Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/25541
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dc.contributor.authorGarcia-Esperon, Carlos-
dc.contributor.authorVisser, Milanka-
dc.contributor.authorChurilov, Leonid-
dc.contributor.authorMiteff, Ferdinand-
dc.contributor.authorBivard, Andrew-
dc.contributor.authorLillicrap, Thomas-
dc.contributor.authorLevi, Christopher R-
dc.contributor.authorSpratt, Neil J-
dc.contributor.authorParsons, Mark W-
dc.date2020-12-02-
dc.date.accessioned2021-01-04T23:56:33Z-
dc.date.available2021-01-04T23:56:33Z-
dc.date.issued2021-01-
dc.identifier.citationStroke 2021; 52(1): 339-343en
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/25541-
dc.description.abstractLacunar syndromes correlate with a lacunar stroke on imaging in 50% to 60% of cases. Computed tomography perfusion (CTP) is becoming the preferred imaging modality for acute stroke triage. We aimed to estimate the sensitivity, specificity, and predictive values for noncontrast computed tomography and CTP in lacunar syndromes, and for cortical, subcortical, and posterior fossa regions. A retrospective analysis of confirmed ischemic stroke patients who underwent acute CTP and follow-up magnetic resonance imaging between 2010 and 2018 was performed. Brain noncontrast computed tomography and CTP were assessed independently by 2 stroke neurologists. Receiver operating characteristic curve analysis was performed to estimate sensitivity, specificity, and area under the curve (AUC) for the detection of strokes in patients with lacunar syndromes using different CTP maps. We found 106 clinical lacunar syndromes, but on diffusion-weighted imaging, these consisted of 59 lacunar, 33 cortical, and 14 posterior fossa strokes. The discrimination of ischemia identification was very poor using noncontrast computed tomography in all 3 regions, but good for cortical (AUC, 0.82) and poor for subcortical and posterior regions (AUCs, 0.55 and 0.66) using automated core-penumbra maps. The addition of delay time and mean transient time maps substantially increased subcortical (AUC, 0.80) and slightly posterior stroke detection (AUC, 0.69). Analysis of mean transient time and delay time maps in combination with core-penumbra maps improves detection of subcortical and posterior strokes.en
dc.language.isoeng-
dc.subjectbrainen
dc.subjectmagnetic resonance imagingen
dc.subjectperfusionen
dc.subjecttomographyen
dc.subjecttriageen
dc.titleRole of Computed Tomography Perfusion in Identification of Acute Lacunar Stroke Syndromes.en
dc.typeJournal Articleen
dc.identifier.journaltitleStrokeen
dc.identifier.affiliationMaridulu budyari gumal, The Sydney Partnership for Health Education Research & Enterprise (SPHERE), University of New South Wales, Australiaen
dc.identifier.affiliationMedicine (University of Melbourne)en
dc.identifier.affiliationDepartment of Neurology, John Hunter Hospital, University of Newcastle, Australiaen
dc.identifier.affiliationHunter Medical Research Institute and University of Newcastle, Australiaen
dc.identifier.affiliationDepartment of Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australiaen
dc.identifier.doi10.1161/STROKEAHA.120.030455en
dc.type.contentTexten
dc.identifier.pubmedid33370180-
local.name.researcherChurilov, Leonid
item.openairetypeJournal Article-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptMedicine (University of Melbourne)-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
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