Patent Foramen Ovale and Atrial Septal Defect.

Patent foramen ovale (PFO) and atrial septal defects (ASDs) are two types of interatrial communications with unique clinical presentations and management strategies. The PFO is a normal part of fetal development that typically closes shortly after birth but may persist in as many as 25% to 30% of adults. The communication between atria may result in paradoxic embolism and embolic stroke. On the other hand, ASDs (anatomically defined as secundum, primum, sinus venosus, and coronary sinus in order of prevalence) typically result in right heart volume overload and are often associated with other congenital defects. The diagnostic methods, treatment options including surgical and percutaneous approaches, and potential complications are described. Both conditions underline the significance of precise diagnosis and appropriate management to mitigate risks and ensure optimal patient outcomes.

A Randomized, Placebo-Controlled, Phase II Trial of Intravenous Allogeneic Non-HLA Matched, Unrelated Donor, Cord Blood Infusion for Ischemic Stroke.

Stroke remains a leading cause of death and disability in the US, and time-limited reperfusion strategies remain the only approved treatment options. To address this unmet clinical need, we conducted a phase II randomized clinical trial to determine whether intravenous infusion of banked, non-HLA matched unrelated donor umbilical cord blood (UCB) improved functional outcome after stroke. Participants were randomized 2:1 to UCB or placebo within strata of National Institutes of Health Stroke Scale Score (NIHSS) and study center. Study product was infused 3-10 days following index stroke. The primary endpoint was change in modified Rankin Scale (mRS) from baseline to day 90. Key secondary outcomes included functional independence, NIHSS, the Barthel Index, and assessment of adverse events. The trial was terminated early due to slow accrual and logistical concerns associated with the COVID-19 pandemic, and a total of 73 of a planned 100 participants were included in primary analyses. The median (range) of the change in mRS was 1 point (-2, 3) in UCB and 1 point (-1,4) in Placebo (P = 0.72). A shift analysis comparing the mRS at day 90 utilizing proportional odds modeling showed a common odds ratio of 0.9 (95% CI: 0.4, 2.3) after adjustment for baseline NIHSS and randomization strata. The distribution of adverse events was similar between arms. Although this study did not suggest any safety concerns related to UCB in ischemic stroke, we did not show a clinical benefit in the reduced sample size evaluated.

Robot-Assisted Transcranial Doppler Versus Transthoracic Echocardiography for Right to Left Shunt Detection.

BACKGROUND: Right to left shunt (RLS), including patent foramen ovale, is a recognized risk factor for stroke. RLS/patent foramen ovale diagnosis is made by transthoracic echocardiography (TTE), which is insensitive, transesophageal echocardiography, which is invasive, and transcranial Doppler (TCD), which is noninvasive and accurate but scarce. METHODS: We conducted a prospective, single-arm device clinical trial of robot-assisted TCD (raTCD) versus TTE for RLS diagnosis at 6 clinical sites in patients who presented with an event suspicious for embolic cerebrovascular ischemia from October 6, 2020 to October 20, 2021. raTCD was performed with standard TCD bubble study technique. TTE bubble study was performed per local standards. The primary outcome was rate of RLS detection by raTCD versus TTE. RESULTS: A total of 154 patients were enrolled, 129 evaluable (intent to scan) and 121 subjects had complete data per protocol. In the intent to scan cohort, mean age was 60±15 years, 47% were women, and all qualifying events were diagnosed as ischemic stroke or transient ischemic attack. raTCD was positive for RLS in 82 subjects (64%) and TTE was positive in 26 (20%; absolute difference 43.4% [95% CI, 35.2%-52.0%]; P<0.001). On prespecified secondary analysis, large RLS was detected by raTCD in 35 subjects (27%) versus 13 (10%) by TTE (absolute difference 17.0% [95% CI, 11.5%-24.5%]; P<0.001). There were no serious adverse events. CONCLUSIONS: raTCD was safe and ≈3 times more likely to diagnose RLS than TTE. TTE completely missed or underdiagnosed two thirds of large shunts diagnosed by raTCD. The raTCD device, used by health professionals with no prior TCD training, may allow providers to achieve the known sensitivity of TCD for RLS and patent foramen ovale detection without the need for an experienced operator to perform the test. Pending confirmatory studies, TCD appears to be the superior screen for RLS compared with TTE (funded by NeuraSignal). REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT04604015.

Stroke severity mediates the effect of socioeconomic disadvantage on poor outcomes among patients with intracerebral hemorrhage.

Background: Socioeconomic deprivation drives poor functional outcomes after intracerebral hemorrhage (ICH). Stroke severity and background cerebral small vessel disease (CSVD) burden have each been linked to socioeconomic status and independently contribute to worse outcomes after ICH, providing distinct, plausible pathways for the effects of deprivation. We investigate whether admission stroke severity or cerebral small vessel disease (CSVD) mediates the effect of socioeconomic deprivation on 90-day functional outcomes. Methods: Electronic medical record data, including demographics, treatments, comorbidities, and physiological data, were analyzed. CSVD burden was graded from 0 to 4, with severe CSVD categorized as ≥3. High deprivation was assessed for patients in the top 30% of state-level area deprivation index scores. Severe disability or death was defined as a 90-day modified Rankin Scale score of 4-6. Stroke severity (NIH stroke scale (NIHSS)) was classified as: none (0), minor (1-4), moderate (5-15), moderate-severe (16-20), and severe (21+). Univariate and multivariate associations with severe disability or death were determined, with mediation evaluated through structural equation modelling. Results: A total of 677 patients were included (46.8% female; 43.9% White, 27.0% Black, 20.7% Hispanic, 6.1% Asian, 2.4% Other). In univariable modelling, high deprivation (odds ratio: 1.54; 95% confidence interval: [1.06-2.23]; p = 0.024), severe CSVD (2.14 [1.42-3.21]; p < 0.001), moderate (8.03 [2.76-17.15]; p < 0.001), moderate-severe (32.79 [11.52-93.29]; p < 0.001), and severe stroke (104.19 [37.66-288.12]; p < 0.001) were associated with severe disability or death. In multivariable modelling, severe CSVD (3.42 [1.75-6.69]; p < 0.001) and moderate (5.84 [2.27-15.01], p < 0.001), moderate-severe (27.59 [7.34-103.69], p < 0.001), and severe stroke (36.41 [9.90-133.85]; p < 0.001) independently increased odds of severe disability or death; high deprivation did not. Stroke severity mediated 94.1% of deprivation's effect on severe disability or death (p = 0.005), while CSVD accounted for 4.9% (p = 0.524). Conclusion: CSVD contributed to poor functional outcome independent of socioeconomic deprivation, while stroke severity mediated the effects of deprivation. Improving awareness and trust among disadvantaged communities may reduce admission stroke severity and improve outcomes.

Reliability of the National Institutes of Health (NIH) Stroke Scale Between Emergency Room and Neurology Physicians for Initial Stroke Severity Scoring.

INTRODUCTION: In patients with acute ischemic stroke (AIS), the National Institutes of Health Stroke Scale (NIHSS) is essential to establishing a patient's initial stroke severity. While previous research has validated NIHSS scoring reliability between neurologists and other clinicians, it has not specifically evaluated NIHSS scoring reliability between emergency room (ER) and neurology physicians within the same clinical scenario and timeframe in a large cohort of patients. This study specifically addresses the key question: does an ER physician's NIHSS score agree with the neurologist's NIHSS score in the same patient at the same time in a real-world context? METHODS: Data was retrospectively collected from 1,946 patients being evaluated for AIS at Houston Methodist Hospital from 05/2016 - 04/2018. Triage NIHSS scores assessed by both the ER and neurology providers within one hour of each other under the same clinical context were evaluated for comparison. Ultimately, 129 patients were included in the analysis. All providers in this study were NIHSS rater-certified. RESULTS: The distribution of the NIHSS score differences (ER score - neurology score) had a mean of -0.46 and a standard deviation of 2.11. The score difference between provider teams ranged ±5 points. The intraclass correlation coefficient (ICC) for the NIHSS scores between the ER and neurology teams was 0.95 (95% CI, 0.93 - 0.97) with an F-test of 42.41 and a p-value of 4.43E-69. Overall reliability was excellent between the ER and neurology teams. CONCLUSION: We evaluated triage NIHSS scores performed by ER and neurology providers under matching time and treatment conditions and found excellent interrater reliability. The excellent score agreement has important implications for treatment decision-making during patient handoff and further in stroke modeling, prediction, and clinical trial registries where missing NIHSS scores may be equivalently substituted from either provider team.

BBox-Guided Segmentor: Leveraging expert knowledge for accurate stroke lesion segmentation using weakly supervised bounding box prior.

Stroke is one of the leading causes of death and disability in the world. Despite intensive research on automatic stroke lesion segmentation from non-invasive imaging modalities including diffusion-weighted imaging (DWI), challenges remain such as a lack of sufficient labeled data for training deep learning models and failure in detecting small lesions. In this paper, we propose BBox-Guided Segmentor, a method that significantly improves the accuracy of stroke lesion segmentation by leveraging expert knowledge. Specifically, our model uses a very coarse bounding box label provided by the expert and then performs accurate segmentation automatically. The small overhead of having the expert provide a rough bounding box leads to large performance improvement in segmentation, which is paramount to accurate stroke diagnosis. To train our model, we employ a weakly-supervised approach that uses a large number of weakly-labeled images with only bounding boxes and a small number of fully labeled images. The scarce fully labeled images are used to train a generator segmentation network, while adversarial training is used to leverage the large number of weakly-labeled images to provide additional learning signals. We evaluate our method extensively using a unique clinical dataset of 99 fully labeled cases (i.e., with full segmentation map labels) and 831 weakly labeled cases (i.e., with only bounding box labels), and the results demonstrate the superior performance of our approach over state-of-the-art stroke lesion segmentation models. We also achieve competitive performance as a SOTA fully supervised method using less than one-tenth of the complete labels. Our proposed approach has the potential to improve stroke diagnosis and treatment planning, which may lead to better patient outcomes.

Readmission in patients undergoing percutaneous patent foramen ovale closure in the United States.

Current estimates suggest that a patent foramen ovale (PFO) may exist in up to 25% of the general population and is a potential risk factor for embolic, ischemic stroke. PFO closure complications include bleeding, need for procedure-related surgical intervention, pulmonary emboli, device malpositioning, new onset atrial arrhythmias, and transient atrioventricular block. Rates of PFO closure complications at a national level in the Unites States remain unknown. To address this, we performed a contemporary nationwide study using the 2016 and 2017 Nationwide Readmissions Database (NRD) to identify patterns of readmissions after percutaneous PFO closure. In conclusion, our study showed that following PFO closure, the most common complications were atrial fibrillation/atrial flutter followed by acute heart failure syndrome, supraventricular tachycardia and acute myocardial infarction.

DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning.

In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical tests are commonly referred to during the process, but the misdiagnosis rate remains high. We propose a novel multimodal deep learning framework, DeepStroke, to achieve computer-aided stroke presence assessment by recognizing patterns of minor facial muscles incoordination and speech inability for patients with suspicion of stroke in an acute setting. Our proposed DeepStroke takes one-minute facial video data and audio data readily available during stroke triage for local facial paralysis detection and global speech disorder analysis. Transfer learning was adopted to reduce face-attribute biases and improve generalizability. We leverage a multi-modal lateral fusion to combine the low- and high-level features and provide mutual regularization for joint training. Novel adversarial training is introduced to obtain identity-free and stroke-discriminative features. Experiments on our video-audio dataset with actual ER patients show that DeepStroke outperforms state-of-the-art models and achieves better performance than both a triage team and ER doctors, attaining a 10.94% higher sensitivity and maintaining 7.37% higher accuracy than traditional stroke triage when specificity is aligned. Meanwhile, each assessment can be completed in less than six minutes, demonstrating the framework's great potential for clinical translation.

Automatic Segmentation in Acute Ischemic Stroke: Prognostic Significance of Topological Stroke Volumes on Stroke Outcome.

BACKGROUND: Stroke infarct volume predicts patient disability and has utility for clinical trial outcomes. Accurate infarct volume measurement requires manual segmentation of stroke boundaries in diffusion-weighted magnetic resonance imaging scans which is time-consuming and subject to variability. Automatic infarct segmentation should be robust to rotation and reflection; however, prior work has not encoded this property into deep learning architecture. Here, we use rotation-reflection equivariance and train a deep learning model to segment stroke volumes in a large cohort of well-characterized patients with acute ischemic stroke in different vascular territories. METHODS: In this retrospective study, patients were selected from a stroke registry at Houston Methodist Hospital. Eight hundred seventy-five patients with acute ischemic stroke in any brain area who had magnetic resonance imaging with diffusion-weighted imaging were included for analysis and split 80/20 for training/testing. Infarct volumes were manually segmented by consensus of 3 independent clinical experts and cross-referenced against radiology reports. A rotation-reflection equivariant model was developed based on U-Net and grouped convolutions. Segmentation performance was evaluated using Dice score, precision, and recall. Ninety-day modified Rankin Scale outcome prediction was also evaluated using clinical variables and segmented stroke volumes in different brain regions. RESULTS: Segmentation model Dice scores are 0.88 (95% CI, 0.87-0.89; training) and 0.85 (0.82-0.88; testing). The modified Rankin Scale outcome prediction AUC using stroke volume in 30 refined brain regions based upon modified Rankin Scale-relevance areas adjusted for clinical variables was 0.80 (0.76-0.83) with an accuracy of 0.75 (0.72-0.78). CONCLUSIONS: We trained a deep learning model with encoded rotation-reflection equivariance to segment acute ischemic stroke lesions in diffusion- weighted imaging using a large data set from the Houston Methodist stroke center. The model achieved competitive performance in 175 well-balanced hold-out testing cases that include strokes from different vascular territories. Furthermore, the location specific stroke volume segmentations from the deep learning model combined with clinical factors demonstrated high AUC and accuracy for 90-day modified Rankin Scale in an outcome prediction model.

An Intelligent Augmented Lifelike Avatar App for Virtual Physical Examination of Suspected Strokes.

An intelligent-augmented lifelike avatar mobile app (iLAMA) that integrates computer vision and sensor readings to automate and streamline the NIH Stroke Scale (NIHSS) physical examination is presented. The user interface design is optimized for elderly patients while the app showcases an animated lifelike 3D model of a friendly physician who walks the user through the exam. The standardized NIHSS examination included in iLAMA consists of five core tasks. The first two tasks involve rolling the eyes to the left and then to the right, and then smiling as wide as the user can. The app determines facial landmarks and analyzes the palsy of the face. The next task is to extend the arm and hold the phone at the shoulder level, and the smart phone gyroscope is used to detect acceleration to determine possible weakness in the arm. Next, the app tracks the location of the hand keypoints and determines possible ataxia based on the precision and accuracy of the locations of the touches. Finally, the app determines the user's forward acceleration in walking and possible imbalances using the accelerometer. The app then sends analyzed results of these tasks to the neurologist or stroke specialist for review and decisions.Clinical Relevance- The physical examination of a stroke patient is a time consuming and repetitive process, and there is a lack of infrastructure and resource to monitor patient in post-stroke recovery after they leave the hospital for home or rehabilitation facilities. iLAMA app aims to automate a subset of the NIHSS physical examinations in measuring motor function recovery and also allows individual patients to track their performance over time. It will be an essential component in monitoring rehabilitation recovery and therapy effectiveness after hospitalization and can easily scaled to lo help millions of patients at a fraction of the cost.

Retrospective study of deep learning to reduce noise in non-contrast head CT images.

PURPOSE: Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framework with group convolutions and a novel loss function to improve the subjective and objective image quality for improved disease detection in patients with acute ischemic stroke (AIS). MATERIALS AND METHODS: In this retrospective study, confirmed AIS patients with full-dose NCCT head scans were randomly selected from a stroke registry between 2016 and 2020. 325 patients (67 ± 15 years, 176 men) were included. 18 patients each with 4-7 NCCTs performed within 5-day timeframe (83 total scans) were used for model training; 307 patients each with 1-4 NCCTs performed within 5-day timeframe (380 total scans) were used for hold-out testing. In the training group, a mean CT was created from the patient's co-registered scans for each input CT to train a rotation-reflection equivariant U-Net with skip and residual connections, as well as a group convolutional neural network (SRED-GCNN) using a custom loss function to remove image noise. Denoising performance was compared to the standard Block-matching and 3D filtering (BM3D) method and RED-CNN quantitatively and visually. Signal-to-noise ratio (SNR) and contrast-to-noise (CNR) were measured in manually drawn regions-of-interest in grey matter (GM), white matter (WM) and deep grey matter (DG). Visual comparison and impact on spatial resolution were assessed through phantom images. RESULTS: SRED-GCNN reduced the original CT image noise significantly better than BM3D, with SNR improvements in GM, WM, and DG by 2.47x, 2.83x, and 2.64x respectively and CNR improvements in DG/WM and GM/WM by 2.30x and 2.16x respectively. Compared to the proposed SRED-GCNN, RED-CNN reduces noise effectively though the results are visibly blurred. Scans denoised by the SRED-GCNN are shown to be visually clearer with preserved anatomy. CONCLUSION: The proposed SRED-GCNN model significantly reduces image noise and improves signal-to-noise and contrast-to-noise ratios in 380 unseen head NCCT cases.

Transcranial Doppler and magnetic resonance angiography assessment of intracranial stenosis: An analysis of screening modalities.

BACKGROUND: Time-of-flight (TOF) magnetic resonance angiography (MRA) of the head and transcranial Doppler (TCD) are used to diagnose intracranial stenosis, an important cause of ischemic stroke. We aimed to compare TCD findings with TOF-MRA results in a population of patients with symptoms of cerebrovascular disease in whom both tests were done within a short intervening period of each other. METHODS: This is a retrospective, single-center study. Among adult patients referred for symptoms of cerebrovascular disease in both outpatient and inpatient settings, those who received a TCD with adequate insonation of all intracranial arteries and underwent MRA within 3 months intervals of TCD were included in this study. We evaluated the agreement between the results of these two modalities, and also assessed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of TCD through receiver-operating characteristic (ROC) curve analysis, while MRA considered as a comparator. RESULTS: Among eighty included patients, 720 arteries were examined. An overall significant agreement of 96.5% was observed between TCD and MRA (Kappa = 0.377, P < 0.001). Compared to MRA, TCD had sensitivity of 42.1%, specificity of 99.6%, PPV of 72.7%, and NPV of 98.4% (ROC area: 0.708 [0.594-0.822]). TCD is specifically accurate in evaluating middle cerebral artery (MCA) (ROC area = 0.83). CONCLUSIONS: The high NPV of TCD in our study indicates the utility of TCD as a diagnostic test to exclude the presence of intracranial stenosis. This study supports TCD as a convenient, safe, and reproducible imaging modality applicable in the screening of intracranial stenosis, especially to evaluate MCA.

Cerebrovascular Disease in Patients with COVID-19: A Review of the Literature and Case Series.

COVID-19 has been associated with a hypercoagulable state causing cardiovascular and neurovascular complications. To further characterize cerebrovascular disease (CVD) in COVID-19, we review the current literature of published cases and additionally report the clinical presentation, laboratory and diagnostic testing results of 12 cases with COVID-19 infection and concurrent CVD from two academic medical centers in Houston, TX, USA, between March 1 and May 10, 2020. To date, there are 12 case studies reporting 47 cases of CVD in COVID-19. However, only 4 small case series have described the clinical and laboratory findings in patients with COVID-19 and concurrent stroke. Viral neurotropism, endothelial dysfunction, coagulopathy and inflammation are plausible proposed mechanisms of CVD in COVID-19 patients. In our case series of 12 patients, 10 patients had an ischemic stroke, of which 1 suffered hemorrhagic transformation and two had intracerebral hemorrhage. Etiology was determined to be embolic without a clear cause identified in 6 ischemic stroke patients, while the remaining had an identifiable source of stroke. The majority of the patients had elevated inflammatory markers such as D-dimer and interleukin-6. In patients with embolic stroke of unclear etiology, COVID-19 may have played a direct or indirect role in the processes that eventually led to the strokes while in the remaining cases, it is unclear if infection contributed partially or was an incidental finding.

Multifocal transcranial stimulation in chronic ischemic stroke: A phase 1/2a randomized trial.

BACKGROUND AND PURPOSE: Repetitive transcranial magnetic stimulation (rTMS) may promote recovery of motor function after stroke by inducing functional reorganization of cortical circuits. The objective of this study was to examine whether multifocal cortical stimulation using a new wearable transcranial rotating permanent magnet stimulator (TRPMS) can promote recovery of motor function after stroke by inducing functional reorganization of cortical circuits. METHODS: Thirty30 patients with chronic ischemic stroke and stable unilateral weakness were enrolled in a Phase 1/2a randomized double-blind sham-controlled clinical trial to evaluate safety and preliminary efficacy. Bilateral hemispheric stimulation was administered for 20 sessions 40 min each over 4 weeks. The primary efficacy endpoint was the change in functional MRI BOLD activation immediately after end of treatment. Secondary efficacy endpoints were clinical scales of motor function, including the Fugl-Meyer motor arm score, ARAT, grip strength, pinch strength, gait velocity, and NIHSS. RESULTS: TRPMS treatment was well-tolerated with no device-related adverse effects. Active treatment produced a significantly greater increase in the number of active voxels on fMRI than sham treatment (median +48.5 vs -30, p = 0.038). The median active voxel number after active treatment was 8.8-fold greater than after sham (227.5 vs 26, p = 0.016). Although the statistical power was inadequate to establish clinical endpoint benefits, numerical improvements were demonstrated in 5 of 6 clinical scales of motor function. The treatment effects persisted over a 3-month duration of follow-up. CONCLUSIONS: Multifocal bilateral TRPMS was safe and showed significant fMRI changes suggestive of functional reorganization of cortical circuits in patients with chronic ischemic stroke. A larger randomized clinical trial is warranted to verify recovery of motor function.

Thrombectomy in DAWN- and DEFUSE-3-Ineligible Patients: A Subgroup Analysis From the BEST Prospective Cohort Study.

BACKGROUND: Because of the overwhelming benefit of thrombectomy for highly selected trial patients with large vessel occlusion (LVO), some trial-ineligible patients are being treated in practice. OBJECTIVE: To determine the safety and efficacy of thrombectomy in DAWN/DEFUSE-3-ineligible patients. METHODS: Using a multicenter prospective observational study of consecutive patients with anterior circulation LVO who underwent late thrombectomy, we compared symptomatic intracerebral hemorrhage (sICH) and good outcome (90-d mRS 0-2) among DAWN/DEFUSE-3-ineligible patients to trial-eligible patients and to untreated DAWN/DEFUSE-3 controls. RESULTS: Ninety-eight patients had perfusion imaging and underwent thrombectomy >6 h; 46 (47%) were trial ineligible (41% M2 occlusions, 39% mild deficits, 28% ASPECTS <6). In multivariable regression, the odds of a good outcome (aOR 0.76, 95% CI 0.49-1.19) and sICH (aOR 3.33, 95% CI 0.42-26.12) were not different among trial-ineligible vs eligible patients. Patients with mild deficits were more likely to achieve a good outcome (aOR 3.62, 95% CI 1.48-8.86) and less sICH (0% vs 10%, P = .16), whereas patients with ASPECTS <6 had poorer outcomes (aOR 0.14, 95% CI 0.05-0.44) and more sICH (aOR 24, 95% CI 5.7-103). Compared to untreated DAWN/DEFUSE-3 controls, trial-ineligible patients had more sICH (13%BEST vs 3%DAWN [P = .02] vs 4%DEFUSE [P = .05]), but were more likely to achieve a good outcome at 90 d (36%BEST vs 13%DAWN [P < .01] vs 17%DEFUSE [P = .01]). CONCLUSION: Thrombectomy is used in practice for some patients ineligible for the DAWN/DEFUSE-3 trials with potentially favorable outcomes. Additional trials are needed to confirm the safety and efficacy of thrombectomy in broader populations, such as large core infarction and M2 occlusions.

Noncontrast CT versus Perfusion-Based Core Estimation in Large Vessel Occlusion: The Blood Pressure after Endovascular Stroke Therapy Study.

BACKGROUND AND PURPOSE: The 2018 AHA guidelines recommend perfusion imaging to select patients with acute large vessel occlusion (LVO) for thrombectomy in the extended window. However, the relationship between noncontrast CT and CT perfusion imaging has not been sufficiently characterized >6 hours after last known normal (LKN). METHODS: From a multicenter prospective cohort of consecutive adults who underwent thrombectomy for anterior LVO 0-24 hours after LKN, we correlated baseline core volume (rCBF < 30%) and the Alberta Stroke Program Early CT Scale (ASPECTS) score. We compared perfusion findings between patients with an unfavorable ASPECTS (<6) against those with a favorable ASPECTS (≥6), and assessed findings over time. RESULTS: Of 485 enrolled patients, 177 met inclusion criteria (median age: 69 years, interquartile range [IQR: 57-81], 49% female, median ASPECTS 8 [IQR: 6-9], median core 10 cc [IQR: 0-30]). ASPECTS and core volume moderately correlated (r = -.37). A 0 cc core was observed in 54 (31%) patients, 70% of whom had ASPECTS <10. Of the 28 patients with ASPECTS <6, 3 (11%) had a 0 cc core. After adjustment for age and stroke severity, there was a lower ASPECTS for every 1 hour delay from LKN (cOR: 0.95, 95% confidence of interval [CI]: 0.91-1.00, P = .04). There was no difference in core (P = .51) or penumbra volumes (P = .87) across patients over time. CONCLUSIONS: In this multicenter prospective cohort of patients who underwent thrombectomy, one-third of patients had normal CTP core volumes despite nearly three quarters of patients showing ischemic changes on CT. This finding emphasizes the need to carefully assess both noncontrast and perfusion imaging when considering thrombectomy eligibility.

Blood Pressure after Endovascular Therapy for Ischemic Stroke (BEST): A Multicenter Prospective Cohort Study.

Background and Purpose- To identify the specific post-endovascular stroke therapy (EVT) peak systolic blood pressure (SBP) threshold that best discriminates good from bad functional outcomes (a priori hypothesized to be 160 mm Hg), we conducted a prospective, multicenter, cohort study with a prespecified analysis plan. Methods- Consecutive adult patients treated with EVT for an anterior ischemic stroke were enrolled from November 2017 to July 2018 at 12 comprehensive stroke centers accross the United States. All SBP values within 24 hours post-EVT were recorded. Using Youden index, the threshold of peak SBP that best discriminated primary outcome of dichotomized 90-day modified Rankin Scale score (0-2 versus 3-6) was identified. Association of this SBP threshold with the outcomes was quantified using multiple logistic regression. Results- Among 485 enrolled patients (median age, 69 [interquartile range, 57-79] years; 51% females), a peak SBP of 158 mm Hg was associated with the largest difference in the dichotomous modified Rankin Scale score (absolute risk reduction of 19%). Having a peak SBP >158 mm Hg resulted in an increased likelihood of modified Rankin Scale score 3 to 6 (odds ratio, 2.24 [1.52-3.29], P<0.01; adjusted odds ratio, 1.29 [0.81-2.06], P=0.28, after adjustment for prespecified variables). Conclusions- A peak post-EVT SBP of 158 mm Hg was prospectively identified to best discriminate good from bad functional outcome. Those with a peak SBP >158 had an increased likelihood of having a bad outcome in unadjusted, but not in adjusted analysis. The observed effect size was similar to prior studies. This finding should undergo further testing in a future randomized trial of goal-targeted post-EVT antihypertensive treatment.