Analysis And Evaluation Of Risk Factors Of Intracranial Aneurysm Rupture

Objective This study analyzed the clinical factors,morphology,and hemodynamics of patients with intracranial aneurysms,compared the differences in clinical factors,morphology,and hemodynamics between ruptured and unruptured aneurysms,established a risk assessment model for intracranial aneurysms,and validated the model in order to obtain more accurate research results and provide reference for the clinical diagnosis and treatment of aneurysms.Methods A total of 98 patients with intracranial aneurysms confirmed by cerebral angiography were selected,and 70 patients were included in the modeling queue.They were divided into rupture group and non rupture group,and the general data(age,gender,smoking history,hypertension history,diabetes history)Morphology [aneurysm size,size ratio(SR),aspect ratio(AR),fluctuation index(UI),ellipticity index(EI),non-sphericity index(NSI)]and hemodynamic factors [wall shear stress(WSS),shear oscillation index(OSI)],relevant factors were obtained through single factor analysis,And apply these factors to establish a binomial logistic regression model.The following 28 patients were included in the validation queue,and the model was tested in the validation queue to evaluate the accuracy of the prediction results of the model.Results The analysis showed that there was no significant difference in age,gender,smoking history,hypertension and diabetes in the clinical data(P>0.05).Morphological and hemodynamic comparison,size ratio(SR),The wall shear stress(WSS)was significantly different between the ruptured and non-ruptured groups(P<0.05).The SR of patients in the ruptured group was significantly higher than that in the non-ruptured group,and the WSS was significantly lower than that in the non-ruptured group.The overall prediction accuracy of the research model was 67.86%.Conclusion The SR and low WSS in the morphological and hemodynamic parameters of intracranial aneurysms are important factors affecting the rupture of intracranial aneurysms.The prediction model constructed from this has certain predictive value for aneurysm rupture and helps to evaluate the risk of rupture.