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

Author:

Kuang Hulin1ORCID,Qiu Wu1ORCID,Najm Mohamed1,Dowlatshahi Dar2ORCID,Mikulik Robert3,Poppe Alex Y4,Puig Josep5,Castellanos Mar5,Sohn Sung I6,Ahn Seong H6,Calleja Ana7,Jin Albert8,Asil Talip9,Asdaghi Negar10,Field Thalia S11ORCID,Coutts Shelagh11213ORCID,Hill Michael D11213ORCID,Demchuk Andrew M11213,Goyal Mayank11213ORCID,Menon Bijoy K11213,

Affiliation:

1. Calgary Stroke Program, Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada

2. Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada

3. International Clinical Research Center, Department of Neurology, St Ann’s University Hospital, Masaryk University, Brno, Czech Republic

4. Department of Neurosciences, University of Montreal, Montreal, Québec, Canada

5. IDI-IDIBGI, Dr Josep Trueta University Hospital, Girona, Spain

6. Department of Neurology, Keimyung University, Daegu, South Korea

7. Department of Medicine, University of Valladolid, Valladolid, Spain

8. Faculty of Health Sciences, Queen’s University, Kingston, Ontario, Canada

9. Bezmialem Vakif Univesitesi Noroloji, Istanbul, Turkey

10. Department of Neurology, University of Miami, Miami, FL, USA

11. Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada

12. Department of Radiology, University of Calgary, Calgary, Alberta, Canada

13. Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada

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.

Funder

Canadian Institute of Health Research

Publisher

SAGE Publications

Subject

Neurology

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