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

Narata, Ana Paula; Blasco, Jordi; Román, Luís San; Macho, Juan; Fernández, Héctor; Moyano, Raquel Kale; Winzenrieth, Renaud; Larrabide, Ignacio

doi:10.1093/ons/opx288

Cited by 17 publications

(19 citation statements)

References 24 publications

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“…[25][26][27][28][29] Previous work has revealed, for instance, how virtual simulation reduces the error in length prediction compared with the nominal length provided by the manufacturers. 30,31 Much of this research in the field of virtual device simulation has focused, however, on technical aspects of accurate modeling and prediction of intraluminal device behavior, with only a very few small case series of in vivo use of simulation tools in the field of neurointervention. 32 Moreover, previous software solutions generally remain of limited use with regard to their application in a real-world setting, given the constraints such as a lack of information regarding wall apposition and the inability to test, in real-time, multiple device dimensions and positions.…”

Section: Figmentioning

confidence: 99%

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

Ospel¹,

Gascou

Costalat

et al. 2019

AJNR Am J Neuroradiol

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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. 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 (for diameter ϭ 0.219; for length ϭ 0.149, P Ͻ .01). Computed optimal device lengths were significantly shorter (median, 14 versus 16 mm, T ϭ 402, r ϭ Ϫ0.28, P Ͻ .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.

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Section: Figmentioning

confidence: 99%

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

Ospel¹,

Gascou

Costalat

et al. 2019

AJNR Am J Neuroradiol

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“…10,[25][26][27] Previous retrospective studies that evaluated the application of computational modeling to FD sizing have demonstrated the potential benefits of the technology for improving FD size selection. 10,25 To date, few, if any, studies have exclusively focused on both the utility and predictive fidelity of computational device modeling in a prospective case series. Yet, evaluations under typical clinical workflows are essential for understanding the contribution of the technology to clinical practice and its potential for adoption.…”

Section: Discussionmentioning

confidence: 99%

“…FDs can also elongate by .50% of the nominal length indicated by labeling. 10 Furthermore, measurements of vessel size taken from angiographic image data can be operator-dependent and are prone to measurement error. A recent study on intra-and interobserver variability when measuring cerebral aneurysm size in CT and MR angiography images showed a standard difference range of 12%-18% in size measurements.…”

mentioning

confidence: 99%

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

Chong

Bendok

Krishna

et al. 2019

AJNR Am J Neuroradiol

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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.

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“…When selecting the threshold value, both the treated vessel and aneurysm, were considered as the priority to achieve a high quality reconstruction of the local vascular anatomy (Larrabide et al, 2012b). Some cases needed additional post-processing to achieve a good quality representation of the anatomy, leading to a post-processing rate similar to previous studies (Narata et al, 2018). Before preforming the CFD simulation, each 3D model was then visually validated by expert interventional neuroradiologists (INR).…”

Section: Image Acquisition and 3d Modellingmentioning

confidence: 91%

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

Dazeo

Dottori

Boroni

et al. 2020

Journal of Biomechanics

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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 setup 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.

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

Abstract: 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.

Cited by 17 publications

References 24 publications

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

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

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

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

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