Application of 3D T1-SPACE combined with 3D-TOF sequence for follow-up evaluation of stent-assisted coil embolization for intracranial aneurysm

Predictors of aneurysm shrinkage after flow diversion treatment for internal carotid artery aneurysms: quantitative volume analysis with MRI

Background and purpose

Although aneurysm shrinkage often occurs after flow diversion treatment for intracranial aneurysms, no reports have addressed the factors associated with aneurysm shrinkage.

Materials and methods

This retrospective single-center study was performed to examine patients with unruptured internal carotid artery aneurysms who were treated using flow diversion and followed up by imaging for at least 12 months. The study outcome was aneurysm shrinkage (volume reduction of ≥10%) 12 months after treatment. Aneurysm volume was quantitatively assessed using the MRIcroGL software. Patient and aneurysm characteristics were statistically analyzed.

Results

This study involved 81 patients with 88 aneurysms. At the 6 months, 12 months, and last follow-ups, the proportion of aneurysms that had shrunk was 50, 64, and 65%, respectively. No adjunctive coiling (odds ratio, 56.7; 95% confidence interval, 7.03-457.21; p < 0.001) and aneurysm occlusion (odds ratio, 90.7; 95% confidence interval, 8.32-988.66; p < 0.001) were significantly associated with aneurysm shrinkage. In patients treated by flow diversion with adjunctive coiling, only the volume embolization rate was a factor significantly associated with aneurysm shrinkage (p < 0.001). Its cutoff value was 15.5% according to the receiver operating characteristic curve analysis (area under the curve, 0.87; sensitivity, 0.87; specificity, 0.83).

Conclusion

The rate of aneurysm shrinkage after flow diversion increased during the first 12 months after treatment, but not thereafter. No adjunctive coiling and aneurysm occlusion were predictors of aneurysm shrinkage, respectively. If adjunctive coiling is required, a volume embolization rate of ≤15.5% may be suggested for aneurysm regression.

Flow diversion for unruptured fusiform aneurysms of the proximal middle cerebral artery

Background

Managing fusiform aneurysms of the proximal (M1) segment of the middle cerebral artery (MCA) is challenging due to difficulties in both surgical and endovascular treatment. In this study, we present our experience using flow diverter stents for managing unruptured M1 segment fusiform aneurysms.

Methods

We conducted a retrospective review of the database of our institution to identify all patients who underwent flow diversion treatment for unruptured M1 segment fusiform aneurysms. We collected data on patient demographics, aneurysm characteristics, complications, angiographic follow-up results, and clinical outcomes.

Results

A total of 10 patients (five male and five female patients) with 10 unruptured M1 segment fusiform aneurysms were included in the study. The average age of the patients was 48 years (range: 16-64 years); five patients had aneurysms smaller than 10 mm, four had aneurysms measuring between 10 and 25 mm, and one patient had an aneurysm larger than 25 mm. The successful deployment of flow-diverting stents was achieved in all cases. Procedure-related morbidity was observed in 10% of patients, but there were no deaths. All patients showed good outcomes (modified Rankin Scale score of 0-1); eight out of 10 patients had available follow-up angiography results with a mean follow-up period of 11.6 months (range: 6-24 months). Complete occlusion occurred in six out of eight reviewed cases (75%).

Conclusion

Our preliminary findings suggest that using flow diversion for treating unruptured fusiform aneurysms in the proximal MCA is feasible and safe, with a satisfactory rate of complete occlusion. However, further studies involving larger case series are needed to validate the durability and efficacy of this treatment approach.

A machine learning-derived gene signature for assessing rupture risk and circulatory immunopathologic landscape in patients with intracranial aneurysms

Background

Intracranial aneurysm (IA) is an uncommon but severe subtype of cerebrovascular disease, with high mortality after aneurysm rupture. Current risk assessments are mainly based on clinical and imaging data. This study aimed to develop a molecular assay tool for optimizing the IA risk monitoring system.

Methods

Peripheral blood gene expression datasets obtained from the Gene Expression Omnibus were integrated into a discovery cohort. Weighted gene co-expression network analysis (WGCNA) and machine learning integrative approaches were utilized to construct a risk signature. QRT-PCR assay was performed to validate the model in an in-house cohort. Immunopathological features were estimated using bioinformatics methods.

Results

A four-gene machine learning-derived gene signature (MLDGS) was constructed for identifying patients with IA rupture. The AUC of MLDGS was 1.00 and 0.88 in discovery and validation cohorts, respectively. Calibration curve and decision curve analysis also confirmed the good performance of the MLDGS model. MLDGS was remarkably correlated with the circulating immunopathologic landscape. Higher MLDGS scores may represent higher abundance of innate immune cells, lower abundance of adaptive immune cells, and worse vascular stability.

Conclusions

The MLDGS provides a promising molecular assay panel for identifying patients with adverse immunopathological features and high risk of aneurysm rupture, contributing to advances in IA precision medicine.