계명대학교 의학도서관 Repository

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

Metadata Downloads
Author(s)
Mar CastellanosJosep PuigSung I SohnSeong H AhnAna CallejaAlbert JinTalip AsilNegar AsdaghiThalia S FieldShelagh CouttsMichael D HillAndrew M DemchukMayank GoyalBijoy K MenonHulin KuangWu QiuMohamed NajmDar DowlatshahiRobert MikulikAlex Y Poppe
Keimyung Author(s)
Sohn, Sung Il
Department
Dept. of Neurology (신경과학)
Journal Title
International journal of stroke : official journal of the International Stroke Society.
Issued Date
2019
Keyword
Alberta Stroke Program Early CT scorenon-contrast computed tomographyischemic strokemachine learningautomated ASPECTS scoring
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.
Keimyung Author(s)(Kor)
손성일
Publisher
School of Medicine (의과대학)
Citation
Mar Castellanos et al. (2019). Validation of an automated ASPECTS method on non-contrast computed tomography scans of acute ischemic stroke patients. International journal of stroke : official journal of the International Stroke Society., 1747493019895702–1747493019895702. doi: 10.1177/1747493019895702
Type
Article
ISSN
1747-4949
Source
https://journals.sagepub.com/doi/10.1177/1747493019895702
DOI
10.1177/1747493019895702
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/42636
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Neurology (신경과학)
공개 및 라이선스
  • 공개 구분공개
  • 엠바고Forever
파일 목록
  • 관련 파일이 존재하지 않습니다.

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.