic performance of NCCT markers is influenced by imaging time. Hypodensities identified four out of five patients with HE within 2 h from onset, whereas irregular shape performed better in late presenters. Our findings may improve the use of NCCT markers in future studies and trials targeting HE.

BACKGROUND:The objective of this study was to assess the performance of the first publicly available automated 3D segmentation for spontaneous intracerebral hemorrhage (ICH) based on a 3D neural network before and after retraining. METHODS:We performed an independent validation of this model using a multicenter retrospective cohort. Performance metrics were evaluated using the dice score (DSC), sensitivity, and positive predictive values (PPV). We retrained the original model (OM) and assessed the performance via an external validation design. A multivariate linear regression model was used to identify independent variables associated with the model's performance. Agreements in volumetric measurements and segmentation were evaluated using Pearson's correlation coefficients (r) and intraclass correlation coefficients (ICC), respectively. With 1040 patients, the OM had a median DSC, sensitivity, and PPV of 0.84, 0.79, and 0.93, compared to thoseo f 0.83, 0.80, and 0.91 in the retrained model (RM). However, the median DSC for infratentorial ICH was relatively low and improved significantly after retraining, at p < 0.001. ICH volume and location were significantly associated with the DSC, at p < 0.05. The agreement between volumetric measurements (r > 0.90, p > 0.05) and segmentations (ICC ≥ 0.9, p < 0.001) was excellent. CONCLUSION:The model demonstrated good generalization in an external validation cohort. Location-specific variances improved significantly after retraining. External validation and retraining are important steps to consider before applying deep learning models in new clinical settings.