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BackgroundAccess to endovascular thrombectomy (EVT) is relatively limited. Hub‐and‐spoke networks seek to transfer appropriate large‐vessel occlusion stroke candidates to EVT‐capable hubs. However, some patients are ineligible upon hub arrival, and factors that drive transfer inefficiencies are not well described. We sought to quantify EVT transfer efficiency and identify reasons for EVT ineligibility.MethodsConsecutive EVT candidates presenting to 25 spokes from 2018 to 2020 with pretransfer computed tomography angiography‐defined large‐vessel occlusion and Alberta Stroke Program Early Computed Tomography Score of ≥6 were identified from a prospectively maintained database. Outcomes of interest included hub EVT, reasons for EVT ineligibility, and 90‐day modified Rankin scale score of ≤2.ResultsAmong 258 patients, the median age was 70 years (interquartile range, 60–81 years); 50% were women. A total of 56% were ineligible for EVT after hub arrival. Cited reasons were large established infarct (49%), mild symptoms (33%), recanalization (6%), distal occlusion (5%), subocclusive lesion (3%), and goals of care (3%). Late window patients (last known well >6 hours) were more likely to be ineligible (67% versus 43%;PP=0.04), had lower National Institutes of Health Stroke Scale score (10 versus 16;PPPP=0.04) compared with eligible patients. EVT ineligibility independently reduced the odds of 90‐day modified Rankin scale score of ≤2 (adjusted odds ratio, 0.26; 95% CI, 0.12–0.56;P=0.001) when controlling for age, National Institutes of Health Stroke Scale score, and last known well‐to‐hub arrival time.ConclusionsAmong patients transferred for EVT, there are multiple reasons for ineligibility upon hub arrival, with most excluded for infarct growth and mild symptoms. Understanding factors that drive transfer inefficiencies is important to improve EVT access and outcomes.

Background: Ischemic stroke (IS) is a leading cause of long-term disability with sex-specific differences in outcomes. Identifying the influential factors that contribute to sex-specific disparities in stroke outcomes, therefore, holds potential to develop individualized interventions for reducing long-term disability. Further, investigating the association between sex and Patient-Reported Outcome Measures (PROMs) provides additional information on the individual impact and heterogeneity of IS. We aimed to identify sex-specific differences in stroke outcomes and relationship with PROMs in IS patients with 3-month follow-up. Methods: Between February 2017 and February 2020, a total of 410 patients admitted with IS to the Massachusetts General Hospital, in Boston, were enrolled in this prospective cohort. At 3-month poststroke, patients were assessed for Barthel Index, modified Rankin Scale, and PROM-10 questionnaires. T scores for physical and mental health were determined from the summing of PROM-10 responses in each domain. Regression analysis was performed to identify sex-specific determinants of functional and patient-reported outcomes. Results: At baseline, 242 participants were male (mean age, 65 years) and 168 were female (mean age, 70 years). Groups had similar rates of cardiovascular risk factors, admission National Institutes of Health Stroke Scale, and discharge modified Rankin Scale. At follow-up, male participants were more likely to have better rates of T Physical and Barthel Index. In regression analysis, PROMs T Physical (odds ratio, 1.06; P =0.01), Barthel Index (odds ratio, 1.06; P =0.01), and modified Rankin Scale score of ≥2 (odds ratio, 2.60; P =0.01) were associated with female sex. Female sex was also associated with lower scores for PROMs Physical subcomponents and with patient-reported general health and emotional problems. Conclusions: Women have worse outcomes after ischemic stroke, including objective measures of functional disability and patient-reported outcomes. Incorporating PROMs into IS outcome measures may offer additional insight into sex-specific differences in stroke recovery and outcomes.

A leading cause of white matter (WM) injury in older individuals is cerebral small vessel disease (SVD). Cerebral SVD is the most prevalent vascular contributor to cognitive impairment and dementia. Therapeutic progress for cerebral SVD and other WM disorders depends on the development and validation of neuroimaging markers suitable as outcome measures in future interventional trials. Diffusion-tensor imaging (DTI) is one of the best-suited MRI techniques for assessing the extent of WM damage in the brain. But the optimal method to analyze individual DTI data remains hindered by labor-intensive and time-consuming processes. Peak width of skeletonized mean diffusivity (PSMD), a recently developed fast, fully automated DTI marker, was designed to quantify the WM damage secondary to cerebral SVD and reflect related cognitive impairment. Despite its promising results, knowledge about PSMD is still limited in the radiologic community. This focused review provides an overview of the technical details of PSMD while synthesizing the available data on its clinical and neuroimaging associations. From a critical expert viewpoint, the authors discuss the limitations of PSMD and its current validation status as a neuroimaging marker for vascular cognitive impairment. Finally, they point out the gaps to be addressed to further advance the field.

This study aimed to investigate the influence of stroke lesions in pre-defined 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 (AIS) enrolled in the multisite MRI-GENIE study. Structural stroke lesions were spatially normalized and parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS>2) was modeled in a Bayesian logistic regression framework that relied on both lesion location, as well as the covariates: age, sex, total DWI lesion volume and comorbidities. 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. Via model comparisons, we first tested whether the rich club region model was superior to a baseline model considering clinical covariates and lesion volume only. 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 1,000 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 region effects.A total of 822 patients (age: 64.7 (standard deviation: 15.0), 39% women, 27.7% with mRS>2) were analyzed. The rich club model substantially outperformed the baseline model (weights of model comparison: rich club model: 0.96; baseline: 0.04). 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 (15/1,000 random constellations with higher mean posterior values). Among the these 15 random constellations with higher means, the most frequently selected regions were the inferior temporal gyrus (posterior division, 8/15), the putamen (8/15), the cingulate gyrus (7/15) and the superior parietal lobule (6/15). Rich club regions were substantially more important in explaining long-term outcome in women than in men (mean of the difference distribution:-0.107, 90%-HDPI:-0.193 to -0.0124).Lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific, i.e., the majority of random combinations of six regions had comparably smaller effects on long-term outcome. Effects were substantially more pronounced in women.

For over two decades, telestroke has been utilized as a means for improving acute access to a stroke specialist when this expertise is otherwise unavailable. During this time, telestroke use has increased and improvements in care metrics have been widely reported. Several telestroke model variations are utilized; each has different workflow implications. A successful telestroke system should include adequate protocols and training, equipment, documentation system, and tracking of quality metrics. Upfront costs of needed technology and devices, credentialing hurdles, and limited reimbursement are all reported barriers to the utilization of telestroke. Emphasis on safety measures during the COVID-19 pandemic resulted in the dramatic upscaling of telehealth utilization, although overall stroke volumes declined in many areas in the early phases of the pandemic. Going forward, continued reduction in cost of required devices and broadband connections, increased use of automated and advanced analytical software, and a universal licensing and credentialing system are needed to continue the expansion of telestroke use.

Background and ObjectivesThe care of patients with large vessel occlusion (LVO) stroke has been revolutionized by endovascular thrombectomy (EVT). While EVT has a large effect size, most patients treated with EVT remain disabled or die within 90 days. A better understanding of outcomes may influence EVT selection criteria, novel therapies, and prognostication. We sought to identify associations between outcomes and brain regions involved in ischemic lesions.MethodsFor this cohort study, consecutive patients with LVO who were treated with EVT and underwent post-EVT MRI were identified from a tertiary referral center (2011–2019). Acute ischemic lesions were manually segmented from diffusion-weighted imaging and spatially normalized. Individual lesions were parcellated (atlas-defined 94 cortical regions, 14 subcortical nuclei, 20 white matter tracts) and reduced to 10 essential lesion patterns with the use of unsupervised dimensionality reduction techniques. Ninety-day modified Rankin Scale (mRS) score (>2) was modeled via bayesian regression, taking the 10 lesion patterns as inputs and controlling for lesion size, age, sex, acute NIH Stroke Scale (NIHSS) score, alteplase, prior stroke, intracerebral hemorrhage, and good reperfusion (Thrombolysis in Cerebral Infarction 2b–3). In comparative analyses, 90-day mRS score was modeled considering covariates only, and compartment-wise relevances for acute stroke severity and 90-day mRS score were evaluated.ResultsThere were 151 patients with LVO identified (age 68 ± 15 years, 52% female). The median NIHSS score was 16 (interquartile range 13–20); 56% had mRS score >2. Lesion locations predictive of 90-day mRS score involved bilateral but left hemispherically more pronounced precentral and postcentral gyri, insular and opercular cortex, and left putamen and caudate (area under the curve 0.91, highest probability density interval [HPDI] covering 90% certainty 0.90–0.92). The lesion location model outperformed the simpler model relying on covariates only (bayesian model comparison of 97% weight to the model with vs 3% weight to the model without lesion location). While lesions affecting subcortical nuclei had the highest relevance for stroke severity (posterior distribution mean 0.75, 90% HPDI 0.256–1.31), lesions affecting white matter tracts had the highest relevance for 90-day mRS score (0.656, 90% HPDI 0.0864–1.12).DiscussionThese data describe the significance for outcomes of specific brain regions involved in ischemic lesions on MRI after EVT. Future work in additional datasets is needed to confirm these granular findings.

Background For patients with large vessel occlusion (LVO) stroke, time to treatment with endovascular thrombectomy is crucial to prevent infarction and improve outcomes. We sought to evaluate the hub arrival‐to‐puncture times and outcomes for transferred patients accepted directly to the angio‐suite (LVO to operating room, LVO2OR) versus those accepted through the emergency department in a hub‐and‐spoke telestroke network. Methods Consecutive patients transferred for endovascular thrombectomy with spoke computed tomography angiography–confirmed LVO, spoke Alberta Stroke Program Early Computed Tomography score >6, and last known well–to–hub arrival Results The LVO2OR cohort was composed of 91 patients, and the emergency department cohort was composed of 90 patients. LVO2OR patients had more atrial fibrillation (51% versus 32%; P =0.02) and more M2 occlusions (27% versus 10%; P =0.01). LVO2OR patients had faster median hub arrival‐to‐puncture time (11 versus 92 minutes; P P P P =0.04). In a multivariable model, LVO2OR significantly increased the odds of 90‐day modified Rankin scale score P =0.04) even when controlling for age, baseline modified Rankin scale score, atrial fibrillation, National Institutes of Health Stroke Scale score, M2 occlusion location, and Thrombolysis in Cerebral Infarction score 2b to 3. Conclusions In a hub‐and‐spoke telestroke network, accepting transferred patients directly to the angio‐suite was associated with dramatically reduced hub arrival‐to‐puncture time and may lead to improved 90‐day outcomes. Direct–to–angio‐suite protocols should continue to be evaluated in other geographic regions and telestroke network models.

Sex-specific differences in ischemic stroke outcomes are prevalent. We sought to investigate sex differences in the determinants of reperfusion and functional outcomes after endovascular thrombectomy (EVT) for emergent large vessel occlusion ischemic stroke (ELVO). Patients presenting to a single referral center with an anterior circulation ELVO that underwent EVT from 2011 to 2019 were included in this retrospective analysis. Sex differences in history, presentation, adequate reperfusion (TICI 2b-3), and 90-day good outcome [delta modified Rankin Scale (mRS) ≤ 2 from pre-stroke] were examined. Multivariable logistic regression analyses were performed to assess sex-specific associations with outcomes. Three hundred and eighty-one consecutive ELVO patients were identified. Women (N = 193) were older (75 vs 64 years, p

Background and Purpose: Patient care-seeking has likely changed during the coronavirus disease 2019 (COVID-19) pandemic. In stroke, delayed or avoided care may translate to substantial morbidity. We sought to determine the effect of the pandemic on patterns of stroke patient presentation and quality of care. Methods: We analyzed data from 25 New England hospitals: one urban, academic comprehensive stroke center and telestroke hub, and 24 spoke hospitals in the telestroke network. We included all telestroke consultations from the 24 spokes, and all stroke admissions to the comprehensive stroke center hub from November 1, 2019 through April 30, 2020. We compared rates of presentation, timeliness presentation, and quality of care pre- versus post-March 1, 2020. We examined trends in patient demographics, stroke severity, timeliness, diagnoses including large vessel occlusion, alteplase use, and endovascular thrombectomy among eligible subjects. We compared proportions and bivariate comparisons to examine for changes pre- versus post-March 1, 2020 and used linear regression to examine trends over time. Results: Among 1248 patient presentations (844 telestroke consultations, 404 comprehensive stroke center admissions), telestroke consultations and ischemic stroke patient admissions decreased among the spokes and hub. Age and stroke severity were unchanged over the study period. We found no change in alteplase administration at telestroke spoke hospitals but did note a decrease in both alteplase use and thrombectomy at our comprehensive stroke center. Time metrics for patient presentation and care delivery were unchanged; however, rates of adherence for the quality measures dysphagia screening, early antithrombotic initiation, and early venous thromboembolism prophylaxis were reduced during the pandemic. Conclusions: In this regional analysis, we found decreasing telestroke consultations and ischemic stroke admissions, and reduced performance on stroke quality of care measures during the COVID-19 pandemic. Contrary to prior reports, we did not find an increase in thrombectomy nor decrease in clinical severity that might be expected if patients with milder symptoms avoided hospitalization.

Background and purposeDepression is common after stroke and is often treated with antidepressant medications (AD). ADs have also been hypothesised to improve stroke recovery, although recent randomised trials were neutral. We investigated the patterns of in-hospital AD initiation after ischaemic stroke and association with clinical and readmission outcomes.MethodsAll Medicare fee-for-service beneficiaries aged 65 or older hospitalised for ischaemic stroke in participating Get With The Guidelines-Stroke hospitals between April and December 2014 were eligible for this analysis. Outcome measures included days alive and not in a healthcare institution (home time), all-cause mortality and readmission within 1-year postdischarge. Propensity score (PS)-adjusted logistic regression models were used to evaluate the associations between AD use and each outcome measure. We also compared outcomes in patients prescribed selective serotonin reuptake inhibitors (SSRIs) AD versus those prescribed non-SSRI ADs.ResultsOf 21 805 AD naïve patients included in this analysis, 1835 (8.4%) were started on an AD at discharge. Patients started on an AD had higher rates of depression and prior ischaemic stroke, presented with higher admission National Institutes of Health Stroke Scale score and were less likely to be discharged home. Similarly, patients started on an SSRI had lower rates of discharge to home. Adjusting for stroke severity, patients started on an AD had worse all-cause mortality, all-cause readmission, major adverse cardiac events, readmission for depression and decreased home-time. However, AD use was also associated with an increased risk for the sepsis, a falsification endpoint, suggesting the presence of residual confounding.ConclusionsPatients with ischaemic stroke initiated on AD therapy are at increased risk of poor clinical outcomes and readmission even after PS adjustment, suggesting that poststroke depression requiring medication is a poor prognostic sign. Further research is needed to explore the reasons why depression is associated with worse outcome, and whether AD treatment modifies this risk or not.

BackgroundPersons with pre-existing disabilities represent over one-third of acute stroke presentations, but account for a far smaller proportion of those receiving endovascular thrombectomy (EVT) and thrombolysis. This is despite existing ethical, economic, legal, and social directives to maximize equity for this vulnerable population. We sought to determine associations between baseline modified Rankin Scale (mRS) and outcomes after EVT.MethodsIndividuals who underwent EVT were identified from a prospectively maintained database. Demographics, medical history, presentations, treatments, and outcomes were recorded. Baseline disability was defined as baseline mRS≥2. Accumulated disability was defined as the delta between baseline mRS and absolute 90-day mRS.ResultsOf 381 individuals, 49 had baseline disability (five with mRS=4, 23 mRS=3, 21 mRS=2). Those with baseline disability were older (81 vs 68 years, PConclusionsWhile baseline mRS was associated with absolute 90-day disability, there was no association with accumulated disability or other outcomes. Patients with baseline disability should not be routinely excluded from EVT based on baseline mRS alone.

Effective treatment options for patients with life-threatening neurological disorders are limited. To address this unmet need, high-impact translational research is essential for the advancement and development of novel therapeutic approaches in neurocritical care. “The Neurotherapeutics Symposium 2019—Neurological Emergencies” conference, held in Rochester, New York, in June 2019, was designed to accelerate translation of neurocritical care research via transdisciplinary team science and diversity enhancement. Diversity excellence in the neuroscience workforce brings innovative and creative perspectives, and team science broadens the scientific approach by incorporating views from multiple stakeholders. Both are essential components needed to address complex scientific questions. Under represented minorities and women were involved in the organization of the conference and accounted for 30–40% of speakers, moderators, and attendees. Participants represented a diverse group of stakeholders committed to translational research. Topics discussed at the conference included acute ischemic and hemorrhagic strokes, neurogenic respiratory dysregulation, seizures and status epilepticus, brain telemetry, neuroprognostication, disorders of consciousness, and multimodal monitoring. In these proceedings, we summarize the topics covered at the conference and suggest the groundwork for future high-yield research in neurologic emergencies.

Since approval by the United States Food and Drug Administration in 1996, alteplase utilization rates for acute ischemic stroke have increased. Despite its efficacy for improving stroke outcomes, however, the majority of ischemic stroke patients still do not receive alteplase. To address this issue, different methods for improving access to alteplase have been tested with varying degrees of success.This article gives an overview of the recent approaches pursued to improve access to alteplase for acute ischemic stroke patients. Utilization of stroke systems of care, quality metrics, and quality-improvement initiatives to improve alteplase treatment rates are discussed. The implementation of Telestroke networks to improve access and timely evaluation by a stroke specialist are also reviewed. Lastly, this review discusses the use of neuroimaging techniques to identify alteplase candidates in stroke of unknown symptom onset or beyond the 4.5-h treatment window.Expanding access to alteplase therapy for acute ischemic stroke is a multi-faceted approach. Specific considerations based on region, population, and health-care resources should be considered for each strategy. Neuroimaging approaches to identify alteplase-eligible patients beyond the 4.5-h treatment window are a recent development in acute stroke care that holds promise for increasing alteplase treatment rates.

OBJECTIVE:To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). PATIENTS AND METHODS:This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission. RESULTS:Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm3) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes. CONCLUSION:Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.

Backgrounds: Telestroke is associated with improved reperfusion and improved outcomes for stroke patients. Our objective was to examine the effect of telestroke on procedural timeliness and outcomes among patients transferred for endovascular therapy (EVT). Methods: We identified all EVT encounters at our urban, telestroke-enabled, academic comprehensive stroke center (CSC) from 1/1/2017 to 12/31/2020 in our institutional Get With The Guidelines-Stroke registry linked with our telestroke consultation records. EVT encounters were categorized based on mode of arrival: i) transferred via the telestroke network (Tx+TS), ii) transferred without telestroke (Tx-TS), or iii) directly presenting to the CSC (DP). The three groups were then compared on efficacy and safety measurements including first-pass rate, successful reperfusion (TICI 2b/3) and post-procedure complications, as well as mortality and functional independence (mRS ≤ 2) outcomes both at discharge and 90-day post discharge using multi-group testing. Results: After excluding 29 encounters with unknown arrival mode, our sample of 287 EVT encounters included 168 Tx+TS cases, 35 Tx-TS cases, and 84 DP cases. Patients’ demographics and baseline characteristics (NIHSS at admission and prior comorbidities) were balanced across the groups (Table). Compared to both Tx-TS and DP, Tx+TS has significantly shorter door to puncture time (Tx+TS: 30 mins vs. Tx-TS: 62 mins vs. DP: 92 mins, p < 0.001). Procedural efficacy and safety, in-hospital outcomes and post discharge outcomes were similar across groups. Conclusion: Our study demonstrates that telestroke plays an important role among patients transferred for EVT with improved procedural timeliness, and outcomes similar to those of directly presenting patients.

Introduction: Endovascular thrombectomy (EVT) has revolutionized the care of emergent large vessel occlusion (ELVO) stroke patients. It is, therefore, crucial to optimize its delivery to eligible candidates. Within hub-and-spoke hospital system models, some patients first present to distant spoke hospitals and require transfer to hub hospitals for EVT. We sought to understand changes in EVT eligibility during transfer. Methods: Consecutive EVT candidates presenting to 25 spokes from 2018 to 2020 with pre-transfer CTA-defined ELVO and Alberta Stroke Program Early CT Score ≥6 were identified from a prospectively maintained database. Outcomes of interest included hub EVT, reasons for EVT ineligibility, and 90-day functional independence (modified Rankin Scale, mRS ≤2). Results: Among 258 patients, the median age was 70 years (IQR 60-81) and 50% were female. Forty-four percent underwent EVT upon hub arrival, of which 87% achieved Thrombolysis in Cerebral Infarction 2b-3 reperfusion. Compared to EVT-eligible patients, ineligible patients were older (73 vs 68 years, p=0.04), had lower NIH Stroke Scale (NIHSS, 10 vs 16, p Conclusions: These data support that approaches to increase EVT eligibility among ELVO transfers may improve long term outcomes. Infarct growth represents the primary reason for ineligibility. Possible interventions include direct field triage to the hub when feasible, improving inter-hospital transfer times, supporting ischemic penumbra before EVT, and developing novel agents to slow infarct growth.

Background The relationship of global white matter microstructural integrity and ischemic stroke outcomes is not well understood. Aims To investigate the relationship of global white matter microstructural integrity with clinical variables and functional outcomes after acute ischemic stroke. Methods A retrospective analysis of neuroimaging data from 300 acute ischemic stroke patients with magnetic resonance imaging brain obtained within 48 hours of stroke onset and long-term functional outcomes (modified Rankin, mRS) was performed. Peak width of skeletonized mean diffusivity (PSMD), as a measure of global white matter microstructural injury, was calculated in the hemisphere contralateral to the acute infarct. Multivariable linear and logistic regression analyses were performed to identify variables associated with PSMD and excellent functional outcome (mRS Results White matter hyperintensity volume, age, pre-stroke disability, and normal-appearing white matter mean diffusivity were independently associated with increased PSMD. In logistic regression analysis, increased infarct volume and PSMD were independent predictors of excellent functional outcome. Additionally, the effect of age on functional outcomes was indirectly mediated by PSMD ( P Conclusions As a marker of global white matter microstructural injury, increased PSMD mediates the effect of increased age to contribute to poor acute ischemic stroke functional outcomes. PSMD could serve as a putative radiographic marker of brain age for stroke outcomes prognostication.

While chronological age is one of the most influential determinants of post-stroke outcomes, little is known of the impact of neuroimaging-derived biological brain age. We here first examine whether radiomics analysis of the texture of brain T2-FLAIR MRI images can be used to predict brain age in stroke patients. We then assess the clinical determinants of accelerated brain aging and, finally, its impact on post-stroke functional outcomes. Leveraging a multisite cohort of 4,163 ischemic stroke patients, we show that older-appearing patients have more hypertension, diabetes mellitus, prior strokes, and smoking history and are more likely to develop worse post-stroke outcomes than their younger-appearing counterparts. Our results strengthen the importance of preventive medicine for maintaining brain health in stroke patients as they age and suggest a novel methodology to capture previously undescribed prognostic information available on commonly acquired MRI sequences during routine stroke care.

Objective: To personalize the prognostication of post-stroke outcome using MRI-detected cerebrovascular pathology, we sought to investigate the association between the excessive white matter hyperintensity (WMH) burden unaccounted for by the traditional stroke risk profile of individual patients and their long-term functional outcomes after a stroke. Methods: We included 890 patients who survived after an acute ischemic stroke from the MRI-Genetics Interface Exploration (MRI-GENIE) study, for whom data on vascular risk factors (VRFs), including age, sex, atrial fibrillation, diabetes mellitus, hypertension, coronary artery disease, smoking, prior stroke history, as well as acute stroke severity, 3- to-6-month modified Rankin Scale score (mRS), WMH, and brain volumes, were available. We defined the unaccounted WMH (uWMH) burden via modeling of expected WMH burden based on the VRF profile of each individual patient. The association of uWMH and mRS score was analyzed by linear regression analysis. The odds ratios of patients who achieved full functional independence (mRS < 2) in between trichotomized uWMH burden groups were calculated by pair-wise comparisons. Results: The expected WMH volume was estimated with respect to known VRFs. The uWMH burden was associated with a long-term functional outcome (β = 0.104, p < 0.01). Excessive uWMH burden significantly reduced the odds of achieving full functional independence after a stroke compared to the low and average uWMH burden [OR = 0.4, 95% CI: (0.25, 0.63), p < 0.01 and OR = 0.61, 95% CI: (0.42, 0.87), p < 0.01, respectively]. Conclusion: The excessive amount of uWMH burden unaccounted for by the traditional VRF profile was associated with worse post-stroke functional outcomes. Further studies are needed to evaluate a lifetime brain injury reflected in WMH unrelated to the VRF profile of a patient as an important factor for stroke recovery and a plausible indicator of brain health. NIH-NINDS (MRI-GENIE: R01NS086905 - PI NR; K23NS064052, R01NS082285 - NR; SiGN: U01 NS069208 - JR, SK; R01NS059775, R01NS063925, R01NS082285, P50NS051343, R01NS086905, U01 NS069208 - OW); NIH NIBIB (NAC P41EB015902 PG, U01NS030678 Kissela, Kleindorfer; EB015325 OW); ISGS (R01NS423733 P.I. JM, Swedish Heart and Lung Foundation, Lund University, Region Skåne, the Freemasons Lodge of Instruction Eos Lund, Skåne University Hospital, the Foundation of Färs &Frosta (One of Sparbanken Skånes ownership Foundations), and the Swedish Stroke Association - AL, Swedish Research Council and the Swedish Heart and Lung Foundation, the Swedish State under the ALF agreement CJ, Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (Funding for Research in Health PI051737, PI10/02064, PI12/01238 and PI15/00451 JJ-C), Fondos FEDER/EDRF Red de Investigación Cardiovascular (RD12/0042/0020 JJ-C), Fundació la Marató TV3 (76/C/2011 - JJ-C) and Recercaixa13 (JJ086116 JJ-C), Wistron Corporation (PG); The European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 753896 - MS; RL is a senior clinical investigator of FWO Flanders; MB was supported by the ISITE-ULNE Fundation, the Société Française de Neuroradiologie, the Société Française de Radiologie, the Thérèse and René Planiol Fundation; ME was supported by the American Academy of Neurology and MGH Executive Council on Research; TT was supported by the Helsinki University Central Hospital, Sigrid Juselius Foundation, Sahlgrenska University Hospital, and University of Gothenburg. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article of the decision to submit it for publication.

ObjectiveNeuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes.MethodsWe analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask–WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA).ResultsRadiomic features were predictive of WMH burden (R2 = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-valuesCV1–6 < 0.001, p-valueCV7 = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes.ConclusionRadiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients’ brain health.

Introduction: Patterns of hospital presentation have changed during the COVID-19 pandemic. In stroke, delayed or avoided care may translate to substantial morbidity. We sought to determine the effect of the pandemic on patterns of stroke patient presentation and quality of care. Methods: We analyzed data from 25 New England hospitals: one urban, academic comprehensive stroke center (CSC) and telestroke hub, and 24 spoke hospitals in the telestroke network. We included all telestroke consultations from the 24 spokes and stroke admissions to the CSC from 11/1/2019 through 4/30/2020. We examined trends in stroke presentation including large vessel occlusion (LVO), alteplase use, and endovascular thrombectomy among eligible subjects. We compared proportions and bivariate comparisons to examine for changes pre- vs. post-3/1/2020, and used linear regression to examine trends over time. Results: Among 1248 patient presentations, telestroke consultations (0.4 fewer consults per week, p=0.005) and ischemic stroke patient admissions (decrease of 0.2 patients per week, p=0.04) decreased among the spokes and hub. Age and stroke severity were unchanged over the study period. We found no change in alteplase administration at telestroke spoke hospitals, but did note a decrease in both alteplase use (1.5 per week prior to March 1 st and 1 per week after, p=0.05) and thrombectomy at our CSC (0.1 fewer cases per week, p=0.02). Time metrics for patient presentation and care delivery were unchanged, however, rates of adherence for several quality measures were reduced during the pandemic (Table 1). Conclusions: In this regional analysis, we found decreasing telestroke consultations and ischemic stroke admissions, and reduced performance on stroke quality of care measures during the COVID-19 pandemic. Contrary to prior reports, we did not find an increase in thrombectomy nor decrease in clinical severity that might be expected if patients with milder symptoms avoided hospitalization.

Introduction: As a radiographic signature of end-stage small vessel disease, white matter hyperintensity (WMH) burden impacts recovery and outcomes after acute ischemic stroke (AIS). In this study, we sought to investigate the effect of WMH volume (WMHv) on stroke severity and functional outcomes independent of the infarct size and topography. Methods: We analyzed 503 AIS patients with MRI data obtained on admission for index stroke enrolled in the multi-center MRI-GENIE study (cohort 1), followed by validation of the findings in an independent single-site study of 555 AIS patients (cohort 2). Stroke severity (NIHSS score) at index stroke and the long-term outcome (3-6 months mRS score) were modeled via Bayesian linear regression. Models included WMHv, age, sex, a 10-dimensional spatial ischemic lesion representation, acute infarct (DWI) volume, and common vascular risk factors (hypertension, diabetes mellitus, atrial fibrillation, coronary artery disease). Results: Cohorts did not differ significantly in major clinical characteristics [cohort 1: age: 65.0±14.6, 41% female, NIHSS: 5.5±5.4, mRS: 1(iqr 2); cohort 2: age: 65.0±14.8, 38% female, NIHSS: 5.0±6.0, mRS: 1(iqr 3), p >0.05 for all comparisons]. WMHv did not substantially affect AIS severity ( Fig A ); in contrast, it emerged as an independent predictor of functional outcome in both datasets ( Fig B ). Conclusions: When accounted for AIS lesion topography and stroke volume, total WMH lesion burden did not appear to modulate initial stroke severity but was associated with worse functional post-stroke outcomes. Future studies are needed to explore potential origins of these detrimental effects of pre-existing WMH burden on recovery after AIS.

Introduction: MRI-detected white matter hyperintensity (WMH) burden is linked to the overall brain health and incident stroke outcomes. However, data are limited as to whether specific acute stroke lesion patterns purport greater stroke severity in patients with extensive pre-existing WMH. In this analysis, we sought to investigate lesion pattern-specific WMH effects on AIS severity. Methods: We analyzed clinical and lesion data from 621 AIS patients enrolled in the multi-site MRI-GENIE study. The acute NIHSS was modelled via Bayesian hierarchical regression. Using ten stroke lesion patterns, that served as input variables of main interest, we introduced a hierarchical level differentiating between patients with higher and lower than median WMH volume (WMHv). Lesion pattern posterior distributions for higher and lower WMHv patients were subtracted to infer substantial differences. Results: In this AIS cohort [age: 65.3±14.6, 60% male], a higher WMHv was associated with greater stroke severity only when specific left-hemispheric brain regions were infarcted. This “lesion pattern 3” was mainly characterized by left middle and inferior frontal gyrus, insular and opercular cortex, pre- and post-central gyrus, and subcortical basal ganglia regions ( Fig ). Conclusions: Higher WMH burden appears to enhance the detrimental effect of acute stroke lesions involving left-hemispheric brain regions underlying language and motor functions. This effect might be due to an exacerbated disruption of functional network integrity by the combination of WMH and stroke lesions and could be explored further in functional imaging studies that simultaneously considered information from both lesion types.

Introduction: Endovascular thrombectomy (EVT) has revolutionized large vessel occlusion (LVO) stroke care. However, over half remain functionally disabled or die despite treatment. Understanding outcomes may influence EVT selection, novel therapies, and prognostication. We sought to identify associations between outcomes and brain regions involved in ischemic lesions. Methods: For consecutive LVO patients with post-EVT MRI, acute ischemic lesions were manually segmented from DWI and spatially normalized. Individual lesion volumes were automatically parcellated (atlas-defined 94 cortical regions, 14 subcortical nuclei, 20 white matter tracts) and then reduced to ten anatomically plausible lesion patterns using unsupervised dimensionality reduction techniques. Ninety-day modified Rankin Scale (mRS) was modeled via Bayesian regression, taking the ten lesion patterns as inputs and controlling for lesion size, age, sex, acute NIH Stroke Scale, alteplase, and TICI 2b-3 reperfusion. Results: We identified 153 LVO patients with mean age 68±15 years and 51% female. Median NIHSS was 16 (IQR 13-20), 56% received alteplase, and 84% achieved TICI2b-3. The lesion patterns predictive of 90-day mRS involved bilateral subcortical nuclei, pre- and postcentral gyri, insular and opercular cortex, as well as left-sided inferior frontal and angular gyri ( Figure 1A ). Lesions affecting white matter tracts had the highest relevance predicting 90-day mRS ( Figure 1B ). Conclusions: These data describe the significance for outcomes of specific brain regions involved in ischemic lesions on MRI after EVT. Future work in additional datasets is needed to confirm these granular findings.

Introduction: Peak width of skeletonized mean diffusivity (PSMD) is a novel fully automated diffusion tensor imaging (DTI) marker that has been consistently associated with cognition in cerebral small vessel disease (SVD) cohorts, including cerebral amyloid angiopathy (CAA). We hypothesized that PSMD would be more strongly associated with cognitive performance compared to other conventional DTI metrics in our CAA sample. Methods: We recruited non-demented subjects with probable-CAA from a single-center memory-clinic cohort. We analyzed structural MRIs to compute a validated CAA burden score (0-6 points scale, based on the following MRI features: lobar microbleeds, superficial siderosis, perivascular spaces in centrum semiovale, and white matter hyperintensities). PSMD was obtained using a freely available script ( www.psmd-marker.com ). We used the same skeleton-mask to compute: mean of skeletonized mean diffusivity (mean MD) and mean of skeletonized fractional anisotropy (mean FA). We used linear regression analyses to explore relationships with CAA burden score and cognitive composite scores (processing speed, executive function, memory, and language - z-scores adjusted for age, sex and education level). Results: We included 43 subjects (mean age 74.4 ± 5.9 years; 48.8% female; PSMD median [IQR]: 4.05 [3.58 - 4.80] x 10 -4 mm 2 /s). In linear regression models adjusting for age, DTI metrics were significantly associated with CAA burden score (mean FA: β = -0.563, Adj. R 2 : 0.27; p < 0.001; mean MD: β = 0.581; Adj. R 2 : 0.32; p < 0.001; PSMD: β = 0.364, Adj. R 2 : 0.12; p = 0.018). PSMD was significantly associated with cognitive performance, specifically in the domains of executive function ( β = -0.568; Adj. R 2 : 0.25; p < 0.001) and processing speed ( β = -0.447; Adj. R 2 : 0.19; p = 0.004). Other DTI metrics were not significantly associated with cognitive scores. Conclusion: In this CAA sample, all DTI metrics were associated with CAA burden scores, however, only PSMD was significantly associated with cognition, in domains that are commonly affected in vascular cognitive impairment. Our results warrant confirmation in larger samples, but support PSMD as biomarker for cognition in CAA, outperforming other conventional DTI metrics.

Introduction: Structural integrity of cerebral parenchyma is an essential radiographic equivalent of brain health; but its assessment usually requires dedicated advanced image acquisitions. Radiomics analyses bear the potential to describe radiophenotypes beyond what meets the naked eye. We sought to: 1) evaluate this novel approach to predict white matter hyperintensity (WMH) burden and 2) uncover latent clinico-radiological associations. Methods: An international, multi-site cohort of 4,164 acute ischemic stroke (AIS) patients with FLAIR MRI (MRI-GENIE study) underwent total brain and WMH lesion segmentation using convolutional neural networks. Radiomic features (n=1905) were extracted from clinical FLAIR images outside of the WMH (brain mask - WMH mask). Prediction of the WMH burden using radiomics was done using LASSO regression. Radiomic signature of WMH was built with the most stable selected features, then compared to the clinical variables using canonical correlation analysis. Results: In this cohort, (mean age=62.8±15.0, median WMH volume=4.2cc IQR 1.4-11.2), radiomic features were highly predictive of WMH burden (R2=0.8±0.012). Radiomic signature of WMH included 68 features. All 7 pairs of extracted canonical variates (CV) were statistically significant with respective canonical correlations of 0.79, 0.64, 0.44, 0.21, 0.16, 0.15 (Bonferroni corrected p-values CV1-6 CV7 =.003). Upon examination, CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes mellitus (DM), CV4 by hypertension, CV5 by atrial fibrillation (AF) and DM, CV6 by coronary artery disease (CAD) and CV7 by CAD and DM. Conclusion: Radiomics extracted from clinical grade FLAIR images of AIS patients seem able to capture structural integrity of the cerebral parenchyma and to correlate with clinical phenotypes. Further research could evaluate radiomics to predict the progression of cerebral small vessel disease on longitudinal data.

IntroductionNeuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of describing the texture of conventional images beyond what meets the naked eye, radiomic analyses hold potential for evaluating brain health. We sought to: 1) evaluate this novel approach to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and 2) uncover associations between predictive radiomic features and patients’ clinical phenotypes.MethodsOur analyses were based on a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images and corresponding deep-learning-generated total brain and WMH segmentation. Radiomic features were extracted from normal-appearing brain tissue (brain mask–WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with the most stable selected features predictive of WMH burden and then related this signature to clinical variables (age, sex, hypertension (HTN), atrial fibrillation (AF), diabetes mellitus (DM), coronary artery disease (CAD), and history of smoking) using canonical correlation analysis.ResultsRadiomic features were highly predictive of WMH burden (R2=0.855±0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-valuesCV1-6CV7=.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and DM, CV4 by HTN, CV5 by AF and DM, CV6 by CAD, and CV7 by CAD and DM.ConclusionRadiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes. Further research could evaluate radiomics to predict the progression of WMH.Research in contextEvidence before this studyWe did a systematic review on PubMed until December 1, 2020, for original articles and reviews in which radiomics were used to characterize stroke or cerebrovascular diseases. Radiomic analyses cover a broad ensemble of high-throughput quantification methods applicable to digitalized medical images that extract high-dimensional data by describing a given region of interest by its size, shape, histogram, and relationship between voxels. We used the search terms “radiomics” or “texture analysis”, and “stroke”, “cerebrovascular disease”, “small vessel disease”, or “white matter hyperintensities”. Our research identified 24 studies, 18 studying radiomics of stroke lesions and 6 studying cerebrovascular diseases. All the latter six studies were based on MRI (T1-FLAIR, dynamic contrast-enhanced imaging, T1 & T2-FLAIR, T2-FLAIR post-contrast, T2-FLAIR, and T2-TSE images). Four studies were describing small vessel disease, and two were predicting longitudinal progression of WMH. The average sample size was small with 96 patients included (maximum: 204). One study on 141 patients identified 7 T1-FLAIR radiomic features correlated with cardiovascular risk factors (age and hyperlipidemia) using univariate correlations. All studies were monocentric and performed on a single MRI scanner.Added value of this studyTo date and to the best of our knowledge, this is the largest radiomics study performed on cerebrovascular disease or any topic, and one of the very few to include a great diversity of participating sites with diverse clinical MRI scanners. This study is the first one to establish a radiomic signature of WMH and to interpret its relationship with common cardiovascular risk factors. Our findings add to the body of evidence that damage caused by small vessel disease extend beyond the visible white matter hyperintensities, but the added value resides in the detection of that subvisible damage on routinely acquired T2-FLAIR imaging. It also suggests that cardiovascular phenotypes might manifest in distinct textural patterns detectable on conventional clinical-grade T2-FLAIR images.Implications of all the available evidenceAssessing brain structural integrity has implications for treatment selection, follow-up, prognosis, and recovery prediction in stroke patients but also other neurological disease populations. Measuring cerebral parenchymal structural integrity usually requires advanced imaging such as diffusion tensor imaging or functional MRI. Translation of those neuroimaging biomarkers remains uncommon in clinical practice mainly because of their time-consuming and costly acquisition. Our study provides a potential novel solution to assess brains’ structural integrity applicable to standard, routinely acquired T2-FLAIR imaging.Future research could, for instance, benchmark this radiomics approach against diffusion or functional MRI metrics in the prediction of cognitive or functional outcomes after stroke.

BACKGROUND AND PURPOSE: Whole-brain network connectivity has been shown to be a useful biomarker of cerebral amyloid angiopathy and related cognitive impairment. We evaluated an automated DTI-based method, peak width of skeletonized mean diffusivity, in cerebral amyloid angiopathy, together with its association with conventional MRI markers and cognitive functions. MATERIALS AND METHODS: We included 24 subjects (mean age, 74.7 [SD, 6.0] years) with probable cerebral amyloid angiopathy and mild cognitive impairment and 62 patients with MCI not attributable to cerebral amyloid angiopathy (non-cerebral amyloid angiopathy–mild cognitive impairment). We compared peak width of skeletonized mean diffusivity between subjects with cerebral amyloid angiopathy–mild cognitive impairment and non-cerebral amyloid angiopathy–mild cognitive impairment and explored its associations with cognitive functions and conventional markers of cerebral small-vessel disease, using linear regression models. RESULTS: Subjects with Cerebral amyloid angiopathy–mild cognitive impairment showed increased peak width of skeletonized mean diffusivity in comparison to those with non-cerebral amyloid angiopathy–mild cognitive impairment (P < .001). Peak width of skeletonized mean diffusivity values were correlated with the volume of white matter hyperintensities in both groups. Higher peak width of skeletonized mean diffusivity was associated with worse performance in processing speed among patients with cerebral amyloid angiopathy, after adjusting for other MRI markers of cerebral small vessel disease. The peak width of skeletonized mean diffusivity did not correlate with cognitive functions among those with non-cerebral amyloid angiopathy–mild cognitive impairment. CONCLUSIONS: Peak width of skeletonized mean diffusivity is altered in cerebral amyloid angiopathy and is associated with performance in processing speed. This DTI-based method may reflect the degree of white matter structural disruption in cerebral amyloid angiopathy and could be a useful biomarker for cognition in this population.

The aim of the current study was to explore the whole‐brain dynamic functional connectivity patterns in acute ischemic stroke (AIS) patients and their relation to short and long‐term stroke severity. We investigated resting‐state functional MRI‐based dynamic functional connectivity of 41 AIS patients two to five days after symptom onset. Re‐occurring dynamic connectivity configurations were obtained using a sliding window approach and k‐means clustering. We evaluated differences in dynamic patterns between three NIHSS‐stroke severity defined groups (mildly, moderately, and severely affected patients). Furthermore, we built Bayesian hierarchical models to evaluate the predictive capacity of dynamic connectivity and examine the interrelation with clinical measures, such as white matter hyperintensity lesions. Finally, we established correlation analyses between dynamic connectivity and AIS severity as well as 90‐day neurological recovery (ΔNIHSS). We identified three distinct dynamic connectivity configurations acutely post‐stroke. More severely affected patients spent significantly more time in a configuration that was characterized by particularly strong connectivity and isolated processing of functional brain domains (three‐level ANOVA: p, By employing dynamic functional connectivity analyses, Bonkhoff et al. demonstrate that severe acute ischemic stroke is linked to transiently increased isolated information processing in multiple functional domains. Additionally, they show that dynamic connectivity involving default mode network components significantly correlates with recovery in the first three months poststroke.

Objectives Despite the proven efficacy of endovascular thrombectomy (EVT) for large vessel occlusion stroke, over half treated remain functionally disabled or die. Infarct topography may have implications for prognostication, patient selection, and the development of tissue-specific neuroprotective agents. We sought to quantify white matter injury in anterior circulation acute infarcts post-EVT to understand its significance and identify its determinants. Materials and Methods Demographics, history, presentations, and outcomes for consecutive patients treated with EVT were recorded in a prospectively maintained database at a single center. Acute infarct masks were coregistered to standard space. Standard atlases of white matter, cortex, and basal ganglia were used to determine region-specific infarct volumes. Results 167 individuals were identified with median age 69 years and 53% women. 85% achieved adequate reperfusion (TICI 2b-3) after EVT; 43% achieved 90-day functional independence (mRS 0-2). Median infarct volumes were 45cc (IQR 18-122) for total, 17cc (6-49) for white matter, 21cc (4-53) for cortex, and 5cc (1-8) for basal ganglia. The odds of 90-day mRS 0-2 were reduced in patients with larger white matter infarct volume (cc, OR=0.89, 95%CI=0.81-0.96), independent of cortex infarct volume, basal ganglia infarct volume, age, NIHSS, and TICI 2b-3 reperfusion. Reperfusion-to-MRI time was associated with white matter infarct volume (hr, β=0.119, p=0.017), but not cortical or basal ganglia infarct volume. Conclusions These data quantitatively describe region-specific infarct volumes after EVT and suggest the clinical relevance of white matter infarct volume as a predictor of long-term outcomes. Further study is warranted to examine delayed white matter infarction and the significance of specific white matter tracts.

Background and purpose Endovascular thrombectomy (EVT) has revolutionized large vessel occlusion stroke care. However, not all patients with good endovascular results achieve good outcomes. We sought to understand the clinical significance of magnetic resonance imaging defined infarct growth despite adequate reperfusion and identify associated clinical and radiographic variables. Methods History, presentation, treatments, and outcomes for consecutive EVT patients at a referral center were collected. Adequate reperfusion was defined as thrombolysis in cerebral infarction (TICI) score 2b-3. Region-specific infarct volumes in white matter, cortex, and basal ganglia were determined on diffusion-weighted imaging. Infarct growth was defined as post-EVT minus pre-EVT volume. Good outcome was defined as 90-day modified Rankin Scale ≤2. Results Forty-four patients with adequate reperfusion were identified with median age 72 years; 64% were women. Each region showed infarct growth: white matter (median pre-EVT 7 cubic centimeters [cc], post-EVT 16 cc), cortex (4 cc, 15 cc), basal ganglia (2 cc, 4 cc), total (20 cc, 39 cc). In multivariable regression, total infarct growth independently decreased the odds of good outcome (odds ratio = .946, 95% CI = .897, .998). Further multivariable analyses for determinants of infarct growth identified female sex was associated with less total growth (β = -.294, P = .042), TICI 3 was associated with less white matter growth (β = -.277, P = .048) and cortical growth (β = -.335, P = .017), and both female sex (β = -.332, P = .015) and coronary disease (β = -.337, P = .015) were associated with less cortical growth. Conclusions Infarct growth occurred despite adequate reperfusion, disproportionately in the cortex, and independently decreased the odds of good outcome. Infarct growth occurred while patients were hospitalized and may represent a therapeutic target. Potential determinants of region-specific infarct growth were identified that require confirmation in larger studies.

Acute ischemic stroke affects men and women differently in many ways. In particular, women are oftentimes reported to experience a higher acute stroke severity than men. Here, we derived a low-dimensional representation of anatomical stroke lesions and designed a sex-aware Bayesian hierarchical modelling framework for a large-scale, well phenotyped stroke cohort. This framework was tailored to carefully estimate possible sex differences in lesion patterns explaining acute stroke severity (NIHSS) in 1,058 patients (39% female). Anatomical regions known to subserve motor and language functions emerged as relevant regions for both men and women. Female patients, however, presented a more widespread pattern of stroke severity-relevant lesions than male patients. Furthermore, particularly lesions in the posterior circulation of the left hemisphere underlay a higher stroke severity exclusively in women. These sex-sensitive lesion pattern effects could be discovered and subsequently robustly replicated in two large independent, multisite lesion datasets. The constellation of findings has several important conceptual and clinical implications: 1) suggesting sex-specific functional cerebral asymmetries, and 2) motivating a sex-stratified approach to management of acute ischemic stroke. To go beyond sex-averaged stroke research, future studies should explicitly test whether acute therapies administered on the basis of sex-specific cutoff volumes of salvageable tissue will lead to improved outcomes in women after acute ischemic stroke.

The purpose of this article is to review the current approaches using neuroimaging techniques to expand eligibility for intravenous thrombolytic therapy in acute ischemic stroke patients with stroke of unknown symptom onset. In recent years, several randomized, placebo-controlled trials have shown neuroimaging-guided approaches to be feasible in determining eligibility for alteplase beyond 4.5 h from last known well, and efficacious for reducing disability. DWI-FLAIR mismatch on MRI is an effective tool to identify stroke lesions less than 4.5 h in onset in patients with stroke of unknown symptom onset. Additionally, an automated perfusion-based approach, assessing for a disproportionate amount of salvageable tissue, is effective in identifying patients likely to benefit from late window alteplase treatment. In patients with stroke of unknown symptom onset, an individualized approach using neuroimaging to determine time of stroke onset or presence of salvageable brain tissue is feasible in the acute setting and associated with improved long-term outcomes.

Purpose of review This article reviews the clinical significance and neuroimaging characteristics of cerebral small vessel disease and the impact on neurologic disease and current and potential therapeutic approaches. Recent findings Cerebral small vessel disease is increasingly prevalent and highly heterogeneous in neuroimaging and clinical presentation. Small subcortical infarcts, lacunes, cerebral microbleeds, cortical microinfarcts, and white matter hyperintensity of presumed vascular origin represent the major neuroimaging markers of small vessel disease. Increasing small vessel disease burden is associated with risk of incident stroke and dementia, as well as other neuropsychiatric symptoms. Current research strategies are targeting elucidation of the mechanisms of small vessel disease pathogenesis and pursuing clinical trials of therapeutic agents to reduce the clinical manifestations of cerebral small vessel disease. Summary Cerebral small vessel disease is common in aging adults and represents a major risk factor for multiple acute and chronic neurologic diseases. Increased awareness of cerebral small vessel disease as a modifiable risk factor holds potential for reducing neurologic disease morbidity and mortality across diverse populations in the United States and worldwide.

Background:Telestroke provides access to vascular neurology expertise for hospitals lacking stroke coverage, and its use has risen rapidly in the past decade. We aim to characterize consultations, spoke behavior, and the relationship between spoke telestroke utilization (number of telestroke consults per year) and spoke alteplase treatment metrics in an academic telestroke network.Methods and Results:We analyzed prospectively collected data on all telestroke consults from 2003 to 2018. Trends in network performance and spoke characteristics were analyzed using generalized estimating equations and Kendall τβ nonparametric tests as appropriate. Unadjusted and adjusted linear regression models determined associations between telestroke utilization and treatment metrics. The network included 2 hubs and 43 spokes with 12 803 consults performed during the study period. Network growth overall was +1.8 spokes per year, and median duration of spoke participation was 7.9 years. The numbers of consults and alteplase-treated patients increased annually, even after adjusting for the number of spokes in the network (PPP=0.02), number of patients treated with alteplase was an additional 1.7 (PP=0.03).Conclusions:Telestroke network size and utilization increased over time. Increased use of teleconsults was associated with increased and timely use of alteplase. Over time, the delivery of timely emergency care has improved significantly among emergency departments participating in this telestroke network. Replication of these findings in other networks is warranted.

Background: Early outcome prediction after acute ischemic stroke (AIS) is critical to guide care and rehabilitation strategies. Pre-existing chronic structural injury to cerebral white matter (WM), including ischemic WM hyperintensity (WMH) and microstructural changes within the normal-appearing WM (NAWM), is known to impede post-stroke recovery. Quantitative assessment of total pre-existing WM injury may therefore improve prognostication of functional stroke outcomes. Peak width of skeletonized mean diffusivity (PSMD) is an automated marker of cerebral small vessel disease and global WM injury. In a cohort of AIS patients, we measured PSMD in the hemisphere contralateral to the acute infarct and characterized its association with 90-day functional outcomes. Methods: Brain MRI with diffusion tensor imaging sequences was acquired within 48 hours of AIS admission. WMH volume (WMHv) was measured in a semi-automated manner. NAWM masks were constructed by subtracting the WMH and chronic infarct masks from a probabilistic WM atlas. NAWM mean diffusivity (MD) was then measured in the NAWM mask. PSMD was extracted by skeletonizing the WM tracts in the MD image using the Fractional Anisotropy image and the FSL Tract-Based Spatial Statistics pipeline with a mask for the contralesional hemisphere. Excellent outcome was defined as a modified Rankin scale score < 2 at 3-6 months post-stroke. Logistic regression analysis was performed to evaluate predictors of excellent outcome. Results: In 292 AIS patients, increasing PSMD and NAWM MD, but not WMHv, were associated with decreased likelihood of excellent outcome in univariable analysis. Increasing age, admission NIHSS score, DWI volume, and female sex were also negatively associated with excellent outcome. In backward stepwise logistic regression, including all significant variables from the univariable step, increasing age (β = -0.03; P = 0.01), NIHSS (β = -0.1; P = 0.0005), DWI volume (β = -0.02; P = 0.0004), PSMD (β = -0.08; P = 0.03), and female sex (β = -0.7; P = 0.01) were associated with decreased likelihood of excellent outcome. Conclusion: In AIS patients, automated determination of contralesional PSMD, as a marker of chronic, global white matter injury, is an independent predictor of functional outcomes.

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Registration is a core component of many imaging pipelines. In case of clinical scans, with lower resolution and sometimes substantial motion artifacts, registration can produce poor results. Visual assessment of registration quality in large clinical datasets is inefficient. In this work, we propose to automatically assess the quality of registration to an atlas in clinical FLAIR MRI scans of the brain. The method consists of automatically segmenting the ventricles of a given scan using a neural network, and comparing the segmentation to the atlas ventricles propagated to image space. We used the proposed method to improve clinical image registration to a general atlas by computing multiple registrations - one directly to the general atlas and others via different age-specific atlases - and then selecting the registration that yielded the highest ventricle overlap. Finally, as an example application of the complete pipeline, a voxelwise map of white matter hyperintensity burden was computed using only the scans with registration quality above a predefined threshold. Methods were evaluated in a single-site dataset of more than 1000 scans, as well as a multi-center dataset comprising 142 clinical scans from 12 sites. The automated ventricle segmentation reached a Dice coefficient with manual annotations of 0.89 in the single-site dataset, and 0.83 in the multi-center dataset. Registration via age-specific atlases could improve ventricle overlap compared to a direct registration to the general atlas (Dice similarity coefficient increase up to 0.15). Experiments also showed that selecting scans with the registration quality assessment method could improve the quality of average maps of white matter hyperintensity burden, instead of using all scans for the computation of the white matter hyperintensity map. In this work, we demonstrated the utility of an automated tool for assessing image registration quality in clinical scans. This image quality assessment step could ultimately assist in the translation of automated neuroimaging pipelines to the clinic.

BackgroundSelective serotonin reuptake inhibitors (SSRIs) have been implicated in contributing to recovery after acute ischaemic stroke. In particular, poststroke initiation of an SSRI has been demonstrated to improve motor recovery. The role of prestroke SSRI use on functional outcomes and stroke recovery is less clear. We aimed to examine the effect of prestroke SSRI use on metrics of hospitalisation and functional recovery.MethodsWe included 4968 consecutive patients from January 2006 to June 2015 in our local Get With The Guidelines-Stroke registry in whom a preadmission drug list could be extracted from an administrative research data registry. Univariate and multivariate analyses were performed to identify predictors of functional outcomes.ResultsOn univariate analysis, among 4698 ischaemic strokes (740 SSRI users and 3948 non-users), SSRI use before acute ischaemic stroke did not impact the National Institutes of Health Stroke Scale (NIHSS) admission score, length of stay or rate of symptomatic haemorrhage. Patients using SSRIs prior to their stroke were more likely to present with weakness (57% vs 47.3%; PConclusionsSSRI use preceding an acute ischaemic stroke is associated with lower rates of discharge to home despite no significant increase in length of stay or NIHSS score.

We present the case of a 63-year-old woman with a glioblastoma multiforme on immunosuppressive steroid doses who developed lethargy and fever. We review the differential diagnosis and emphasize the importance of reframing the case when the clinical course differs from expectation. Once the diagnosis is evident, we discuss the incidence and clinical course in different patient populations.