Validation of two automated ASPECTS software on non-contrast computed tomography scans of patients with acute ischemic stroke

Frontiers in Neurology

Neurology

Yu Luo¹  Fei Lu²  Dan Tong²  Zhongping Chen²  Linna Li²  Shuo Wang²  Zhenzhen Shi²  Mingyang Li²  Yongxin Li³  Wenxin Wang⁴ 

[1] Department of Radiology, Shanghai Fourth People's Hospital, Shanghai, China;Department of Radiology, The First Hospital of Jilin University, Changchun, China;Neusoft Medical Systems Co., Ltd., Shenyang, Liaoning, China;Philips Healthcare, Beijing, China;

关键词: image interpretation;    computer-assisted;    software validation;    brain ischemia;    computed tomography;   

DOI  :  10.3389/fneur.2023.1170955

 received in 2023-02-21, accepted in 2023-03-20,  发布年份 2023

来源: Frontiers

【 摘 要 】

PurposeThe Alberta Stroke Program Early Computed Tomography Score (ASPECTS) was designed for semi-quantitative assessment of early ischemic changes on non-contrast computed tomography (NCCT) for acute ischemic stroke (AIS). We evaluated two automated ASPECTS software in comparison with reference standard.MethodsNCCT of 276 AIS patients were retrospectively reviewed (March 2018–June 2020). A three-radiologist consensus for ASPECTS was used as reference standard. Imaging data from both baseline and follow-up were evaluated for reference standard. Automated ASPECTS were calculated from baseline NCCT with 1-mm and 5-mm slice thickness, respectively. Agreement between automated ASPECTS and reference standard was assessed using intra-class correlation coefficient (ICC). Correlation of automated ASPECTS with baseline stroke severity (NIHSS) and follow-up ASPECTS were evaluated using Spearman correlation analysis.ResultsIn score-based analysis, automated ASPECTS calculated from 5-mm slice thickness images agreed well with reference standard (software A: ICC = 0.77; software B: ICC = 0.65). Bland–Altman analysis revealed that the mean differences between automated ASPECTS and reference standard were ≤ 0.6. In region-based analysis, automated ASPECTS derived from 5-mm slice thickness images by software A showed higher sensitivity (0.60 vs. 0.54), lower specificity (0.91 vs. 0.94), and higher AUC (0.76 vs. 0.74) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS derived from 5-mm slice thickness images by software B showed higher sensitivity (0.56 vs. 0.51), higher specificity (0.87 vs. 0.81), higher accuracy (0.80 vs. 0.73), and higher AUC (0.71 vs. 0.66) than those using 1-mm slice thickness images (p < 0.05). Automated ASPECTS were significantly associated with baseline NIHSS and follow-up ASPECTS.ConclusionAutomated ASPECTS showed good reliability and 5 mm was the optimal slice thickness.

【 授权许可】

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Copyright © 2023 Chen, Shi, Lu, Li, Li, Wang, Wang, Li, Luo and Tong.