Vascular inflammation with eosinophils after the use of n-butyl cyanoacrylate liquid embolic system.

OBJECTIVE AND IMPORTANCE: Currently, n-butyl cyanoacrylate (n-BCA) is one of the most widely used liquid embolic agents in the treatment of intracranial arteriovenous malformations (AVMs). The cases of three patients are reported who underwent endovascular embolization with n-BCA, followed by resection in two and post-embolization hemorrhage with emergent evacuation in one, with histologic demonstration of an eosinophilic vasculitis found in resected AVM specimens. This is probably the first report of this tissue reaction, which may have theoretically serious clinical implications. CLINICAL PRESENTATION: In this series, three patients (2 women, 1 man) presented with intracranial AVMs (Spetzler-Martin I-III) with the lesions located in the frontal lobe in two of the patients and in the parietal lobe in one. All patients presented with headache, and one also had new-onset seizures. INTERVENTION: All patients underwent embolization with n-BCA before a planned, staged surgical resection of the embolized AVMs. One patient had four embolizations over a 5-month period, one had three embolizations over 3 months complicated by hemorrhage after embolization requiring emergent evacuation of the hematoma, and the third patient had a single embolization. In all three patients, surgical and autopsy specimens showed an inflammatory response within the embolized vasculature with a prominent eosinophilic infiltrate. CONCLUSION: The eosinophilic vasculitis seen in the pathology specimens may represent a previously undocumented hypersensitivity reaction following exposure to n-BCA, with the potential for adverse sequelae, including increased risk of hemorrhage as was seen in one of our patients.

Predicting aneurysm rupture probabilities through the application of a computed tomography angiography-derived binary logistic regression model.

OBJECT: The goal of this study was to establish a biomathematical model to accurately predict the probability of aneurysm rupture. Biomathematical models incorporate various physical and dynamic phenomena that provide insight into why certain aneurysms grow or rupture. Prior studies have demonstrated that regression models may determine which parameters of an aneurysm contribute to rupture. In this study, the authors derived a modified binary logistic regression model and then validated it in a distinct cohort of patients to assess the model's stability. METHODS: Patients were examined with CT angiography. Three-dimensional reconstructions were generated and aneurysm height, width, and neck size were obtained in 2 orthogonal planes. Forward stepwise binary logistic regression was performed and then applied to a prospective cohort of 49 aneurysms in 37 patients (not included in the original derivation of the equation) to determine the log-odds of rupture for this aneurysm. RESULTS: A total of 279 aneurysms (156 ruptured and 123 unruptured) were observed in 217 patients. Four of 6 linear dimensions and the aspect ratio were significantly larger (each with p < 0.01) in ruptured aneurysms than unruptured aneurysms. Calculated volume and aneurysm location were correlated with rupture risk. Binary logistic regression applied to an independent prospective cohort demonstrated the model's stability, showing 83% sensitivity and 80% accuracy. CONCLUSIONS: This binary logistic regression model of aneurysm rupture identified the status of an aneurysm with good accuracy. The use of this technique and its validation suggests that biomorphometric data and their relationships may be valuable in determining the status of an aneurysm.