Abstract WP50: MRI Biomarkers in Acute Stroke: Addition of Clinical Parameters Improves the Identification of Patients Eligible for Thrombolysis
| Autor: | Ivana Galinovic, Carla N. Wood, Steve Z. Martin, Federico C. von Samson-Himmelstjerna, Olivier Zaro Weber, Martin Ebinger, Walter Moeller-Hartmann, Jochen B. Fiebach, Jan Sobesky, Gajanan S. Revankar, Vince I. Madai, Wolf-Dieter Heiss, Sophie K. Piper, Ulrike Grittner |
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| Rok vydání: | 2016 |
| Předmět: |
Advanced and Specialized Nursing
medicine.medical_specialty business.industry medicine.medical_treatment Thrombolysis Fluid-attenuated inversion recovery medicine.disease Surgery Stroke onset Time windows medicine In patient cardiovascular diseases Neurology (clinical) Radiology Cardiology and Cardiovascular Medicine business Stroke Diffusion MRI Acute stroke |
| Zdroj: | Stroke. 47 |
| ISSN: | 1524-4628 0039-2499 |
| Popis: | Introduction: Patients with unknown time from stroke onset, e.g. in wake-up stroke, are not eligible for thrombolyic treatment. Relative signal intensities (rSI) of DWI and FLAIR MRI are biomarkers for eligibility for thrombolysis, but have shown heterogeneous results to date. We investigated if the addition of available clinical parameters improves the prediction of the thrombolysis time window in patients with acute stroke. Hypothesis: Inclusion of clinical parameters improves the prediction of the thrombolysis time window by quantitative MRI biomarkers Methods: Patients from two centers with proven stroke and stroke-onset Results: 82 patients were included. In the unadjusted analysis, DWI-mean and -std (AUC: 0.86, 0.87) performed best. Adjustment for clinical parameters significantly improved the performance of FLAIR-mean (0.87) and DWI-std (0.91). The best performance was found for the final stratified and adjusted models of DWI-std (0.94) and FLAIR-mean (0.96). ADC-rSIs showed no clinically acceptable performance in all models. Conclusion: rSIs of DWI and FLAIR MRI predict eligibility for thrombolysis in acute stroke with high precision, when easily available clinical parameters are included in the prediction. |
| Databáze: | OpenAIRE |
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