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Background: In the SPOTLIGHT trial (Spot Sign Selection of Intracerebral Hemorrhage to Guide Hemostatic Therapy), patients with a computed tomography (CT) angiography spot-sign positive acute intracerebral hemorrhage were randomized to rFVIIa (recombinant activated factor VIIa; 80 μg/kg) or placebo within 6 hours of onset, aiming to limit hematoma expansion. Administration of rFVIIa did not significantly reduce hematoma expansion. In this prespecified analysis, we aimed to investigate the impact of delays from baseline imaging to study drug administration on hematoma expansion. Methods: Hematoma volumes were measured on the baseline CT, early post-dose CT, and 24 hours CT scans. Total hematoma volume (intracerebral hemorrhage+intraventricular hemorrhage) change between the 3 scans was calculated as an estimate of how much hematoma expansion occurred before and after studying drug administration. Results: Of the 50 patients included in the trial, 44 had an early post-dose CT scan. Median time (interquartile range) from onset to baseline CT was 1.4 hours (1.2–2.6). Median time from baseline CT to study drug was 62.5 (55–80) minutes, and from study drug to early post-dose CT was 19 (14.5–30) minutes. Median (interquartile range) total hematoma volume increased from baseline CT to early post-dose CT by 10.0 mL (−0.7 to 18.5) in the rFVIIa arm and 5.4 mL (1.8–8.3) in the placebo arm ( P =0.96). Median volume change between the early post-dose CT and follow-up scan was 0.6 mL (−2.6 to 8.3) in the rFVIIa arm and 0.7 mL (−1.6 to 2.1) in the placebo arm ( P =0.98). Total hematoma volume decreased between the early post-dose CT and 24-hour scan in 44.2% of cases (rFVIIa 38.9% and placebo 48%). The adjusted hematoma growth in volume immediately post dose for FVIIa was 0.998 times that of placebo ([95% CI, 0.71–1.43]; P =0.99). The hourly growth in FFVIIa was 0.998 times that for placebo ([95% CI, 0.994–1.003]; P =0.50; Table 3). Conclusions: In the SPOTLIGHT trial, the adjusted hematoma volume growth was not associated with Factor VIIa treatment. Most hematoma expansion occurred between the baseline CT and the early post-dose CT, limiting any potential treatment effect of hemostatic therapy. Future hemostatic trials must treat intracerebral hemorrhage patients earlier from onset, with minimal delay between baseline CT and drug administration. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01359202.

Background and ObjectivesEndovascular thrombectomy (EVT) is effective for patients with large vessel occlusion (LVO) stroke with smaller volumes of CT perfusion (CTP)-defined ischemic core. However, the benefit of EVT is unclear in those with a core volume >70 mL. We aimed to compare outcomes of EVT and non-EVT patients with an ischemic core volume ≥70 mL, hypothesizing that there would be a benefit from EVT for fair outcome (3-month modified Rankin scale [mRS] 0–3) after stroke.MethodsA retrospective analysis of patients enrolled into a multicenter (Australia, China, and Canada) registry (2012–2020) who underwent CTP within 24 hours of stroke onset and had a baseline ischemic core volume ≥70 mL was performed. The primary outcome was the estimation of the association of EVT in patients with core volume ≥70 mL and within 70–100 and ≥100 mL subgroups with fair outcome.ResultsOf the 3,283 patients in the registry, 299 had CTP core volume ≥70 mL and 269 complete data (135 had core volume between 70 and 100 mL and 134 had core volume ≥100 mL). EVT was performed in 121 (45%) patients. EVT-treated patients were younger (median 69 vs 75 years; p = 0.011), had lower prestroke mRS, and smaller median core volumes (92 [79–116.5] mL vs 105.5 [85.75–138] mL, p = 0.004). EVT-treated patients had higher odds of achieving fair outcome in adjusted analysis (30% vs 13.9% in the non-EVT group; adjusted odds ratio [aOR] 2.1, 95% CI 1–4.2, p = 0.038). The benefit was seen predominantly in those with 70–100 mL core volume (71/135 [52.6%] EVT-treated), with 54.3% in the EVT-treated vs 21% in the non-EVT group achieving a fair outcome (aOR 2.5, 95% CI 1–6.2, p = 0.005). Of those with a core volume ≥100 mL, 50 of the 134 (37.3%) underwent EVT. Proportions of fair outcome were very low in both groups (8.1% vs 8.7%; p = 0.908).DiscussionWe found a positive association of EVT with the 3-month outcome after stroke in patients with a baseline CTP ischemic core volume 70–100 mL but not in those with core volume ≥100 mL. Randomized data to confirm these findings are required.Classification of EvidenceThis study provides Class III evidence that EVT is associated with better motor outcomes 3 months after CTP-defined ischemic stroke with a core volume of 70–100 mL.

BackgroundAt least 20% of strokes involve the posterior circulation (PC). Compared to the anterior circulation, posterior circulation infarction (POCI) are frequently misdiagnosed. CT perfusion (CTP) has advanced stroke care by improving diagnostic accuracy and expanding eligibility for acute therapies. Clinical decisions are predicated upon precise estimates of the ischaemic penumbra and infarct core. Current thresholds for defining core and penumbra are based upon studies of anterior circulation stroke. We aimed to define the optimal CTP thresholds for core and penumbra in POCI.MethodsData were analyzed from 331-patients diagnosed with acute POCI enrolled in the International-stroke-perfusion-registry (INSPIRE). Thirty-nine patients with baseline multimodal-CT with occlusion of a large PC-artery and follow up diffusion weighted MRI at 24–48 h were included. Patients were divided into two-groups based on artery-recanalization on follow-up imaging. Patients with no or complete recanalisation were used for penumbral and infarct-core analysis, respectively. A Receiver operating curve (ROC) analysis was used for voxel-based analysis. Optimality was defined as the CTP parameter and threshold which maximized the area-under-the-curve. Linear regression was used for volume based analysis determining the CTP threshold which resulted in the smallest mean volume difference between the acute perfusion lesion and follow up MRI. Subanalysis of PC-regions was performed.ResultsMean transit time (MTT) and delay time (DT) were the best CTP parameters to characterize ischaemic penumbra (AUC = 0.73). Optimal thresholds for penumbra were a DT >1 s and MTT>145%. Delay time (DT) best estimated the infarct core (AUC = 0.74). The optimal core threshold was a DT >1.5 s. The voxel-based analyses indicated CTP was most accurate in the calcarine (Penumbra-AUC = 0.75, Core-AUC = 0.79) and cerebellar regions (Penumbra-AUC = 0.65, Core-AUC = 0.79). For the volume-based analyses, MTT >160% demonstrated best correlation and smallest mean-volume difference between the penumbral estimate and follow-up MRI (R2 = 0.71). MTT >170% resulted in the smallest mean-volume difference between the core estimate and follow-up MRI, but with poor correlation (R2 = 0.11).ConclusionCTP has promising diagnostic utility in POCI. Accuracy of CTP varies by brain region. Optimal thresholds to define penumbra were DT >1 s and MTT >145%. The optimal threshold for core was a DT >1.5 s. However, CTP core volume estimates should be interpreted with caution.

The development of reperfusion therapies has profoundly impacted stroke care, initially with the advent of IV thrombolytic treatment and, more recently, with the development and refinement of endov...

The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in traumatic brain injury (TBI).Systematic review, in accordance with PRISMA 2020 and SPIRIT-AI extension guidelines, with a search of 4 databases (Medline, Embase, IEEE Xplore, and Web of Science) was performed to find AI studies that automated the clinical tasks for identifying and quantifying CT findings of TBI-related abnormalities.A total of 531 unique publications were reviewed, which resulted in 66 articles that met our inclusion criteria. The following components for identification and quantification regarding TBI were covered and automated by existing AI studies: identification of TBI-related abnormalities; classification of intracranial hemorrhage types; slice-, pixel-, and voxel-level localization of hemorrhage; measurement of midline shift; and measurement of hematoma volume. Automated identification of obliterated basal cisterns was not investigated in the existing AI studies. Most of the AI algorithms were based on deep neural networks that were trained on 2- or 3-dimensional CT imaging datasets.We identified several important TBI-related CT findings that can be automatically identified and quantified with AI. A combination of these techniques may provide useful tools to enhance reproducibility of TBI identification and quantification by supporting radiologists and clinicians in their TBI assessments and reducing subjective human factors.

Hemorrhagic transformation is caused by extravasation of blood products from vessels after acute ischemic stroke. It is an undesirable and potentially devastating complication, which occurs in 10%-40% of clinical cases. Hemorrhagic transformation is classified into four subtypes based on European cooperative acute stroke study II. Predicting hemorrhagic complications at presentation can be useful life saving/altering decisions for the patient. Also, understanding the mechanisms of hemorrhagic transformation can lead to new treatments and intervention measures. We highlighted various imaging techniques that have been used to predict hemorrhagic transformation. Specifically, we looked at the usefulness of perfusion and permeability imaging for hemorrhagic transformation. Use of imaging to predict hemorrhagic transformation could change patient management that may lead to the prevention of hemorrhagic transformation before it occurs. We concluded that the current evidence is not strong enough to rely on these imaging parameters for predicting hemorrhagic transformation and more studies are required.

Purpose To assess the sensitivity and specificity of common carotid ultrasound method for carotid near-occlusion diagnosis. Methods Five hundred forty-eight patients examined with both ultrasound and CTA within 30 days of each other were analyzed. CTA graded by near-occlusion experts was used as reference standard. Low flow velocity, unusual findings, and commonly used flow velocity parameters were analyzed. Results One hundred three near-occlusions, 272 conventional ≥50% stenosis, 162 n = 13, 13%), conventional ≥50% stenosis (n = 65, 63%) and < 50% stenosis (n = 2, 2%). No velocity parameter or combination of parameters could identify the 65 near-occlusions mistaken for conventional ≥50% stenoses with >75% sensitivity and specificity. Conclusion Near-occlusion is difficult to diagnose with commonly used carotid ultrasound methods. Improved carotid ultrasound methods are needed if ultrasound is to retain its position as sole preoperative modality.

Purpose Rapid identification of hematoma expansion (HE) risk at baseline is a priority in intracerebral hemorrhage (ICH) patients and may impact clinical decision making. Predictive scores using clinical features and Non-Contract Computed Tomography (NCCT)-based features exist, however, the extent to which each feature set contributes to identification is limited. This paper aims to investigate the relative value of clinical, radiological, and radiomics features in HE prediction. Methods Original data was retrospectively obtained from three major prospective clinical trials [“Spot Sign” Selection of Intracerebral Hemorrhage to Guide Hemostatic Therapy (SPOTLIGHT)NCT01359202; The Spot Sign for Predicting and Treating ICH Growth Study (STOP-IT)NCT00810888] Patients baseline and follow-up scans following ICH were included. Clinical, NCCT radiological, and radiomics features were extracted, and multivariate modeling was conducted on each feature set. Results 317 patients from 38 sites met inclusion criteria. Warfarin use (p=0.001) and GCS score (p=0.046) were significant clinical predictors of HE. The best performing model for HE prediction included clinical, radiological, and radiomic features with an area under the curve (AUC) of 87.7%. NCCT radiological features improved upon clinical benchmark model AUC by 6.5% and a clinical & radiomic combination model by 6.4%. Addition of radiomics features improved goodness of fit of both clinical (p=0.012) and clinical & NCCT radiological (p=0.007) models, with marginal improvements on AUC. Inclusion of NCCT radiological signs was best for ruling out HE whereas the radiomic features were best for ruling in HE. Conclusion NCCT-based radiological and radiomics features can improve HE prediction when added to clinical features.

Despite intracerebral haemorrhage causing 5% of deaths worldwide, few evidence-based therapeutic strategies other than stroke unit care exist. Tranexamic acid decreases haemorrhage in conditions such as acute trauma and menorrhoea. We aimed to assess whether tranexamic acid reduces intracerebral haemorrhage growth in patients with acute intracerebral haemorrhage.We did a prospective, double-blind, randomised, placebo-controlled, investigator-led, phase 2 trial at 13 stroke centres in Australia, Finland, and Taiwan. Patients were eligible if they were aged 18 years or older, had an acute intracerebral haemorrhage fulfilling clinical criteria (eg, Glasgow Coma Scale score of7, intracerebral haemorrhage volume70 mL, no identified or suspected secondary cause of intracerebral haemorrhage, no thrombotic events within the previous 12 months, no planned surgery in the next 24 h, and no use of anticoagulation), had contrast extravasation on CT angiography (the so-called spot sign), and were treatable within 4·5 h of symptom onset and within 1 h of CT angiography. Patients were randomly assigned (1:1) to receive either 1 g of intravenous tranexamic acid over 10 min followed by 1 g over 8 h or matching placebo, started within 4·5 h of symptom onset. Randomisation was done using a centralised web-based procedure with randomly permuted blocks of varying size. All patients, investigators, and staff involved in patient management were masked to treatment. The primary outcome was intracerebral haemorrhage growth (33% relative or6 mL absolute) at 24 h. The primary and safety analyses were done in the intention-to-treat population. The trial is registered at ClinicalTrials.gov (NCT01702636).Between March 1, 2013, and Aug 13, 2019, we enrolled and randomly assigned 100 participants to the tranexamic acid group (n=50) or the placebo group (n=50). Median age was 71 years (IQR 57-79) and median intracerebral haemorrhage volume was 14·6 mL (7·9-32·7) at baseline. The primary outcome was not different between the two groups: 26 (52%) patients in the placebo group and 22 (44%) in the tranexamic acid group had intracerebral haemorrhage growth (odds ratio [OR] 0·72 [95% CI 0·32-1·59], p=0·41). There was no evidence of a difference in the proportions of patients who died or had thromboembolic complications between the groups: eight (16%) in the placebo group vs 13 (26%) in the tranexamic acid group died and two (4%) vs one (2%) had thromboembolic complications. None of the deaths was considered related to study medication.Our study does not provide evidence that tranexamic acid prevents intracerebral haemorrhage growth, although the treatment was safe with no increase in thromboembolic complications. Larger trials of tranexamic acid, with simpler recruitment methods and an earlier treatment window, are justified.National Health and Medical Research Council, Royal Melbourne Hospital Foundation.

Cerebral vasculitis is increasingly recognized as a common cause of pediatric arterial stroke. It can present with focal neurological deficits, psychiatric manifestations, seizures, and encephalopathy. The etiopathogenesis of childhood cerebral vasculitis (CCV) is multifactorial, making an inclusive classification challenging. In this review, we describe the common and uncommon CCV with a comprehensive discussion of etiopathogenesis, the role of various imaging modalities, and advanced techniques in diagnosing CCV. We also highlight the implications of relevant clinical, laboratory, and genetic findings to reach the final diagnosis. Based on the clinicoradiological findings, a stepwise diagnostic approach is proposed to facilitate CCV diagnosis and rule out potential mimics. Identification of key clinical manifestations, pertinent blood and cerebrospinal fluid results, and evaluation of central nervous system vessels for common and disease-specific findings will be emphasized. We discuss the role of magnetic resonance imaging, MR angiography, and vessel wall imaging as the imaging investigation of choice, and reservation of catheter angiography as a problem-solving tool. We emphasize the utility of brain and leptomeningeal biopsy for diagnosis and exclusion of imitators and masqueraders.

OBJECTIVE We sought to examine the diagnostic utility of existing predictors of any hemorrhagic transformation (HT) and compare them with new perfusion imaging permeability measures in ischemic stroke patients receiving alteplase only. METHODS A pixel-based analysis of pretreatment CT perfusion (CTP) was undertaken to define the optimal CTP permeability thresholds to predict the likelihood of HT. We then compared previously proposed predictors of HT using regression analyses and receiver operating characteristic curve analysis to produce an area under the curve (AUC). We compared AUCs using χ2 analysis. RESULTS From 5 centers, 1,407 patients were included in this study; of these, 282 had HT. The cohort was split into a derivation cohort (1,025, 70% patients) and a validation cohort (382 patients or 30%). The extraction fraction (E) permeability map at a threshold of 30% relative to contralateral had the highest AUC at predicting any HT (derivation AUC 0.85, 95% confidence interval [CI], 0.79-0.91; validation AUC 0.84, 95% CI 0.77-0.91). The AUC improved when permeability was assessed within the acute perfusion lesion for the E maps at a threshold of 30% (derivation AUC 0.91, 95% CI 0.86-0.95; validation AUC 0.89, 95% CI 0.86-0.95). Previously proposed associations with HT and parenchymal hematoma showed lower AUC values than the permeability measure. INTERPRETATION In this large multicenter study, we have validated a highly accurate measure of HT prediction. This measure might be useful in clinical practice to predict hemorrhagic transformation in ischemic stroke patients before receiving alteplase alone. ANN NEUROL 2020;88:466-476.

Background and Purpose— Definitions of significant hematoma expansion traditionally focus on changes in intraparenchymal volume. The presence of intraventricular hemorrhage (IVH) is a predictor of poor outcome, but current definitions of hematoma expansion do not include IVH expansion. We evaluated whether including IVH expansion to current definitions of hematoma expansion improves the ability to predict 90-day outcome. Methods— Using data from the PREDICT-ICH study (Predicting Hematoma Growth and Outcome in Intracerebral Hemorrhage Using Contrast Bolus CT), we compared a standard definition of hematoma expansion (≥6 mL or ≥33%) to revised definitions that includes new IVH development or expansion (≥6 mL or ≥33% or any IVH; ≥6 mL or ≥33% or IVH expansion ≥1 mL). The primary outcome was poor clinical outcome (modified Rankin Scale score, 4–6) at 90 days. Diagnostic accuracy measures were calculated for each definition, and C statistics for each definition were compared using nonparametric methods. Results— Of the 256 patients eligible for primary analysis, 127 (49.6%) had a modified Rankin Scale score of 4 to 6. Sensitivity and specificity for the standard definition (n=80) were 45.7% (95% CI, 36.8–54.7) and 82.9% (95% CI, 75.3–88.9), respectively. The revised definition, ≥6 mL or ≥33% or any IVH (n=113), possessed a sensitivity of 63.8% (95% CI, 54.8–72.1) and specificity of 75.2% (95% CI, 66.8–82.4). Overall accuracy was significantly improved with the revised definition ( P =0.013) and after adjusting for relevant covariates, was associated with a 2.55-fold increased odds (95% CI, 1.31–4.94) of poor outcome at 90 days. A second revised definition, ≥6 mL or ≥33% or IVH expansion ≥1 mL, performed similarly (sensitivity, 56.7% [95% CI, 47.6–65.5]; specificity, 78.3% [95% CI, 40.2–85.1]; aOR, 2.40 [95% CI, 1.23–4.69]). Conclusions— In patients with mild-to-moderate ICH, including IVH expansion to the definition of hematoma expansion improves sensitivity with only minimal decreases to specificity and improves overall prediction of 90-day outcome.

Background and Purpose— Patients with intracerebral hemorrhage (ICH) are often subject to rapid deterioration due to hematoma expansion. Current prognostic scores are largely based on the assessment of baseline radiographic characteristics and do not account for subsequent changes. We propose that calculation of prognostic scores using delayed imaging will have better predictive values for long-term mortality compared with baseline assessments. Methods— We analyzed prospectively collected data from the multicenter PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign). We calculated the ICH Score, Functional Outcome in Patients With Primary Intracerebral Hemorrhage (FUNC) Score, and modified ICH Score using imaging data at initial presentation and at 24 hours. The primary outcome was mortality at 90 days. We generated receiver operating characteristic curves for all 3 scores, both at baseline and at 24 hours, and assessed predictive accuracy for 90-day mortality with their respective area under the curve. Competing curves were assessed with nonparametric methods. Results— The analysis included 280 patients, with a 90-day mortality rate of 25.4%. All 3 prognostic scores calculated using 24-hour imaging were more predictive of mortality as compared with baseline: the area under the curve was 0.82 at 24 hours (95% CI, 0.76–0.87) compared with 0.78 at baseline (95% CI, 0.72–0.84) for ICH Score, 0.84 at 24 hours (95% CI, 0.79–0.89) compared with 0.76 at baseline (95% CI, 0.70–0.83) for FUNC, and 0.82 at 24 hours (95% CI, 0.76–0.88) compared with 0.74 at baseline (95% CI, 0.67–0.81) for modified ICH Score. Conclusions— Calculation of the ICH Score, FUNC Score, and modified ICH Score using 24-hour imaging demonstrated better prognostic value in predicting 90-day mortality compared with those calculated at presentation.

Rationale Following endovascular treatment, poor clinical outcomes are more frequent if the initial infarct core or volume of irreversible brain damage is large. Clinical outcomes may be improved using neuroprotective agents that reduce stroke volume and improve recovery. Aim The aim of the REPERFUSE NA1 was to replicate the preclinical neuroprotection study that significantly reduced infarct volume in a primate model of ischemia reperfusion. Specifically, REPERFUSE NA1 will determine if administration of the neuroprotectant NA1 prior to endovascular therapy can significantly reduce early (Day 2 subtract Day 1 diffusion-weighted imaging volume) and delayed secondary infarct (90-day whole brain atrophy plus FLAIR volume—Day 1 diffusion-weighted imaging volume) growth, as measured by magnetic resonance imaging. Methods and design REPERFUSE-NA1 is a magnetic resonance imaging observational substudy of ESCAPE-NA1 (ClinicalTrialGov NCT02930018). A total of 150 acute stroke patients will be recruited (including 20% attrition) that have been randomized to either NA1 or placebo in the ESCAPE-NA1 trial. Study outcomes Primary—Early infarct growth measured using diffusion-weighted imaging will be at least 30% smaller in patients receiving NA1 compared to placebo. Secondary—Delayed secondary stroke injury at 90 days will be significantly reduced in patients receiving NA1 compared to placebo, as well as delayed secondary growth at 90 days. Conclusion REPERFUSE-NA1 will demonstrate the effect of NA1 neuroprotection on reducing the early and delayed stroke injury after reperfusion treatment.

Differentiating carotid near-occlusion (tight atherosclerotic stenosis causing distal artery size reduction) from conventional stenosis is the first step when grading carotid stenoses with NASCET method. The internal carotid artery (ICA) can be asymmetrically associated with Circle of Willis variations. When such ICA asymmetry coincides with stenosis, it may mimic near-occlusion. We studied ICA anatomical variant prevalence in 4042 consecutive CTA exams from all indications, 53 excluded due to carotid occlusion, 814 with any ≥ 50% steno-occlusive disease intra- or extracranially, 3228 without. Of the 3989 included cases, 568 (14%) had ICA asymmetry, of which 335 (59%) were from associated with Circle of Willis variations. Of 3228 patients without ≥ 50% stenosis or other steno-occlusive disease intra- and extracranially; 257 (8.0%) demonstrated ICA asymmetry associated with Circle of Willis variations, equally common among sexes and age unrelated and most frequently attributed to an ipsilateral A1 hypoplasia/aplasia, less often attributed to large contralateral posterior communicating artery. As ICA asymmetry associated with Circle of Willis variations are common, caution should be exercised diagnosing near-occlusion on asymmetry alone.

Objective To develop and internally validate a deep-learning algorithm from fetal ultrasound images for the diagnosis of cystic hygromas in the first trimester. Methods All first trimester ultrasound scans with a diagnosis of a cystic hygroma between 11 and 14 weeks gestation at our tertiary care centre in Ontario, Canada were studied. Ultrasound scans with normal nuchal translucency were used as controls. The dataset was partitioned with 75% of images used for model training and 25% used for model validation. Images were analyzed using a DenseNet model and the accuracy of the trained model to correctly identify cases of cystic hygroma was assessed by calculating sensitivity, specificity, and the area under the receiver-operating characteristic (ROC) curve. Gradient class activation heat maps (Grad-CAM) were generated to assess model interpretability. Results The dataset included 289 sagittal fetal ultrasound images;129 cystic hygroma cases and 160 normal NT controls. Overall model accuracy was 93% (95% CI: 88–98%), sensitivity 92% (95% CI: 79–100%), specificity 94% (95% CI: 91–96%), and the area under the ROC curve 0.94 (95% CI: 0.89–1.0). Grad-CAM heat maps demonstrated that the model predictions were driven primarily by the fetal posterior cervical area. Conclusions Our findings demonstrate that deep-learning algorithms can achieve high accuracy in diagnostic interpretation of cystic hygroma in the first trimester, validated against expert clinical assessment.

BACKGROUND Data extraction from radiology free-text reports is time-consuming when performed manually. Recently, more automated extraction methods using natural language processing (NLP) are proposed. A previously developed rule-based NLP algorithm showed promise in its ability to extract stroke-related data from radiology reports. OBJECTIVE We aimed to externally validate the accuracy of CHARTextract, a rule-based NLP algorithm, to extract stroke-related data from free-text radiology reports. METHODS Free-text reports of CT angiography (CTA) and perfusion (CTP) studies of consecutive patients with acute ischemic stroke admitted to a regional Stroke center for endovascular thrombectomy were analyzed from January 2015 - 2021. Stroke-related variables were manually extracted (reference standard) from the reports, including proximal and distal anterior circulation occlusion, posterior circulation occlusion, presence of ischemia, hemorrhage, Alberta stroke program early CT score (ASPECTS), and collateral status. These variables were simultaneously extracted using a rule-based NLP algorithm. The NLP algorithm's accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. RESULTS The NLP algorithm's accuracy was >90% for identifying distal anterior occlusion, posterior circulation occlusion, hemorrhage, and ASPECTS. Accuracy was 85%, 74%, and 79% for proximal anterior circulation occlusion, presence of ischemia, and collateral status respectively. The algorithm had an accuracy of 87-100% for the detection of variables not reported in radiology reports. CONCLUSIONS Rule-based NLP has a moderate to good performance for stroke-related data extraction from free-text imaging reports. The algorithm's accuracy was affected by inconsistent report styles and lexicon among reporting radiologists.

In the present study we sought to measure the relative statistical value of various multimodal CT protocols at identifying treatment responsiveness in patients being considered for thrombolysis. We used a prospectively collected cohort of acute ischemic stroke patients being assessed for IV-alteplase, who had CT-perfusion (CTP) and CT-angiography (CTA) before a treatment decision. Linear regression and receiver operator characteristic curve analysis were performed to measure the prognostic value of models incorporating each imaging modality. One thousand five hundred and sixty-two sub-4.5 h ischemic stroke patients were included in this study. A model including clinical variables, alteplase treatment, and NCCT ASPECTS was weak (R2 0.067, P < 0.001, AUC 0.605) at predicting 90 day mRS. A second model, including dynamic CTA variables (collateral grade, occlusion severity) showed better predictive accuracy for patient outcome (R2 0.381, P < 0.001, AUC 0.781). A third model incorporating CTP variables showed very high predictive accuracy (R2 0.488, P < 0.001, AUC 0.899). Combining all three imaging modalities variables also showed good predictive accuracy for outcome but did not improve on the CTP model (R2 0.439, P < 0.001, AUC 0.825). CT perfusion predicts patient outcomes from alteplase therapy more accurately than models incorporating NCCT and/or CT angiography. This data has implications for artificial intelligence or machine learning models.

The development of reperfusion therapies has profoundly impacted stroke care, initially with the advent of IV thrombolytic treatment and, more recently, with the development and refinement of endovascular treatment (EVT). Progress in neuroim-aging has supported the paradigm shift of stroke care, and advanced neuroimaging now has a fundamental role in triaging patients for both IV thrombolytic treatment and EVT. As the standard of care for acute ischemic stroke (AIS) evolves, controversies remain in certain clinical scenarios. This article explores the use of multimodality imaging for treatment selection of patients with AIS in the context of recent guidelines, highlighting controversial topics and providing guidance for clinical practice. The results of major randomized trials supporting EVT are reviewed. The advantages and disadvantages of CT, CTA, MRI, and MRA in stroke diagnosis are summarized with attention to level 1 evidence supporting the role of vascular imaging and perfusion imaging. Patient selection is compared between approaches based on time thresholds and physiologic approaches based on infarct core measurement using imaging. Moreover, various imaging approaches to core measurement are described. As ongoing studies push treatment boundaries, advanced imaging is expected to help identify a widening range of patients who may benefit from therapy.

The computed tomography angiography (CTA) spot sign is widely used to assess the risk of hematoma expansion following acute intracerebral hemorrhage (ICH). However, not all patients can receive intravenous contrast nor are all hospital systems equipped with this technology. We aimed to independently validate the Hematoma Expansion Prediction (HEP) Score, an 18-point non-contrast prediction scale, in an external cohort and compare its diagnostic capability to the CTA spot sign. We performed a retrospective analysis of the predicting hematoma growth and outcome in intracerebral hemorrhage using contrast bolus CT (PREDICT) Cohort Study. Primary outcome was significant hematoma expansion (≥ 6 mL or ≥ 33%). We generated a receiver operating characteristic (ROC) curve comparing the HEP score to significant expansion. We calculated sensitivity, specificity, positive and negative predictive values (PPV/NPV) for each score point. We determined independent predictors of significant hematoma expansion via logistic regression. A total of 292 patients were included in primary analysis. Hematoma growth of ≥ 6 mL or ≥ 33% occurred in 94 patients (32%). The HEP score was associated with significant expansion (adjusted odds ratio [aOR] 1.14, 95% confidence interval [CI] 1.01–1.30). ROC curves comparing HEP score to significant expansion had an area under the curve of 0.64 (95% CI 0.57–0.71). Youden’s method showed an optimum score of 4. HEP Scores ≥ 4 (n = 100, sensitivity 49%, specificity 73%, PPV 46%, NPV 75%, aOR 1.99, 95% CI 1.09–3.64) accurately predicted significant expansion. PPV increased with higher HEP scores, but at the cost of lower sensitivity. The diagnostic characteristics of the spot sign (n = 82, Sensitivity 49%, Specificity 81%, PPV 55%, NPV 76%, aOR 2.95, 95% CI 1.61–5.42) were similar to HEP scores ≥ 4. The HEP score is predictive of significant expansion (≥ 6 mL or ≥ 33%) and is comparable to the spot sign in diagnostic accuracy. Non-contrast prediction tools may have a potential role in the recruitment of patients in future intracerebral hemorrhage trials.

In forensic investigations of unknown skeletal remains, a biological profile is used to narrow the pool of potential matches in the missing person’s database; one of the important component...

BACKGROUND Diagnostic neurovascular imaging data are important in stroke research, but obtaining these data typically requires laborious manual chart reviews. OBJECTIVE We aimed to determine the accuracy of a natural language processing (NLP) approach to extract information on the presence and location of vascular occlusions as well as other stroke-related attributes based on free-text reports. METHODS From the full reports of 1320 consecutive computed tomography (CT), CT angiography, and CT perfusion scans of the head and neck performed at a tertiary stroke center between October 2017 and January 2019, we manually extracted data on the presence of proximal large vessel occlusion (primary outcome), as well as distal vessel occlusion, ischemia, hemorrhage, Alberta stroke program early CT score (ASPECTS), and collateral status (secondary outcomes). Reports were randomly split into training (n=921) and validation (n=399) sets, and attributes were extracted using rule-based NLP. We reported the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the overall accuracy of the NLP approach relative to the manually extracted data. RESULTS The overall prevalence of large vessel occlusion was 12.2%. In the training sample, the NLP approach identified this attribute with an overall accuracy of 97.3% (95.5% sensitivity, 98.1% specificity, 84.1% PPV, and 99.4% NPV). In the validation set, the overall accuracy was 95.2% (90.0% sensitivity, 97.4% specificity, 76.3% PPV, and 98.5% NPV). The accuracy of identifying distal or basilar occlusion as well as hemorrhage was also high, but there were limitations in identifying cerebral ischemia, ASPECTS, and collateral status. CONCLUSIONS NLP may improve the efficiency of large-scale imaging data collection for stroke surveillance and research.

Background and Purpose— The Graeb score is a visual rating scale of intraventricular hemorrhage (IVH) on noncontrast head CT. Little data exist in the hyperacute ( Methods— A retrospective analysis of multicenter prospective intracranial hemorrhage study was performed. oGS and mGS inter-observer agreement and IVH volume correlation on the baseline noncontrast head CT were calculated by intraclass correlation coefficient and Pearson coefficient respectively. Predictors of poor outcome (modified Rankin Scale scores ≥4) at 3 months were identified using a backward stepwise selection multivariable analysis. oGS and mGS performance for modified Rankin Scale scores ≥4 was determined by receiver operating characteristic analysis. Results— One hundred forty-one patients (65±12 years) with median (interquartile range) time to CT of 82.5 (70.3–157.5) minutes were included. IVH was observed in 43 (30%) patients. Inter-observer agreement was excellent for both oGS (intraclass correlation coefficient, 0.90 [95% CI, 0.80–0.95]) and mGS (intraclass correlation coefficient, 0.97 [95% CI, 0.84–0.99]). mGS (R=0.79; P P P =0.02). Models of thresholded oGS and mGS were not different from a model of planimetric baseline intracranial hemorrhage and IVH volume for poor outcome prediction. Area under the curves were 0.70, 0.73, and 0.72, respectively. Conclusions— Excellent correlation for oGS and mGS with IVH volume was seen. Thresholded oGS and mGS are reasonable surrogates for planimetric IVH volume for hyperacute intracranial hemorrhage studies.

An 81-year-old woman presented to the hospital after a week of intermittent episodes of decreased level of consciousness, right facial droop, and slurred speech, lasting approximately 30 minutes. Her medical history included chronic obstructive pulmonary disease, dyslipidemia, orthostatic hypotension, and 2 previous TIAs. She had fallen once in the preceding week, presumably as a result of her drowsiness. On examination, she was afebrile with a heart rate of 81 bpm and a blood pressure of 108/65 mm Hg. She was alert and cooperative, but disoriented to the year and location. Language examination was normal. Cranial nerves, motor, coordination, and sensory examinations were all normal without any focal deficits. However, when assessed during one of her episodes, she was less responsive, had decreased verbal output, and was noted to have a right facial droop. Basic serologic tests (complete blood count, electrolytes, renal function tests) were unremarkable. A head CT showed bilateral subarachnoid hemorrhage over the cerebral hemispheres without further abnormality.

ObjectiveTo determine whether the ABC/2 method could accurately and reliably measure infarct volume and guide thrombectomy decision in acute stroke cases presenting with late or unknown onset.MethodsFour physicians who routinely use MRI for acute stroke imaging, blinded to the RAPID results, measured the diffusion-weighted imaging (DWI) infarct volume using the ABC/2 method. Measurements with ABC/2 (the index test) were compared with RAPID (the reference standard) to calculate sensitivity, specificity, and accuracy measures for various volume cutpoints. Thrombectomy decisions based on RAPID and raters' measurements using the criteria from the Diffusion-Weighted Imaging or Computerized Tomography Perfusion Assessment With Clinical Mismatch in the Triage of Wake-Up and Late-Presenting Strokes Undergoing Neurointervention With Trevo (DAWN) trial criteria were compared. Interrater and intrarater agreement was measured using kappa statistics.ResultsAccuracy with the ABC/2 method was greater than 80% for each rater and each volume cut point. Interrater and intrarater agreement was substantial to excellent for each volume cut point. Treatment decisions with ABC/2 volume estimations showed strong interrater and intrarater agreement, and led to similar thrombectomy decisions compared with RAPID in more than 85% of cases.ConclusionDWI infarct volume measurement using ABC/2 method shows strong accuracy and reliability and may be an acceptable alternative to RAPID software for the application of DAWN criteria for thrombectomy decision-making.

BACKGROUND AND PURPOSE: Graph theory uses structural similarity to analyze cortical structural connectivity. We used a voxel-based definition of cortical covariance networks to quantify and assess the relationship of network characteristics to cognition in a cohort of patients with relapsing-remitting MS with and without cognitive impairment. MATERIALS AND METHODS: We compared subject-specific structural gray matter network properties of 18 healthy controls, 25 patients with MS with cognitive impairment, and 55 patients with MS without cognitive impairment. Network parameters were compared, and predictive value for cognition was assessed, adjusting for confounders (sex, education, gray matter volume, network size and degree, and T1 and T2 lesion load). Backward stepwise multivariable regression quantified predictive factors for 5 neurocognitive domain test scores. RESULTS: Greater path length (r = –0.28, P < .0057) and lower normalized path length (r = 0.36, P < .0004) demonstrated a correlation with average cognition when comparing healthy controls with patients with MS. Similarly, MS with cognitive impairment demonstrated a correlation between lower normalized path length (r = 0.40, P < .001) and reduced average cognition. Increased normalized path length was associated with better performance for processing (P < .001), learning (P < .001), and executive domain function (P = .0235), while reduced path length was associated with better executive (P = .0031) and visual domains. Normalized path length improved prediction for processing (R(2) = 43.6%, G(2) = 20.9; P < .0001) and learning (R(2) = 40.4%, G(2) = 26.1; P < .0001) over a null model comprising confounders. Similarly, higher normalized path length improved prediction of average z scores (G(2) = 21.3; P < .0001) and, combined with WM volume, explained 52% of average cognition variance. CONCLUSIONS: Patients with MS and cognitive impairment demonstrate more random network features and reduced global efficiency, impacting multiple cognitive domains. A model of normalized path length with normal-appearing white matter volume improved average cognitive z score prediction, explaining 52% of variance.

Introduction: We sought to train and validate an automated machine learning algorithm for ICH segmentation and volume calculation using multicenter data. Methods: An open-source 3D deep machine learning algorithm “DeepMedic” was trained using manually segmented ICH from 208 CT scans (129 patients) from the multicenter PREDICT study. The algorithm was then validated with 125 manually segmented CT scans (48 patients) from the SPOTLIGHT study. Manual segmentation was performed with Quantomo semi-automated software. ABC/2 was measured for all studies by two neuroradiologists. Accuracy of DeepMedic segmentation was assessed using the Dice similarity coefficient. Analysis was stratified by presence of IVH. Intraclass correlation (ICC) with 95% confidence intervals (CI) assessed agreement between manual vs. DeepMedic segmentation volume; and manual segmentation and ABC/2 volume. Bland-Altman charts were analyzed for ABC/2 and DeepMedic vs. manual segmentation volumes. Results: DeepMedic demonstrated high segmentation accuracy in the training cohort (median Dice 0.96; IQR 0.95 - 0.97) and in the validation cohort (median Dice 0.91; IQR 0.86 - 0.94). Dice coefficients were not significantly different between patients with IVH in the training cohort; however was significantly worse in the validation cohort in patients with IVH (Wilcoxon p Conclusion: ICH machine learning segmentation with DeepMedic is feasible and accurate; and demonstrates greater agreement with manual segmentation compared to ABC/2 volumes. Accuracy of the machine learning algorithm however is limited in patients with IVH.

Introduction: Diagnostic imaging reports contain important data for stroke surveillance and clinical research but converting a large amount of free-text data into structured data with manual chart abstraction is resource-intensive. We determined the accuracy of CHARTextract, a natural language processing (NLP) tool, to extract relevant stroke-related attributes from full reports of computed tomograms (CT), CT angiograms (CTA), and CT perfusion (CTP) performed at a tertiary stroke centre. Methods: We manually extracted data from full reports of 1,320 consecutive CT/CTA/CTP performed between October 2017 and January 2019 in patients presenting with acute stroke. Trained chart abstractors collected data on the presence of anterior proximal occlusion, basilar occlusion, distal intracranial occlusion, established ischemia, haemorrhage, the laterality of these lesions, and ASPECT scores, all of which were used as a reference standard. Reports were then randomly split into a training set (n= 921) and validation set (n= 399). We used CHARTextract to extract the same attributes by creating rule-based information extraction pipelines. The rules were human-defined and created through an iterative process in the training sample and then validated in the validation set. Results: The prevalence of anterior proximal occlusion was 12.3% in the dataset (n=86 left, n=72 right, and n=4 bilateral). In the training sample, CHARTextract identified this attribute with an overall accuracy of 97.3% (PPV 84.1% and NPV 99.4%, sensitivity 95.5% and specificity 97.5%). In the validation set, the overall accuracy was 95.2% (PPV 76.3% and NPV 98.5%, sensitivity 90.0% and specificity 96.0%). Conclusions: We showed that CHARTextract can identify the presence of anterior proximal vessel occlusion with high accuracy, suggesting that NLP can be used to automate the process of data collection for stroke research. We will present the accuracy of CHARTextract for the remaining neurological attributes at ISC 2020.

Introduction: Hematoma expansion is a predictor of poor clinical outcome in intracerebral hemorrhage (ICH). The CT angiography (CTA) spot sign is a validated predictor of hematoma expansion, but its predictive performance is modest. This is in part because traditional “static” CTA can miss delayed spot signs, depending on the timing of image acquisition. Dynamic CTA (dCTA) can detect delayed spot sign formation and allows calculation of contrast extravasation rate. However, the predictive performance of a delayed “dynamic spot” and the relationship between rate of extravasation and hematoma expansion are not known. Our primary objective was to calculate the prevalence and predictive performance of the dynamic spot sign with dCTA. Our secondary objective was to determine whether the rate of contrast extravasation predicts significant hematoma expansion. Methods: We prospectively enrolled 79 patients who presented with primary ICH and underwent dCTA within 6 hours from onset. Primary outcomes were the prevalence of dCTA spot sign and its predictive performance for significant hematoma expansion (increase in hematoma by 6mL or 33% from baseline). For the secondary objective, we calculated the rate of contrast extravasation as the slope of the time curve from the first appearance of contrast at a spot sign to the maximal volume of contrast in 19 acquisitions over 60 seconds. We assessed the relationship between rate of extravasation and hematoma expansion using Mann-Whitney U test and logistic regression. Results: The prevalence of the dCTA spot sign was 45.6% (95% CI, 34.5-56.6%). Significant HE was seen in 58.1% (18/31) of spot-positive patients versus 29.0% (9/31) of spot-negative patients (P=0.04). The sensitivity and specificity of the dCTA spot sign in predicting significant HE was 67% and 63%, respectively. Median rate of extravasation was 0.0022 mL/min in patients with hematoma expansion vs 0.0013 mL/min in those without (p=0.05). Conclusion: Dynamic CTA had a higher spot sign prevalence than conventional CTA. While the sensitivity in predicting expansion was higher with dCTA, the specificity was lower, possibly due to a lower risk of expansion with delayed spot signs. The rate of extravasation was roughly double in patients with hematoma expansion.

Objective To assess the risk of recurrent ipsilateral ischemic stroke in patients with symptomatic near-occlusion with and without full collapse. Methods Included were consecutive patients eligible for revascularization, grouped into symptomatic conventional ≥ 50% carotid stenosis (n = 266), near-occlusion without full collapse (n = 57) and near-occlusion with full collapse (n = 42). The risk of preoperative recurrent ipsilateral ischemic stroke was analyzed, or, for cases not revascularized within 90 days, 90-day risk was analyzed. Results The risk of a preoperative recurrent ipsilateral ischemic stroke or ipsilateral retinal artery occlusion was 15% (95% CI 9–20%) for conventional ≥ 50% stenosis, 22% (95% CI 6–38%) among near-occlusion without full collapse and 30% (95% CI 16–44%) among near-occlusion with full collapse (p = 0.01, log rank test). In multivariate analysis, near-occlusion with full collapse had a higher risk of recurrent ipsilateral ischemic stroke (adjusted HR 2.6, 95% CI 1.3–5.3) and near-occlusion without full collapse tended to have a higher risk (adjusted HR 2.0, 95% CI 0.9–4.5) than conventional ≥ 50% stenosis. Only 24% of near-occlusion with full collapse underwent revascularization, common causes for abstaining were misdiagnosis as occlusion (31%), deemed surgically unfeasible (21%) and low perceived benefit (10%). Conclusions Symptomatic carotid near-occlusion has a high short-term risk of recurrent ipsilateral ischemic stroke, especially near-occlusion with full collapse.

Background and Purpose— Although perfusion abnormality is an increasingly important therapeutic target, the natural history of tissue at risk without reperfusion treatment is understudied. Our objective was to determine how time affects penumbral salvage and infarct growth in untreated acute ischemic stroke patients and whether collateral status affects this relationship. Methods— We used a prospectively collected, multicenter acute stroke registry to assess acute stroke patients who were not treated with intravenous thrombolysis or endovascular treatment. We analyzed baseline computed tomography angiogram and computed tomography perfusion within 24 hours of stroke onset along with follow-up imaging and assessed time from stroke onset to baseline imaging, ASPECTS (Alberta Stroke Program Early CT Score), vessel occlusion, collaterals, ischemic core, and penumbra. Penumbral salvage and infarct growth were calculated. Correlations between time and penumbral salvage and infarct growth were evaluated with Spearman correlation. Penumbral salvage and infarct growth were compared between subjects with good versus poor collateral status using the Wilcoxon rank-sum test. Clinical and imaging factors affecting penumbral salvage and infarct growth were evaluated by linear regression. Results— Among 94 untreated stroke patients eligible for this analysis, the mean age was 65 years, median National Institutes of Health Stroke Scale score was 13, and median (range) time from stroke onset to baseline imaging was 2.9 (0.4–23) hours. There was no correlation between time and salvaged penumbra ( r =0.06; P =0.56) or infarct growth ( r =−0.05; P =0.61). Infarct growth was higher among those with poor collaterals versus those with good collaterals (median, 52.3 versus 0.9 cm 3 ; P 3 [0–29.4]; P Conclusions— In this natural history study, penumbral salvage and infarct growth were less time dependent and more a measure of collateral flow.

Purpose:The aim was to assess the ability of post-treatment diffusion-weighted imaging (DWI) to predict 90-day functional outcome in patients with endovascular therapy (EVT) for large vessel occlusion in acute ischemic stroke (AIS).Methods:We examined a retrospective cohort from March 2016 to January 2018, of consecutive patients with AIS who received EVT. Planimetric DWI was obtained and infarct volume calculated. Four blinded readers were asked to predict modified Rankin Score (mRS) at 90 days post-thrombectomy.Results:Fifty-one patients received endovascular treatment (mean age 65.1 years, median National Institutes of Health Stroke Scale (NIHSS) 18). Mean infarct volume was 43.7 mL. The baseline NIHSS, 24-hour NIHSS, and the DWI volume were lower for the mRS 0–2 group. Also, the thrombolysis in cerebral infarction (TICI) 2b/3 rate was higher in the mRS 0–2 group. No differences were found in terms of the occlusion level, reperfusion technique, or recombinant tissue plasminogen activator use. There was a significant association noted between average infarct volume and mRS at 90 days. On multivariable analysis, higher infarct volume was significantly associated with 90-day mRS 3–5 when adjusted to TICI scores and occlusion location (OR 1.01; CI 95% 1.001–1.03; p = 0.008). Area under curve analysis showed poor performance of DWI volume reader ability to qualitatively predict 90-day mRS.Conclusion:The subjective impression of DWI as a predictor of clinical outcome is poorly correlated when controlling for premorbid status and other confounders. Qualitative DWI by experienced readers both overestimated the severity of stroke for patients who achieved good recovery and underestimated the mRS for poor outcome patients. Infarct core quantitation was reliable.

Background and Purpose— The intracerebral hemorrhage (ICH) score is the most commonly used grading scale for stratifying functional outcome in patients with acute ICH. We sought to determine whether a combination of the ICH score and the computed tomographic angiography spot sign may improve outcome prediction in the cohort of a prospective multicenter hemorrhage trial. Methods— Prospectively collected data from 241 patients from the observational PREDICT study (Prediction of Hematoma Growth and Outcome in Patients With Intracerebral Hemorrhage Using the CT-Angiography Spot Sign) were analyzed. Functional outcome at 3 months was dichotomized using the modified Rankin Scale (0–3 versus 4–6). Performance of (1) the ICH score and (2) the spot sign ICH score—a scoring scale combining ICH score and spot sign number—was tested. Results— Multivariable analysis demonstrated that ICH score (odds ratio, 3.2; 95% confidence interval, 2.2–4.8) and spot sign number (n=1: odds ratio, 2.7; 95% confidence interval, 1.1–7.4; n>1: odds ratio, 3.8; 95% confidence interval, 1.2–17.1) were independently predictive of functional outcome at 3 months with similar odds ratios. Prediction of functional outcome was not significantly different using the spot sign ICH score compared with the ICH score alone (spot sign ICH score area under curve versus ICH score area under curve: P =0.14). Conclusions— In the PREDICT cohort, a prognostic score adding the computed tomographic angiography–based spot sign to the established ICH score did not improve functional outcome prediction compared with the ICH score.

Background and Purpose— Although the computed tomographic angiography spot sign performs well as a biomarker for hematoma expansion (HE), computed tomographic angiography is not routinely performed in the emergency setting. We developed and validated a score to predict HE-based on noncontrast computed tomography (NCCT) findings in spontaneous acute intracerebral hemorrhage. Methods— After developing the score in a single-center cohort of patients with intracerebral hemorrhage (n=344), we validated it in a large clinical trial population (n=954) and in a multicenter intracerebral hemorrhage cohort (n=241). The following NCCT markers of HE were analyzed: hypodensities, blend sign, hematoma shape and density, and fluid level. HE was defined as hematoma growth >6 mL or >33%. The score was created using the estimates from multivariable logistic regression after final predictors were selected from bootstrap samples. Results— Presence of blend sign (odds ratio, 3.09; 95% confidence interval [CI],1.49–6.40; P =0.002), any intrahematoma hypodensity (odds ratio, 4.54; 95% CI, 2.44–8.43; P P =0.0002) were predictors of HE. A 5-point score was created (BAT score: 1 point for blend sign, 2 points for any hypodensity, and 2 points for timing of NCCT Conclusions— An easy to use 5-point prediction score can identify subjects at high risk of HE with good specificity and accuracy. This tool requires just a baseline NCCT scan and may help select patients with intracerebral hemorrhage for antiexpansion clinical trials.

Background Intraosseous vascular anomalies (IOVA) are rare in the craniofacial skeleton and present a diagnostic and therapeutic challenge. This study aims to describe the clinical management based on a large case series. Methods A retrospective chart review was performed and 9 IOVA were identified over a 15-year period. Data on demographics, diagnostic features, clinical management, and outcomes were reviewed. Results Five frontal bone IOVA and 4 orbital IOVA were identified. The postoperative follow-up ranged from 4 months to 4 years. All 9 lesions were diagnosed with computed tomography (CT) imaging. Magnetic resonance imaging (MRI) was used to delineate soft tissue involvement in 2 patients presenting with oculo-orbital dystopia and ophthalmoplegia. En bloc excision was performed in all patients. Preoperative interventional embolization was critical in the successful resection of an orbital IOVA following 2 previously failed attempts that were aborted secondary to hemorrhage. Intraoperative 3-dimensional stereotactic navigation was used for the accurate en bloc excision of a frontal IOVA to prevent injury to the frontal sinus. Reconstruction of esthetic and functional deformities was successfully accomplished. Conclusion The diagnosis of IOVA relies primarily on clinical assessment and CT imaging. Further interpretation of the involvement of periorbital, facial, and intracranial soft tissue is best defined by MRI. Multidisciplinary care with interventional radiology and neurosurgery must be considered for ensuring the safe and adequate en bloc excision of craniofacial IOVA.