Validation of an Automated ASPECTS Software via a Multi-Reader Multi-Case Clinical Reader Study.

Rotem Golan¹, Kauê T N Duarte², Chris C Duszynski², Luis A Souto Maior Neto², Bijoy K Menon²

¹From the Circle Cardiovascular Imaging Inc. (R.G., C.C.D., L.A.S.M.N.), Calgary, AB, Canada; Department of Clinical Neurosciences (K.T.N.D., B.K.M.), Hotchkiss Brain Institute (K.T.N.D., B.K.M.), Department of Clinical Neurosciences (B.K.M.), Cumming School of Medicine and Department of Community Health Sciences (B.K.M.), University of Calgary, Calgary, AB, Canada. rotem.golan@circlecvi.com.

²From the Circle Cardiovascular Imaging Inc. (R.G., C.C.D., L.A.S.M.N.), Calgary, AB, Canada; Department of Clinical Neurosciences (K.T.N.D., B.K.M.), Hotchkiss Brain Institute (K.T.N.D., B.K.M.), Department of Clinical Neurosciences (B.K.M.), Cumming School of Medicine and Department of Community Health Sciences (B.K.M.), University of Calgary, Calgary, AB, Canada.

PubMed DOI

Abstract

BACKGROUND: Rapid, accurate detection of early ischemic changes (EIC) on non-contrast computed tomography (NCCT) is critical for the triage and treatment of acute ischemic stroke (AIS) patients, yet NCCT interpretation remains challenging due to low soft-tissue contrast and inter-reader variability. MATERIALS AND METHODS: This study validates StrokeSENS ASPECTS, a fully automated AI-based softwar…

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