The Risk Assessment Models Of Rupture And Growth Of Multiple Intracranial Aneurysms

Objective: The morphological and hemodynamic parameters of multiple intracranial aneurysms were used to screen out the risk factors for rupture and growth,and to establish the risks prediction models.Methods: This study included patients with multiple intracranial aneurysms who received cerebral angiography.Of the ruptured cases,each included patient had only 1 treated aneurysm and the ruptured aneurysm was also identified with preoperative CT and surgical procedure.Of the grown cases,the follow-up outcome was the increased aneurysm size or aneurysm rupture.Paired test and conditional logistic regression analysis were used to evaluate the morphological and hemodynamic parameters of aneurysm.And the predictive models for aneurysm rupture and growth were established according to their independent risk factors.The prediction sensitivity and accuracy of the independent risk factors and scoring systems were examined by the receiver operating characteristic curve(ROC)and the area under the curve(AUC).Results: 172 patients with ruptured multiple aneurysms and 19 patients with grown unruptured multiple aneurysms were included.Multivariate conditional logistics regression showed that aneurysm width,daughter sac,aneurysm height≥width,aneurysm’s location and maximum wall shear stress(WSS max)were independent risk factors for rupture.And aneurysm width,and WSS max were independent risk factors for growth.According to the independent risk factors,scoring systems for the risks of aneurysm rupture and growth were established respectively.And their AUC values were0.846 and 0.762,individually.Conclusions: Using the predictive models can identify patients with higher risks for aneurysm rupture and growth,so that they can receive treatments as soon as possible or take more frequent follow-up procedures.Part Ⅰ: Morphological and hemodynamic risk factors for multiple intracranial aneurysms ruptureObjective: To identify morphological and hemodynamic risk factors for rupture in multiple intracranial aneurysms.Methods: From August 2014 to June 2022,the digital angiography(DSA)data of patients with rupture multiple aneurysms in our center were collected.Each included patient had only 1 treated aneurysm and the ruptured aneurysm was also identified with preoperative CT and surgical procedure.Paired analysis and conditional logistics regression were used to analyse the following morphological and hemodynamic parameters: aneurysm height,width,neck width,daughter sac,location,side,parent artery diameter,flow angle,aspect ratio,bottle neck factor,size ratio,height/width ratio,aneurysm height≥width,WSS,velocity,and static pressure.Predictive model was established according to the odd ratios(OR)of the independent risk factors.ROC and AUC were used to evaluate the specificity and sensitivity of the risk factors and predictive model.Results: 172 patients with ruptured multiple aneurysms were included.Among them,there were 240 unruptured aneurysms.Aneurysm width(OR=1.277,P=0.024),aneurysm height≥width(OR=4.754,P<0.001),daughter sac(OR=14.742,P<0.001),aneurysm located on posterior communicating artery,anterior communicating artery and posterior circulation(OR=5.084,OR=4.481 and OR=15.501,P=0.020,P=0.045 and P=0.029),and WSS max(OR=1.036,P=0.022)were independent risk factors for rupture.Predictive model was established according to the odd ORs of the independent risk factors,and ROC was used to evaluate the accuracy.The AUC value of the predictive model was 0.846,which was significantly higher than that of the independent risk factors.Conclusions: Using the predictive model can identify patients with higher risks for aneurysm rupture,so that they can receive treatments as soon as possible.Part Ⅱ: Morphological and hemodynamic risk factors for unruptured multiple intracranial aneurysms growthObjective: To identify morphological and hemodynamic risk factors for growth in unruptured multiple intracranial aneurysms.Methods: From August 2014 to June 2022,the DSA data of patients with unrupture multiple aneurysms in our center were collected.Of each grown case,the follow-up outcome was the increased aneurysm size or aneurysm rupture.Paired analysis and conditional logistics regression were used to analyse the following morphological and hemodynamic parameters: aneurysm height,width,neck width,daughter sac,location,side,parent artery diameter,flow angle,aspect ratio,bottle neck factor,size ratio,height/width ratio,aneurysm height≥width,WSS,velocity,and static pressure.Predictive model was established according to the ORs of the independent risk factors.ROC and AUC were used to evaluate the specificity and sensitivity of the risk factors and predictive model.Results: 19 patients with grown unruptured multiple aneurysms were included.Among them,there were 20 grown aneurysms and 25 steady aneurysms.Aneurysm width(OR=5.955,P=0.020),and WSS max(OR=1.474,P=0.026)were independent risk factors for growth.Predictive model was established according to the ORs of the independent risk factors.And the AUC value of the predictive model was 0.762,which was higher than that of the independent risk factors.Compared to the initial DSA image,aneurysm width,WSS max and the predictive model of rupture were significantly higher in the follow-up DSA(P=0.001、P=0.039 and P=0.005).Conclusions: Using the predictive model can identify patients with higher risks for aneurysm growth,so that they can take more frequent follow-up procedures.