Personalizing flow-diverter intervention for cerebral aneurysms: from computational hemodynamics to biochemical modeling

Treatment for middle cerebral artery bifurcation aneurysms: in silico comparison of the novel Contour device and conventional flow-diverters

Endovascular treatment has become the standard therapy for cerebral aneurysms, while the effective treatment for middle cerebral artery (MCA) bifurcation aneurysms remains a challenge. Current flow-diverting techniques with endovascular coils cover the aneurysm orifice as well as adjacent vessel branches, which may lead to branch occlusion. Novel endovascular flow disruptors, such as the Contour device (Cerus Endovascular), are of great potential to eliminate the risk of branch occlusion. However, there is a lack of valid comparison between novel flow disruptors and conventional (intraluminal) flow-diverters. In this study, two in silico MCA bifurcation aneurysm models were treated by specific Contour devices and flow-diverters using fast-deployment algorithms. Computational fluid dynamic simulations were used to examine the performance and efficiency of deployed devices. Hemodynamic parameters, including aneurysm inflow and wall shear stress, were compared among each Contour device, conventional flow-diverter, and untreated condition. Our results show that the placement of devices can effectively reduce the risk of aneurysm rupture, while the deployment of a Contour device causes more flow reduction than using flow-diverters (e.g. Silk Vista Baby). Besides, the Contour device presents the flow diversion capability of targeting the aneurysm neck without occluding the daughter vessel. In summary, the in silico aneurysm models presented in this study can serve as a powerful pre-planning tool for testing new treatment techniques, optimising device deployment, and predicting the performance in patient-specific aneurysm cases. Contour device is proved to be an effective treatment of MCA bifurcation aneurysms with less daughter vessel occlusion.

Uncertainty quantification of a thrombosis model considering the clotting assay PFA-100®

Mathematical models of thrombosis are currently used to study clinical scenarios of pathological thrombus formation. As these models become more complex to predict thrombus formation dynamics high computational cost must be alleviated and inherent uncertainties must be assessed. Evaluating model uncertainties allows to increase the confidence in model predictions and identify avenues of improvement for both thrombosis modeling and anti-platelet therapies. In this work, an uncertainty quantification analysis of a multi-constituent thrombosis model is performed considering a common assay for platelet function (PFA-100®). The analysis is facilitated thanks to time-evolving polynomial chaos expansions used as a parametric surrogate for the full thrombosis model considering two quantities of interest; namely, thrombus volume and occlusion percentage. The surrogate is thoroughly validated and provides a straightforward access to a global sensitivity analysis via computation of Sobol' coefficients. Six out of 15 parameters linked to thrombus consitution, vWF activity, and platelet adhesion dynamics were found to be most influential in the simulation variability considering only individual effects; while parameter interactions are highlighted when considering the total Sobol' indices. The influential parameters are related to thrombus constitution, vWF activity, and platelet to platelet adhesion dynamics. The surrogate model allowed to predict realistic PFA-100® closure times of 300,000 virtual cases that followed the trends observed in clinical data. The current methodology could be used including common anti-platelet therapies to identify scenarios that preserve the hematological balance.

Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study

Numerical modeling is an effective tool for preoperative planning. The present work is devoted to a retrospective analysis of neurosurgical treatments for the occlusion of cerebral aneurysms using flow-diverters and hemodynamic factors affecting stent endothelization. Several different geometric approaches have been considered for virtual flow-diverters deployment. A comparative analysis of hemodynamic parameters as a result of computational modeling has been carried out basing on the four clinical cases: one successful treatment, one with no occlusion and two with in stent stenosis. For the first time, a quantitative assessment of both: the limiting magnitude of shear stresses that are necessary for the occurrence of in stent stenosis (MaxWSS > 1.23) and for conditions in which endothelialization is insufficiently active and occlusion of the cervical part of the aneurysm does not occur (MaxWSS < 1.68)—has been statistacally proven (p < 0.01).

Effect of Pulsatility on the Transport of Thrombin in an Idealized Cerebral Aneurysm Geometry

Computational models of cerebral aneurysm thrombosis are designed for use in research and clinical applications. A steady flow assumption is applied in many of these models. To explore the accuracy of this assumption a pulsatile-flow thrombin-transport computational fluid dynamics (CFD) model, which uses a symmetrical idealized aneurysm geometry, was developed. First, a steady-flow computational model was developed and validated using data from an in vitro experiment, based on particle image velocimetry (PIV). The experimental data revealed an asymmetric flow pattern in the aneurysm. The validated computational model was subsequently altered to incorporate pulsatility, by applying a data-derived flow function at the inlet boundary. For both the steady and pulsatile computational models, a scalar function simulating thrombin generation was applied at the aneurysm wall. To determine the influence of pulsatility on thrombin transport, the outputs of the steady model were compared to the outputs of the pulsatile model. The comparison revealed that in the pulsatile case, an average of 10.2% less thrombin accumulates within the aneurysm than the steady case for any given time, due to periodic losses of a significant amount of thrombin-concentrated blood from the aneurysm into the parent vessel’s bloodstream. These findings demonstrate that pulsatility may change clotting outcomes in cerebral aneurysms.

Virtual Flow-T Stenting for Two Patient-Specific Bifurcation Aneurysms

The effective treatment of wide necked cerebral aneurysms located at vessel bifurcations (WNBAs) remains a significant challenge. Such aneurysm geometries have typically been approached with Y or T stenting configurations of stents and/or flow diverters, often with the addition of endovascular coils. In this study, two WNBAs were virtually treated by a novel T-stenting technique (Flow-T) with a number of braided stents and flow-diverter devices. Multiple possible device deployment configurations with varying device compression levels were tested, using fast-deployment algorithms, before a steady state computational hemodynamic simulation was conducted to examine the efficacy and performance of each scenario. The virtual fast deployment algorithm based on a linear and torsional spring analogy is used to accurately deploy nine stents in two WNBAs geometries. The devices expand from the distal to proximal side of the devices with respect to aneurysm sac. In the WNBAs modelled, all configurations of Flow-T device placement were shown to reduce factors linked with increased aneurysm rupture risk including aneurysm inflow jets and high aneurysm velocity, along with areas of flow impingement and elevated wall shear stress (WSS). The relative position of the flow-diverting device in the secondary daughter vessel in the Flow-T approach was found to have a negligible effect on overall effectiveness of the procedure in the two geometries considered. The level of interventionalist-applied compression in the braised stent that forms the other arm of the Flow-T approach was shown to impact the aneurysm inflow reduction and aneurysm flow pattern more substantially. In the Flow-T approach the relative position of the secondary daughter vessel flow-diverter device (the SVB) was found to have a negligible effect on inflow reduction, aneurysm flow pattern, or WSS distribution in both aneurysm geometries. This suggests that the device placement in this vessel may be of secondary importance. By contrast, substantially more variation in inflow reduction and aneurysm flow pattern was seen due to variations in braided stent (LVIS EVO or Baby Leo) compression at the aneurysm neck. As such we conclude that the success of a Flow-T procedure is primarily dictated by the level of compression that the interventionalist applies to the braided stent. Similar computationally predicted outcomes for both aneurysm geometries studied suggest that adjunct coiling approach taken in the clinical intervention of the second geometry may have been unnecessary for successful aneurysm isolation. Finally, the computational modelling framework proposed offers an effective planning platform for complex endovascular techniques, such as Flow-T, where the scope of device choice and combination is large and selecting the best strategy and device combination from several candidates is vital.

Thrombin-Fibrinogen In Vitro Flow Model of Thrombus Growth in Cerebral Aneurysms

Cerebral aneurysms are balloon-like structures that develop on weakened areas of cerebral artery walls, with a significant risk of rupture. Thrombi formation is closely associated with cerebral aneurysms and has been observed both before and after intervention, leading to a wide variability of outcomes in patients with the condition. The attempt to manage the outcomes has led to the development of various computational models of cerebral aneurysm thrombosis. In the current study, we developed a simplified thrombin–fibrinogen flow system, based on commercially available purified human-derived plasma proteins, which enables thrombus growth and tracking in an idealized cerebral aneurysm geometry. A three-dimensional printed geometry of an idealized cerebral aneurysm and parent vessel configuration was developed. An unexpected outcome was that this phantom-based flow model allowed us to track clot growth over a period of time, by using optical imaging to record the progression of the growing clot into the flow field. Image processing techniques were subsequently used to extract important quantitative metrics from the imaging dataset, such as end point intracranial thrombus volume. The model clearly demonstrates that clot formation, in cerebral aneurysms, is a complex interplay between mechanics and biochemistry. This system is beneficial for verifying computational models of cerebral aneurysm thrombosis, particularly those focusing on initial angiographic occlusion outcomes, and will also assist manufacturers in optimizing interventional device designs.

Cerebral arterial architectonics and CFD simulation in mice with type 1 diabetes mellitus of different duration

Type 1 diabetes is a chronic autoimmune disease that affects tens of millions of people. Diabetes mellitus is one of the strongest factors in the development of cerebrovascular diseases. In this study we used NOD.CB17 Prkdcscid mice and the pharmacological model of type 1 diabetes mellitus of different duration to study changes in the cerebral vasculature. We used two combined approaches using magnetic resonance angiography both steady and transient CFD blood flow modeling. We identified the influence of type 1 diabetes on the architectonics and hemodynamics of the large blood vessels of the brain as the disease progresses. For the first time, we detected a statistically significant change in angioarchitectonics (the angles between the vessels of the circle of Willis, cross-sections areas of vessels) and hemodynamic (maximum blood flow rate, hydraulic resistance) in animals with diabetes duration of 2 months, that is manifested by the development of asymmetry of cerebral blood flow. The result shows the negative effect of diabetes on cerebral circulation as well as the practicability of CFD modeling. This may be of extensive interest, in pharmacological and preclinical studies.

Failure of Flow Diverter Therapy: Predictors and Management Strategies

Flow diversion is a safe and effective treatment for many types of brain aneurysms. Even so, there remain some aneurysms that persist despite initial treatment. In studies with the longest follow-up (5 yr), at least 5% of aneurysms persist with this treatment modality. As the cumulative experience and clinical indications for flow diversion continue to expand, the anatomic and functional characteristics that are associated with aneurysm persistence are increasingly described. Identification of these factors preoperatively can help to guide initial treatment decisions, enhance monitoring protocols in the follow-up period, and establish best practices for re-treatment when necessary. Herein, we review published clinical series and provide examples to highlight variables implicated in aneurysm persistence after treatment with flow diversion.

Implementation of computer simulation to assess flow diversion treatment outcomes: systematic review and meta-analysis

Introduction

Despite a decade of research into virtual stent deployment and the post-stenting aneurysmal hemodynamics, the hemodynamic factors which correlate with successful treatment remain inconclusive. We aimed to examine the differences in various post-treatment hemodynamic parameters between successfully and unsuccessfully treated cases, and to quantify the additional flow diversion achievable through stent compaction or insertion of a second stent.

Methods

A systematic review and meta-analysis were performed on eligible studies published from 2000 to 2019. We first classified cases according to treatment success (aneurysm occlusion) and then calculated the pooled standardized mean differences (SMD) of each available parameter to examine their association with clinical outcomes. Any additional flow diversion arising from the two common strategies for improving the stent wire density was quantified by pooling the results of such studies.

Results

We found that differences in the aneurysmal inflow rate (SMD −6.05, 95% CI −10.87 to −1.23, p=0.01) and energy loss (SMD −5.28, 95% CI −7.09 to −3.46, p<0.001) between the successfully and unsuccessfully treated groups were indicative of statistical significance, in contrast to wall shear stress (p=0.37), intra-aneurysmal average velocity (p=0.09), vortex core-line length (p=0.46), and shear rate (p=0.09). Compacting a single stent could achieve additional flow diversion comparable to that by dual-stent implantation.

Conclusions

Inflow rate and energy loss have shown promise as identifiers to discriminate between successful and unsuccessful treatment, pending future research into their diagnostic performance to establish optimal cut-off values.

The impact of arterial flow complexity on flow diverter outcomes in aneurysms

The flow diverter is becoming a standard device for treating cerebral aneurysms. The aim of this in vitro study was to evaluate the impact of flow complexity on the effectiveness of flow diverter stents in a cerebral aneurysm model. The flow pattern of a carotid artery was decomposed into harmonics to generate four flow patterns with different pulsatility indexes ranging from 0.72 to 1.44. The effect of flow diverters on the aneurysm was investigated by injecting red dye or erythrocytes as markers. The recorded images were postprocessed to evaluate the maximum filling of the aneurysm cavity and the washout time. There were significant differences in the cut-off flows between the markers, linked to the flow complexity. Increasing the pulsatility index altered the performance of the flow diverter. The red dye was more sensitive to changes in flow than the red blood cell markers. The flow cut-off depended on the diverter design and the diverter deployment step was crucial for reproducibility of the results. These results strongly suggest that flow complexity should be considered when selecting a flow diverter.

Evaluation of a Desktop 3D Printed Rigid Refractive-Indexed-Matched Flow Phantom for PIV Measurements on Cerebral Aneurysms

PURPOSE

Fabrication of a suitable flow model or phantom is critical to the study of biomedical fluid dynamics using optical flow visualization and measurement methods. The main difficulties arise from the optical properties of the model material, accuracy of the geometry and ease of fabrication.

METHODS

Conventionally an investment casting method has been used, but recently advancements in additive manufacturing techniques such as 3D printing have allowed the flow model to be printed directly with minimal post-processing steps. This study presents results of an investigation into the feasibility of fabrication of such models suitable for particle image velocimetry (PIV) using a common 3D printing Stereolithography process and photopolymer resin.

RESULTS

An idealised geometry of a cerebral aneurysm was printed to demonstrate its applicability for PIV experimentation. The material was shown to have a refractive index of 1.51, which can be refractive matched with a mixture of de-ionised water with ammonium thiocyanate (NH₄SCN). The images were of a quality that after applying common PIV pre-processing techniques and a PIV cross-correlation algorithm, the results produced were consistent within the aneurysm when compared to previous studies.

CONCLUSIONS

This study presents an alternative low-cost option for 3D printing of a flow phantom suitable for flow visualization simulations. The use of 3D printed flow phantoms reduces the complexity, time and effort required compared to conventional investment casting methods by removing the necessity of a multi-part process required with investment casting techniques.

Respiratory healthcare by design: Computational approaches bringing respiratory precision and personalised medicine closer to bedside

Precision medicine represents a potentially powerful means to alleviate the growing burden of chronic respiratory diseases. To realise its potential, however, we need a systems level understanding of how biological events (signalling pathways, cell-cell interactions, tissue mechanics) integrate across multiple spatial and temporal scales to give rise to pathology. This can be achieved most practically in silico: a paradigm that offers tight control over model parameters and rapid means of testing and generating mechanistic hypotheses. Patient-specific computational models that can enable identification of pathological mechanisms unique to patients' (omics, physiological, and anatomical) profiles and, therefore, personalised drug targets represent a major milestone in precision medicine. Current patient-based models in literature, especially medical devices, cardiac modelling, and respiratory medicine, rely mostly on (partial/ordinary) differential equations and have reached relatively advanced level of maturity. In respiratory medicine, patient-specific simulations mainly include subject scan-based lung mechanics models that can predict pulmonary function, but they treat the (sub)cellular processes as "black-boxes". A recent advance in simulating human airways at a cellular level to make clinical predictions raises the possibility of linking omics and cell level data/models with lung mechanics to understand respiratory pathology at a systems level. This is significant as this approach can be extended to understanding pathologies in other organs as well. Here, I will discuss ways in which computational models have already made contributions to personalised healthcare and how the paradigm can expedite clinical uptake of precision medicine strategies. I will mainly focus on an agent-based, asthmatic virtual patient that predicted the impact of multiple drug pharmacodynamics at the patient level, its potential to develop efficacious precision medicine strategies in respiratory medicine, and the regulatory and ethical challenges accompanying the mainstream application of such models.

COMPUTATIONAL INVESTIGATION OF THROMBIN CONCENTRATION IN CEREBRAL ANEURYSMS TREATED WITH FLOW-DIVERTING STENTS

Flow-diverting stent is an ongoing embolization device to treat cerebral aneurysms, and it diverts the flow direction to reduce the flow velocity inside the aneurysmal sacs and promote the thrombus formation. However, its effect for aneurysm embolization is controversial. A hemodynamic-biomedical coupling model was constructed to describe the generation and transport of thrombin in arteries, and the model was applied to investigate the variation of thrombin concentration, which plays a key role in thrombus formation, in two patient-specific cerebral aneurysm models when they are treated with Pipeline flow diverting stents. It is observed from computational fluid dynamics simulations that thrombin concentration in the aneurysmal sac without collateral artery increases significantly after Pipeline implantation, however, it has hardly any variation in the aneurysmal sac without collateral artery or in the giant aneurysmal sac after Pipeline implantation. Therefore, we believe that single Pipeline is very effective to embolize a small aneurysm without collateral artery, but cannot embolize a giant aneurysm or a small aneurysm with a collateral artery on its sac effectively.

Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review

Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities.

Predicting false lumen thrombosis in patient-specific models of aortic dissection

Aortic dissection causes splitting of the aortic wall layers, allowing blood to enter a ‘false lumen’ (FL). For type B dissection, a significant predictor of patient outcomes is patency or thrombosis of the FL. Yet, no methods are currently available to assess the chances of FL thrombosis. In this study, we present a new computational model that is capable of predicting thrombus formation, growth and its effects on blood flow under physiological conditions. Predictions of thrombus formation and growth are based on fluid shear rate, residence time and platelet distribution, which are evaluated through convection–diffusion–reaction transport equations. The model is applied to a patient-specific type B dissection for which multiple follow-up scans are available. The predicted thrombus formation and growth patterns are in good qualitative agreement with clinical data, demonstrating the potential applicability of the model in predicting FL thrombosis for individual patients. Our results show that the extent and location of thrombosis are strongly influenced by aortic dissection geometry that may change over time. The high computational efficiency of our model makes it feasible for clinical applications. By predicting which aortic dissection patient is more likely to develop FL thrombosis, the model has great potential to be used as part of a clinical decision-making tool to assess the need for early endovascular intervention for individual dissection patients.

Haemodynamic effects of stent diameter and compaction ratio on flow-diversion treatment of intracranial aneurysms: A numerical study of a successful and an unsuccessful case

BACKGROUND

Compacting a flow-diverting (FD) stent is an emerging technique to create a denser configuration of wires across the aneurysm ostium. However, quantitative analyses of post-stenting haemodynamics affected by the compaction level of different stent sizes remain inconclusive.

OBJECTIVE

To compare the aneurysmal haemodynamic alterations after virtual FD treatments with different device diameters at different compaction ratios.

METHODS

We virtually implanted three sizes of FD stent, with each size deployed at four compaction ratios, into two patient aneurysms previously treated with the Silk+FD-one successful case and the other unsuccessful. Wire configurations of the FD in the 24 treatment scenarios were examined, and aneurysmal haemodynamic alterations were resolved by computational fluid dynamics (CFD) simulations. We investigated the aneurysmal flow patterns, aneurysmal average velocity (AAV), mass flowrate (MF), and energy loss (EL) in each scenario.

RESULTS

Compactions of the stent in the successful case resulted in a greater metal coverage rate than that achieved in the unsuccessful one. A 25% increment in compaction ratio further decreased the AAV (12%), MF (11%), and EL (9%) in both cases (average values). The averaged maximum differences attributable to device size were 10% (AAV), 8% (MF), and 9% (EL).

CONCLUSIONS

Both stent size and compaction level could markedly affect the FD treatment outcomes. It is therefore important to individualise the treatment plan by selecting the optimal stent size and deployment procedure. CFD simulation can be used to investigate the treatment outcomes, thereby assisting doctors in choosing a favourable treatment plan.

Computer-Assisted Adjuncts for Aneurysmal Morphologic Assessment: Toward More Precise and Accurate Approaches

Neurosurgeons currently base most of their treatment decisions for intracranial aneurysms (IAs) on morphological measurements made manually from 2D angiographic images. These measurements tend to be inaccurate because 2D measurements cannot capture the complex geometry of IAs and because manual measurements are variable depending on the clinician's experience and opinion. Incorrect morphological measurements may lead to inappropriate treatment strategies. In order to improve the accuracy and consistency of morphological analysis of IAs, we have developed an image-based computational tool, AView. In this study, we quantified the accuracy of computer-assisted adjuncts of AView for aneurysmal morphologic assessment by performing measurement on spheres of known size and anatomical IA models. AView has an average morphological error of 0.56% in size and 2.1% in volume measurement. We also investigate the clinical utility of this tool on a retrospective clinical dataset and compare size and neck diameter measurement between 2D manual and 3D computer-assisted measurement. The average error was 22% and 30% in the manual measurement of size and aneurysm neck diameter, respectively. Inaccuracies due to manual measurements could therefore lead to wrong treatment decisions in 44% and inappropriate treatment strategies in 33% of the IAs. Furthermore, computer-assisted analysis of IAs improves the consistency in measurement among clinicians by 62% in size and 82% in neck diameter measurement. We conclude that AView dramatically improves accuracy for morphological analysis. These results illustrate the necessity of a computer-assisted approach for the morphological analysis of IAs.

Hemodynamics of Flow Diverters

Cerebral aneurysms are pathological focal evaginations of the arterial wall at and around the junctions of the circle of Willis. Their tenuous walls predispose aneurysms to leak or rupture leading to hemorrhagic strokes with high morbidity and mortality rates. The endovascular treatment of cerebral aneurysms currently includes the implantation of fine-mesh stents, called flow diverters, within the parent artery bearing the aneurysm. By mitigating flow velocities within the aneurysmal sac, the devices preferentially induce thrombus formation in the aneurysm within hours to days. In response to the foreign implant, an endothelialized arterial layer covers the luminal surface of the device over a period of days to months. Organization of the intraneurysmal thrombus leads to resorption and shrinkage of the aneurysm wall and contents, eventually leading to beneficial remodeling of the pathological site to a near-physiological state. The devices' primary function of reducing flow activity within aneurysms is corollary to their mesh structure. Complete specification of the device mesh structure, or alternately device permeability, necessarily involves the quantification of two variables commonly used to characterize porous media—mesh porosity and mesh pore density. We evaluated the flow alteration induced by five commercial neurovascular devices of varying porosity and pore density (stents: Neuroform, Enterprise, and LVIS; flow diverters: Pipeline and FRED) in an idealized sidewall aneurysm model. As can be expected in such a model, all devices substantially reduced intraneurysmal kinetic energy as compared to the nonstented case with the coarse-mesh stents inducing a 65–80% reduction whereas the fine-mesh flow diverters induced a near-complete flow stagnation (∼98% reduction). We also note a trend toward greater device efficacy (lower intraneurysmal flow) with decreasing device porosity and increasing device pore density. Several such flow studies have been and are being conducted in idealized as well as patient-derived geometries with the overarching goals of improving device design, facilitating treatment planning (what is the optimal device for a specific aneurysm), and predicting treatment outcome (will a specific aneurysm treated with a specific device successfully occlude over the long term). While the results are generally encouraging, there is poor standardization of study variables between different research groups, and any consensus will only be reached after standardized studies are conducted on collectively large datasets. Biochemical variables may have to be incorporated into these studies to maximize predictive values.

Virtual flow-diverter treatment planning: The effect of device placement on bifurcation aneurysm haemodynamics

Bifurcation aneurysms account for a large fraction of cerebral aneurysms and often present morphologies that render traditional endovascular treatments, such as coiling, challenging and problematic. Flow-diverter stents offer a potentially elegant treatment option for such aneurysms, but clinical use of these devices remains controversial. Specifically, the deployment of a flow-diverter device in a bifurcation entails jailing one or more potentially vital vessels with a low-porosity mesh designed to restrict the flow. When multiple device placement configurations exist, the most appropriate clinical decision becomes increasingly opaque. In this study, three bifurcation aneurysm geometries were virtually treated by flow-diverter device. Each aneurysm was selected to offer two possible device deployment positions. Flow-diverters similar to commercially available designs were deployed with a fast-deployment algorithm before transient and steady state computational fluid dynamics simulations were performed. Reductions in aneurysm inflow, mean wall shear stress and maximum wall shear stress, all factors often linked with aneurysm treatment outcome, were compared for different device configurations in each aneurysm. In each of the three aneurysms modelled, a particular preferential device placement was shown to offer superior performance with the greatest reduction in the flow metrics considered. In all the three aneurysm geometries, substantial variations in inflow reduction (up to 25.3%), mean wall shear stress reduction (up to 14.6%) and maximum wall shear stress reduction (up to 12.1%) were seen, which were all attributed to device placement alone. Optimal device placement was found to be non-trivial and highly aneurysm specific; in only one-third of the simulated geometries, the best overall performance was achieved by deploying a device in the daughter vessel with the highest flow rate. Good correspondence was seen between transient results and steady state computations that offered a significant reduction in simulation run time. If accurate steady state computations are combined with the fast-deployment algorithm used, the modest run time and corresponding hardware make a virtual treatment pipeline in the clinical setting a meaningful possibility.

Does Arterial Flow Rate Affect the Assessment of Flow-Diverter Stent Performance?

BACKGROUND AND PURPOSE

Our aim was to assess the performance of flow-diverter stents. The pre- and end-of-treatment angiographies are commonly compared. However, the arterial flow rate may change between acquisitions; therefore, a better understanding of its influence on the local intra-aneurysmal hemodynamics before and after flow-diverter stent use is required.

MATERIALS AND METHODS

Twenty-five image-based aneurysm models extracted from 3D rotational angiograms were conditioned for computational fluid dynamics simulations. Pulsatile simulations were performed at different arterial flow rates, covering a wide possible range of physiologic flows among 1-5 mL/s. The effect of flow-diverter stents on intra-aneurysmal hemodynamics was numerically simulated with a porous medium model. Spatiotemporal-averaged intra-aneurysmal flow velocity and flow rate were calculated for each case to quantify the hemodynamics after treatment. The short-term flow-diverter stent performance was characterized by the relative velocity reduction inside the aneurysm.

RESULTS

Spatiotemporal-averaged intra-aneurysmal flow velocity before and after flow-diverter stent use is linearly proportional to the mean arterial flow rate (minimum R² > 0.983 of the linear regression models for untreated and stented models). Relative velocity reduction asymptotically decreases with increasing mean arterial flow rate. When the most probable range of arterial flow rate was considered (3-5 mL/s), instead of the wide possible flow range, the mean SD of relative velocity reduction was reduced from 3.6% to 0.48%.

CONCLUSIONS

Both intra-aneurysmal aneurysm velocity and flow-diverter stent performance depend on the arterial flow rate. The performance could be considered independent of the arterial flow rates within the most probable range of physiologic flows.

A computational model based on fibrin accumulation for the prediction of stasis thrombosis following flow-diverting treatment in cerebral aneurysms

Flow diverters, the specially designed low porosity stents, have been used to redirect blood flow from entering aneurysm, which induces flow stasis in aneurysm and promote thrombosis for repairing aneurysm. However, it is not clear how thrombus develops following flow-diversion treatment. Our objective was to develop a computation model for the prediction of stasis-induced thrombosis following flow-diversion treatment in cerebral aneurysms. We proposed a hypothesis to initiate coagulation following flow-diversion treatment. An experimental model was used by ligating rat's right common carotid artery (RCCA) to create flow-stasis environment. Thrombus formed in RCCA as a result of flow stasis. The fibrin distributions in different sections along the axial length of RCCA were measured. The fibrin distribution predicted by our computational model displayed a trend of increase from the proximal neck to the distal tip, consistent with the experimental results on rats. The model was applied on a saccular aneurysm treated with flow diverter to investigate thrombus development following flow diversion. Thrombus was predicted to form inside the sac, and the aneurysm was occluded with only a small remnant neck remained. Our model can serve as a tool to evaluate flow-diversion treatment outcome and optimize the design of flow diverters.

Computational fluid dynamics modelling in cardiovascular medicine

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.

Towards Predicting Patient-Specific Flow-Diverter Treatment Outcomes for Bifurcation Aneurysms: From Implantation Rehearsal to Virtual Angiograms

Despite accounting for the majority of all cerebral aneurysm cases, bifurcation aneurysms present many challenges to standard endovascular treatment techniques. This study examines the treatment of bifurcation aneurysms endovascularly with flow-diverting stents and presents an integrative computational modeling suite allowing for rehearsing all aspects of the treatment. Six bifurcation aneurysms are virtually treated with 70% porosity flow-diverters. Substantial reduction (>50%) in aneurysm inflow due to device deployment is predicted in addition to reductions in peak and average aneurysm wall shear stress to values considered physiologically normal. The subsequent impact of flow-diverter deployment on daughter vessels that are jailed by the device is investigated further, with a number of simulations conducted with increased outlet pressure conditions at jailed vessels. Increased outlet pressures at jailed daughter vessels are found to have little effect on device-induced aneurysm inflow reduction, but large variation (13–86%) is seen in the resulting reduction in daughter vessel flow rate. Finally, we propose a potentially powerful approach for validation of such models, by introducing an angiographic contrast model, with contrast transport modeled both before and after virtual treatment. Virtual angiograms and contrast residence curves are created, which offer unique clinical relevance and the potential for future in vivo verification of simulated results.

Computation of the change in length of a braided device when deployed in realistic vessel models

PURPOSE

An important issue in the deployment of braided stents, such as flow diverters, is the change in length, also known as foreshortening, underwent by the device when is released from the catheter into a blood vessel. The position of the distal end is controlled by the interventionist, but knowing a priori the position of the proximal end of the device is not trivial. In this work, we assess and validate a novel computer method to predict the length that a braided stent will adopt inside a silicon model of an anatomically accurate vessel.

METHODS

Three-dimensional rotational angiography images of aneurysmatic patients were used to generate surface models of the vessels (3D meshes) and then create accurate silicon models from them. A braided stent was deployed into each silicon model to measure its length. The same stents deployed on the silicon models were virtually deployed on the 3D meshes using the method being evaluated.

RESULTS

The method was applied to five stent placements on three different silicon models. The length adopted by the real braided device in the silicon models varies between 15 and 30% from the stent length specified by the manufacturer. The final length predicted by the method was within the estimated error of the measured real stent length.

CONCLUSIONS

The method provides, in a few seconds, the length of a braided stent deployed inside a vessel, showing an accurate estimation of the final length for the cases studied. This technique could provide useful information for planning the intervention and improve endovascular treatment of intracranial aneurysms in the future.