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

High variability in physician estimations of flow-diverting stent deployment versus PreSize Neurovascular software simulation: a comparison study

BACKGROUND

Physician variablity in preoperative planning of endovascular implant deployment and associated inaccuracies have not been documented. This study aimed to quantify the variability in accuracy of physician flow diverter (FD) planning and directly compares it with PreSize Neurovascular (Oxford Heartbeat Ltd) software simulations.

METHODS

Eight experienced neurointerventionalists (NIs), blinded to procedural details, were provided with preoperative 3D rotational angiography (3D-RA) volumetric data along with images annotated with the distal landing location of a deployed Surpass Evolve (Stryker Neurovascular) FD from 51 patient cases. NIs were asked to perform a planning routine reflecting their normal practice and estimate the stent's proximal landing using volumetric data and the labeled dimensions of the FD used. Equivalent deployed length estimation was performed using PreSize software. NI- and software-estimated lengths were compared with postprocedural observed deployed stent length (control) using Bland-Altman plots. NI assessment agreement was assessed with the intraclass correlation coefficient (ICC).

RESULTS

The mean accuracy of NI-estimated deployed FD length was 81% (±15%) versus PreSize's accuracy of 95% (±4%), demonstrating significantly higher accuracy for the software (p<0.001). The mean absolute error between estimated and control lengths was 4 mm (±3.5 mm, range 0.03-30.2 mm) for NIs and 1 mm (±0.9 mm, range 0.01-3.9 mm) for PreSize. No discernable trends in accuracy among NIs or across vasculature and aneurysm morphology (size, vessel diameter, tortuousity) were found.

CONCLUSIONS

The study quantified experienced physicians' significant variablity in predicting an FD deployment with current planning approaches. In comparison, PreSize-simulated FD deployment was consistently more accurate and reliable, demonstrating its potential to improve standard of practice.

Comparison of Flow Reduction Efficacy of Nominal and Oversized Flow Diverters Using a Novel Measurement-assisted in Silico Method

PURPOSE

The high efficacy of flow diverters (FD) in the case of wide-neck aneurysms is well demonstrated, yet new challenges have arisen because of reported posttreatment failures and the growing number of new generation of devices. Our aim is to present a measurement-supported in silico workflow that automates the virtual deployment and subsequent hemodynamic analysis of FDs. In this work, the objective is to analyze the effects of FD deployment variability of two manufacturers on posttreatment flow reduction.

METHODS

The virtual deployment procedure is based on detailed mechanical calibration of the flow diverters, while the flow representation is based on hydrodynamic resistance (HR) measurements. Computational fluid dynamic simulations resulted in 5 untreated and 80 virtually treated scenarios, including 2 FD designs in nominal and oversized deployment states. The simulated aneurysmal velocity reduction (AMVR) is correlated with the HR values and deployment scenarios.

RESULTS

The linear HR coefficient and AMVR revealed a power-law relationship considering all 80 deployments. In nominal deployment scenarios, a significantly larger average AMVR was obtained (60.3%) for the 64-wire FDs than for 48-wire FDs (51.9%). In oversized deployments, the average AMVR was almost the same for 64-wire and 48-wire device types, 27.5% and 25.7%, respectively.

CONCLUSION

The applicability of our numerical workflow was demonstrated, also in large-scale hemodynamic investigations. The study revealed a robust power-law relationship between a HR coefficient and AMVR. Furthermore, the 64 wire configurations in nominal sizing produced a significantly higher posttreatment flow reduction, replicating the results of other in vitro studies.

Predicting flow diverter sizing using the AneuGuideTM software: a validation study

BACKGROUND

Stent sizing remains a challenging task for flow diverter implantation because of stent foreshortening. In this study, we aimed to quantify the change in length after implantation and assess the error in length prediction using AneuGuide^TM software.

METHODS

In a retrospective cohort of 101 patients with 102 aneurysms undergoing treatment with a pipeline embolization device (PED; Covidien, Irvine, California, USA), we used AneuGuide^TM software to obtain measured lengths (ML) and calculated lengths (CL) after stent implantation. Stent elongation was defined as the ratio of ML-LL to the labeled length (LL). Simulation error was defined as the ratio of the absolute value of CL-ML to ML. The correlation and consistency between ML and LL and between ML and CL were analyzed using Pearson's correlation test and the Bland-Altman plot. Statistical significance was set at p<0.05.

RESULTS

The mean elongation of ML was 32.6% (range 26.3-109.2%). Moderate consistency was observed between LL and ML (ρ=0.74, p<0.001). With the AneuGuide^TM software, the mean simulation error was 6.6% (range 0.32-21.2%). Pearson's correlation test and the Bland-Altman plot showed a high correlation and consistency between ML and CL (ρ=0.96, p<0.001).

CONCLUSION

Labeled length provides only a low reference value for predicting the actual length of the flow diverter after implantation. The high consistency between ML and CL obtained from AneuGuide^TM software shows its great potential for the optimization of the flow diverter sizing process.

How precise is PreSize Neurovascular? Accuracy evaluation of flow diverter deployed-length prediction

OBJECTIVE

The use of flow-diverting stents has been increasingly important in intracranial aneurysm treatment. However, accurate sizing and landing zone prediction remain challenging. Inaccurate sizing can lead to suboptimal deployment, device waste, and complications. This study presents stent deployment length predictions offered in medical software (PreSize Neurovascular) that provides physicians with real-time planning support, allowing them to preoperatively "test" different devices in the patient's anatomy in a safe virtual environment. This study reports the software evaluation methodology and accuracy results when applied to real-world data from a wide range of cases and sources as a necessary step in demonstrating its reliability, prior to impact assessment in prospective clinical practice.

METHODS

Imaging data from 138 consecutive stent cases using the Pipeline embolization device were collected from 5 interventional radiology centers in the United Kingdom and retrospectively analyzed. Prediction accuracy was calculated as the degree of agreement between stent deployed length measured intraoperatively and simulated in the software.

RESULTS

The software predicted the deployed stent length with a mean accuracy of 95.61% (95% confidence interval [CI] 94.87%-96.35%), the highest reported accuracy in clinical stent simulations to date. By discounting 4 outlier cases, in which events such as interactions with coils and severe push/pull maneuvers impacted deployed length to an extent the software was not able to simulate or predict, the mean accuracy further increases to 96.13% (95% CI 95.58%-96.69%). A wide discrepancy was observed between labeled and measured deployed stent length, in some cases by more than double, with no demonstrable correlation between device dimensions and deployment elongation. These findings illustrate the complexity of stent behavior and need for simulation-assisted sizing for optimal surgical planning.

CONCLUSIONS

The software predicts the deployed stent length with excellent accuracy and could provide physicians with real-time accurate device selection support.

Simulation of intra-saccular devices for pre-operative device size selection: Method and validation for sizing and porosity simulation

Intra-saccular devices (ID) are novel braided devices used for complex intracranial aneurysms treatment. Treatment success is associated with correct device size selection. A technique that predicts the ID size within the aneurysm before intervention will provide a powerful computational tool to aid the interventionist during device selection. We present a method to calculate the device's final height, radial expansion and porosity within the patient's anatomy, which allows assessing different device sizes before treatment takes place. The proposed sizing technique was tested in-vitro and in real patient's geometries obtained from 3DRA angiographic images of 8 unruptured aneurysms previously treated with IDs. The obtained simulated height was compared to the real height, with a mean error of less than 0.28 mm (±0.44). The porosity calculation method was tested in-vitro with an error of 0.02 (±0.022). The results of both sizing and porosity experiments resemble well measures from real patients. This methodology could be used before treatment to provide the interventionist with additional information that allows selecting the device that best fits the patient's aneurysm to be treated.

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.

Intra-saccular device modeling for treatment planning of intracranial aneurysms: from morphology to hemodynamics

MOTIVATION

Intra-saccular devices (ID), developed for the treatment of bifurcation aneurysms, offer new alternatives for treating complex terminal and bifurcation aneurysms. In this work, a complete workflow going from medical images to post-treatment CFD analysis is described and used in the assessment of a concrete clinical problem.

MATERIALS AND METHODS

Two different intra-saccular device sizes were virtually implanted in 3D models of the patient vasculature using the ID-Fit method. After deployment, the local porosity at the closed end of the device in contact with the blood flow was computed. This porosity was then used to produce a CFD porous medium model of the device. Velocities and wall shear stress were assessed for each model.

RESULTS

Six patients treated with intra-saccular devices were included in this work. For each case, 2 different device sizes were virtually implanted and 3 CFD simulations were performed: after deployment simulation with each size and before deployment simulation (untreated). A visible reduction in velocities was observed after device implantation. Velocity and WSS reduction was statistically significant (K-S statistics, [Formula: see text]).

CONCLUSIONS

Placement of different device size can lead to a partial filling of the aneurysm, either at the dome or at the neck, depending on the particular positioning by the interventionist. The methodology used in this work can have a strong clinical impact, since it provides additional information in the process of device selection using preoperative data.

Stenting as porous media in anatomically accurate geometries. A comparison of models and spatial heterogeneity

Modelling intracranial aneurysm blood flow after flow diverter treatment has proven to be of great scientific and clinical interest. One of the reasons for not having CFD as an everyday clinical tool yet is the time required to set-up such simulations plus the required computational time. The speed-up of these simulations can have a considerable impact during treatment planning and device selection. Modelling flow diverters as a porous medium (PM) can considerably improve the computational time. Many models have been presented in literature, but quantitative comparisons between models are scarce. In this study, the untreated case, the explicit definition of the flow diverter wires as no-slip boundary condition and five different porous medium models were chosen for comparison, and evaluated on intracranial aneurysm of 14 patients with different shapes, sizes, and locations. CFD simulations were made using finite volume method on steady flow conditions. Velocities, kinetic energy, wall shear stress, and computational time were assessed for each model. Then, all models are compared against the no-slip boundary condition using non parametric Kolmogorov-Smirnov test. The model with least performance showed a mean K-S statistic of 0.31 and deviance of 0.2, while the model with best values always gave K-S statistics below 0.2. Kinetic energy between PM models varied between an over estimation of 218.3% and an under estimation of 73.06%. Also, speedups were between 4.75x and 5.3x (stdev: 0.38x and 0.15x) when using PM models. Flow diverters can be simulated with PM with a good agreement to standard CFD simulations were FD wires are represented with no-slip boundary condition in less than a quarter of the time. Best results were obtained on PM models based on geometrical properties, in particular, when using a heterogeneous medium based on equations for flat rhomboidal wire frames.

A Multicenter Pilot Study on the Clinical Utility of Computational Modeling for Flow-Diverter Treatment Planning

BACKGROUND AND PURPOSE

Selection of the correct flow-diverter size is critical for cerebral aneurysm treatment success, but it remains challenging due to the interplay of device size, anatomy, and deployment. Current convention does not address these challenges well. The goals of this pilot study were to determine whether computational modeling improves flow-diverter sizing over current convention and to validate simulated deployments.

MATERIALS AND METHODS

Seven experienced neurosurgeons and interventional neuroradiologists used computational modeling to prospectively plan 19 clinical interventions. In each patient case, physicians simulated 2-4 flow-diverter sizes that were under consideration based on preprocedural imaging. In addition, physicians identified a preferred device size using the current convention. A questionnaire on the impact of computational modeling on the procedure was completed immediately after treatment. Rotational angiography image data were acquired after treatment and compared with flow-diverter simulations to validate the output of the software platform.

RESULTS

According to questionnaire responses, physicians found the simulations useful for treatment planning, and they increased their confidence in device selection in 94.7% of cases. After viewing the simulations results, physicians selected a device size that was different from the original conventionally planned device size in 63.2% of cases. The average absolute difference between clinical and simulated flow-diverter lengths was 2.1 mm. In 57% of cases, average simulated flow-diverter diameters were within the measurement uncertainty of clinical flow-diverter diameters.

CONCLUSIONS

Physicians found computational modeling to be an impactful and useful tool for flow-diverter treatment planning. Validation results showed good agreement between simulated and clinical flow-diverter diameters and lengths.

Deployment of flow diverter devices: prediction of foreshortening and validation of the simulation in 18 clinical cases

PURPOSE

Flow diverter (FD) devices show severe shortening during deployment in dependency of the vessel geometry. Valid information regarding the geometry of the targeted vessel is therefore mandatory for correct device selection, and to avoid complications. But the geometry of diseased tortuous intracranial vessels cannot be measured accurately with standard methods. The goal of this study is to prove the accuracy of a novel virtual stenting method in prediction of the behavior of a FD in an individual vessel geometry.

METHODS

We applied a virtual stenting method on angiographic 3D imaging data of the specific vasculature of patients, who underwent FD treatment. The planning tool analyzes the local vessel morphology and deploys the FD virtually. We measured in 18 cases the difference between simulated FD length and real FD length after treatment in a landmark-based registration of pre-/post-interventional 3D angiographic datasets.

RESULTS

The mean value of length deviation of the virtual FD was 2.2 mm (SD ± 1.9 mm) equaling 9.5% (SD ± 8.2%). Underestimated cases present lower deviations compared with overestimated FDs. Flow diverter cases with a nominal device length of 20 mm had the highest prediction accuracy.

CONCLUSION

The results suggest that the virtual stenting method used in this study is capable of predicting FD length with a clinically sufficient accuracy in advance and could therefore be a helpful tool in intervention planning. Imaging data of high quality are mandatory, while processing and manipulation of the FD during the intervention may impact the accuracy.

Comparison of Pipeline Embolization Device Sizing Based on Conventional 2D Measurements and Virtual Simulation Using the Sim&Size Software: An Agreement Study

BACKGROUND AND PURPOSE

The Sim&Size software simulates case-specific intraluminal Pipeline Embolization Device behavior, wall apposition, and device length in real-time on the basis of rotational angiography DICOM data. The purpose of this multicenter study was to evaluate whether preimplantation device simulation with the Sim&Size software results in selection of different device dimensions than manual sizing.

MATERIALS AND METHODS

In a multicenter cohort of 74 patients undergoing aneurysm treatment with the Pipeline Embolization Device, we compared apparent optimal device dimensions determined by neurointerventionalists with considerable Pipeline Embolization Device experience based on manual 2D measurements taken from rotational angiography with computed optimal dimensions determined by Sim&Size experts blinded to the neurointerventionalists' decision. Agreement between manually determined and computed optimal dimensions was evaluated with the Cohen κ. The significance of the difference was analyzed with the Wilcoxon signed rank test.

RESULTS

The agreement index between manual selection and computed optimal dimensions was low (κ for diameter = 0.219; κ for length = 0.149, P < .01). Computed optimal device lengths were significantly shorter (median, 14 versus 16 mm, T = 402, r = -0.28, P < .01). No significant difference was observed for device diameters.

CONCLUSIONS

Low agreement between manually determined and computed optimal device dimensions is not proof, per se, that virtual simulation performs better than manual selection. Nevertheless, it ultimately reflects the potential for optimization of the device-sizing process, and use of the Sim&Size software reduces, in particular, device length. Nevertheless, further evaluation is required to clarify the impact of device-dimension modifications on outcome.