CSF-Based Volumetric Imaging Biomarkers Highlight Incidence and Risk Factors for Cerebral Edema After Ischemic Stroke.

BACKGROUND: Cerebral edema has primarily been studied using midline shift or clinical deterioration as end points, which only captures the severe and delayed manifestations of a process affecting many patients with stroke. Quantitative imaging biomarkers that measure edema severity across the entire spectrum could improve its early detection, as well as identify relevant mediators of this important stroke complication. METHODS: We applied an automated image analysis pipeline to measure the displacement of cerebrospinal fluid (ΔCSF) and the ratio of lesional versus contralateral hemispheric cerebrospinal fluid (CSF) volume (CSF ratio) in a cohort of 935 patients with hemispheric stroke with follow-up computed tomography scans taken a median of 26 h (interquartile range 24-31) after stroke onset. We determined diagnostic thresholds based on comparison to those without any visible edema. We modeled baseline clinical and radiographic variables against each edema biomarker and assessed how each biomarker was associated with stroke outcome (modified Rankin Scale at 90 days). RESULTS: The displacement of CSF and CSF ratio were correlated with midline shift (r = 0.52 and - 0.74, p < 0.0001) but exhibited broader ranges. A ΔCSF of greater than 14% or a CSF ratio below 0.90 identified those with visible edema: more than half of the patients with stroke met these criteria, compared with only 14% who had midline shift at 24 h. Predictors of edema across all biomarkers included a higher National Institutes of Health Stroke Scale score, a lower Alberta Stroke Program Early CT score, and lower baseline CSF volume. A history of hypertension and diabetes (but not acute hyperglycemia) predicted greater ΔCSF but not midline shift. Both ΔCSF and a lower CSF ratio were associated with worse outcome, adjusting for age, National Institutes of Health Stroke Scale score, and Alberta Stroke Program Early CT score (odds ratio 1.7, 95% confidence interval 1.3-2.2 per 21% ΔCSF). CONCLUSIONS: Cerebral edema can be measured in a majority of patients with stroke on follow-up computed tomography using volumetric biomarkers evaluating CSF shifts, including in many without visible midline shift. Edema formation is influenced by clinical and radiographic stroke severity but also by chronic vascular risk factors and contributes to worse stroke outcomes.

The relevance of rich club regions for functional outcome post-stroke is enhanced in women.

This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS > 2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.

Multi-ancestry GWAS reveals excitotoxicity associated with outcome after ischaemic stroke.

During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6 h of stroke onset and NIHSS at 24 h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24 h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke.

Single nucleotide variations in ZBTB46 are associated with post-thrombolytic parenchymal haematoma.

Haemorrhagic transformation is a complication of recombinant tissue-plasminogen activator treatment. The most severe form, parenchymal haematoma, can result in neurological deterioration, disability, and death. Our objective was to identify single nucleotide variations associated with a risk of parenchymal haematoma following thrombolytic therapy in patients with acute ischaemic stroke. A fixed-effect genome-wide meta-analysis was performed combining two-stage genome-wide association studies (n = 1904). The discovery stage (three cohorts) comprised 1324 ischaemic stroke individuals, 5.4% of whom had a parenchymal haematoma. Genetic variants yielding a P-value < 0.05 1 × 10-5 were analysed in the validation stage (six cohorts), formed by 580 ischaemic stroke patients with 12.1% haemorrhagic events. All participants received recombinant tissue-plasminogen activator; cases were parenchymal haematoma type 1 or 2 as defined by the European Cooperative Acute Stroke Study (ECASS) criteria. Genome-wide significant findings (P < 5 × 10-8) were characterized by in silico functional annotation, gene expression, and DNA regulatory elements. We analysed 7 989 272 single nucleotide polymorphisms and identified a genome-wide association locus on chromosome 20 in the discovery cohort; functional annotation indicated that the ZBTB46 gene was driving the association for chromosome 20. The top single nucleotide polymorphism was rs76484331 in the ZBTB46 gene [P = 2.49 × 10-8; odds ratio (OR): 11.21; 95% confidence interval (CI): 4.82-26.55]. In the replication cohort (n = 580), the rs76484331 polymorphism was associated with parenchymal haematoma (P = 0.01), and the overall association after meta-analysis increased (P = 1.61 × 10-8; OR: 5.84; 95% CI: 3.16-10.76). ZBTB46 codes the zinc finger and BTB domain-containing protein 46 that acts as a transcription factor. In silico studies indicated that ZBTB46 is expressed in brain tissue by neurons and endothelial cells. Moreover, rs76484331 interacts with the promoter sites located at 20q13. In conclusion, we identified single nucleotide variants in the ZBTB46 gene associated with a higher risk of parenchymal haematoma following recombinant tissue-plasminogen activator treatment.

Performance of Automated RAPID Intracranial Hemorrhage Detection in Real-World Practice: A Single-Institution Experience.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is a common finding in patients presenting to the emergency department with acute neurological symptoms. Noncontrast head computed tomography (NCCT) is the primary modality for assessment and detection of ICH in the acute setting. RAPID ICH software aims to automatically detect ICH on NCCT and was previously shown to have high accuracy when applied to a curated test data set. Here, we measured the test performance characteristics of RAPID ICH software in detecting ICH on NCCT performed in patients undergoing emergency stroke evaluation at a tertiary academic comprehensive stroke center. MATERIALS AND METHODS: This retrospective study assessed consecutive patients over a 6-month period who presented with acute neurological symptoms suspicious for stroke and underwent NCCT with RAPID ICH postprocessing. RAPID ICH detection was compared with the interpretation of a reference standard comprising a board-certified or board-eligible neuroradiologist, or in cases of discrepancy, adjudicated by a consensus panel of 3 neuroradiologists. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RAPID ICH for ICH detection were determined. RESULTS: Three hundred seven NCCT scans were included in the study. RAPID ICH correctly identified 34 of 37 cases with ICH and 228 of 270 without ICH. RAPID ICH had a sensitivity of 91.9% (78.1%-98.3%), specificity of 84.4% (79.6%-88.6%), NPV of 98.7% (96.3%-99.6%), PPV of 44.7% (37.6%-52.1%), and overall accuracy of 85.3% (80.9%-89.1%). CONCLUSIONS: In a real-world scenario, RAPID ICH software demonstrated high NPV but low PPV for the presence of ICH when evaluating possible stroke patients.

Accurate Prediction of Persistent Upper Extremity Impairment in Patients With Ischemic Stroke.

OBJECTIVE: To develop a simple and effective risk score for predicting which stroke patients will have persistent impairment of upper extremity motor function at 90 days. DESIGN: Post hoc analysis of clinical trial patients hospitalized with acute ischemic stroke who were followed for 90 days to determine functional outcome. SETTING: Patient were hospitalized at facilities across the United States. PARTICIPANTS: We created a harmonized cohort of individual patients (N=1653) from the NINDS tPA, ALIAS part 2, IMS-III, DEFUSE 3, and FAST-MAG trials. We split the cohort into balanced derivation and validation samples. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The primary outcome was persistent arm impairment, defined as a National Institutes of Health Stroke Scale (NIHSS) arm domain score of 2 to 4 at 90 days in patients who had a 24-hour NIHSS arm score of 1 or more. We used least absolute shrinkage and selection operator regression to determine the elements of the persistent upper extremity impairment (PUPPI) index, which we validated as a predictive tool. RESULTS: We included 1653 patients (827 derivation, 826 validation), of whom 803 (48.6%) had persistent arm impairment. The PUPPI index gives 1 point each for age 55 years or older and NIHSS values of worse arm (4), worse leg (>2), facial palsy (3), and total NIHSS (≥10). The optimal cutpoint for the PUPPI index was 3 or greater, at which the area under the curve was greater than 0.75 for the derivation and validation cohorts and when using NIHSS values from either 24 hours or in a subacute or discharge time window. Results were similar across different levels of stroke severity. CONCLUSION: The PUPPI index uses readily available information to accurately predict persistent upper extremity motor impairment at 90 days poststroke. The PUPPI index can be administered in minutes and could be used as inclusion criterion in recovery-related clinical trials or, with additional development, as a prognostic tool for patients, caregivers, and clinicians.

Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks.

BACKGROUND: Malignant cerebral edema is a devastating complication of stroke, resulting in deterioration and death if hemicraniectomy is not performed prior to herniation. Current approaches for predicting this relatively rare complication often require advanced imaging and still suffer from suboptimal performance. We performed a pilot study to evaluate whether neural networks incorporating data extracted from routine computed tomography (CT) imaging could enhance prediction of edema in a large diverse stroke cohort. METHODS: An automated imaging pipeline retrospectively extracted volumetric data, including cerebrospinal fluid (CSF) volumes and the hemispheric CSF volume ratio, from baseline and 24 h CT scans performed in participants of an international stroke cohort study. Fully connected and long short-term memory (LSTM) neural networks were trained using serial clinical and imaging data to predict those who would require hemicraniectomy or die with midline shift. The performance of these models was tested, in comparison with regression models and the Enhanced Detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score, using cross-validation to construct precision-recall curves. RESULTS: Twenty of 598 patients developed malignant edema (12 required surgery, 8 died). The regression model provided 95% recall but only 32% precision (area under the precision-recall curve [AUPRC] 0.74), similar to the EDEMA score (precision 28%, AUPRC 0.66). The fully connected network did not perform better (precision 33%, AUPRC 0.71), but the LSTM model provided 100% recall and 87% precision (AUPRC 0.97) in the overall cohort and the subgroup with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 (p = 0.0001 vs. regression and fully connected models). Features providing the most predictive importance were the hemispheric CSF ratio and NIHSS score measured at 24 h. CONCLUSIONS: An LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients for surgery prior to deterioration.

Early Neurological Change After Ischemic Stroke Is Associated With 90-Day Outcome.

BACKGROUND AND PURPOSE: Large-scale observational studies of acute ischemic stroke (AIS) promise to reveal mechanisms underlying cerebral ischemia. However, meaningful quantitative phenotypes attainable in large patient populations are needed. We characterize a dynamic metric of AIS instability, defined by change in National Institutes of Health Stroke Scale score (NIHSS) from baseline to 24 hours baseline to 24 hours (NIHSSbaseline - NIHSS24hours = ΔNIHSS6-24h), to examine its relevance to AIS mechanisms and long-term outcomes. METHODS: Patients with NIHSS prospectively recorded within 6 hours after onset and then 24 hours later were enrolled in the GENISIS study (Genetics of Early Neurological Instability After Ischemic Stroke). Stepwise linear regression determined variables that independently influenced ΔNIHSS6-24h. In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS6-24h was examined. Finally, the association of ΔNIHSS6-24h with 90-day favorable outcomes (modified Rankin Scale score 0-2) was assessed. Independent analysis was performed using data from the 2 NINDS-tPA stroke trials (National Institute of Neurological Disorders and Stroke rt-PA). RESULTS: For 2555 patients with AIS, median baseline NIHSS was 9 (interquartile range, 4-16), and median ΔNIHSS6-24h was 2 (interquartile range, 0-5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS6-24h (R2=0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R2=0.27), but much of the variance remained unexplained. ΔNIHSS6-24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS3-24h was similarly associated with 90-day outcomes. CONCLUSIONS: The dynamic phenotype, ΔNIHSS6-24h, captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS6-24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.

PATJ Low Frequency Variants Are Associated With Worse Ischemic Stroke Functional Outcome.

RATIONALE: Ischemic stroke is among the leading causes of adult disability. Part of the variability in functional outcome after stroke has been attributed to genetic factors but no locus has been consistently associated with stroke outcome. OBJECTIVE: Our aim was to identify genetic loci influencing the recovery process using accurate phenotyping to produce the largest GWAS (genome-wide association study) in ischemic stroke recovery to date. METHODS AND RESULTS: A 12-cohort, 2-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent ischemic stroke cases. Functional outcome was recorded using 3-month modified Rankin Scale. Analyses were adjusted for confounders such as discharge National Institutes of Health Stroke Scale. A gene-based burden test was performed. The discovery phase (n=1225) was followed by open (n=2482) and stringent joint-analyses (n=1791). Those cohorts with modified Rankin Scale recorded at time points other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in PATJ (Pals1-associated tight junction) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, ß=0.40, P=1.70×10-9). CONCLUSIONS: Our results identify a set of common variants in PATJ gene associated with 3-month functional outcome at genome-wide significance level. Future studies should examine the role of PATJ in stroke recovery and consider stringent phenotyping to enrich the information captured to unveil additional stroke outcome loci.

Reduction in Cerebrospinal Fluid Volume as an Early Quantitative Biomarker of Cerebral Edema After Ischemic Stroke.

Background and Purpose- Cerebral edema (CED) develops in the hours to days after stroke; the resulting increase in brain volume may lead to midline shift (MLS) and neurological deterioration. The time course and implications of edema formation are not well characterized across the spectrum of stroke. We analyzed displacement of cerebrospinal fluid (ΔCSF) as a dynamic quantitative imaging biomarker of edema formation. Methods- We selected subjects enrolled in a stroke cohort study who presented within 6 hours of onset and had baseline and ≥1 follow-up brain computed tomography scans available. We applied a neural network-based algorithm to quantify hemispheric CSF volume at each imaging time point and modeled CSF trajectory over time (using a piecewise linear mixed-effects model). We evaluated ΔCSF within the first 24 hours as an early biomarker of CED (defined as developing MLS on computed tomography beyond 24 hours) and poor outcome (modified Rankin Scale score, 3-6). Results- We had serial imaging in 738 subjects with stroke, of whom 91 (13%) developed CED with MLS. Age did not differ (69 versus 70 years), but baseline National Institutes of Health Stroke Scale was higher (16 versus 7) and baseline CSF volume lower (132 versus 161 mL, both P<0.001) in those with CED. ΔCSF was faster in those developing MLS, with the majority seen by 24 hours (36% versus 11% or 2.4 versus 0.8 mL/h; P<0.0001). Risk of CED almost doubled for every 10% ΔCSF within 24 hours (odds ratio, 1.76 [95% CI, 1.46-2.14]), adjusting for age, glucose, and National Institutes of Health Stroke Scale. Risk of neurological deterioration (1.6-point increase in National Institutes of Health Stroke Scale at 24 hours) and poor outcome (adjusted odds ratio, 1.34 [95% CI, 1.15-1.56]) was also greater for every 10% increase in ΔCSF. Conclusions- CSF volumetrics provides quantitative evaluation of early edema formation. ΔCSF from baseline to 24-hour computed tomography is a promising early biomarker for the development of MLS and worse neurological outcome.

Quantitative Serial CT Imaging-Derived Features Improve Prediction of Malignant Cerebral Edema after Ischemic Stroke.

INTRODUCTION: Malignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-h. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema. METHODS: We identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-h clinical and CT imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-h data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC). RESULTS: Twenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66). CONCLUSION: Incorporating quantitative CT-based imaging features from baseline and 24-h CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine-learning models are required.

Overlap in the Genetic Architecture of Stroke Risk, Early Neurological Changes, and Cardiovascular Risk Factors.

Background and Purpose- The genetic relationships between stroke risk, stroke severity, and early neurological changes are complex and not completely understood. Genetic studies have identified 32 all stroke risk loci. Polygenic risk scores can be used to compare the genetic architecture of related traits. In this study, we compare the genetic architecture of stroke risk, stroke severity, and early neurological changes with that of 2 stroke risk factors: type 2 diabetes mellitus (T2DM) and hypertension. Methods- We assessed the degree of overlap in the genetic architecture of stroke risk, T2DM, hypertension, and 2 acute stroke phenotypes based on the National Institutes of Health Stroke Scale (NIHSS), which ranges from 0 for no stroke symptoms to 21 to 42 for a severe stroke: baseline (within 6 hours after onset) and change in NIHSS (ΔNIHSS=NIHSS at baseline-NIHSS at 24 hours). This was done by (1) single-nucleotide polymorphism by single-nucleotide polymorphism comparison, (2) weighted polygenic risk scores with sentinel variants, and (3) whole-genome polygenic risk scores using multiple P thresholds. Results- We found evidence of genetic architecture overlap between stroke risk and T2DM ( P=2.53×10-169), hypertension ( P=3.93×10-04), and baseline NIHSS ( P=0.03). However, there was no evidence of overlap between ΔNIHSS and stroke risk, T2DM, or hypertension. Conclusions- The genetic architecture of stroke risk is correlated with that of T2DM, hypertension, and initial stroke severity (NIHSS within 6 hours of stroke onset). However, the genetic architecture of early neurological change after stroke (ΔNIHSS) is not correlated with that of ischemic stroke risk, T2DM, or hypertension. Thus, stroke risk and early neurological change after stroke have distinct genetic architectures.

Genome-Wide Association Study of White Blood Cell Counts in Patients With Ischemic Stroke.

Background and Purpose- Immune cells play a key role in the first 24h poststroke (acute phase), being associated with stroke outcome. We aimed to find genetic risk factors associated with leukocyte counts during the acute phase of stroke. Methods- Ischemic stroke patients with leukocyte counts data during the first 24h were included. Genome-wide association study and gene expression studies were performed. Results- Our genome-wide association study, which included 2064 (Discovery) and 407 (Replication) patients, revealed a new locus (14q24.3) associated with leukocyte counts. After Joint analysis (n=2471) 5 more polymorphisms reached genome-wide significance (P<5×10-8). The 14q24.3 locus was associated with acute stroke outcome (rs112809786, P=0.036) and with ACOT1 and PTGR2 gene expression. Previous polymorphisms associated with leukocyte counts in general-population did not show any significance in our study. Conclusions- We have found the first locus associated with leukocyte counts in ischemic stroke, also associated with acute outcome. Genetic analysis of acute endophenotypes could be useful to find the genetic factors associated with stroke outcome. Our findings suggested a different modulation of immune cells in stroke compared with healthy conditions.

Genetic variation at 16q24.2 is associated with small vessel stroke.

OBJECTIVE: Genome-wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger-onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age-at-onset informed GWAS meta-analysis, including a large younger-onset SVS population, to identify novel associations with stroke. METHODS: We used a three-stage age-at-onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain. RESULTS: We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10-1.22]; p = 3.2 × 10-9 ). The lead single-nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05-1.16]; p = 5.3 × 10-5 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84-1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues (p = 9.4 × 10-7 ) and DNA methylation at probe cg16596957 in whole blood (p = 5.3 × 10-6 ). INTERPRETATION: 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383-394.

Streamlined Hyperacute Magnetic Resonance Imaging Protocol Identifies Tissue-Type Plasminogen Activator-Eligible Stroke Patients When Clinical Impression Is Stroke Mimic.

BACKGROUND AND PURPOSE: Stroke mimics (SM) challenge the initial assessment of patients presenting with possible acute ischemic stroke (AIS). When SM is considered likely, intravenous tissue-type plasminogen activator (tPA) may be withheld, risking an opportunity to treat AIS. Although computed tomography is routinely used for tPA decision making, magnetic resonance imaging (MRI) may diagnose AIS when SM is favored but not certain. We hypothesized that a hyperacute MRI (hMRI) protocol would identify tPA-eligible AIS patients among those initially favored to have SM. METHODS: A streamlined hMRI protocol was designed based on barriers to rapid patient transport, MRI acquisition, and post-MRI tPA delivery. Neurologists were trained to order hMRI when SM was favored and tPA was being withheld. The use of hMRI for tPA decision making, door-to-needle times, and outcomes were compared before hMRI implementation (pre-hMRI: August 1, 2011 to July 31, 2013) and after (post-hMRI, August 1, 2013, to January 15, 2015). RESULTS: Post hMRI, 57 patients with suspected SM underwent hMRI (median MRI-order-to-start time, 29 minutes), of whom, 11 (19%) were diagnosed with AIS and 7 (12%) received tPA. Pre-hMRI, no tPA-treated patients were screened with hMRI. Post hMRI, 7 of 106 (6.6%) tPA-treated patients underwent hMRI to aid in decision making because of suspected SM (0% versus 6.6%; P=0.001). To ensure standard care was maintained after implementing the hMRI protocol, pre- versus post-hMRI tPA-treated cohorts were compared and did not differ: door-to-needle time (39 versus 37 minutes; P=0.63), symptomatic hemorrhage rate (4.5% versus 1.9%; P=0.32), and favorable discharge location (85% versus 89%; P=0.37). CONCLUSIONS: A streamlined hMRI protocol permitted tPA administration to a small, but significant, subset of AIS patients initially considered to have SM.

CSF Volumetric Analysis for Quantification of Cerebral Edema After Hemispheric Infarction.

BACKGROUND: Malignant cerebral edema (CED) complicates at least 20 % of large hemispheric infarcts (LHI) and may result in neurological deterioration or death. Midline shift (MLS) is a standard but crude measure of edema severity. We propose that volumetric analysis of shifts in cerebrospinal fluid (CSF) over time provides a reliable means of quantifying the spectrum of edema severity after LHI. METHODS: We identified 38 patients from 2008 to 2014 with NIHSS ≥8, baseline CT <6 h after stroke onset, at least 1 follow-up (FU) CT, and no parenchymal hematoma. The volumes of CSF (sulci, ventricles, and cisterns) ipsilateral (IL) and contralateral (CL) to infarct on baseline and FU CTs were quantified by manually assisted outlining with MIPAV image analysis software, as was infarct volume and MLS on FU CTs. Percentage change in CSF volumes (∆CSF) from baseline to FU scans was correlated with MLS and compared in those with vs. without malignant edema (defined as hemicraniectomy, osmotic therapy, or death/neurological deterioration with MLS ≥5 mm). RESULTS: 11 of 38 subjects (29 %) developed malignant edema. Neither baseline NIHSS nor CSF volume differed between those with and without edema (median NIHSS 18 vs. 13, p = 0.12, CSF volume 102 vs. 124 ml, p = 0.16). Inter-rater reliability for CSF measurements was excellent (intraclass correlation coefficient 0.97). ∆CSF correlated strongly with MLS at peak edema (r = -0.75), even adjusting for infarct volume (p = 0.009). ∆CSF was also greater in those with malignant edema [-55 % (IQR -49 to -62) vs. -36 % (-27 to -45), p = 0.004]. ∆CSF was the greatest within IL sulci [-97 % (-86 to -99) vs. -71 % (-41 to -79), p = 0.002] but also significantly greater within CL sulci in those with malignant edema [-50 % (-29 to -65) vs. -25 % (0 to -31), p = 0.014]. More than half this CSF volume reduction occurred by the time of first FU CT around 24 h after stroke, while MLS rose later. CONCLUSIONS: Volumetric CSF analysis reliably quantifies CED and distinguishes those with malignant edema and MLS from those with a more benign course after LHI. ∆CSF may provide an earlier and more sensitive indicator of edema severity across a broader dynamic range than MLS.

Accuracy of emergency medical services-reported last known normal times in patients suspected with acute stroke.

BACKGROUND AND PURPOSE: The last known normal (LKN) time is a critical determinant of IV tissue-type plasminogen activator (IV tPA) eligibility; however, the accuracy of emergency medical services (EMS)-reported LKN times is unknown. We determined the congruence between neurologist-determined and EMS-reported LKN times and identified predictors of incongruent LKN times. METHODS: We prospectively collected EMS-reported LKN times for patients brought into the emergency department with suspected acute stroke and calculated the absolute difference between the neurologist-determined and EMS-reported LKN times (|ΔLKN|). We determined the rate of inappropriate IV tPA use if EMS-reported times had been used in place of neurologist-determined times. Univariate and multivariable linear regression assessed for any predictors of prolonged |ΔLKN|. RESULTS: Of 251 patients, mean and median |ΔLKN| were 28 and 0 minutes, respectively. |ΔLKN| was <15 minutes in 91% of the entire cohort and <15 minutes in 80% of patients with a diagnosis of stroke (n=86). Of patients who received IV tPA, none would have been incorrectly excluded from IV tPA if the EMS LKN time had been used. Conversely, of patients who did not receive IV tPA, 6% would have been incorrectly included for IV tPA consideration had the EMS time been used. In patients with wake-up stroke symptoms, EMS underestimated LKN times: mean neurologist LKN time-EMS LKN time=208 minutes. The presence of wake-up stroke symptoms (P<0.0001) and older age (P=0.019) were independent predictors of prolonged |ΔLKN|. CONCLUSIONS: EMS-reported LKN times were largely congruent with neurologist-determined times. Focused EMS training regarding wake-up stroke symptoms may further improve accuracy.

Profiles of the National Institutes of Health Stroke Scale items as a predictor of patient outcome.

BACKGROUND AND PURPOSE: Initial National Institutes of Health Stroke Scale (NIHSS) score is highly predictive of outcome after ischemic stroke. We examined whether grouping strokes by presence of individual NIHSS symptoms could provide prognostic information additional or alternative to the NIHSS total score. METHODS: Ischemic strokes from the Greater Cincinnati Northern Kentucky Stroke Study in 2005 were used to develop the model. Latent class analysis was implemented to form groups of patients with similar retrospective NIHSS (rNIHSS) item responses. Profile group was then used as an independent predictor of discharge modified Rankin and mortality, using logistic regression and Cox proportional hazards model. RESULTS: A total of 2112 stroke patients were identified in 2005. Six distinct profiles were characterized. Consistent with the profile patterns, the median rNIHSS total score decreased from profile A "most severe" (median [interquartile range], 20 [15-25]) to profile F "mild" (1[1-2]). Two profiles falling between these extremes, C and D, both had median rNIHSS total score of 5, but different survival rates. Compared with A, C was associated with 59% risk reduction for death, whereas D with 70%. C patients were more likely to have decreased level of consciousness and abnormal language, whereas D patients were more likely to have abnormal right arm and right leg motor function. CONCLUSIONS: Six rNIHSS profiles were identifiable using latent class analysis. In particular, 2 symptom profiles with identical median rNIHSSS were observed with widely disparate outcomes, which may prove useful both clinically and for research studies as an enhancement to the overall NIHSS score.

Imaging biomarkers of cerebral edema automatically extracted from routine CT scans of large vessel occlusion strokes.

BACKGROUND AND PURPOSE: Volumetric and densitometric biomarkers have been proposed to better quantify cerebral edema after stroke, but their relative performance has not been rigorously evaluated. METHODS: Patients with large vessel occlusion stroke from three institutions were analyzed. An automated pipeline extracted brain, cerebrospinal fluid (CSF), and infarct volumes from serial CTs. Several biomarkers were measured: change in global CSF volume from baseline (ΔCSF); ratio of CSF volumes between hemispheres (CSF ratio); and relative density of infarct region compared with mirrored contralateral region (net water uptake [NWU]). These were compared to radiographic standards, midline shift and relative hemispheric volume (RHV) and malignant edema, defined as deterioration resulting in need for osmotic therapy, decompressive surgery, or death. RESULTS: We analyzed 255 patients with 210 baseline CTs, 255 24-hour CTs, and 81 72-hour CTs. Of these, 35 (14%) developed malignant edema and 63 (27%) midline shift. CSF metrics could be calculated for 310 (92%), while NWU could only be obtained from 193 (57%). Peak midline shift was correlated with baseline CSF ratio (ρ = -.22) and with CSF ratio and ΔCSF at 24 hours (ρ = -.55/.63) and 72 hours (ρ = -.66/.69), but not with NWU (ρ = .15/.25). Similarly, CSF ratio was correlated with RHV (ρ = -.69/-.78), while NWU was not. Adjusting for age, National Institutes of Health Stroke Scale, tissue plasminogen activator treatment, and Alberta Stroke Program Early CT Score, CSF ratio (odds ratio [OR]: 1.95 per 0.1, 95% confidence interval [CI]: 1.52-2.59) and ΔCSF at 24 hours (OR: 1.87 per 10%, 95% CI: 1.47-2.49) were associated with malignant edema. CONCLUSION: CSF volumetric biomarkers can be automatically measured from almost all routine CTs and correlate better with standard edema endpoints than net water uptake.

Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes. METHODS: We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input. RESULTS: We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes. DISCUSSION: T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.