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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Validation of an Automated ASPECTS Software via a Multi-Reader Multi-Case Clinical Reader Study.

Rotem Golan1, Kauê T N Duarte2, Chris C Duszynski2

  • 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.

AJNR. American Journal of Neuroradiology
|June 29, 2026
PubMed
Summary

StrokeSENS ASPECTS, an AI tool, significantly improves early ischemic change detection in acute ischemic stroke patients. It enhances accuracy and reduces variability among clinicians interpreting non-contrast CT scans.

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Neurology

Background:

  • Early detection of ischemic changes on non-contrast CT is crucial for acute ischemic stroke (AIS) patient triage.
  • Interpreting non-contrast CT scans for early ischemic changes (EIC) is challenging due to low contrast and reader variability.

Purpose of the Study:

  • To validate StrokeSENS ASPECTS, an AI tool for automated grading of EIC on NCCT.
  • To assess the impact of StrokeSENS ASPECTS on clinician performance and inter-reader agreement.

Main Methods:

  • A multi-reader, multi-case study involving eight clinicians evaluating 100 NCCT scans.
  • Clinicians interpreted scans unaided and aided by StrokeSENS ASPECTS.
  • Performance was measured using binary classification metrics and inter-reader agreement (Fleiss's kappa).

Main Results:

  • StrokeSENS ASPECTS improved balanced accuracy by 5.7%, overall accuracy by 2.6%, sensitivity by 9.7%, and specificity by 1.6%.
  • Inter-reader agreement significantly increased, with Fleiss's kappa rising from 0.323 (unaided) to 0.608 (aided).

Conclusions:

  • StrokeSENS ASPECTS enhances clinicians' ability to detect EIC on NCCT.
  • The AI tool effectively reduces inter-reader variability, demonstrating safety and effectiveness for AIS evaluation.