Background: The rupture risk of anterior communicating artery aneurysms (ACoAAs) has been known to be higher than that of aneurysms at other locations. Thus, the aim of this study is to investigate the clinical and morphological characteristics associated with risk factors for the rupture of ACoAAs. Methods: In total, 361 consecutive patients with 361 ACoAAs between August 2011 and December 2017 were retrospectively reviewed. Patients and ACoAAs were divided into ruptured and unruptured groups. In addition to clinical characteristics, ACoAA characteristics were evaluated by CT angiography (CTA). A multiple logistic regression analysis was used to identify the independent risk factors associated with ACoAA rupture. The assignment score of these variables depends on the β coefficient. A receiver operating characteristic (ROC) curve analysis was used to calculate the optimal thresholds. Results: The multiple logistic regression model revealed that A1 dominance [odds ratio (OR) 3.034], an irregular shape (OR 3.358), and an aspect ratio ≥1.19 (AR; OR 3.163) increased the risk of rupture, while cerebral atherosclerosis (OR 0.080), and mean diameters ≥2.48 mm (OR 0.474) were negatively correlated with ACoAA rupture. Incorporating these five factors, the ROC analysis revealed that the threshold value of the multifactors was one, the sensitivity was 88.3%, and the specificity was 66.0%. Conclusions: The scoring model is a simple method that is based on A1 dominance, irregular shape, aspect ratio, cerebral atherosclerosis, and mean diameters from CTA and is of great value in the prediction of the rupture risk of ACoAAs.

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Background For patients with aneurysmal subarachnoid hemorrhages (SAHs) and multiple intracranial aneurysms (MIAs), a simple and fast imaging method that can identify ruptured intracranial aneurysms (RIAs) may have great clinical value. We sought to use the aneurysm-specific prediction score to identify RIAs in patients with MIAs and evaluate the aneurysm-specific prediction score. Methods Between May 2018 and May 2021, 134 patients with 290 MIAs were retrospectively analyzed. All patients had an SAH due to IA rupture. CT angiography (CTA) was used to assess the maximum diameter, shape, and location of IAs to calculate the aneurysm-specific prediction score. Then, the aneurysm-specific prediction score was applied to RIAs in patients with MIAs. Results The IAs with the highest aneurysm-specific prediction scores had not ruptured in 17 (12.7%) of the 134 patients with 290 MIAs. The sensitivity, specificity, false omission rate, diagnostic error rate, and diagnostic accuracy of the aneurysm-specific prediction score were higher than those of the maximum diameter, shape, and location of IAs. Conclusions The present study suggests that the aneurysm-specific prediction score has high diagnostic accuracy in identifying RIAs in patients with MIAs and SAH, but that it needs further evaluation.

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