Study On Net Water Uptake For Discriminating The Onset Time And Establishing Clinical Prognosis Model Of AIS Based On Multimodal CT

Objective:To explore the value of Net water uptake(NWU)based on multimodal CT in predicting the onset time and clinical outcome of patients with acute ischemic stroke,so as to provide objective basis for clinical diagnosis and treatment decision.This study is divided into two parts:Part one: By comparing the general data and NWU of patients with different onset time,and further studying the correlation between NWU and onset time,analyzing the diagnostic efficacy of NWU in identifying different onset time,to help clinicians to accurately judge the onset time of patients with acute ischemic stroke,so as to guide clinical treatment.Part two: By screening the independent risk factors for predicting poor prognosis in patients with acute ischemic stroke,based on independent risk factors such as neutrophil to lymphocyte ratio,National Institutes of Health Stroke Scale score,core infarction volume,and NWU,a multivariate logistic regression model was established for both non NWU and NWU added individuals.The predictive effects of the two models were evaluated and compared.Furthermore,a Nomogram prediction model based on all independent risk factors was established,and the prediction efficiency of the model was evaluated in order to provide a reference for clinicians to judge the risk of poor prognosis and to implement corresponding treatment decisions.Part one Study on Net water uptake based on multimodal CT for predicting the onset time of acute ischemic stroke1.Materials and methodsPatients with acute anterior circulation ischemic stroke admitted to the affiliated Hospital of Yan’an University from March 2020 to December 2022 were collected retrospectively.Siemens 256 layer new dual source spiral CT scanner is used for image acquisition.The parameter diagrams were calculated automatically by e Stroke National Thrombus extraction and Thrombolysis platform(https://www.medimagecloud.com/rsplatform).Firstly,the ischemic brain tissue is located by the parameter maps of Time to drain(TTD)and cerebral blood volume(CBV).Secondly,3Dslicer(https://www.Slicer.Org/)the core infarct area in the CBV parameter map was co-registered with the Non-contrast CT(NCCT)images to get the early cerebral infarction focus,and further calculated the Density of ischemic lesion(Dischemic)in the ischemic area of the lesion side,mirrored the same ROI in the contralateral cerebral hemisphere and measured the density of normal brain tissue in the corresponding region of the Density of normal issue(Dnormal).Finally,the formula was used to calculate the NWU of ischemic brain tissue,and the formula was as follows: NWU=(1-Dischemic/Dnormal)× 100%.The NWU was calculated independently by two neuroimaging attending physicians,and the final result was taken as the average of the two.Student t-test,Mann-Whitney U test or chi-square test were used to analyze whether there were significant differences between the two groups.By drawing the ROC curve,the diagnostic efficiency and the optimal critical value of NWU in identifying different onset time were analyzed,and the area under the curve(AUC),sensitivity and specificity were compared.The correlation between water uptake rate and onset time was analyzed by Pearson or Spearman correlation.2.ResultsThere were no significant differences in age,sex,admission systolic blood pressure,admission diastolic blood pressure,body mass index(BMI),hypertension,coronary heart disease,atrial fibrillation,diabetes,smoking,alcohol consumption,hyperlipidemia,hyperhomocysteinemia and baseline NIHSS scores among different groups.There were significant differences in NWU and onset time among different groups.Within 4.5 hours after the onset of symptoms identified by NWU,the AUC of the patients was 0.861(95%CI: 0.811 to 0.911,P < 0.001),the cutoff value was 15.95%,the sensitivity was 76.4%,and the specificity was 86.1%.Within 6 hours after the onset of symptoms identified by NWU,the AUC of the patients was 0.825(95% CI: 0.768 to 0.882,P<0.001),the cutoff value was 17.55%,the sensitivity was 72.3%,and the specificity was 83.8%.Within 9hours after the onset of symptoms identified by NWU,the AUC of the patients was 0.821(95% CI: 0.753 to 0.889,P<0.001),the cutoff value was 18.35%,the sensitivity was78.6%,and the specificity was 72.6%.There was a moderate correlation between NWU and the time of onset(r=0.674,P<0.001).3.Brief summaryIn this study,by comparing the NWU of acute ischemic stroke patients with different onset time,it was found that the net water uptake could well judge the onset time of acute ischemic stroke patients.Through ROC curve and correlation analysis,it was found that NWU had high recognition ability for stroke patients with different onset time,and it had a moderate correlation with the onset time(r=0.674,P<0.001).As a quantitative imaging biomarker,NWU has the ability to judge the onset time of patients with acute ischemic stroke,which is of great significance for the stratification of newly diagnosed stroke patients and guiding further treatment.Part two Study on Predictive Model of Clinical outcome in patients with Acute Ischemic Stroke based on Multimodal CT1.Materials and methodsPatients with acute anterior circulation ischemic stroke admitted to the affiliated Hospital of Yan’an University from March 2020 to December 2022 were collected retrospectively.According to the modified Rankin scale(m RS)score after 3 months,the patients were divided into two groups: good prognosis and poor prognosis.Collect the patient’s sex,age,admission systolic blood pressure,diastolic blood pressure,BMI,hypertension history,coronary heart disease history,atrial fibrillation history,diabetes,smoking history,drinking history,hyperlipidemia,hyperhomocysteinemia,neutrophil count,lymphocyte count,monocyte count,platelet count,NLR,Platelet to lymphocyte ratio(PLR),Lymphocyte to monocyte ratio(LMR),baseline NIHSS score,m RS score after 3 months,and multimodal CT index core infarct volume,low perfusion volume,Hypoperfusion index ratio(HIR)and NWU.Student t-test,Mann-Whitney U test and chi-square test were used to analyze whether there were significant differences between the two groups.The independent influencing factors of poor prognosis in patients with acute ischemic stroke were screened by multi-factor stepwise Logistic regression analysis,and multivariate logistic regression models were established without and after NWU.The prediction efficiency of each model was analyzed by drawing ROC curve,and the AUC differences between different models were tested by Delong test.The improvement of the regression model with NWU compared with the regression model without NWU was judged by net reclassification index(NRI)and Integrated discrimination improvement(IDI).The independent predictors of the risk of poor prognosis were determined by multivariate stepwise Logistic regression,and the Nomogram prediction model was constructed by using rms package in R software.The calibration curve was drawn by Bootstrap repeated sampling for 1000 times to evaluate the calibration degree of the model,the predictive efficiency of the model was evaluated by the area under the ROC curve,and the clinical application value of the model was evaluated by decision curve analysis(DCA).2.Results193 patients were included in this study,including 81 patients with good prognosis and 112 patients with poor prognosis.There were statistically significant differences between the two groups in indicators such as coronary heart disease history(χ2=7.746,P=0.005),hyperhomocysteinemia(χ2=9.978,P=0.001),neutrophilic count(Z=-2.251,P=0.024),lymphocyte count(Z=-2.174,P=0.030),NLR(Z=-7.076,P<0.001),PLR(Z=-5.015,P< 0.001),LMR(Z=-4.154,P< 0.001),baseline NIHSS score(Z=-8.375,P<0.001),low perfusion volume(Z=2.578,P<0.001),core infarct volume(Z=4.287,P<0.001),HIR(Z=1.881,P= 0.002)and NWU(Z=-8.497,P<0.001).There were no significant difference in age,sex,systolic blood pressure,diastolic blood pressure,BMI,history of hypertension,history of atrial fibrillation,history of diabetes,history of smoking,history of drinking,hyperlipidemia,monocyte count and platelet count between the two groups.Coronary heart disease history,hyperhomocysteinemia,neutrophil count,lymphocyte count,NLR,PLR,LMR,baseline NIHSS score,low perfusion volume,core infarction volume,HIR and NWU were included in the regression model with poor prognosis as dependent variables.Multivariate Logistic regression analysis showed that NIHSS score(OR=1.181,95%CI:1.058~1.318,P=0.003),NLR(OR=1.352,95%CI:1.077~1.696,P=0.009),core infarction volume(OR=1.042,95%CI:1.008~1.077,P=0.014)and NWU(OR=1.247,95%CI:1.115~1.393,P<0.001)were independent risk factors for poor prognosis in patients with acute ischemic stroke.Regression model 1 was constructed based on baseline NIHSS score,NLR and core infarction volume,and regression model 2 was constructed based on baseline NIHSS score,NLR,core infarction volume and NWU.According to ROC curve analysis,the AUC of regression model 1 and regression model 2 were 0.940 and 0.956 respectively,the sensitivity and specificity of model 1 were 91.1% and 85.2%,and the sensitivity and specificity of model 2 were 90.2% and 95.1%,respectively.The Delong test showed that there was a significant difference between the AUC of regression model 1 and that of regression model 2(Z=-1.973,P=0.048).The NRI and IDI analysis between regression model 1 and regression model 2 showed that the prediction efficiency of model 2 was significantly better than that of model 1(NRI=0.575,P<0.001;IDI=0.081,P<0.001).Baseline NIHSS score,NLR,core infarction volume and NWU were used as independent predictors of poor prognosis,and a Nomogram predictive model was established.The calibration curve shows that the predicted occurrence risk of the model is in good agreement with the actual occurrence risk.ROC curve analysis showed that the AUC of Nomogram model was 0.956,and the best cutoff value,sensitivity and specificity were 0.603,0.902 and 0.951,respectively.DCA showed that when the threshold probability is in the range of 0-93%,the Nomogram model has a good clinical net benefit in predicting the risk of poor prognosis.3.Brief summaryIn this study,the nomogram model based on multimodal CT has good efficacy and clinical practical value in predicting the poor prognosis of patients with acute ischemic stroke.it can help clinicians to evaluate the risk of poor prognosis more objectively and concretely,improve the ability of doctors to predict the poor prognosis of patients with acute ischemic stroke,and provide a more accurate basis for clinical diagnosis and treatment decisions.Conclusions1)NWU based on multimodal CT has high recognition ability for stroke patients with different onset time,and there is a good correlation between NWU and onset time.2)NLR,baseline NIHSS score,core infarction volume and NWU were independent predictors of poor prognosis in patients with acute ischemic stroke.the AUC,sensitivity and specificity of the Logistic regression model based on the above predictors were 0.956,90.2% and 95.1%,respectively.Compared with the regression model without NWU,its predictive efficiency was significantly improved.Based on all independent predictors,a Nomogram model for predicting the risk of poor prognosis in patients with acute ischemic stroke was established.The calibration curve showed that the prediction risk was consistent with the actual risk,and the decision curve analysis showed that it had high clinical practical value.The prediction model established in this study can help clinicians to make a more objective and specific assessment of the risk of poor prognosis and improve the ability of doctors to predict the poor prognosis of patients with acute ischemic stroke.to provide more accurate help for clinical diagnosis and treatment decisions.