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Validation of an automated ASPECTS method on non-contrast computed tomography scans of acute ischemic stroke patients
H. Kuang, W. Qiu, M. Najm, D. Dowlatshahi, R. Mikulik, AY. Poppe, J. Puig, M. Castellanos, SI. Sohn, SH. Ahn, A. Calleja, A. Jin, T. Asil, N. Asdaghi, TS. Field, S. Coutts, MD. Hill, AM. Demchuk, M. Goyal, BK. Menon, INTERRSeCT Collaborators
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
Grant support
Canadian Institute of Health Research
- MeSH
- Stroke * diagnostic imaging MeSH
- Ischemic Stroke * MeSH
- Brain Ischemia * diagnostic imaging MeSH
- Humans MeSH
- Tomography, X-Ray Computed MeSH
- Retrospective Studies MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Alberta MeSH
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.
Bezmialem Vakif Univesitesi Noroloji Istanbul Turkey
Department of Medicine University of Ottawa Ottawa Ontario Canada
Department of Medicine University of Valladolid Valladolid Spain
Department of Neurology Keimyung University Daegu South Korea
Department of Neurology University of Miami Miami FL USA
Department of Neurosciences University of Montreal Montreal Québec Canada
Department of Radiology University of Calgary Calgary Alberta Canada
Faculty of Health Sciences Queen's University Kingston Ontario Canada
Faculty of Medicine University of British Columbia Vancouver British Columbia Canada
Hotchkiss Brain Institute University of Calgary Calgary Alberta Canada
References provided by Crossref.org
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- $a 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.
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