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Gray-Matter Volume Estimate Score: A Novel Semi-Automatic Method Measuring Early Ischemic Change on CT

Title
Gray-Matter Volume Estimate Score: A Novel Semi-Automatic Method Measuring Early Ischemic Change on CT
Authors
Song, DongbeomLee, KijeongKim, Eun HyeKim, Young DaeLee, Hye SunKim, JinkwonSong, Tae-JinAhn, Sung SooNam, Hyo SukHeo, Ji Hoe
Ewha Authors
송태진
SCOPUS Author ID
송태진scopus
Issue Date
2016
Journal Title
JOURNAL OF STROKE
ISSN
2287-6391JCR Link

2287-6405JCR Link
Citation
JOURNAL OF STROKE vol. 18, no. 1, pp. 80 - 86
Keywords
Acute ischemic strokeAcute stroke imagingComputed tomographyASPECTSPrediction of outcome
Publisher
KOREAN STROKE SOC
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Background and Purpose We developed a novel method named Gray-matter Volume Estimate Score (GRAVES), measuring early ischemic changes on Computed Tomography (CT) semi-automatically by computer software. This study aimed to compare GRAVES and Alberta Stroke Program Early CT Score (ASPECTS) with regards to outcome prediction and inter-rater agreement. Methods This was a retrospective cohort study. Among consecutive patients with ischemic stroke in the anterior circulation who received intra-arterial therapy (IAT), those with a readable pretreatment CT were included. Two stroke neurologists independently measured both the GRAVES and ASPECTS. GRAVES was defined as the percentage of estimated hypodense lesion in the gray matter of the ipsilateral hemisphere. Spearman correlation analysis, receiver operating characteristic (ROC) comparison test, and intra-class correlation coefficient (ICC) comparison tests were performed between GRAVES and ASPECTS. Results Ninety-four subjects (age: 68.7 +/- 10.3; male: 54 [54.9%]) were enrolled. The mean GRAVES was 9.0 +/- 8.9 and the median ASPECTS was 8 (interquartile range, 6-9). Correlation between ASPECTS and GRAVES was good (Spearman's rank correlation coefficient, 0.642; P<0.001). ROC comparison analysis showed that the predictive value of GRAVES for favorable outcome was not significantly different from that of ASPECTS (area under curve, 0.765 vs. 0.717; P = 0.308). ICC comparison analysis revealed that inter-rater agreement of GRAVES was significantly better than that of ASPECTS (0.978 vs. 0.895; P<0.001). Conclusions GRAVES had a good correlation with ASPECTS. GRAVES was as good as ASPECTS in predicting a favorable clinical outcome, but was better than ASPECTS regarding inter-rater agreement. GRAVES may be used to predict the outcome of IAT.
DOI
10.5853/jos.2015.01298
Appears in Collections:
의료원 > 의료원 > Journal papers
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