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

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KUANG H. L. QIU W. NAJM M. DOWLATSHAHI D. MIKULÍK Robert POPPE A. Y. PUIG J. CASTELLANOS M. SOHN S. I. AHN S. H. CALLEJA A. JIN A. ASIL T. ASDAGHI N. FIELD T. S. COUTTS S. HILL M. D. DEMCHUK A. M. GOYAL M. MENON B. K.

Rok publikování 2020
Druh Článek v odborném periodiku
Časopis / Zdroj International Journal of Stroke
Fakulta / Pracoviště MU

Lékařská fakulta

Citace
www https://journals.sagepub.com/doi/10.1177/1747493019895702
Doi http://dx.doi.org/10.1177/1747493019895702
Klíčová slova Alberta Stroke Program Early CT score; non-contrast computed tomography; ischemic stroke; machine learning; automated ASPECTS scoring
Popis 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 x 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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