Automated ASPECT scoring in acute ischemic stroke: comparison of three software tools

医学 接收机工作特性 神经组阅片室 神经学 组内相关 冲程(发动机) 放射科 类间相关 神经外科 相关性 内科学 临床心理学 机械工程 数学 精神科 工程类 心理测量学 几何学
作者
Philip Hoelter,Iris Muehlen,Philipp Goelitz,Vanessa D. Beuscher,Stefan Schwab,Arnd Doerfler
出处
期刊:Neuroradiology [Springer Nature]
卷期号:62 (10): 1231-1238 被引量:53
标识
DOI:10.1007/s00234-020-02439-3
摘要

Various software applications offer support in the diagnosis of acute ischemic stroke (AIS), yet it remains unclear whether the performance of these tools is comparable to each other. Our study aimed to evaluate three fully automated software applications for Alberta Stroke Program Early CT (ASPECT) scoring (Syngo.via Frontier ASPECT Score Prototype V2, Brainomix e-ASPECTS® and RAPID ASPECTS) in AIS patients. Retrospectively, 131 patients with large vessel occlusion (LVO) of the middle cerebral artery or the internal carotid artery, who underwent endovascular therapy (EVT), were included. Pre-interventional non-enhanced CT (NECT) datasets were assessed in random order using the automated ASPECT software and by three experienced neuroradiologists in consensus. Interclass correlation coefficient (ICC), Bland-Altman, and receiver operating characteristics (ROC) were applied for statistical analysis. Median ASPECTS of the expert consensus reading was 8 (7–10). Highest correlation was between the expert read and Brainomix (r = 0.871 (0.818, 0.909), p < 0.001). Correlation between expert read and Frontier V2 (r = 0.801 (0.719, 0.859), p < 0.001) and between expert read and RAPID (r = 0.777 (0.568, 0.871), p < 0.001) was high, respectively. There was a high correlation among the software tools (Frontier V2 and Brainomix: r = 0.830 (0.760, 0.880), p < 0.001; Frontier V2 and RAPID: r = 0.847 (0.693, 0.913), p < 0.001; Brainomix and RAPID: r = 0.835 (0.512, 0.923), p < 0.001). An ROC curve analysis revealed comparable accuracy between the applications and expert consensus reading (Brainomix: AUC = 0.759 (0.670–0.848), p < 0.001; Frontier V2: AUC = 0.752 (0.660–0.843), p < 0.001; RAPID: AUC = 0.734 (0.634–0.831), p < 0.001). Overall, there is a convincing yet developable grade of agreement between current ASPECT software evaluation tools and expert evaluation with regard to ASPECT assessment in AIS.
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