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September 1, 2001

New imaging strategies for patient selection for thrombolytic and neuroprotective therapies

September 1, 2001 issue
57 (suppl_2) S48-S52

Abstract

Ischemic stroke trials have traditionally sought to limit the range of disease studied according to several dimensions based on clinical examination and CT scan results. It has been proposed that the optimal sample for stroke trials would include a positive imaging diagnosis of a pathology rationally linked to the drug’s mechanisms of action and that this would improve the likelihood of positive results.
This principle has been supported by the results of the Prolyse in Acute Cerebral Thromoembolism II (PROACT II) study. Whereas trials of iv thrombolysis between 3 and 6 hours after symptom onset in a general sample of patients were not positive, selection of a subgroup by angiography was an effective strategy in this time period for PROACT II. This study contradicted the hypothesis that treatment of stroke beyond 3 hours would not be successful.
MRI with diffusion and perfusion has been an appealing imaging modality because it provides pretreatment angiography, perfusion, and lesion volume information during a brief, non-invasive assessment. Current literature supports the validity of MRI as a marker for clinical severity and clinical improvement. The diffusion–perfusion mismatch, the MRI marker for the ischemic penumbra, is a very strong predictor of lesion volume growth. Several acute trials in progress use a positive imaging diagnosis for the basis of selection. As the field of stroke clinical trials examines opportunities for improving trial design, positive imaging diagnoses in patient selection are likely to assume an increasingly useful role.

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Information & Authors

Information

Published In

Neurology®
Volume 57Number suppl_2September 1, 2001
Pages: S48-S52
PubMed: 11552055

Publication History

Published online: September 1, 2001
Published in print: September 1, 2001

Authors

Affiliations & Disclosures

Steven Warach, MD, PhD
From the National Institute of Neurological Disorders and Stroke, Bethesda, Maryland.

Notes

Address correspondence and reprint requests to Dr. Steven Warach, National Institute of Neurological Disorders and Stroke, Section on Stroke Diagnostics and Therapeutics, 36 Convent Drive, MSC 4129, Room 4A03, Bethesda, MD, 20892-4129.

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  1. Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP), Insights into Imaging, 14, 1, (2023).https://doi.org/10.1186/s13244-023-01472-z
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  2. Clinical Application of Perfusion and Diffusion in Stroke, Functional Neuroradiology, (161-173), (2023).https://doi.org/10.1007/978-3-031-10909-6_6
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  3. Detection of tissue pH with quantitative chemical exchange saturation transfer magnetic resonance imaging, NMR in Biomedicine, 36, 6, (2022).https://doi.org/10.1002/nbm.4711
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  4. Whole blood viscosity is associated with baseline cerebral perfusion in acute ischemic stroke, Neurological Sciences, 43, 4, (2375-2381), (2021).https://doi.org/10.1007/s10072-021-05666-5
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  5. False ischaemic penumbras in CT perfusion in patients with carotid artery stenosis and changes following angioplasty and stenting, Neurología (English Edition), 35, 1, (24-31), (2020).https://doi.org/10.1016/j.nrleng.2017.06.001
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  7. Evidence-Based Emergency Neuroimaging in Children and Adults with Sickle Cell Disease and Symptoms of Stroke, Evidence-Based Emergency Imaging, (519-543), (2018).https://doi.org/10.1007/978-3-319-67066-9_33
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  8. Comparison of 3- and 20-Gradient Direction Diffusion-Weighted Imaging in a Clinical Subacute Cohort of Patients with Transient Ischemic Attack: Application of Standard Vendor Protocols for Lesion Detection and Final Infarct Size Projection, Frontiers in Neurology, 8, (2017).https://doi.org/10.3389/fneur.2017.00691
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  9. Management of Acute Hypertensive Response in Patients With Ischemic Stroke, The Neurohospitalist, 6, 3, (122-129), (2016).https://doi.org/10.1177/1941874416630029
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  10. Diffusion Magnetic Resonance Imaging Study of a Rat Hippocampal Slice Model for Acute Brain Injury, Journal of Cerebral Blood Flow & Metabolism, 23, 12, (1461-1470), (2016).https://doi.org/10.1097/01.WCB.0000100852.67976.C2
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