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      Temporal similarity perfusion mapping: A standardized and model-free method for detecting perfusion deficits in stroke

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          Abstract

          Introduction

          Interpretation of the extent of perfusion deficits in stroke MRI is highly dependent on the method used for analyzing the perfusion-weighted signal intensity time-series after gadolinium injection. In this study, we introduce a new model-free standardized method of temporal similarity perfusion (TSP) mapping for perfusion deficit detection and test its ability and reliability in acute ischemia.

          Materials and methods

          Forty patients with an ischemic stroke or transient ischemic attack were included. Two blinded readers compared real-time generated interactive maps and automatically generated TSP maps to traditional TTP/MTT maps for presence of perfusion deficits. Lesion volumes were compared for volumetric inter-rater reliability, spatial concordance between perfusion deficits and healthy tissue and contrast-to-noise ratio (CNR).

          Results

          Perfusion deficits were correctly detected in all patients with acute ischemia. Inter-rater reliability was higher for TSP when compared to TTP/MTT maps and there was a high similarity between the lesion volumes depicted on TSP and TTP/MTT (r( 18) = 0.73). The Pearson's correlation between lesions calculated on TSP and traditional maps was high (r( 18) = 0.73, p<0.0003), however the effective CNR was greater for TSP compared to TTP (352.3 vs 283.5, t(19) = 2.6, p<0.03.) and MTT (228.3, t(19) = 2.8, p<0.03).

          Discussion

          TSP maps provide a reliable and robust model-free method for accurate perfusion deficit detection and improve lesion delineation compared to traditional methods. This simple method is also computationally faster and more easily automated than model-based methods. This method can potentially improve the speed and accuracy in perfusion deficit detection for acute stroke treatment and clinical trial inclusion decision-making.

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          Most cited references25

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          High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis.

          The authors review the theoretical basis of determination of cerebral blood flow (CBF) using dynamic measurements of nondiffusible contrast agents, and demonstrate how parametric and nonparametric deconvolution techniques can be modified for the special requirements of CBF determination using dynamic MRI. Using Monte Carlo modeling, the use of simple, analytical residue models is shown to introduce large errors in flow estimates when actual, underlying vascular characteristics are not sufficiently described by the chosen function. The determination of the shape of the residue function on a regional basis is shown to be possible only at high signal-to-noise ratio. Comparison of several nonparametric deconvolution techniques showed that a nonparametric deconvolution technique (singular value decomposition) allows estimation of flow relatively independent of underlying vascular structure and volume even at low signal-to-noise ratio associated with pixel-by-pixel deconvolution.
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            Real-time diffusion-perfusion mismatch analysis in acute stroke.

            Diffusion-perfusion mismatch can be used to identify acute stroke patients that could benefit from reperfusion therapies. Early assessment of the mismatch facilitates necessary diagnosis and treatment decisions in acute stroke. We developed the RApid processing of PerfusIon and Diffusion (RAPID) for unsupervised, fully automated processing of perfusion and diffusion data for the purpose of expedited routine clinical assessment. The RAPID system computes quantitative perfusion maps (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT; and the time until the residue function reaches its peak, T(max)) using deconvolution of tissue and arterial signals. Diffusion-weighted imaging/perfusion-weighted imaging (DWI/PWI) mismatch is automatically determined using infarct core segmentation of ADC maps and perfusion deficits segmented from T(max) maps. The performance of RAPID was evaluated on 63 acute stroke cases, in which diffusion and perfusion lesion volumes were outlined by both a human reader and the RAPID system. The correlation of outlined lesion volumes obtained from both methods was r(2) = 0.99 for DWI and r(2) = 0.96 for PWI. For mismatch identification, RAPID showed 100% sensitivity and 91% specificity. The mismatch information is made available on the hospital's PACS within 5-7 min. Results indicate that the automated system is sufficiently accurate and fast enough to be used for routine care as well as in clinical trials. © 2010 Wiley-Liss, Inc.
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              AFNI: what a long strange trip it's been.

              AFNI is an open source software package for the analysis and display of functional MRI data. It originated in 1994 to meet the specific needs of researchers at the Medical College of Wisconsin, in particular the mapping of activation maps to Talairach-Tournoux space, but has been expanded steadily since then into a wide-ranging set of tool for FMRI data analyses. AFNI was the first platform for real-time 3D functional activation and registration calculations. One of AFNI's main strengths is its flexibility and transparency. In recent years, significant efforts have been made to increase the user-friendliness of AFNI's FMRI processing stream, with the introduction of "super-scripts" to setup the entire analysis, and graphical front-ends for these managers. Published by Elsevier Inc.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draft
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SoftwareRole: Supervision
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ResourcesRole: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                3 October 2017
                2017
                : 12
                : 10
                Affiliations
                [1 ] NIH/NINDS, Human Cortical Physiology and Neurorehabilitation Section, Bethesda, Maryland, United States of America
                [2 ] Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
                [3 ] NIH/NINDS, Stroke Branch, Bethesda, Maryland, United States of America
                [4 ] NIH/NIMH, Scientific and Statistical Computing Core, Bethesda, Maryland, United States of America
                Henry Ford Health System, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-17-08945
                10.1371/journal.pone.0185552
                5626465
                28973000
                1be4531f-676a-47cb-9614-73e56920b01b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                Page count
                Figures: 8, Tables: 1, Pages: 16
                Product
                Funding
                Funded by: Intramural Research Program of the National Institute of Neurological Disorders and Stroke at the National Institutes of Health
                Funded by: funder-id http://dx.doi.org/10.13039/501100002996, Hartstichting;
                Award ID: 2013T047
                Award Recipient :
                This work was supported by the Intramural Research Program of the National Institute of Neurological Disorders and Stroke at the National Institutes of Health. R.P.H. Bokkers receives support from the Dutch Heart Foundation (Grant 2013T047).
                Categories
                Research Article
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Lesions
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Lesions
                Medicine and Health Sciences
                Vascular Medicine
                Ischemia
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Brain Morphometry
                Diffusion Weighted Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Brain Morphometry
                Diffusion Weighted Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Research and Analysis Methods
                Imaging Techniques
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Trials
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Clinical Trials
                Research and Analysis Methods
                Clinical Trials
                Custom metadata
                All imaging and data files are available from Figshare ( https://figshare.com/projects/Temporal_Similarity_Mapping/23032).

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                Uncategorized

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