XiaoQing Cheng1, Hang Wu2, JiaQian Shi3, Zheng Dong3, Jia Liu1, ChangSheng Zhou1, QuanHui Liu1, XiaoQin Su1, Zhao Shi1, YingLe Li4, LuLu Xiao5, WuSheng Zhu6, GuangMing Lu7,8. 1. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, 305 Zhongshan East Road, Nanjing, 210002, Jiangsu, China. 2. Department of Neurology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China. 3. Department of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China. 4. Department of Neurology, The First School of Clinical Medicine, Jinling Hospital, Southern Medical University, Nanjing, China. 5. Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China. 6. Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China. zwsemail@sina.com. 7. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, 305 Zhongshan East Road, Nanjing, 210002, Jiangsu, China. cjr.luguangming@vip.163.com. 8. Department of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China. cjr.luguangming@vip.163.com.
Abstract
OBJECTIVE: We assessed the value of computed tomography (CT) and automated Alberta Stroke Program Early CT Score (ASPECTS) with net water uptake (NWU) to predict stroke onset time. METHODS: Two-hundred forty stroke patients with anterior circulation large-vessel occlusion were included. CT-ASPECTS-NWU values were calculated by comparing the mean Hounsfield units of affected ASPECTS regions with unaffected contralateral regions. The correlation between ASPECTS-NWU and stroke onset to CT time was assessed. ASPECTS-NWU predictive values were calculated to identify a stroke onset to CT time of within 4.5/6 h. RESULTS: A correlation existed between stroke onset to CT time and ASPECTS-NWU (r = 0.65, p < 0.001), which was affected by collateral status and infarct location. The area under the receiver operating characteristic (ROC) curve (AUC) for distinguishing a stroke onset to CT time of within 4.5 h was 0.837 (95% confidence interval [CI] 0.784-0.881; optimal cutoff 7%; sensitivity 87.10%; specificity 62.36%). The multi-index AUC was 0.884 (95% CI 0.837-0.922). The AUC for distinguishing a stroke onset to CT time of within 6 h was 0.836 (95% CI 0.783-0.880; optimal cutoff 9%; sensitivity 72.73%; specificity 81.16%). The multi-index AUC was 0.881 (95% CI 0.834-0.920). CONCLUSIONS: ASPECTS-NWU may be used to determine stroke onset time in patients with unwitnessed or wake-up stroke.
OBJECTIVE: We assessed the value of computed tomography (CT) and automated Alberta Stroke Program Early CT Score (ASPECTS) with net water uptake (NWU) to predict stroke onset time. METHODS: Two-hundred forty strokepatients with anterior circulation large-vessel occlusion were included. CT-ASPECTS-NWU values were calculated by comparing the mean Hounsfield units of affected ASPECTS regions with unaffected contralateral regions. The correlation between ASPECTS-NWU and stroke onset to CT time was assessed. ASPECTS-NWU predictive values were calculated to identify a stroke onset to CT time of within 4.5/6 h. RESULTS: A correlation existed between stroke onset to CT time and ASPECTS-NWU (r = 0.65, p < 0.001), which was affected by collateral status and infarct location. The area under the receiver operating characteristic (ROC) curve (AUC) for distinguishing a stroke onset to CT time of within 4.5 h was 0.837 (95% confidence interval [CI] 0.784-0.881; optimal cutoff 7%; sensitivity 87.10%; specificity 62.36%). The multi-index AUC was 0.884 (95% CI 0.837-0.922). The AUC for distinguishing a stroke onset to CT time of within 6 h was 0.836 (95% CI 0.783-0.880; optimal cutoff 9%; sensitivity 72.73%; specificity 81.16%). The multi-index AUC was 0.881 (95% CI 0.834-0.920). CONCLUSIONS: ASPECTS-NWU may be used to determine stroke onset time in patients with unwitnessed or wake-up stroke.
Entities:
Keywords:
ASPECTS; Biomarker; CT; Ischemic stroke; Time