Research Article - Biomedical Research (2017) Volume 28, Issue 13

The risk factors of intracranial aneurysm rupture and the assessing efficacy of CTA

Objective: The objective is to apply the Computed Tomographic Angiography (CTA) on assessing the risk factors of intracranial aneurysm rupture, providing the reference for the prevention of intracranial aneurysm rupture.

Methods: 252 intracranial aneurysm rupture patients admitted in our hospital between February 2014- February 2017 were selected for prospective study. The rate of intracranial aneurysm rupture was evaluated and calculated. The univariate analysis was used to evaluate the different clinical characteristics and CTA results of patients with intracranial aneurysm rupture patients, and then the factors with statistical difference were included in Logistic multivariate regression analysis to analyse the risk factors of intracranial aneurysm rupture.

Results: In 252 patients, 45 patients were confirmed as intracranial aneurysm rupture during the surgery, the rate of intracranial aneurysm rupture was 17.86%. Logistic multivariate regression analysis results showed that complicating with hypertension, the diameter of aneurysm ≥ 3.850 mm, the ratio of aneurysm depth to aneurysm neck width (aspect ratio, AR) ≥ 1.448, the ratio of tumor depth to patent artery diameter (size ratio, SR) ≥ 1.388, the ratio of aneurysm area to the patent artery area at aneurysm neck ≥ 1.192, irregular aneurysm wall and the aneurysm locating at posterior communicating artery, internal carotid artery or middle cerebral artery were the independent risk factors of intracranial aneurysm rupture. The age ≥ 60, male patient and complicating with diabetes were the protective factors (P<0.05).

Conclusion: Intracranial aneurysm rupture is closely related to clinical characteristics, aneurysm morphology and location. Based on the baseline characteristics, aneurysm diameter, AR, SR and area ratio in CTA image could be the reliable references of intracranial aneurysm rupture risk.

Author(s): Yan-Ying Li, Bai-Lu Liu, Yan-Ming Zhao, Wen-Ying Yan, Ya-Hua Huang, Guang-Sheng Jia, De-Li Zhao, Hai-Bo Wang, Wei-Dong Zhang, Jia-Wei Tian

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