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Background: Diffusion-weighted imaging lesion reversal (DWIR) is frequently observed after mechanical thrombectomy for acute ischemic stroke, but little is known about age-related differences and impact on outcome. We aimed to compare, in patients Methods: We retrospectively analyzed data of patients treated for an anterior circulation acute ischemic stroke with large vessel occlusion in 2 French hospitals, who underwent baseline and 24-hour follow-up magnetic resonance imaging, with baseline DWI lesion volume ≥10 cc. The percentage of DWIR (DWIR%), was calculated as follows: DWIR%=(DWIR volume/baseline DWI volume)×100. Data on demographics, medical history, and baseline clinical and radiological characteristics were collected. Results: Among 433 included patients (median age, 68 years), median DWIR% after mechanical thrombectomy was 22% (6–35) in patients ≥80, and 19% (interquartile range, 10–34) in patients P =0.948). In multivariable analyses, successful recanalization after mechanical thrombectomy was associated with higher median DWIR% in both ≥80 ( P =0.004) and P =0.002) patients. In subgroup analyses performed on a minority of subjects, collateral vessels status score (n=87) and white matter hyperintensity volume (n=131) were not associated with DWIR% ( P >0.2). In multivariable analyses, DWIR% was associated with increased rates of favorable 3-month outcomes in both ≥80 ( P =0.003) and P =0.013) patients; the effect of DWIR% on outcome was not influenced by the age group ( P interaction=0.185) Conclusions: DWIR might be an important and nonage-dependent effect of arterial recanalization, as it seems to beneficially impact 3-month outcomes of both younger and older subjects treated with mechanical thrombectomy for acute ischemic stroke and large vessel occlusion.

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.

Introduction: Predicting individual outcomes post-stroke with the highest possible accuracy is a crucial steppingstone in the realization of precision medicine. We here evaluated various types of lesion information in their capacity to predict stroke severity in a large cohort of patients with acute ischemic stroke. Methods: A total of 1,075 patients of the MRI-GENIE study [age: 64.2(14.7), 38% women] contributed to analyses (N=792 as train and N=283 as test sample). We employed ridge regression with hyperparameter optimization and nested five-fold cross-validation to predict acute NIHSS-based stroke severity. Our baseline model considered DWI lesion volume. Further models tested structural lesion location, indirect structural and functional lesion connectivity, individually and combined with lesion volume. Data was preprocessed by principal component analysis (PCA), retaining 95% of the variance of the original data. Model performance was compared in terms of explained variance (R-squared) and 95% confidence intervals in the outer loop of the training set and the test set. Results: Structural lesion connectivity enabled the highest prediction performance in the test set ( Figure 1 ). Prediction performance did not change notably with inclusion of lesion volume information. This contrasted with the combination of functional lesion connectivity and lesion volume that achieved a substantially higher prediction performance compared to functional lesion connectivity or lesion volume in isolation. Lesion location resulted in a prediction performance that was in the range of lesion volume alone and significantly lower than the ones of structural or functional connectivity with lesion volume. Conclusions: Structural connectivity facilitated the most convincing prediction of stroke severity. The capacity of functional lesion connectivity was substantially improved by the inclusion of lesion volume, indicating both represent complementary information.

Introduction: Deep learning (DL) has allowed for substantial progress in many, often machine vision-focused medical scenarios. Since DL models typically require 10 5 -10 7 examples, it is currently unknown whether DL can also enhance predictions of outcomes post-stroke in real-world samples of stroke patients that are several magnitudes smaller. We here compared the capacities of linear and DL algorithms regarding their prediction of stroke severity. Methods: Our analyses relied on a total of 1435 patients assembled from the MRI-GENIE study and a Massachusetts General Hospital-based study. The primary outcome was acute NIHSS-based stroke severity, which we predicted by means of lesion location. We automatically derived lesion segmentations from DWI scans, performed spatial normalization and principal component analysis (PCA), retaining 95% of the variance of the original data. We then separated a train, validation, and test set, of sizes 918, 230, and 287 respectively. We downsampled the train set to 100, 300, and 900 and learned to predict the NIHSS score for each sample size with regularized linear regression and an 8-layered neural network. We selected hyperparameters on the validation set and conducted 500 dataset splits. We here report explained variance (R-squared) in the test set. Results: While linear regression performed favorably for a sample size of 100 patients (R-squared=0.28), DL started to significantly outperform linear regression when trained on 900 patients (R-squared=0.34, Figure 1 ). Average prediction performance improved by ~20% when increasing the sample size 9x. Conclusions: For sample sizes of ~1000 patients, DL showed a more convincing prediction performance for stroke severity than typically employed linear methods. Our findings suggest the existence of non-linear relationships between lesion location and outcome post-stroke that can be utilized for an improved prediction performance once samples are reasonably large.

Background Intravenous thrombolysis (IVT) before mechanical thrombectomy (MT) for large‐vessel occlusion (LVO) stroke is increasingly controversial. Recent trials suggest MT without IVT is reasonable for patients presenting directly to MT‐capable “hub” centers. However, bypassing IVT has not been evaluated for patients presenting to IVT‐capable “spoke” hospitals that require hub transfer for MT. A perceived lack of efficacy of IVT to result in LVO early recanalization (ER) is often cited to support bypassing IVT, but data for IVT in patients who require interhospital transfer are limited. Here, we examined LVO ER rates after spoke‐administered IVT in our hub‐and‐spoke stroke network. Methods Patients presenting to 25 spokes before hub transfer for MT consideration from 2018 to 2020 were retrospectively identified from a prospectively maintained database. Inclusion criteria were pretransfer computed tomography angiography–defined LVO, Alberta Stroke Program Early Computed Tomography Score ≥6, and posttransfer repeat vessel imaging. Results Of 167 patients, median age was 69, and 51% were women. Seventy‐six received spoke IVT, and 91 did not. Alteplase was the only IVT used in this study. Comorbidities and National Institutes of Health Stroke Scale were similar between groups. ER frequency was increased 7.2‐fold in patients who received spoke IVT (12/76 [15.8%] versus 2/91 [2.2%]; P P P Conclusion Within our network, patients who received spoke IVT had a 7.2‐fold increased ER relative likelihood. This real‐world analysis supports IVT use in eligible patients with LVO at spoke hospitals before hub transfer for MT.

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.

ObjectiveTo determine whether the association between increasing number of clot retrieval attempts (CRA) and unfavorable outcome is due to an increase in emboli to new territory (ENT) and greater infarct growth (IG) in successfully recanalized patients with acute ischemic stroke due to large vessel occlusion (AIS-LVO).MethodsData were extracted from 2 pooled multicentric prospective registries of consecutive patients with anterior AIS-LVO treated with mechanical thrombectomy (MT) between January 2016 and 2019. Patients with pretreatment and 24-hour posttreatment diffusion-weighted imaging (DWI) achieving successful recanalization, defined as expanded Thrombolysis in Cerebral Infarction Scale score of 2B, 2C, or 3, were included. ENT were assessed and IG was measured by voxel-based segmentation after DWI coregistration. Associations between number of CRA, ENT, IG, and 3-month outcome were analyzed.ResultsFour hundred nineteen patients achieving successful recanalization were included. ENT occurrence was strongly correlated with increasing CRA (ρ = 0.73, p = 10−4). In multivariable linear analysis, IG was independently associated with CRA (β = 1.6 per retrieval attempt, 95% confidence interval [CI] 0.97–9.74, p = 0.03) and ENT (β = 2.7 [95% CI 1.21–4.1], p = 0.03). Unfavorable functional outcome (3-month modified Rankin Scale score >2) increased with each additional CRA. IG was an independent predictor of unfavorable outcome (odds ratio 1.05 [95% CI 1.02–1.07] per 1-mL IG increase, p = 10−4) in binary logistic regression analysis.ConclusionsIncreasing number of CRA in acute stroke is correlated with an increased ENT rate and increased IG volume, affecting functional outcome even when successful recanalization is achieved.Classification of EvidenceThis study provides Class II evidence that, for patients with acute stroke undergoing successful recanalization, an increasing number of CRA is associated with poorer functional outcome.

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.

Introduction: The utility of intravenous thrombolysis (IVT) prior to mechanical thrombectomy (MT) for large vessel occlusion (LVO) stroke is controversial. Low early recanalization (ER) rates and potential delays to MT may support bypassing IVT before MT. Recent trials suggest MT alone is reasonable for LVO patients presenting directly to MT-capable centers. However, bypassing IVT has not been evaluated for patients first presenting to “spoke” hospitals capable of administering IVT but requiring transfer to a “hub” hospital for MT. Here we examined how spoke IVT influences LVO ER and spoke-to-hub transfer time (TT) within our hub-and-spoke network. Methods: Patients presenting to 25 spoke hospitals before hub transfer from 2018 to 2020 who were considered possible EVT candidates with pre-transfer CTA-defined LVO and ASPECTS ≥6 were identified from a prospectively maintained database. ER was determined by chart review of vessel imaging on hub arrival. TT was prospectively recorded. Statistics were performed using permutation resampling and linear regression in R. Results: Of 177 patients included, 76 received IVT. Baseline characteristics, NIHSS, and intracerebral hemorrhage were similar between groups. Spoke IVT improved ER frequency [12/76 (15.8%) vs. 3/101 (3.0%), P Conclusion: Within our network, IVT significantly increases ER and decreases TT, which may contribute to improved 90-day outcomes. This retrospective study supports following current recommendations that IVT be given to all eligible patients at spoke hospitals prior to transfer for MT consideration.

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.

This meeting abstract was removed due to the OA licensing requirements of this journal. The full abstract is listed here : https://www.svin.org/files/SVIN_2021_Abstracts_for_Web.pdf

Introduction : The care of emergent large vessel occlusion (ELVO) stroke patients has been revolutionized by endovascular thrombectomy (EVT). Given its robust efficacy, it is crucial to optimize delivery to eligible patients. 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 reasons EVT candidates become ineligible after transfer for treatment. 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 : 258 patients were identified with median age 70 years (IQR 60–81) and 50% female. 44% 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 : Approaches to increase EVT eligibility among ELVO transfers may improve long term outcomes. A primary reason for becoming EVT ineligible is infarct growth. Future studies should explore triaging patients directly to EVT‐capable hubs when feasible, improving inter‐hospital transfer times, supporting ischemic penumbra before EVT, and developing novel neuroprotective agents.

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.

Objective: Ability of the brain to recover after an acute ischemic stroke (AIS) is linked to the pre-stroke burden of white matter hyperintensity (WMH), a radiographic marker of brain health. We sought to determine the excessive WMH burden in an AIS population and investigate its association with 3-month stroke outcomes. Data: We used 2,435 subjects from the MRI-GENIE study. Three-month functional outcomes of 872 subjects among those subjects were measured by 90-day modified Ranking Scale (mRS). Methods: We automatically quantified WMH volume (WMHv) on FLAIR images and adjusted for a brain volume. We modeled a trend using the factor analysis (FA) log-linear regression using age, sex, atrial fibrillation, diabetes, hypertension, coronary artery disease and smoking as input variables. We categorized three WMH burden groups based on the conditional probability given by the model (LOW: lower 33%, MED: middle 34%, and HIGH: upper 33%). The subgroups were compared with respect to mRS (median and dichotomized odds ratio (OR) (good/poor: mRS 0-2/3-6)). Results: Five FA components out of seven with significant relationship to WMHv (p2 =0.359). The HIGH group showed higher median (median=2, IQR=2) mRS score than LOW (median=1, IQR=1) and MED (median=1, IQR=1). The odds (OR) of good AIS outcome for LOW and MED were 1.8 (p=0.0001) and 1.6 (p=0.006) times higher than HIGH, respectively. Conclusion: Once accounted for clinical covariates, the excessive WMHv was associated with worse 3-month stroke outcomes. These data suggest that a life-time of injury to the white matter reflected in WMH is an important factor for stroke recovery and an indicator of the brain health.

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: Severity of leukoaraiosis detected on T2 MRI scans as white matter hyperintensities (WMH) is associated with infarct growth and poor poststroke outcomes in patients with acute ischemic stroke (AIS). Traditional vascular risk factors (VRF) such as age, hypertension (HTN), type 2 diabetes mellitus (T2D), and cigarette smoking are linked to WMH in large population-based studies, yet casual inferences for WMH in AIS patients are limited. We sought to examine the VRFs for evidence of causal relationships with WMH burden in AIS patients using mendelian randomization principles and polygenic risk score (PRS) methods. Method: We examined FLAIR MRIs obtained within 48 hours of AIS onset in 4,362 European Caucasian patients from the MRI-GENetics Interface Exploration (MRI-GENIE) study. WMH volume (WMHv) was measured using a fully automated deep-learning trained algorithm. We considered 13 VRFs: blood pressure (HTN, SBP, DBP, Pulse Pressure), lipid (total cholesterol, HDL, LDL, TG), BMI, T2D, atrial fibrillation, alcohol use and smoking. For each factor, we calculated a weighted PRS for each individual based on the most recent GWAS with various GWAS p-value cutoff. We then used linear regression to estimate associations between each PRS and log transformed WMHv, controlling for age, gender and principal components of genetic ancestries. Strata-specific estimates were combined using inverse-variance weighting based meta-analysis. Results: PRS of both SBP and DBP were positively and robustly associated with WMHv in the meta-analysis (p value of the association ranging from Conclusion: Using mendelian randomization, our results lend further evidence that high blood pressure is a causal risk factor for WMH in AIS patients. This result is consistent with previous epidemiological studies of leukoaraiosis in stroke-free populations, and it supports universal control of HTN as common contributor to WMH burden and the overall brain health.

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.