An aneurysm-specific preconditioning technique for the acceleration of Newton-Krylov method with application in the simulation of blood flows.

In this paper, we develop an algorithm to simulate blood flows in aneurysmal arteries and focus on the construction of robust and efficient multilevel preconditioners to speed up the convergence of both linear and nonlinear solvers. The work is motivated by the observation that in the local aneurysmal region, the flow is often quite complicated with one or more vortices, but in the healthy section of the artery, the principal component of blood flows along the centerline of the artery. Based on this observation, we introduce a novel two-level additive Schwarz method with a mixed-dimensional coarse preconditioner. The key components of the preconditioner include (1) a three-dimensional coarse preconditioner covering the aneurysm; (2) a one-dimensional coarse preconditioner covering the central line of the healthy section of the artery; (3) a collection of three-dimensional overlapping subdomain preconditioners covering the fine meshes of the entire artery; (4) extension/restriction operators constructed by radial basis functions. The blood flow is modeled by the unsteady incompressible Navier-Stokes equations with resistance outflow boundary conditions discretized by a stabilized finite element method on fully unstructured meshes and the second-order backward differentiation formula in time. The resulting large nonlinear algebraic systems are solved by a Newton-Krylov algorithm accelerated by the new preconditioner in two ways: (1) the initial guess of Newton is obtained by solving a linear system defined by the coarse preconditioner; (2) the Krylov solver of the Jacobian system is preconditioned by the new preconditioner. Numerical experiments indicate that the proposed preconditioner is highly effective and robust for complex flows in a patient-specific artery with aneurysm, and it significantly reduces the numbers of linear and nonlinear iterations.

Impact of Pressure Wire on Fractional Flow Reserve and Hemodynamics of the Coronary Arteries: A Computational and Clinical Study.

OBJECTIVE: Noninvasive fractional flow reserve (FFR) has been extensively studied and gained clinical recognition. However, the effect of an interventional catheter and a pressure wire in the arteries on the noninvasive FFR was not considered in previous studies. We provide quantitative analysis of how a catheter and a pressure wire can affect the estimation of noninvasive FFR using computational fluid dynamics (CFD) techniques. METHODS: Six patients are studied. We calibrate our CFD model with patient-specific conditions so that the noninvasive FFR matches the FFR measured by the pressure wire. Then, we numerically remove the pressure wire and compute the noninvasive FFR again. This allows us to analyze the effect of the pressure wire on FFR. RESULTS: The presence of a catheter and a pressure wire can reduce distal pressure from -0.1 mmHg to -8.1 mmHg, resulting in a reduction of FFR by 5.8 % in average (0.012 to 0.107 or -1.2 % to -16.8 %). The insertion also reduces the time-averaged flow rate at the stenosis by up to 16.2 % (4.9 % in average). CONCLUSION: The impact of the pressure wire on the measured FFR depends on the characteristics of the patient-specific lesion. Significant linear correlations are found between the minimum diameter of the stenotic arteries and the reduction in FFR. SIGNIFICANCE: The impact we found may contribute to provide a correction and improve the estimation of the noninvasive FFR technique for use in clinical practice.

An inner-outer subcycling algorithm for parallel cardiac electrophysiology simulations.

This paper explores cardiac electrophysiological simulations of the monodomain equations and introduces a novel subcycling time integration algorithm to exploit the structure of the ionic model. The aim of this work is to improve upon the efficiency of parallel cardiac monodomain simulations by using our subcycling algorithm in the computation of the ionic model to handle the local sharp changes of the solution. This will reduce the turnaround time for the simulation of basic cardiac electrical function on both idealized and patient-specific geometry. Numerical experiments show that the proposed approach is accurate and also has close to linear parallel scalability on a computer with more than 1000 processor cores. Ultimately, the reduction in simulation time can be beneficial in clinical applications, where multiple simulations are often required to tune a model to match clinical measurements.

Fusing 2D and 3D convolutional neural networks for the segmentation of aorta and coronary arteries from CT images.

Automated segmentation of three-dimensional medical images is of great importance for the detection and quantification of certain diseases such as stenosis in the coronary arteries. Many 2D and 3D deep learning models, especially deep convolutional neural networks (CNNs), have achieved state-of-the-art segmentation performance on 3D medical images. Yet, there is a trade-off between the field of view and the utilization of inter-slice information when using pure 2D or 3D CNNs for 3D segmentation, which compromises the segmentation accuracy. In this paper, we propose a two-stage strategy that retains the advantages of both 2D and 3D CNNs and apply the method for the segmentation of the human aorta and coronary arteries, with stenosis, from computed tomography (CT) images. In the first stage, a 2D CNN, which can extract large-field-of-view information, is used to segment the aorta and coronary arteries simultaneously in a slice-by-slice fashion. Then, in the second stage, a 3D CNN is applied to extract the inter-slice information to refine the segmentation of the coronary arteries in certain subregions not resolved well in the first stage. We show that the 3D network of the second stage can improve the continuity between slices and reduce the missed detection rate of the 2D CNN. Compared with directly using a 3D CNN, the two-stage approach can alleviate the class imbalance problem caused by the large non-coronary artery (aorta and background) and the small coronary artery and reduce the training time because the vast majority of negative voxels are excluded in the first stage. To validate the efficacy of our method, extensive experiments are carried out to compare with other approaches based on pure 2D or 3D CNNs and those based on hybrid 2D-3D CNNs.

Efficient parallel simulation of hemodynamics in patient-specific abdominal aorta with aneurysm.

Surgical planning for aortic aneurysm repair is a difficult task. In addition to the morphological features obtained from medical imaging, alternative features obtained with computational modeling may provide additional useful information. Though numerical studies are noninvasive, they are often time-consuming, especially when we need to study and compare multiple repair scenarios, because of the high computational complexity. In this paper, we present a highly parallel algorithm for the numerical simulation of unsteady blood flows in the patient-specific abdominal aorta before and after the aneurysmic repair. We model the blood flow with the unsteady incompressible Navier-Stokes equations with different outlet boundary conditions, and solve the discretized system with a highly scalable domain decomposition method. With this approach, a high resolution simulation of a full-size adult aorta can be obtained in less than an hour, instead of days with older methods and software. In addition, we show that the parallel efficiency of the proposed method is near 70% on a parallel computer with 2, 880 processor cores.

Parallel finite-volume discrete Boltzmann method for inviscid compressible flows on unstructured grids.

In this paper, a finite-volume discrete Boltzmann method based on a cell-centered scheme for inviscid compressible flows on unstructured grids is presented. In the new method, the equilibrium distribution functions are obtained from the circle function in two-dimensions (2D) and the spherical function in three-dimensions (3D). Moreover, the advective fluxes are evaluated by Roe's flux-difference splitting scheme, the gradients of the density and total energy distribution functions are computed with a least-squares method, and the Venkatakrishnan limiter is employed to prevent oscillations. To parallelize the method we use a graph-based partitioning approach that also guarantees the load balancing. The method is validated by seven benchmark problems: (a) a 2D flow pasting a bump, (b) a 2D Riemann problem, (c) a 2D flow passing the RAE2822 airfoil, (d) flows passing the NACA0012 airfoil, (e) 2D supersonic flows around a cylinder, (f) an explosion in a 3D box, and (g) a 3D flow around the ONERA M6 wing. The benchmark tests show that the results obtained by the proposed method match well with the published results, and the parallel numerical experiments show that the proposed parallel implementation has close to linear strong scalability, and parallel efficiencies of 95.31% and 94.56% are achieved for 2D and 3D problems on a supercomputer with up to 4800 processor cores, respectively.

A highly parallel simulation of patient-specific hepatic flows.

Computational hemodynamics is being developed as an alternative approach for assisting clinical diagnosis and treatment planning for liver diseases. The technology is non-invasive, but the computational time could be high when the full geometry of the blood vessels is taken into account. Existing approaches use either one-dimensional model of the artery or simplified three-dimensional tubular geometry in order to reduce the computational time, but the accuracy is sometime compromised, for example, when simulating blood flows in arteries with plaque. In this work, we study a highly parallel method for the transient incompressible Navier-Stokes equations for the simulation of the blood flows in the full three-dimensional patient-specific hepatic artery, portal vein and hepatic vein. As applications, we also simulate the flow in a patient with hepatectomy and calculate the S (PPG). One of the advantages of simulating blood flows in all hepatic vessels is that it provides a direct estimate of the PPG, which is a gold standard value to assess the portal hypertension. Moreover, the robustness and scalability of the algorithm are also investigated. A 83% parallel efficiency is achieved for solving a problem with 7 million elements on a supercomputer with more than 1000 processor cores.

Numerical Simulation of Blood Flows in Patient-specific Abdominal Aorta with Primary Organs.

The abdominal aorta is the largest artery in the abdominal cavity that supplies blood flows to vital organs through the complex visceral arterial branches, including the celiac trunk (the liver, stomach, spleen, etc.), the renal arteries (the kidneys) and the superior and inferior mesenteric arteries (the small and large intestine, pancreas, etc.). An accurate simulation of blood flows in this network of arteries is important for the understanding of the hemodynamics in various organs of healthy and diseased patients, but the computational cost is very high. As a result, most researchers choose to focus on a portion of the artery or use a low-dimensional approximation of the artery. In the present work, we introduce a parallel algorithm for the modeling of pulsatile flows in the abdominal aorta with branches to the primary organs, and an organ-based two-level method for calculating the resistances for the outflow boundary conditions. With this highly parallel approach, the simulation of the blood flow for a cardiac cycle of the anatomically detailed aorta can be obtained within a few hours, and the blood distribution to organs including liver, spleen and kidneys are also computed with certain accuracy. Moreover, we discuss the significant hemodynamic differences resulted from the influence of the peripheral branches. In addition, we examine the accuracy of the results with respect to the mesh size and time-step size and show the high parallel scalability of the proposed algorithm with up to 3000 processor cores.

A parallel non-nested two-level domain decomposition method for simulating blood flows in cerebral artery of stroke patient.

Numerical simulation of blood flows in patient-specific arteries can be useful for the understanding of vascular diseases, as well as for surgery planning. In this paper, we simulate blood flows in the full cerebral artery of stroke patients. To accurately resolve the flow in this rather complex geometry with stenosis is challenging and it is also important to obtain the results in a short amount of computing time so that the simulation can be used in pre- and/or post-surgery planning. For this purpose, we introduce a highly scalable, parallel non-nested two-level domain decomposition method for the three-dimensional unsteady incompressible Navier-Stokes equations with an impedance outlet boundary condition. The problem is discretized with a stabilized finite element method on unstructured meshes in space and a fully implicit method in time, and the large nonlinear systems are solved by a preconditioned parallel Newton-Krylov method with a two-level Schwarz method. The key component of the method is a non-nested coarse problem solved using a subset of processor cores and its solution is interpolated to the fine space using radial basis functions. To validate and verify the proposed algorithm and its highly parallel implementation, we consider a case with available clinical data and show that the computed result matches with the measured data. Further numerical experiments indicate that the proposed method works well for realistic geometry and parameters of a full size cerebral artery of an adult stroke patient on a supercomputers with thousands of processor cores.

A Photo-clickable ATP-Mimetic Reveals Nucleotide Interactors in the Membrane Proteome.

ATP is an important energy metabolite and allosteric signal in health and disease. ATP-interacting proteins, such as P2 receptors, control inflammation, cell death, migration, and wound healing. However, identification of allosteric ATP sites remains challenging, and our current inventory of ATP-controlled pathways is likely incomplete. Here, we develop and verify mipATP as a minimally invasive photoaffinity probe for ATP-interacting proteins. Its N6 functionalization allows target enrichment by UV crosslinking and conjugation to reporter tags by "click" chemistry. The additions are compact, allowing mipATP to completely retain the calcium signaling responses of native ATP in vitro and in vivo. mipATP specifically enriched for known nucleotide binders in A549 cell lysates and membrane fractions. In addition, it retrieved unannotated ATP interactors, such as the FAS receptor, CD44, and various SLC transporters. Thus, mipATP is a promising tool to identify allosteric ATP sites in the proteome.

A chemical probe of CARM1 alters epigenetic plasticity against breast cancer cell invasion.

CARM1 is a cancer-relevant protein arginine methyltransferase that regulates many aspects of transcription. Its pharmacological inhibition is a promising anti-cancer strategy. Here SKI-73 (6a in this work) is presented as a CARM1 chemical probe with pro-drug properties. SKI-73 (6a) can rapidly penetrate cell membranes and then be processed into active inhibitors, which are retained intracellularly with 10-fold enrichment for several days. These compounds were characterized for their potency, selectivity, modes of action, and on-target engagement. SKI-73 (6a) recapitulates the effect of CARM1 knockout against breast cancer cell invasion. Single-cell RNA-seq analysis revealed that the SKI-73(6a)-associated reduction of invasiveness acts by altering epigenetic plasticity and suppressing the invasion-prone subpopulation. Interestingly, SKI-73 (6a) and CARM1 knockout alter the epigenetic plasticity with remarkable difference, suggesting distinct modes of action for small-molecule and genetic perturbations. We therefore discovered a CARM1-addiction mechanism of cancer metastasis and developed a chemical probe to target this process.

Drugs that are small molecules have the potential to block the individual proteins that drive the spread of cancer, but their design is a challenge. This is because they need to get inside the cell and find their target without binding to other proteins on the way. However, small molecule drugs often have an electric charge, which makes it hard for them to cross the cell membrane. Additionally, most proteins are not completely unique, making it harder for the drugs to find the correct target. CARM1 is a protein that plays a role in the spread of breast cancer cells, and scientists are currently looking for a small molecule that will inhibit its action. The group of enzymes that CARM1 belongs to act by taking a small chemical group, called a methyl group, from a molecule called SAM, and transferring it to proteins that switch genes on and off. In the case of CARM1, this changes cell behavior by turning on genes involved in cell movement. Genetically modifying cells so they will not produce any CARM1 stops the spread of breast cancer cells, but developing a drug with the same effects has proved difficult. Existing drugs that can inhibit CARM1 in a test tube struggle to get inside cells and to distinguish between CARM1 and its related enzymes. Now, Cai et al. have modified and tested a CARM1 inhibitor to address these problems, and find out how these small molecules work. At its core, the inhibitor has a structure very similar to a SAM molecule, so it can fit into the SAM binding pocket of CARM1 and its related enzymes. To stop the inhibitor from binding to other proteins, Cai et al. made small changes to its structure until it only interacted with CARM1.Then, to get the inhibitor inside breast cancer cells, Cai et al. cloaked its charged area with a chemical shield, allowing it to cross the cell membrane. Inside the cell, the chemical shield broke away, allowing the inhibitor to attach to CARM1. Analysis of cells showed that this inhibition only affected the cancer cells most likely to spread. Blocking CARM1 switched off genes involved in cell movement and stopped cancer cells from travelling through 3D gels. This work is a step towards making a drug that can block CARM1 in cancer cells, but there is still further work to be done. The next stages will be to test whether the new inhibitor works in other types of cancer cells, in living animals, and in human patient samples.

Simulation of unsteady blood flows in a patient-specific compliant pulmonary artery with a highly parallel monolithically coupled fluid-structure interaction algorithm.

Computational fluid dynamics (CFD) is increasingly used to study blood flows in patient-specific arteries for understanding certain cardiovascular diseases. The techniques work quite well for relatively simple problems but need improvements when the problems become harder when (a) the geometry becomes complex (eg, a few branches to a full pulmonary artery), (b) the model becomes more complex (eg, fluid-only to coupled fluid-structure interaction), (c) both the fluid and wall models become highly nonlinear, and (d) the computer on which we run the simulation is a supercomputer with tens of thousands of processor cores. To push the limit of CFD in all four fronts, in this paper, we develop and study a highly parallel algorithm for solving a monolithically coupled fluid-structure system for the modeling of the interaction of the blood flow and the arterial wall. As a case study, we consider a patient-specific, full size pulmonary artery obtained from computed tomography (CT) images, with an artificially added layer of wall with a fixed thickness. The fluid is modeled with a system of incompressible Navier-Stokes equations, and the wall is modeled by a geometrically nonlinear elasticity equation. As far as we know, this is the first time the unsteady blood flow in a full pulmonary artery is simulated without assuming a rigid wall. The proposed numerical algorithm and software scale well beyond 10 000 processor cores on a supercomputer for solving the fluid-structure interaction problem discretized with a stabilized finite element method in space and an implicit scheme in time involving hundreds of millions of unknowns.

An efficient parallel simulation of unsteady blood flows in patient-specific pulmonary artery.

Simulation of blood flows in the pulmonary artery provides some insight into certain diseases by examining the relationship between some continuum metrics, eg, the wall shear stress acting on the vascular endothelium, which responds to flow-induced mechanical forces by releasing vasodilators/constrictors. V. Kheyfets, in his previous work, studies numerically a patient-specific pulmonary circulation to show that decreasing wall shear stress is correlated with increasing pulmonary vascular impedance. In this paper, we develop a scalable parallel algorithm based on domain decomposition methods to investigate an unsteady model with patient-specific pulsatile waveforms as the inlet boundary condition. The unsteady model offers tremendously more information about the dynamic behavior of the flow field, but computationally speaking, the simulation is a lot more expensive since a problem which is similar to the steady-state problem has to be solved many times, and therefore, the traditional sequential approach is not suitable anymore. We show computationally that simulations using the proposed parallel approach with up to 10 000 processor cores can be obtained with much reduced compute time. This makes the technology potentially usable for the routine study of the dynamic behavior of blood flows in the pulmonary artery, in particular, the changes of the blood flows and the wall shear stress in the spatial and temporal dimensions.

Corrosion Prediction with Parallel Finite Element Modeling for Coupled Hygro-Chemo Transport into Concrete under Chloride-Rich Environment.

The prediction of the chloride-induced corrosion is very important because of the durable life of concrete structure. To simulate more realistic durability performance of concrete structures, complex scientific methods and more accurate material models are needed. In order to predict the robust results of corrosion initiation time and to describe the thin layer from concrete surface to reinforcement, a large number of fine meshes are also used. The purpose of this study is to suggest more realistic physical model regarding coupled hygro-chemo transport and to implement the model with parallel finite element algorithm. Furthermore, microclimate model with environmental humidity and seasonal temperature is adopted. As a result, the prediction model of chloride diffusion under unsaturated condition was developed with parallel algorithms and was applied to the existing bridge to validate the model with multi-boundary condition. As the number of processors increased, the computational time decreased until the number of processors became optimized. Then, the computational time increased because the communication time between the processors increased. The framework of present model can be extended to simulate the multi-species de-icing salts ingress into non-saturated concrete structures in future work.

Functional assessment of cerebral artery stenosis: A pilot study based on computational fluid dynamics.

The fractional pressure ratio is introduced to quantitatively assess the hemodynamic significance of severe intracranial stenosis. A computational fluid dynamics-based method is proposed to non-invasively compute the FPRCFD and compared against fractional pressure ratio measured by an invasive technique. Eleven patients with severe intracranial stenosis considered for endovascular intervention were recruited and an invasive procedure was performed to measure the distal and the aortic pressure ( Pd and Pa). The fractional pressure ratio was calculated as [Formula: see text]. The computed tomography angiography was used to reconstruct three-dimensional (3D) arteries for each patient. Cerebral hemodynamics was then computed for the arteries using a mathematical model governed by Navier-Stokes equations and with the outflow conditions imposed by a model of distal resistance and compliance. The non-invasive [Formula: see text], [Formula: see text], and FPRCFD were then obtained from the computational fluid dynamics calculation using a 16-core parallel computer. The invasive and non-invasive parameters were tested by statistical analysis. For this group of patients, the computational fluid dynamics method achieved comparable results with the invasive measurements. The fractional pressure ratio and FPRCFD are very close and highly correlated, but not linearly proportional, with the percentage of stenosis. The proposed computational fluid dynamics method can potentially be useful in assessing the functional alteration of cerebral stenosis.

Synthesis of the spiroiminal moiety and approaches to the synthesis of marineosins A and B.

A short and efficient synthesis of model spiroiminals that have the same stereochemistry as marineosins A and B, but different conformations, was carried out in six or seven steps from 6-methyltetrahydropyran-2-one. These spiroiminals were also prepared biomimetically by reduction of an enol ether. A more highly substituted spiroiminal with the same stereochemistry and conformation as marineosin A was prepared in 11 steps from parasorbic acid. A macrocyclic pyrrole lactone was prepared stereospecifically in 10 steps. A five-step sequence converted the lactone to a late hemi-iminal intermediate that has resisted the methylation and spiroiminal formation that would lead to marineosin A.

Synthesis of the spiroiminal moiety of marineosins A and B.

A model for the spiroiminal moiety of marineosins A and B was prepared starting from methylvalerolactone. Addition of vinylmagnesium bromide, protection of the alcohol, and reaction of the vinyl ketone with a protected pyrrole-2-carbonitrile N-oxide gave an isoxazoline. Hydrogenolysis of the N-O bond with Raney nickel gave a keto imine that cyclized to a hemi-iminal. O-Methylation, acid-catalyzed cleavage of the TES group and spiroiminal formation, and deprotection completed a seven-step synthesis.

Simulation of branching blood flows on parallel computers.

We present a fully parallel nonlinearly implicit algorithm for the numerical simulation of some branching blood flow problems, which require efficient and robust solver technologies in order to handle the high nonlinearity and the complex geometry. Parallel processing is necessary because of the large number of mesh points needed to accurately discretize the system of differential equations. In this paper we introduce a parallel Newton-Krylov-Schwarz based implicit method, and software for distributed memory parallel computers, for solving the nonlinear algebraic systems arising from a Q2-Q1 finite element discretization of the incompressible Navier-Stokes equations that we use to model the blood flow in the left anterior descending coronary artery.