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      A Comparison of T 2 Relaxation-Based MRI Stroke Timing Methods in Hyperacute Ischemic Stroke Patients: A Pilot Study

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          Abstract

          Background:

          T 2 relaxation-based magnetic resonance imaging (MRI) signals may provide onset time for acute ischemic strokes with an unknown onset. The ability of visual and quantitative MRI-based methods in a cohort of hyperacute ischemic stroke patients was studied.

          Methods:

          A total of 35 patients underwent 3T (3 Tesla) MRI (<9-hour symptom onset). Diffusion-weighted (DWI), apparent diffusion coefficient (ADC), T 1-weighted (T 1w), T 2-weighted (T 2w), and T 2 relaxation time (T 2) images were acquired. T 2-weighted fluid attenuation inversion recovery (FLAIR) images were acquired for 17 of these patients. Image intensity ratios of the average intensities in ischemic and non-ischemic reference regions were calculated for ADC, DWI, T 2w, T 2 relaxation, and FLAIR images, and optimal image intensity ratio cut-offs were determined. DWI and FLAIR images were assessed visually for DWI/FLAIR mismatch.

          Results:

          The T 2 relaxation time image intensity ratio was the only parameter with significant correlation with stroke duration ( r = 0.49, P = .003), an area under the receiver operating characteristic curve (AUC = 0.77, P < .0001), and an optimal cut-off (T 2 ratio = 1.072) that accurately identified patients within the 4.5-hour thrombolysis treatment window with sensitivity of 0.74 and specificity of 0.74. In the patients with the additional FLAIR, areas under the precision-recall-gain curve (AUPRG) and F 1 scores showed that the T 2 relaxation time ratio (AUPRG = 0.60, F 1 = 0.73) performed considerably better than the FLAIR ratio (AUPRG = 0.39, F 1 = 0.57) and the visual DWI/FLAIR mismatch (F 1 = 0.25).

          Conclusions:

          Quantitative T 2 relaxation time is the preferred MRI parameter in the assessment of patients with unknown onset for treatment stratification.

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          Most cited references46

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          A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion

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            Magnetic Resonance Fingerprinting

            Summary Magnetic Resonance (MR) is an exceptionally powerful and versatile measurement technique. The basic structure of an MR experiment has remained nearly constant for almost 50 years. Here we introduce a novel paradigm, Magnetic Resonance Fingerprinting (MRF) that permits the non-invasive quantification of multiple important properties of a material or tissue simultaneously through a new approach to data acquisition, post-processing and visualization. MRF provides a new mechanism to quantitatively detect and analyze complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to specifically identify the presence of a target material or tissue, which will increase the sensitivity, specificity, and speed of an MR study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern recognition algorithm, MRF inherently suppresses measurement errors and thus can improve accuracy compared to previous approaches.
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              MRI-Guided Thrombolysis for Stroke with Unknown Time of Onset

              Under current guidelines, intravenous thrombolysis is used to treat acute stroke only if it can be ascertained that the time since the onset of symptoms was less than 4.5 hours. We sought to determine whether patients with stroke with an unknown time of onset and features suggesting recent cerebral infarction on magnetic resonance imaging (MRI) would benefit from thrombolysis with the use of intravenous alteplase.
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                Author and article information

                Journal
                J Cent Nerv Syst Dis
                J Cent Nerv Syst Dis
                CNS
                spcns
                Journal of Central Nervous System Disease
                SAGE Publications (Sage UK: London, England )
                1179-5735
                12 September 2020
                2020
                : 12
                : 1179573520943314
                Affiliations
                [1 ]School of Psychological Science, University of Bristol, Bristol, UK
                [2 ]Acute Stroke Programme, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
                [3 ]Institute of Neuroscience and Psychology, Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
                [4 ]Stroke Neurology, Southmead Hospital, North Bristol NHS Trust, Bristol, UK
                [5 ]Faculty of Engineering, University of Bristol, Bristol, UK
                Author notes
                [*]Risto A Kauppinen, Faculty of Engineering, University of Bristol, Office 3D12, Merchant Ventures Building, Woodland Road, Clifton, Bristol BS8 1UB, UK. Email: psrak@ 123456bristol.ac.uk
                Author information
                https://orcid.org/0000-0003-2630-9914
                https://orcid.org/0000-0003-3383-6608
                Article
                10.1177_1179573520943314
                10.1177/1179573520943314
                7488882
                32963473
                3a044ebf-baa6-4c0c-8136-ae5521ca2c6c
                © The Author(s) 2020

                This article is distributed under the terms of the Creative Commons Attribution 4.0 License ( https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 22 March 2020
                : 29 June 2020
                Funding
                Funded by: Dunhill Medical Trust, FundRef https://doi.org/10.13039/501100000377;
                Award ID: R385/1114 and OSRP1/1006
                Categories
                Original Research
                Custom metadata
                January-December 2020
                ts1

                ischemic stroke,unknown onset,t2 relaxation,signal intensities,dwi/flair mismatch

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