Comparison of automated and visual DWI ASPECTS in acute ischemic stroke.
Journal
Journal of neuroradiology = Journal de neuroradiologie
ISSN: 0150-9861
Titre abrégé: J Neuroradiol
Pays: France
ID NLM: 7705086
Informations de publication
Date de publication:
Sep 2019
Sep 2019
Historique:
received:
09
05
2018
revised:
10
12
2018
accepted:
08
02
2019
pubmed:
14
3
2019
medline:
24
4
2020
entrez:
14
3
2019
Statut:
ppublish
Résumé
To assess intra-and inter-rater agreement of the ASPECTS (Alberta Stroke Program Early CT Score) based on diffusion-weighted MRI and to compare it with fully - automated methods (eASPECTS). DWI-ASPECTS of scans of 96 patients with acute ischemic stroke was rated by 2 experts. Automated methods based on thresholding the affected volumes of a coregistered atlas, and a regression tree learning method were established. Intra-rater, inter-rater and human-rater vs. automated methods agreements were investigated based on the intraclass correlation coefficients (ICC) and Bland Altman plots. Intra-rater agreement was good for both raters (ICC of 0.91 and 0.93). Inter-rater agreement was worse (ICC = 0.86) indicating a slight bias between both raters. Agreement with automated methods ranged from 0.81 to 0.87. Root-mean-squared deviation was 0.89 and 0.69 for the human raters and ranged from 0.95 to 1.24 for the automated methods. Agreement values are on the same order or higher compared to a literature review of CT-based ASPECTS. Automated methods perform slightly worse than human expert ratings, but they still have enough power to determine the DWI-ASPECTS with good precision in a clinical setting.
Sections du résumé
BACKGROUND AND PURPOSE
OBJECTIVE
To assess intra-and inter-rater agreement of the ASPECTS (Alberta Stroke Program Early CT Score) based on diffusion-weighted MRI and to compare it with fully - automated methods (eASPECTS).
METHODS
METHODS
DWI-ASPECTS of scans of 96 patients with acute ischemic stroke was rated by 2 experts. Automated methods based on thresholding the affected volumes of a coregistered atlas, and a regression tree learning method were established. Intra-rater, inter-rater and human-rater vs. automated methods agreements were investigated based on the intraclass correlation coefficients (ICC) and Bland Altman plots.
RESULTS
RESULTS
Intra-rater agreement was good for both raters (ICC of 0.91 and 0.93). Inter-rater agreement was worse (ICC = 0.86) indicating a slight bias between both raters. Agreement with automated methods ranged from 0.81 to 0.87. Root-mean-squared deviation was 0.89 and 0.69 for the human raters and ranged from 0.95 to 1.24 for the automated methods.
CONCLUSIONS
CONCLUSIONS
Agreement values are on the same order or higher compared to a literature review of CT-based ASPECTS. Automated methods perform slightly worse than human expert ratings, but they still have enough power to determine the DWI-ASPECTS with good precision in a clinical setting.
Identifiants
pubmed: 30862461
pii: S0150-9861(18)30190-1
doi: 10.1016/j.neurad.2019.02.006
pii:
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
288-293Informations de copyright
Copyright © 2019 Elsevier Masson SAS. All rights reserved.