Whole-body hemodynamic simulations provide quantitative tools for patient-specific treatment planning but require scalable computational methods to model complex physiological systems. We develop a parallel solver within the Newton-Krylov-Schwarz framework to simulate 3D blood flow in a patient-specific arterial network with over 500 branches, governed by the incompressible Navier-Stokes equations on unstructured tetrahedral meshes. Our novel Hybrid Parallel Block Iterative Solver (HPBIS) and its Reduced and Reused variant (RR-HPBIS), optimized for the Sunway TaihuLight’s many-core architecture, employ batched data transfers and computation-communication overlap. Numerical experiments show RR-HPBIS achieves a 25.2x speedup over a homogeneous baseline and scales to 16,384 CPU cores for a 197-million-tetrahedron mesh, yielding a 5.1x speedup at 32% efficiency. The solver captures systemic hemodynamics, including spiral flow and wall shear stress, critical for vascular physiology. Despite simplified boundary conditions, this method advances high-resolution computational modeling for clinical applications.

In this paper a highly parallel method is developed for simulating the elastodynamics of a fourchamber human heart with patient-specific geometry. The heterogeneous hyperelastic model is discretized by a finite element method in space and a fully implicit adaptive method in time, and the resulting nonlinear algebraic systems are solved by a scalable domain decomposition algorithm. The deformations of the cardiac muscles are quite complex due to the realistic geometry, the heterogeneous hyperelasticity of the cardiac tissue, and the myocardial fibers with active stresses. Moreover, the deformations in different chambers and at different phases of the cardiac cycle are very different. To simulate all the muscle movements including the atrial diastole, the atrial systole, the isovolumic contraction, the ventricular ejection, the isovolumic relaxation, and the ventricular filling, the temporal-spatial mesh needs to be sufficiently fine, but not too fine so that the overall computing time is manageable, we introduce a baseline mesh in space and a two-level time stepping strategy including a uniform baseline time step size to obtain the desired time accuracy and an adaptive time stepping method within a baseline time step to guarantee the convergence of the nonlinear solver. Through numerical experiments, we investigate the performance of the proposed method with respect to the material coefficients, the fiber orientations, as well as the mesh sizes and the time step sizes. For an unstructured tetrahedral mesh with more than 200 million degree of freedoms, the method scales well for up to 16,384 processor cores for all steps of an entire cardiac cycle.

In this paper, a parallel overlapping domain decomposition preconditioner is proposed to solve the linear system of equations arising from the extended finite element discretization of elastic crack problems. The algorithm partitions the computational mesh into two types of subdomains: the regular subdomains and the crack tip subdomains based on the observation that the crack tips have a significant impact on the convergence of the iterative method while the impact of the crack lines is not that different from those of regular mesh points. The tip subdomains consist of mesh points at crack tips and all neighboring points where the branch enrichment functions are applied. The regular subdomains consist of all other mesh points, including those on the crack lines. To overcome the mismatch between the number of subdomains and the number of processor cores, the proposed method is divided into two steps: solve the crack tip problem and then the regular subdomain problem during each iteration. The proposed method was used to develop a parallel XFEM package which is able to test different types of iterative methods. To achieve good parallel efficiency, additional methods were introduced to reduce communication and to maintain the load balance between processors. Numerical experiments indicate that the proposed method significantly reduces the number of iterations and the total computation time compared to the classical methods. In addition, the method scales up to 8192 processor cores with over 70\% parallel efficiency to solve problems with more than $2\times10^8$ degrees of freedom.

In this paper, we propose a scalable parallel algorithm for simulating the cardiac fluid-structure interactions (FSI) of a patient-specific human left ventricle. It provides an efficient forward solver to deal with the induced sub-problems in solving an inverse problem that can be used to quantify the interested parameters. The FSI between the blood flow and the myocardium is described in an arbitrary Lagrangian-Eulerian (ALU) framework, in which the velocity and stress are assumed being continuous across the fluid-structure interface. The governing equations are discretized by using a finite element method and a fully implicit backward Eulerian formula, and the resulting algebraic system is solved by using a parallel Newton-Krylov-Schwarz algorithm. We numerically show that the algorithm is robust with respect to multiple model parameters and scales well up to 2300 processor cores. The ability of the proposed method to produce qualitatively true prediction is also demonstrated via comparing the simulation results with the clinic data.

In this paper, we propose a parallel fluid-structure interaction solution method for the simulation of the diastolic process of the human left ventricle. The three dimensional geometry of a patient-specific left ventricle is first segmented from a medical image, and then based on which an unstructured mesh is generated. The coupled fluid-structure interaction equations are spatially discretized by a finite element method on the unstructured mesh and a fully implicit scheme is introduced for the temporal discretization. At each timestep of the fully implicit method, a scalable parallel method is applied for solving the large scale nonlinear system. Numerical experiments show that the proposed method scales up to 1920 processor cores on the Tianhe-2A supercomputer for solving a problem with over 7.9 million unstructured tetrahedrons, which shows a potential to do high-fidelity simulation of human heart for clinical applications.

The blood vessels play a key role in the human circulatory system. As a tremendous amount of efforts have been devoted to develop mathematical models for investigating the elastic behaviors of human blood vessels, high performance numerical algorithms aiming at solving these models have attracted attention. In this work, we present an efficient finite element solver for an elastodynamic model which is commonly used for simulating soft tissues under external pressure loadings. In particular, the elastic material is assumed to satisfy the Saint–Venant–Kirchhoff law, the governing equation is spatially discretized by a finite element method, and a fully implicit backward difference method is used for the temporal discretization. The resulting nonlinear system is then solved by a Newton–Krylov–Schwarz method. It is the first time to apply the Newton–Krylov–Schwarz method to the Saint–Venant–Kirchhoff model for a patient-specific blood vessel. Numerical tests verify the efficiency of the proposed method and demonstrate its capability for bioengineering applications.

Gradient-echo MRI has revealed anisotropic magnetic susceptibility in the brain white matter. This magnetic susceptibility anisotropy can be measured and characterized with susceptibility tensor imaging (STI). In this study, a method of fiber tractography based on STI is proposed and demonstrated in the mouse brain. STI experiments of perfusion-fixed mouse brains were conducted at 7.0T. The magnetic susceptibility tensor was calculated for each voxel with regularization and decomposed into its eigensystem. The major eigenvector is found to be aligned with the underlying fiber orientation. Following the orientation of the major eigenvector, we are able to map distinctive fiber pathways in 3D. As a comparison, diffusion tensor imaging (DTI) and DTI fiber tractography were also conducted on the same specimens. The relationship between STI and DTI fiber tracts was explored with similarities and differences identified. It is anticipated that the proposed method of STI tractography may provide a new way to study white matter fiber architecture. As STI tractography is based on physical principles that are fundamentally different from DTI, it may also be valuable for the ongoing validation of DTI tractography.

Rodent models of Huntington disease (HD) are valuable tools for investigating HD pathophysiology and evaluating new therapeutic approaches. Non-invasive characterization of HD-related phenotype changes is important for monitoring progression of pathological processes and possible effects of interventions. The first transgenic rat model for HD exhibits progressive late-onset affective, cognitive, and motor impairments, as well as neuropathological features reflecting observations from HD patients. In this report, we contribute to the anatomical phenotyping of this model by comparing high-resolution ex vivo DTI measurements obtained in aged transgenic HD rats and wild-type controls. By region of interest analysis supplemented by voxel-based statistics, we find little evidence of atrophy in basal ganglia regions, but demonstrate altered DTI measurements in the dorsal and ventral striatum, globus pallidus, entopeduncular nucleus, substantia nigra, and hippocampus. These changes are largely compatible with DTI findings in preclinical and clinical HD patients. We confirm earlier reports that HD rats express a moderate neuropathological phenotype, and provide evidence of altered DTI measures in specific HD-related brain regions, in the absence of pronounced morphometric changes.

Prenatal ethanol exposure is the leading preventable cause of congenital mental disability. Whereas a diagnosis of fetal alcohol syndrome (FAS) requires identification of a specific pattern of craniofacial dysmorphology, most individuals with behavioral and neurological sequelae of heavy prenatal ethanol exposure do not exhibit these defining facial characteristics. Here, a novel integration of MRI and dense surface modeling-based shape analysis was applied to characterize concurrent face-brain phenotypes in C57Bl/6J fetuses exposed to ethanol on gestational day (GD)7 or GD8.5. The facial phenotype resulting from ethanol exposure depended upon stage of insult and was predictive of unique patterns of corresponding brain abnormalities. Ethanol exposure on GD7 produced a constellation of dysmorphic facial features characteristic of human FAS, including severe midfacial hypoplasia, shortening of the palpebral fissures, an elongated upper lip, and deficient philtrum. In contrast, ethanol exposure on GD8.5 caused mild midfacial hypoplasia and palpebral fissure shortening, a shortened upper lip, and a preserved philtrum. These distinct, stage-specific facial phenotypes were associated with unique volumetric and shape abnormalities of the septal region, pituitary, and olfactory bulbs. By demonstrating that early prenatal ethanol exposure can cause more than one temporally-specific pattern of defects, these findings illustrate the need for an expansion of current diagnostic criteria to better capture the full range of facial and brain dysmorphology in fetal alcohol spectrum disorders.

Background Accurate interpretations of cardiac functions require precise structural models of the myocardium, but the latter is not available always and for all species. Although scaling or substitution of myocardial fiber information from alternate species has been used in cardiac functional modeling, the validity of such practice has not been tested. Methods Fixed mouse (n = 10), rabbit (n = 6), and sheep (n = 5) hearts underwent diffusion tensor imaging (DTI). The myocardial structures in terms of the left ventricular fiber orientation helix angle index were quantitatively compared between the mouse rabbit and sheep hearts. Results The results show that significant fiber structural differences exist between any two of the three species. Specifically, the subepicardial fiber orientation, and the transmural range and linearity of fiber helix angles are significantly different between the mouse and either rabbit or sheep. Additionally, a significant difference was found between the transmural helix angle range between the rabbit and sheep. Across different circumferential regions of the heart, the fiber orientation was not found to be significantly different. Conclusions The current study indicates that myocardial structural differences exist between different size hearts. An immediate implication of the present findings for myocardial structural or functional modeling studies is that caution must be exercised when extrapolating myocardial structures from one species to another.

Magnetic resonance imaging (MRI), now common in the clinical domain, has been adapted for use by the neuropathologist by increasing the spatial resolution over 100,000 times what is common in human clinical imaging. This increase in spatial resolution has been accomplished through a variety of technical advances—higher magnetic fields, more sensitive receivers, and clever encoding methods. Magnetic resonance histology (MRH), that is, the application of MRI to study tissue specimens, now makes three-dimensional imaging of the fixed brain in the cranium routine. Active staining (perfusion fixation with a paramagnetic contrast agent) has allowed us to reduce the scan time by more than 8 times over earlier methods. The result is a three-dimensional isotropic image array that can be viewed along any direction without loss of spatial resolution. Homologous slices can be chosen interactively. Since the tissue is still fully hydrated in the cranium, tissue shrinkage and distortion are virtually eliminated. Volume measurements of neural structures can be made with a high degree of precision and accuracy. MRH will not replace more traditional methods, but it promises enormous value in choosing particular areas and times for more traditional sectioning and assessment.

Rats are widely used in experimental neurobiological research, and rat brain atlases are important resources for identifying brain regions in the context of experimental microsurgery, tissue sampling, and neuroimaging, as well as comparison of findings across experiments. Currently, most available rat brain atlases are constructed from histological material derived from single specimens, and provide two-dimensional or three-dimensional (3D) outlines of diverse brain regions and fiber tracts. Important limitations of such atlases are that they represent individual specimens, and that finer details of tissue architecture are lacking. Access to more detailed 3D brain atlases representative of a population of animals is needed. Diffusion tensor imaging (DTI) is a unique neuroimaging modality that provides sensitive information about orientation structure in tissues, and is widely applied in basic and clinical neuroscience investigations. To facilitate analysis and assignment of location in rat brain neuroimaging investigations, we have developed a population-averaged three-dimensional DTI atlas of the normal adult Sprague Dawley rat brain. The atlas is constructed from high resolution ex vivo DTI images, which were nonlinearly warped into a population-averaged in vivo brain template. The atlas currently comprises a selection of manually delineated brain regions, the caudate–putamen complex, globus pallidus, entopeduncular nucleus, substantia nigra, external capsule, corpus callosum, internal capsule, cerebral peduncle, fimbria of the hippocampus, fornix, anterior commisure, optic tract, and stria terminalis. The atlas is freely distributed and potentially useful for several purposes, including automated and manual delineation of rat brain structural and functional imaging data.

The orientation of MRI-measured diffusion tensor in the myocardium has been directly correlated to the tissue fiber direction and widely characterized. However, the scalar anisotropy indexes have mostly been assumed to be uniform throughout the myocardial wall. The present study examines the fractional anisotropy (FA) as a function of transmural depth and circumferential and longitudinal locations in the normal sheep cardiac left ventricle. Results indicate that FA remains relatively constant from the epicardium to the midwall and then decreases (25.7%) steadily toward the endocardium. The decrease of FA corresponds to 7.9% and 12.9% increases in the secondary and tertiary diffusion tensor diffusivities, respectively. The transmural location of the FA transition coincides with the location where myocardial fibers run exactly circumferentially. There is also a significant difference in the midwall-endocardium FA slope between the septum and the posterior or lateral left ventricular free wall. These findings are consistent with the cellular microstructure from histological studies of the myocardium and suggest a role for MR diffusion tensor imaging in characterization of not only fiber orientation but, also, other tissue parameters, such as the extracellular volume fraction.

MR diffusion tensor imaging (DTI) is a promising tool for characterizing the microstructure of ordered tissues. However, its practical applications are hampered by relatively low signal-to-noise-ratio and spatial and temporal resolution. Reduced-encoding imaging (REI) via k-space sharing with constrained reconstruction has previously been shown to be effective for accelerating DTI, although the implementation was based on rectilinear k-space sampling. Due to the intrinsic oversampling of central k-space and allowance for isotropic downsampling, projection-reconstruction (PR) imaging may be better suited for REI. In this study, regularization procedures, including radial filtering and baseline signal correction to adequately reconstruct reduced encoded PR imaging data, are investigated. The proposed filtered reduced-encoding projection-reconstruction (FREPR) technique is applied to DTI tissue fiber orientation and fractional anisotropy (FA) measurements. Results show that FREPR offers improved reconstructions of the reduced encoded images and on an equal total scan-time basis provides more accurate fiber orientation and FA measurements compared to rectilinear k-space sampling-based REI methods or a control experiment consisting of only fully encoded images. These findings suggest a potentially significant role of FREPR in accelerating repeated imaging and improving the data acquisition-time efficiency of DTI experiments.

OBJECTIVES:It has been proposed that successful left ventricular surgical restoration should restore normal helical myofiber orientation. A magnetic resonance imaging technique, magnetic resonance diffusion tensor imaging, has been developed to measure myocyte orientation. By using magnetic resonance diffusion tensor imaging, this study tested the hypothesis that (1) myocyte orientation is altered after anteroapical myocardial infarction and (2) left ventricular surgical restoration restores normal helix angles.METHODS:Thirteen sheep underwent anteroapical myocardial infarction (25% of left ventricular mass). Ten weeks later, animals underwent either aneurysm plication (n = 8) or sham operations (n = 5). Six weeks after this operation, hearts were excised, perfusion fixed in diastole, and underwent magnetic resonance diffusion tensor imaging. Hearts from normal sheep (n = 5) were also harvested and imaged. Primary eigenvectors of the diffusion tensors from magnetic resonance diffusion tensor imaging were resolved into helix angles relative to a local wall coordinate system. Transmural samples of the helix angles were compared at the border zone of the aneurysm or repair (or a comparable distance from the base in normal sheep), 1 cm below the valves, and halfway between.RESULTS:The helical myofiber orientation did not change after myocardial infarction. However, aneurysm plication caused myofibers in the anterior border zone to rotate counterclockwise (-35.6 +/- 10.5 degrees , P = .028) and those in the lateral border zone to rotate clockwise (34.4 +/- 8.1 degrees , P = .031).CONCLUSIONS:Surgical restoration alters myocyte orientation adjacent to the surgical repair. However, myofiber orientation is not abnormal after myocardial infarction, and thus surgical restoration techniques intent on restoring normal helix angles might not be warranted.

The relative utility of 3D, microscopic resolution assessments of fixed mouse myocardial structure via diffusion tensor imaging is demonstrated in this study. Isotropic 100‐μm resolution fiber orientation mapping within 5.5° accuracy was achieved in 9.1 hr scan time. Preliminary characterization of the diffusion tensor primary eigenvector reveals a smooth and largely linear angular rotation across the left ventricular wall. Moreover, a higher level of structural hierarchy is evident from the organized secondary and tertiary eigenvector fields. These findings are consistent with the known myocardial fiber and laminar structures reported in the literature and suggest an essential role of diffusion tensor microscopy in developing quantitative atlases for studying the structure–function relationships of mouse hearts. Magn Reson Med 52:453–460, 2004. © 2004 Wiley‐Liss, Inc.

MR diffusion tensor imaging (DTI) is a promising tool for characterizing microstructures of ordered tissues. However, its practical applications have been hampered by the low signal-to-noise-ratio and spatial and temporal resolutions. K-space sharing with constrained reconstruction has been effective for accelerating DTI, though the implementation was based on rectilinear k-space sampling. Due to its intrinsic oversampling and averaging of central k-space and isotropic trajectories, projection reconstruction, or radial sampling, imaging may be more suited for k-space sharing reduced encoding schemes. In this study, filtered reduced encoding projection reconstruction (FREPR) is implemented. The key features include the use of radial mask filters to select for spatial frequency information and constrained reconstruction in the form of phase and magnitude baseline correction. The performance of FREPR is evaluated in terms of image differences and deviations in measured fiber orientation with respect to the full-encoded dataset, both in simulation and experiment, against rectilinear k-space sharing method. Results indicate FREPR provides a significant improvement in the acquisition-time efficiency of DTI.