| Stroke is a serious and life-threatening disease,especially acute ischemic stroke caused by large-vessel occlusion.The use of multi-mode CT to assess the tissue status of patients with suspected stroke is an important basis for clinical decision-making.The information provided by multi-mode CT about net water uptake,infarction,penumbra,and the status of the collaterals in the lesion has a relation with the prognosis.Objective:The aim is to investigate the correlation between the parameters of multi-mode CT obtained by automated software and the prognosis of patients with acute large vessel occlusion after mechanical embolization,to identify baseline predictors of poor prognosis after successful revascularization,in order to provide preoperative information for clinical.Methods:Patients with acute ischemic stroke who underwent endovascular treatment with successful reperfusion at the First Hospital of Jilin University for intracranial anterior circulation large vessel occlusion from June 2018 to March 2021 were collected.The collected data were grouped according to the modified Rankin Scale 90 days after endovascular treatment.90-day m RS score 0-2 was defined as the good prognosis group and m RS score >2 was defined as the poor prognosis group.Correlations between clinical and imaging factors and prognosis were compared between the two groups,and clinical models and clinical combined with imaging models were constructed to predict the prognosis of stroke patients.Statistical analysis was performed using SPSS 26.0.Results:1、Of the 97 patients,47 had a good prognosis and 50 had a poor prognosis.There was a statistical difference in the overall age distribution between the good prognosis group and the poor prognosis group（z=2.164,P=0.03）,with patients in the poor prognosis group being older at baseline.There was a statistical difference in lymphocyte count between the good prognosis group and the poor prognosis group（z=4.432,P<0.001）.There was a statistically significant difference in the neutrophil to lymphocyte ratio（z=4.346,P<0.001）,platelet to lymphocyte ratio（z=4.068,P<0.001）and lymphocyte to monocyte ratio（z=5.172,P<0.001）between the good prognosis group and the poor prognosis group.The baseline NHISS score was lower in the good prognosis group（13;IQR=9-15）than in the poor prognosis group（14;IQR=12-17;P=0.036）.2 、After multi-factor logistic regression analysis,age and neutrophil to lymphocyte ratio were independent predictors for prognosis,the older the age,the higher the risk of poor prognosis（OR=1.05,95%CI 为 1.02-1.10;P=0.019）;and the larger the neutrophil to lymphocyte ratio,the higher the risk of poor prognosis（OR=1.33,95%CI 为 1.09-1.61;P=0.004）.3、Baseline net water uptake,baseline net water uptake to time and baseline net water uptake to log（time+1）were lower in the good prognosis group than in the poor prognosis group and the difference were statistically significant（z=3.466,P=0.001;z=2.943,P =0.003;z=3.038,P =0.002）.There was no statistical significance（P> 0.05）between the good prognosis group and the poor prognosis group in terms of side of lesion（left vs.right）and site of lesion（end of internal carotid artery vs.M1 segment of middle cerebral artery）.The proportion of patients with good collateral circulation was higher in the good prognosis group（P=0.008）.The volume of the infarct core and the infarct core growth rate were significantly smaller in the good prognosis group than in the poor prognosis group（z=2.035,P=0.042;z=2.191,P=0.028）,and there was no statistical difference in Tmax volume and mismatch volume between the two groups（P>0.05）.The hypoperfusion index ratio was significantly lower in the good prognosis group than in the poor prognosis group（z=2.916,P=0.004）.4、After multi-factor logistic regression analysis,Tan score and net water uptake were independent predictors for prognosis,poorer collaterals status was associated with a higher risk of poor prognosis（OR=2.76,95% CI 1.12-6.80;P=0.027）and higher net water uptake was associated with a higher risk of poor prognosis（OR=1.22,95% CI 1.06-1.40;P=0.005）.5、Using poor prognosis as the dependent variable,the independent variables age,neutrophil to lymphocyte ratio,Tan score,and net water uptake were included in the regression model,and after adjusting for Tan score,age（OR=1.06,95%CI1.01-1.12;P=0.010）,neutrophil to lymphocyte count ratio（OR=1.43,95% CI 1.18-1.73;P<0.001）,and net water uptake（OR=1.24,95% CI 1.06-1.44;P=0.008）were significantly associated with the occurrence of poor prognosis.6、Baseline NHISS was dichotomised（NHISS≧16 defined as severe,NHISS<16defined as mild to moderate）and logistic regression analysis of net water uptake and poor prognosis was performed.Regardless of the severity of NHISS,a greater rate of net water uptake was associated with a statistically higher risk of poor prognosis（mild to moderate:OR=1.19,95%CI1.01-1.38;P=0.033;severe:OR=1.47,95%CI1.07-2.02;P=0.019）.7、Using poor prognosis as the dependent variable,ROC curves were plotted to compare the AUCs of baseline net water uptake,baseline net water uptake to time,and baseline net water uptake to log（time+1）,with results of 0.703,0.672,and 0.678 respectively.Baseline net water uptake had the best predictive efficacy with a cut-off value of 6.52%,sensitivity of 48%,and specificity of 85.1%.8 、After adjustment,a clinical model and a clinical combined with imaging model including age,neutrophil-to-lymphocyte ratio,and net water uptake rate were constructed.The AUC for the clinical model to predict stroke prognosis was 0.811（95% CI 0.726-0.896）,with a sensitivity of 66% and specificity of 85.1%;the AUC for the clinical model combined with the imaging model to predict stroke prognosis was 0.837（95% CI 0.758-0.915）,with a sensitivity of 82% and specificity of 74.5%.Conclusion:1.Automatic multi-mode CT allows rapid and accurate assessment of net water uptake rate,the volume of infarction,penumbra and collateral circulation without increasing the flow of the care for patients with acute ischaemic stroke.2.Net water uptake is an independent predictor for prognosis in patients with acute ischemic stroke.3.The predictive model of clinical combined imaging have the ability to identify patients at risk of poor prognosis in acute ischemic stroke,thus helping to personalise clinical treatment. |
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