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Background and Objectives: Acute ischemic stroke patients with a large vessel occlusion (LVO) who present to a primary stroke center (PSC) often require transfer to a comprehensive stroke center (CSC) for thrombectomy. Not much is known about specific characteristics at the PSC that are associated with infarct growth during transfer. Gaining more insight into these features could aid future trials with cytoprotective agents targeted at slowing infarct growth. We aimed to identify baseline clinical and imaging characteristics that are associated with fast infarct growth rate (IGR) during interhospital transfer., Methods: We included patients from the CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project, a prospective multicenter study. Patients with an anterior circulation LVO who were transferred from a PSC to a CSC for consideration of thrombectomy were eligible if imaging criteria were fulfilled. A CT perfusion (CTP) needed to be obtained at the PSC followed by an MRI at the CSC, before consideration of thrombectomy. The interhospital IGR was defined as the difference between the infarct volumes on MRI and CTP, divided by the time between the scans. Multivariable logistic regression was used to determine characteristics associated with fast IGR (≥5 mL/h)., Results: A total of 183 patients with a median age of 74 years (interquartile range 61-82), of whom 99 (54%) were male and 82 (45%) were fast progressors, were included. At baseline, fast progressors had a higher NIH Stroke Scale score (median 16 vs 13), lower cerebral blood volume index (median 0.80 vs 0.89), more commonly poor collaterals on CT angiography (35% vs 13%), higher hypoperfusion intensity ratios (HIRs) (median 0.51 vs 0.34), and larger core volumes (median 11.80 mL vs 0.00 mL). In multivariable analysis, higher HIR (adjusted odds ratio [aOR] for every 0.10 increase 1.32 [95% CI 1.10-1.59]) and larger core volume (aOR for every 10 mL increase 1.54 [95% CI 1.20-2.11]) remained independently associated with fast IGR., Discussion: Fast infarct growth during interhospital transfer of acute stroke patients is associated with imaging markers of poor collaterals on baseline imaging. These markers are promising targets for patient selection in cytoprotective trials aimed at reducing interhospital infarct growth.

STAIR XII (12th Stroke Treatment Academy Industry Roundtable) included a workshop to discuss the priorities for advancements in neuroimaging in the diagnostic workup of acute ischemic stroke. The workshop brought together representatives from academia, industry, and government. The participants identified 10 critical areas of priority for the advancement of acute stroke imaging. These include enhancing imaging capabilities at primary and comprehensive stroke centers, refining the analysis and characterization of clots, establishing imaging criteria that can predict the response to reperfusion, optimizing the Thrombolysis in Cerebral Infarction scale, predicting first-pass reperfusion outcomes, improving imaging techniques post-reperfusion therapy, detecting early ischemia on noncontrast computed tomography, enhancing cone beam computed tomography, advancing mobile stroke units, and leveraging high-resolution vessel wall imaging to gain deeper insights into pathology. Imaging in acute ischemic stroke treatment has advanced significantly, but important challenges remain that need to be addressed. A combined effort from academic investigators, industry, and regulators is needed to improve imaging technologies and, ultimately, patient outcomes., Competing Interests: Disclosures Dr Samaniego reports compensation from Rapid Medical for consultant services; compensation from Medtronic for consultant services; compensation from iSchemaView for consultant services; compensation from MicroVention, Inc, for consultant services; and compensation from Cerenovus for consultant services. Dr Boltze reports compensation from Targed Biopharmaceuticals B.V. for consultant services; employment by the University of Warwick; and compensation from Astrocyte Pharmaceuticals for consultant services. Dr Lyden reports compensation from the NIH Clinical Center for other services; compensation from Apex Innovations for consultant services; and employment by the University of Southern California. Dr Hill reports grants from Medtronic; compensation from Brainsgate, Ltd, for consultant services; grants from Boehringer Ingelheim; grants from Medtronic; grants from NoNO, Inc; a patent issued for Systems and Methods for Assisting in Decision-Making and Triaging for Acute Stroke Patients licensed to Circle NVI; grants from Medtronic; grants from the Canadian Institutes of Health Research; grants from MicroVention, Inc; and employment by the University of Calgary. Dr Campbell reports employment by the University of Melbourne. Dr Nguyen reports compensation from Brainomix for consultant services and compensation from Idorsia for other services. Dr Silva reports compensation from Boehringer Ingelheim for consultant services; employment by UNIFESP; compensation from Bayer for consultant services; compensation from iSchemaView for consultant services; employment by Sociedade Beneficente Israelita Brasileira Albert Einstein; and compensation from Pfizer for other services. Dr Sheth reports stock holdings in Verve Therapeutics; compensation from Rhaeos for consultant services; compensation from Sense for data and safety monitoring services; compensation from Astrocyte for consultant services; compensation from Cerevasc for consultant services; grants from Hyperfine; employment by Yale School of Medicine; a patent pending for Stroke wearables licensed to Alva Health; stock holdings in AbbVie; grants from Biogen; compensation from CSL Behring for consultant services; and compensation from ZOLL Medical Corporation for data and safety monitoring services. Dr Fisher reports compensation from Simcere USA for consultant services; employment by Beth Israel Deaconess Medical Center; compensation from Lumosa for consultant services; and employment by Beth Israel Deaconess Medical Center. Dr Hillis reports employment by the Johns Hopkins University School of Medicine; compensation from Elsevier Publishing for other services; compensation from the National Institute on Deafness and Other Communication Disorders for other services; and compensation from the American Heart Association for other services. Dr Carone reports stock options in Brainomix, Ltd, and employment by Brainomix, Ltd. Dr Deljkich reports employment by Imperative Care, Inc. Dr Albers reports compensation from Genentech for consultant services; stock holdings in iSchemaView; and compensation from iSchemaView for consultant services. Dr Heit reports compensation from Medtronic for consultant services; compensation from iSchemaView for consultant services; and compensation from MicroVention, Inc, for consultant services. The other authors report no conflicts.

Background: Acute ischemic infarct identification on noncontrast computed tomography (NCCT) is highly variable between raters. A semiautomated method for segmentation of acute ischemic lesions on NCCT may improve interrater reliability., Methods: Patients with successful endovascular reperfusion from the DEFUSE 3 trial (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke) were included. We created relative NCCT (rNCCT) color-gradient overlays by comparing the density of a voxel on NCCT to the homologous region in the contralateral hemisphere. Regions with a relative hypodensity of at least 5% were visualized. We coregistered baseline and follow-up images. Two neuroradiologists and 6 nonradiologists segmented the acute ischemic lesion on the baseline scans with 2 methods: (1) manually outlining hypodense regions on the NCCT (unassisted segmentation) and (2) manually excluding areas deemed outside of the ischemic lesion on the rNCCT color map (rNCCT-assisted segmentation). Voxelwise interrater agreement was quantified using the Dice similarity coefficient and volumetric agreement between raters with the detection index (DI), defined as the true positive volume minus the false positive volume., Results: From a total of 92, we included 61 patients. Median age was 59 (64-77), and 57% were female. Stroke onset was known in 39%. Onset to NCCT was median, 8.5 hours (7-11) and median 10 hours (8.4-11.5) in patients with known and unknown onset, respectively. Compared with unassisted NCCT segmentation, rNCCT-assisted segmentation increased the Dice similarity coefficient by >50% for neuroradiologists (Dice similarity coefficient, 0.38 versus 0.83; P <0.001) and nonradiologists (Dice similarity coefficient, 0.14 versus 0.84; P <0.001), and improved the DI among nonradiologists (mean improvement, 5.8 mL [95% CI, 3.1-8.5] mL, P <0.001) but not among neuroradiologists., Conclusions: The high variability of manual segmentations of the acute ischemic lesion on NCCT is greatly reduced using semiautomated rNCCT. The rNCCT map may therefore aid acute infarct detection and provide more reliable infarct estimates for clinicians with less experience., Competing Interests: Disclosures Dr Christensen reports stock holdings in Ischemaview. Dr Heit reports compensation from iSchemaView for consultant services; compensation from Medtronic for consultant services; and compensation from MicroVention, Inc, for consultant services. Dr Albers reports compensation from iSchemaView for consultant services; compensation from Genentech for consultant services; and stock holdings in iSchemaView. Dr Lemmens reports compensation from iSchemaView for other services. Other coauthors report no disclosures.

Abstract: Advanced magnetic resonance imaging has been used as selection criteria for both acute ischemic stroke treatment and secondary prevention. The use of artificial intelligence, and in particular, deep learning, to synthesize large amounts of data and to understand better how clinical and imaging data can be leveraged to improve stroke care promises a new era of stroke care. In this article, we review common deep learning model structures for stroke imaging, evaluation metrics for model performance, and studies that investigated deep learning application in acute ischemic stroke care and secondary prevention., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: Robust arterial collaterals are associated with successful reperfusion after thrombectomy treatment of acute ischemic stroke due to large vessel occlusion (AIS-LVO). Excellent venous outflow (VO) reflects excellent tissue perfusion and collateral status in patients with AIS-LVO. The goal of this study was to determine whether favorable VO profiles assessed on pretreatment CT angiography (CTA) images correlate with successful vessel reperfusion after thrombectomy in patients with AIS-LVO., Methods: This was a multicenter retrospective cohort study of consecutive patients with AIS-LVO treated by thrombectomy. Baseline CTA was used to assess collateral status (Tan scale) and VO using the Cortical Vein Opacification Score (COVES). Favorable VO was defined as COVES ≥3. Primary outcome was excellent vessel reperfusion status (modified Thrombolysis in Cerebral Infarction 2c/3). Secondary outcome was good functional outcome defined as a score of 0 to 2 on the modified Rankin Scale after 90 days., Results: Five hundred sixty-five patients met the inclusion criteria. Multivariable logistic regression analysis showed that favorable VO (odds ratio [OR] 2.10 [95% confidence interval (CI) 1.39-3.16]; p < 0.001) was associated with excellent vessel reperfusion during thrombectomy, regardless of good CTA collateral status (OR 0.87 [95% CI 0.58-1.34]; p = 0.48). A favorable VO profile (OR 8.9 [95%CI 5.3-14.9]; p < 0.001) and excellent vessel reperfusion status (OR 2.7 [95%CI 1.7-4.4]; p < 0.001) were independently associated with good functional outcome adjusted for age, sex, glucose, tissue plasminogen activator administration, good CTA collateral status, and presentation NIH Stroke Scale score., Conclusion: A favorable VO profile is associated with reperfusion success and good functional outcomes in patients with AIS-LVO treated by endovascular thrombectomy., Classification of Evidence: This study provides Class II evidence that a favorable VO profile is associated with reperfusion success and good functional outcomes in patients with AIS-LVO treated by endovascular thrombectomy., (© 2021 American Academy of Neurology.)