Cerebral Aneurysm Occlusion at 12-Month Follow-Up After Flow-Diverter Treatment: Statistical Modeling for V&V With Real-World Data.

Background: Flow-Diverter (FD) porosity has been pointed as a critical factor in the occlusion of cerebral aneurysms after treatment. Objective: Verification and Validation of computational models in terms of predictive capacity, relating FD porosity and occlusion after cerebral aneurysms treatment. Methods: Sixty-four aneurysms, with pre-treatment and follow-up images, were considered. Patient demographics and aneurysm morphological information were collected. The computational simulation provided by ANKYRAS provided FD porosity, expansion, and mesh angle. FD occlusion was assessed and recorded from follow-up images. Multiple regression Logit and analysis of covariance (ANCOVA) models were used to model the data with both categorical and continuous models. Results: Occlusion of the aneurysm after 12 months was affected by aneurysm morphology but not by FD mesh morphology. A Time-To-Occlusion (TTO) of 6.92 months on average was observed with an SE of 0.24 months in the aneurysm population surveyed. TTO was estimated with statistical significance from the resulting model for the data examined and was capable of explaining 92% of the data variation. Conclusions: Porosity was found to have the most correction power when assessing TTO, proving its importance in the process of aneurysm occlusion. Still, further Verification and Validation (V&V) of treatment simulation in more extensive, multi-center, and randomized databases is required.

Early Results in Flow Diverter Sizing by Computational Simulation: Quantification of Size Change and Simulation Error Assessment.

BACKGROUND: Sizing of flow diverters (FDs) stent in the treatment of intracranial aneurysms is a challenging task due to the change of stent length after implantation. OBJECTIVE: To quantify the size change and assess the error in length prediction in 82 simulated FD deployments. METHODS: Eighty-two consecutive patients treated with FDs were retrospectively analyzed. Implanted FD length was measured from angiographic images and compared to the nominal sizes of the implanted device. Length change was obtained by subtracting the nominal length from the real length and dividing by the nominal length. Implanted devices were simulated on 3-dimensional models of each patient. Simulation error was obtained by subtracting real length from simulated length and dividing by the real length of the FD. Subanalysis was done using ANOVA. Statistical significance was set to P < .05, and bootstrap resampling was used. RESULTS: When assessing the length change of the FD after implantation, changes of 30% in average and up to 80% with reference to the nominal length of the device were observed. The simulation results showed a lower error of 3.52% in average with a maximum of 30%. Paired t-test showed nonsignificant differences between measured and real length (P = .07, with the mean of differences at 0.45 mm, 95% confidence interval [-0.950 0.038]). CONCLUSION: Nominal length is not an accurate sizing metric when choosing the size of an FD irrespective of the brand and manufacturer. Good estimation of the final length of the stent after deployment as expressed by an error of 3.5% in average.