Multiscale Computational Fluid Dynamics Modeling for Personalized Liver Cancer Radioembolization Dosimetry

A Hybrid Particle-Flow CFD Modeling Approach in Truncated Hepatic Arterial Trees for Liver Radioembolization: A Patient-specific Case Study

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer. At its intermediate, unresectable stage, HCC is typically treated by local injection of embolizing microspheres in the hepatic arteries to selectively damage tumor tissue. Interestingly, computational fluid dynamics (CFD) has been applied increasingly to elucidate the impact of clinically variable parameters, such as injection location, on the downstream particle distribution. This study aims to reduce the computational cost of such CFD approaches by introducing a novel truncation algorithm to simplify hepatic arterial trees, and a hybrid particle-flow modeling approach which only models particles in the first few bifurcations. A patient-specific hepatic arterial geometry was pruned at three different levels, resulting in three trees: Geometry 1 (48 outlets), Geometry 2 (38 outlets), and Geometry 3 (17 outlets). In each geometry, 1 planar injection and 3 catheter injections (each with different tip locations) were performed. For the truncated geometries, it was assumed that, downstream of the truncated outlets, particles distributed themselves proportional to the blood flow. This allowed to compare the particle distribution in all 48 "outlets" for each geometry. For the planar injections, the median difference in outlet-specific particle distribution between Geometry 1 and 3 was 0.21%; while the median difference between outlet-specific flow and particle distribution in Geometry 1 was 0.40%. Comparing catheter injections, the maximum median difference in particle distribution between Geometry 1 and 3 was 0.24%, while the maximum median difference between particle and flow distribution was 0.62%. The results suggest that the hepatic arterial tree might be reliably truncated to estimate the particle distribution in the full-complexity tree. In the resulting hybrid particle-flow model, explicit particle modeling was only deemed necessary in the first few bifurcations of the arterial tree. Interestingly, using flow distribution as a surrogate for particle distribution in the entire tree was considerably less accurate than using the hybrid model, although the difference was much higher for catheter injections than for planar injections. Future work should focus on replicating and experimentally validating these results in more patient-specific geometries.

Deep Learning for Computational Hemodynamics: A Brief Review of Recent Advances

Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better understanding various medical conditions, designing more effective drug delivery systems, and developing novel diagnostic methods and treatments. However, despite significant advances in computational technology and resources, the expensive computational cost of these simulations still hinders their transformation from a research interest to a clinical tool. This bottleneck is even more severe for image-based, patient-specific CFD simulations with realistic boundary conditions and complex computational domains, which make such simulations excessively expensive. To address this issue, deep learning approaches have been recently explored to accelerate computational hemodynamics simulations. In this study, we review recent efforts to integrate deep learning with CFD and discuss the applications of this approach in solving hemodynamics problems, such as blood flow behavior in aorta and cerebral arteries. We also discuss potential future directions in the field. In this review, we suggest that incorporating physiologic understandings and underlying fluid mechanics laws in deep learning models will soon lead to a paradigm shift in the development novel non-invasive computational medical decisions.

The Impact of Injection Distance to Bifurcations on Yttrium-90 Distribution in Liver Cancer Radioembolization

PURPOSE

To model the effect of the injection location on the distribution of yttrium-90 (⁹⁰Y) microspheres in the liver during radioembolization using computational simulation and to determine the potential effects of radial movements of the catheter tip.

MATERIALS AND METHODS

Numerical studies were conducted using images from a representative patient with hepatocellular carcinoma. The right hepatic artery (RHA) was segmented from contrast-enhanced cone-beam computed tomography scans. The blood flow was investigated in the trunk of the RHA using numerical simulations for 6 injection position scenarios at 2 sites located at a distance of approximately 5 and 20 mm upstream of the first bifurcation (RHA diameters of approximately 4.6 mm). The ⁹⁰Y delivery to downstream vessels was calculated from the simulated hepatic artery hemodynamics.

RESULTS

Varying the injection location along the RHA and across the vessel cross-section resulted in different simulated microsphere distributions in the downstream vascular bed. When the catheter tip was 5 mm upstream of the bifurcation, ⁹⁰Y distribution in the downstream branches varied by as much as 53% with a 1.5-mm radial movement of the tip. However, the catheter radial movement had a weaker effect on the microsphere distribution when the injection plane was farther from the first bifurcation (20 mm), with a maximum delivery variation of 9% to a downstream branch.

CONCLUSIONS

An injection location far from bifurcations is recommended to minimize the effect of radial movements of the catheter tip on the microsphere distribution.

Spectral-Clustering of Lagrangian Trajectory Graphs: Application to Abdominal Aortic Aneurysms

PURPOSE

Identification of coherent structures in cardiovascular flows is crucial to describe the transport and mixing of blood. Coherent structures can highlight locations where minimal blood mixing takes place, thus, potential thrombus formation can be expected thither. Graph-based approaches have recently been introduced in order to describe fluid transport and mixing between multiple Lagrangian trajectories, where each trajectory serves as a node that can be connected to another trajectory based on their relative distance during the course of time.

METHODS

In this study, we compute the Lagrangian trajectories from in vitro planar instantaneous velocity fields in two models of abdominal aortic aneurysms, (AAA) namely single bulge and bi-lobed. Then, we construct unweighted and undirected graphs based on the pairwise distance of Lagrangian trajectories. We report local measures of the graph namely the degree and the clustering coefficient. We also perform spectral clustering of the graph Laplacian to extract the flow coherent sets.

RESULTS

Local graph measures reveal fluid regions of high mixing such as vortex boundaries. Through spectral clustering, the fluid is partitioned into a reduced number of coherent sets where within each set, inner mixing of fluid is maximized while the fluid mixing between different coherent sets is minimized. The approach reveals multiple coherent sets adjacent to the AAA bulge that have sustained this adjacency to the wall through their coherent motion during one cardiac cycle.

CONCLUSION

Identifying coherent sets enables tracking their transport during the cardiac cycle and identify their role in the flow dynamics. Moreover, the size and the transport of the long residing coherent sets inside the AAA bulges can be deduced which may aid in predicting thrombus formation at such location.

Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review

MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.

Computational Fluid Dynamics Modeling of Liver Radioembolization: A Review

Yttrium-90 radioembolization (RE) is a widely used transcatheter intraarterial therapy for patients with unresectable liver cancer. In the last decade, computer simulations of hepatic artery hemodynamics during RE have been performed with the aim of better understanding and improving the therapy. In this review, we introduce the concept of computational fluid dynamics (CFD) modeling with a clinical perspective and we review the CFD models used to study RE from the fluid mechanics point of view. Finally, we show what CFD simulations have taught us about the hemodynamics during RE, the current capabilities of CFD simulations of RE, and we suggest some future perspectives.

Realistic boundary conditions in SimVascular through inlet catheter modeling

OBJECTIVE

This study aims at developing a pipeline that provides the capability to include the catheter effect in the computational fluid dynamics (CFD) simulations of the cardiovascular system and other human vascular flows carried out with the open-source software SimVascular. This tool is particularly useful for CFD simulation of interventional radiology procedures such as tumor embolization where estimation of a therapeutic agent distribution is of interest.

RESULTS

A pipeline is developed that generates boundary condition files which can be used in SimVascular CFD simulations. The boundary condition files are modified such that they simulate the effect of catheter presence on the flow field downstream of the inlet. Using this pipeline, the catheter flow, velocity profile, radius, wall thickness, and deviation from the vessel center can be defined. Since our method relies on the manipulation of the boundary condition that is imposed on the inlet, it is sensitive to the mesh density. The finer the mesh is (especially around the catheter wall), the more accurate the velocity estimations are. In this study, we also utilized this pipeline to qualitatively investigate the effect of catheter presence on the flow field in a truncated right hepatic arterial tree of a liver cancer patient.

Flow topology and targeted drug delivery in cardiovascular disease

Targeted drug delivery is a promising technique to direct the drug to the specific diseased region. Nanoparticles have provided an attractive approach for this purpose. In practice, the major focus of targeted delivery has been on targeting cell receptors. However, the complex fluid mechanics in diseased biomedical flows questions if a sufficient number of nanoparticles can reach the desired region. In this paper, we propose that hidden topological structures in cardiovascular flows identified with Lagrangian coherent structures (LCS) control drug transport and provide valuable information for optimizing targeted drug delivery efficiency. We couple image-based computational fluid dynamics (CFD) with continuum transport models to study nanoparticle transport in coronary artery disease. We simulate nanoparticle transport as well as the recently proposed shear targeted drug delivery system that couples micro-carriers with nanoparticle drugs. The role of the LCS formed near the stenosed artery in controlling drug transport is discussed. Our results motivate the design of smart micro-needles guided by flow topology, which could achieve optimal drug delivery efficiency.

Estimation of Yttrium-90 Distribution in Liver Radioembolization using Computational Fluid Dynamics and Deep Neural Networks

Yttrium-90 (⁹⁰Y) radioembolization is a liver cancer therapy based on ⁹⁰Y microspheres injected into the hepatic artery. Current dosimetry methods used to estimate the absorbed dose in order to prescribe the ⁹⁰Y activity to inject are not accurate, which can affect the treatment effectiveness. A new dosimetry based on the hemodynamics simulation of the hepatic arterial tree, CFDose, aimed at overcoming some of the limitations of the current methods. However, due to the expensive computational cost of computational fluid dynamics (CFD) simulations, this method needs to be accelerated before it can be used in real-time during treatment planning. In this paper, we introduce a convolutional neural network model trained with the CFD results of a patient with hepatocellular carcinoma to predict the ⁹⁰Y distribution under different downstream vasculature resistance conditions. The model performance was evaluated using two metrics, the mean squared error and prediction accuracy. The prediction accuracy showed that the average difference between the actual and predicted data was less than 1%. The proposed model could estimate the ⁹⁰Y distribution significantly faster than a CFD simulation.

Computational Modeling of the Liver Arterial Blood Flow for Microsphere Therapy: Effect of Boundary Conditions

Transarterial embolization is a minimally invasive treatment for advanced liver cancer using microspheres loaded with a chemotherapeutic drug or radioactive yttrium-90 (90Y) that are injected into the hepatic arterial tree through a catheter. For personalized treatment, the microsphere distribution in the liver should be optimized through the injection volume and location. Computational fluid dynamics (CFD) simulations of the blood flow in the hepatic artery can help estimate this distribution if carefully parameterized. An important aspect is the choice of the boundary conditions imposed at the inlet and outlets of the computational domain. In this study, the effect of boundary conditions on the hepatic arterial tree hemodynamics was investigated. The outlet boundary conditions were modeled with three-element Windkessel circuits, representative of the downstream vasculature resistance. Results demonstrated that the downstream vasculature resistance affected the hepatic artery hemodynamics such as the velocity field, the pressure field and the blood flow streamline trajectories. Moreover, the number of microspheres received by the tumor significantly changed (more than 10% of the total injected microspheres) with downstream resistance variations. These findings suggest that patient-specific boundary conditions should be used in order to achieve a more accurate drug distribution estimation with CFD in transarterial embolization treatment planning.