Validation of an automated ASPECTS method on non-contrast computed tomography scans of acute ischemic stroke patients

UDC.coleccionInvestigación
UDC.departamentoFisioterapia, Medicina e Ciencias Biomédicas
UDC.endPage534
UDC.grupoInvEnfermidades Cerebrovasculares: Neuroloxía Clínica e Traslacional (INIBIC)
UDC.institutoCentroINIBIC - Instituto de Investigacións Biomédicas de A Coruña
UDC.issue5
UDC.journalTitleInternational Journal of Stroke
UDC.startPage528
UDC.volume15
dc.contributor.authorKuang, Hulin
dc.contributor.authorQiu, Wu
dc.contributor.authorNajm, Mohamed
dc.contributor.authorDowlatshahi, Dar
dc.contributor.authorMikulik, Robert
dc.contributor.authorPoppe, Alex Y.
dc.contributor.authorPuig, Josep
dc.contributor.authorCastellanos, María del Mar
dc.contributor.authorSohn, Sung I.
dc.contributor.authorAhn, Seong H.
dc.contributor.authorCalleja, Ana
dc.contributor.authorJin, Albert
dc.contributor.authorAsil, Talip
dc.contributor.authorAsdaghi, Negar
dc.contributor.authorField, Thalia S.
dc.contributor.authorCoutts, Shelagh
dc.contributor.authorHill, Michel D.
dc.contributor.authorDemchuk, Andrew M.
dc.contributor.authorGoyal, Mayank
dc.contributor.authorMenon, Bijoy K.
dc.date.accessioned2025-10-29T07:15:47Z
dc.date.available2025-10-29T07:15:47Z
dc.date.issued2019-12-18
dc.description.abstract[Abstract] Background: The Alberta Stroke Program Early CT Score (ASPECTS) is a systematic method of assessing the extent of early ischemic change on non-contrast computed tomography in patients with acute ischemic stroke. Our objective was to validate an automated ASPECTS scoring method we recently developed on a large data set. Materials and methods: We retrospectively collected 602 acute ischemic stroke patients' non-contrast computed tomography scans. Expert ASPECTS readings on non-contrast computed tomography were compared to automated ASPECTS. Statistical analyses on the total ASPECTS, region level ASPECTS, and dichotomized ASPECTS (≤4 vs. >4) score were conducted. Results: In total, 602 scans were evaluated and 6020 (602 × 10) ASPECTS regions were scored. Median time from stroke onset to computed tomography was 114 min (interquartile range: 73-183 min). Total ASPECTS for the 602 patients generated by the automated method agreed well with expert readings (intraclass correlation coefficient): 0.65 (95% confidence interval (CI): 0.60-0.69). Region level analysis showed that the automated method yielded accuracy of 81.25%, sensitivity of 61.13% (95% CI: 58.4%-63.8%), specificity of 86.56% (95% CI: 85.6%-87.5%), and area under curve of 0.74 (95% CI: 0.73-0.75). For dichotomized ASPECTS (≤4 vs. >4), the automated method demonstrated sensitivity 97.21% (95% CI: 95.4%-98.4%), specificity 57.81% (95% CI: 44.8%-70.1%), accuracy 93.02%, and area under the curve of 0.78 (95% CI: 0.74-0.81). For each individual region (M1-6, lentiform, insula, and caudate), the automated method demonstrated acceptable performance. Conclusion: The automated system we developed approached the stroke expert in performance when scoring ASPECTS on non-contrast computed tomography scans of acute ischemic stroke patients.
dc.identifier.citationKuang H, Qiu W, Najm M, Dowlatshahi D, Mikulik R, Poppe AY, Puig J, Castellanos M, Sohn SI, Ahn SH, Calleja A, Jin A, Asil T, Asdaghi N, Field TS, Coutts S, Hill MD, Demchuk AM, Goyal M, Menon BK; INTERRSeCT Collaborators. Validation of an automated ASPECTS method on non-contrast computed tomography scans of acute ischemic stroke patients. Int J Stroke. 2020 Jul;15(5):528-534.
dc.identifier.doi10.1177/1747493019895702
dc.identifier.issn1747-4930
dc.identifier.urihttps://hdl.handle.net/2183/46152
dc.language.isoeng
dc.publisherSage
dc.relation.urihttps://doi.org/10.1177/1747493019895702
dc.rights.accessRightsopen access
dc.subjectAlberta Stroke Program Early CT score
dc.subjectAutomated ASPECTS scoring
dc.subjectIschemic stroke
dc.subjectMachine learning
dc.subjectNon-contrast computed tomography
dc.titleValidation of an automated ASPECTS method on non-contrast computed tomography scans of acute ischemic stroke patients
dc.typejournal article
dc.type.hasVersionAM
dspace.entity.typePublication
relation.isAuthorOfPublicationfea87394-0be5-482f-b650-543f2240258c
relation.isAuthorOfPublication.latestForDiscoveryfea87394-0be5-482f-b650-543f2240258c

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