Non-aneurysmal subarachnoid hemorrhage in aplastic or twig-like middle cerebral artery: A case report and literature review.

BACKGROUND: Aplastic or twig-like middle cerebral artery (Ap/T-MCA) is a rare vascular anomaly that can cause hemorrhagic and ischemic stroke. Ap/T-MCA can induce aneurysms due to the fragility of the vessel wall, consequently leading to subarachnoid hemorrhage. Herein, we report a case of Ap/T-MCA with subarachnoid hemorrhage without an aneurysm. CASE PRESENTATION: A 67-year-old man presented to our hospital with a sudden onset of headache. Computed tomography of the head revealed subarachnoid hemorrhage (SAH) in the left Sylvian fissure; however, no aneurysm was observed on digital subtraction angiography. Following conservative treatment, follow-up imaging showed no aneurysm or no recurrent stroke. CONCLUSION: Non-aneurysmal SAH is a possible indication of vessel wall fragility in Ap/T-MCA; however, a standardized treatment strategy for this condition remains to be established.

Central arterial pressure estimation based on two peripheral pressure measurements using one-dimensional blood flow simulation.

Aortic pressure can be estimated using one-dimensional arterial flow simulations. This study demonstrates that two peripheral pressure measurements can be used to acquire the central pressure curve through the patient-specific optimization of a set of system parameters. Radial and carotid pressure measurements and parameter optimization were performed in the case of 62 patients. The two calculated aortic curves were in good agreement, Systolic and Mean Blood Pressures differed on average by 0.5 and -0.5 mmHg, respectively. Good agreement was achieved with the transfer function method as well. The effect of carotid clamping is demonstrated using one resulting patient-specific arterial network.

Modeling and hexahedral meshing of cerebral arterial networks from centerlines.

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both the geometric and topological information and facilitates manual editing. In this work, we propose an automatic method to generate a structured hexahedral mesh suitable for CFD directly from centerlines. We addressed both the modeling and meshing tasks. We proposed a vessel model based on penalized splines to overcome the limitations inherent to the centerline representation, such as noise and sparsity. The bifurcations are reconstructed using a parametric model based on the anatomy that we extended to planar n-furcations. Finally, we developed a method to produce a volume mesh with structured, hexahedral, and flow-oriented cells from the proposed vascular network model. The proposed method offers better robustness to the common defects of centerlines and increases the mesh quality compared to state-of-the-art methods. As it relies on centerlines alone, it can be applied to edit the vascular model effortlessly to study the impact of vascular geometry and topology on hemodynamics. We demonstrate the efficiency of our method by entirely meshing a dataset of 60 cerebral vascular networks. 92% of the vessels and 83% of the bifurcations were meshed without defects needing manual intervention, despite the challenging aspect of the input data. The source code is released publicly.

Computational Assessment of Magnetic Nanoparticle Targeting Efficiency in a Simplified Circle of Willis Arterial Model.

This paper presents the methodology and computational results of simulated medical drug targeting (MDT) via induced magnetism intended for administering intravenous patient-specific doses of therapeutic agents in a Circle of Willis (CoW) model. The multi-physics computational model used in this work is from our previous works. The computational model is used to analyze pulsatile blood flow, particle motion, and particle capture efficiency in a magnetized region using the magnetic properties of magnetite (Fe3O4) and equations describing the magnetic forces acting on particles produced by an external cylindrical electromagnetic coil. A Eulerian-Lagrangian technique is implemented to resolve the hemodynamic flow and the motion of particles under the influence of a range of magnetic field strengths (Br = 2T, 4T, 6T, and 8T). Particle diameter sizes of 10 nm to 4 µm in diameter were assessed. Two dimensionless numbers are also investigated a priori in this study to characterize relative effects of Brownian motion (BM), magnetic force-induced particle motion, and convective blood flow on particle motion. Similar to our previous works, the computational simulations demonstrate that the greatest particle capture efficiency results for particle diameters within the micron range, specifically in regions where flow separation and vortices are at a minimum. Additionally, it was observed that the capture efficiency of particles decreases substantially with smaller particle diameters, especially in the superparamagnetic regime. The highest capture efficiency observed for superparamagnetic particles was 99% with an 8T magnetic field strength and 95% with a 2T magnetic field strength when analyzing 100 nm particles. For 10 nm particles and an 8T magnetic field strength, the particle capture efficiency was 48%, and for a 2T magnetic field strength the particle capture efficiency was 33%. Furthermore, it was found that larger magnetic field strengths, large particle diameter sizes (1 µm and above), and slower blood flow velocity increase the particle capture efficiency. The key finding in this work is that favorable capture efficiencies for superparamagnetic particles were observed in the CoW model for weak fields (Br < 4T) which demonstrates MDT as a possible viable treatment candidate for cardiovascular disease.

Machine Learning Identification Framework of Hemodynamics of Blood Flow in Patient-Specific Coronary Arteries with Abnormality.

In this study, we put forth a new deep neural network framework to predict flow behavior in a coronary arterial network with different properties in the presence of any abnormality like stenosis. An artificial neural network (ANN) model is trained using synthetic data so that it can predict the pressure and velocity within the arterial network. The data required to train the neural network were obtained from the CFD analysis of several geometries of arteries with specific features in ABAQUS software. The proposed approach precisely predicts the hemodynamic behavior of the blood flow. The average accuracy of the pressure prediction was 98.7%, and the average velocity magnitude accuracy was 93.2%. Our model can also be used to predict fractional flow reserve (FFR), which is one of the main indices to determine the severity of stenosis, and our model predicts this index successfully based on the artery features.

Central arterial pressure and patient-specific model parameter estimation based on radial pressure measurements.

One-dimensional arterial flow simulations are suitable to estimate the aortic pressure from peripheral measurements in a patient-specific arterial network. This study introduces a reduction of the system parameters, and a novel calculation method to estimate the patient-specific set and the aortic curve based on radial applanation tonometry. Peripheral and aortic pressure curves were measured in patients, optimization were carried out. The aortic pressure curves were reproduced well, with an overestimation of the measured Systolic and Mean Blood Pressures on average by 0.6 and 0.5 mmHg respectively, and the Root Mean Square Difference of the curves was 3 mmHg on average.

Comparison of algorithms for estimating blood flow velocities in cerebral arteries based on the transport information of contrast agent: An in silico study.

While many algorithms have been proposed to estimate blood flow velocities based on the transport information of contrast agent acquired by digital subtraction angiography (DSA), most relevant studies focused on a single vessel, leaving a question open as to whether the algorithms would be suitable for estimating blood flow velocities in arterial systems with complex topological structures. In this study, a one-dimensional (1-D) modeling method was developed to simulate the transport of contrast agent in cerebral arterial networks with various anatomical variations or having occlusive disease, thereby generating an in silico database for examining the accuracies of some typical algorithms (i.e., time-of-center of gravity (TCG), shifted least-squares (SLS), and cross correlation (CC) algorithms) that estimate blood flow velocity based on the concentration-time curves (CTCs) of contrast agent. The results showed that the TCG algorithm had the best performance in estimating blood flow velocities in most cerebral arteries, with the accuracy being only mildly affected by anatomical variations of the cerebral arterial network. Nevertheless, the presence of a stenosis of moderate to high severity in the internal carotid artery could considerably impair the accuracy of the TCG algorithm in estimating blood flow velocities in some cerebral arteries where the transport of contrast agent was disturbed by strong collateral flows. In summary, the study suggests that the TCG algorithm may offer a promising means for estimating blood flow velocities based on CTCs of contrast agent monitored in cerebral arteries, provided that the shapes of CTCs are not highly distorted by collateral flows.

The nephron-arterial network and its interactions.

Tubuloglomerular feedback and the myogenic mechanism form an ensemble in renal afferent arterioles that regulate single-nephron blood flow and glomerular filtration. Each mechanism generates a self-sustained oscillation, the mechanisms interact, and the oscillations synchronize. The synchronization generates a bimodal electrical signal in the arteriolar wall that propagates retrograde to a vascular node, where it meets similar electrical signals from other nephrons. Each signal carries information about the time-dependent behavior of the regulatory ensemble. The converging signals support synchronization of the nephrons participating in the information exchange, and the synchronization can lead to formation of nephron clusters. We review the experimental evidence and the theoretical implications of these interactions and consider additional interactions that can limit the size of nephron clusters. The architecture of the arterial tree figures prominently in these interactions.

Zero-dimensional lumped approach to incorporate the dynamic part of the pressure at vessel junctions in a 1D wave propagation model.

A benchmark study by Boileau et al tested 6 commonly used numerical schemes for 1D wave propagation, for their ability to capture the main features of pressure, flow, and area waveforms in large arteries. While all numerical schemes showed good agreement in pressure and flow waveforms for smaller arterial networks, the simplified trapezium rule method proposed by Kroon et al showed an overestimation for the systolic pressure of 1% in proximal regions and an underestimation of 3% in distal regions in comparison with the 5 other schemes when using a larger arterial network, published as the ADAN56 model. The authors attributed this difference to the neglection of the dynamic part of the pressure at vessel junctions. Carson et al resolved these differences by proposing 2 methods to implement the dynamic part of the pressure in the simplified trapezium rule method scheme. In the present study, an alternative method is introduced extending the work by Kroon et al. This alternative method consists of a new 0D element, which is placed at vessel junctions. The strength of this new element is the ease of implementation and its flexible coupling with other elements, without introducing additional degrees of freedom or the need of a penalty function. This new approach is compared with 5 other numerical schemes, which already have the dynamic part of the pressure incorporated. The new method shows excellent agreement with these schemes for the ADAN56 model.

Autism risk classification using placental chorionic surface vascular network features.

BACKGROUND: Autism Spectrum Disorder (ASD) is one of the fastest-growing developmental disorders in the United States. It was hypothesized that variations in the placental chorionic surface vascular network (PCSVN) structure may reflect both the overall effects of genetic and environmentally regulated variations in branching morphogenesis within the conceptus and the fetus' vital organs. This paper provides sound evidences to support the study of ASD risks with PCSVN through a combination of feature-selection and classification algorithms. METHODS: Twenty eight arterial and 8 shape-based PCSVN attributes from a high-risk ASD cohort of 89 placentas and a population-based cohort of 201 placentas were examined for ranked relevance using a modified version of the random forest algorithm, called the Boruta method. Principal component analysis (PCA) was applied to isolate principal effects of arterial growth on the fetal surface of the placenta. Linear discriminant analysis (LDA) with a 10-fold cross validation was performed to establish error statistics. RESULTS: The Boruta method selected 15 arterial attributes as relevant, implying the difference in high and low ASD risk can be explained by the arterial features alone. The five principal features obtained through PCA, which accounted for about 88% of the data variability, indicated that PCSVNs associated with placentas of high-risk ASD pregnancies generally had fewer branch points, thicker and less tortuous arteries, better extension to the surface boundary, and smaller branch angles than their population-based counterparts. CONCLUSION: We developed a set of methods to explain major PCSVN differences between placentas associated with high risk ASD pregnancies and those selected from the general population. The research paradigm presented can be generalized to study connections between PCSVN features and other maternal and fetal outcomes such as gestational diabetes and hypertension.

Hemodynamic Impact of the C-Pulse Cardiac Support Device: A One-Dimensional Arterial Model Study.

The C-Pulse is a novel extra-aortic counter-pulsation device to unload the heart in patients with heart failure. Its impact on overall hemodynamics, however, is not fully understood. In this study, the function of the C-Pulse heart assist system is implemented in a one-dimensional (1-D) model of the arterial tree, and central and peripheral pressure and flow waveforms with the C-Pulse turned on and off were simulated. The results were studied using wave intensity analysis and compared with in vivo data measured non-invasively in three patients with heart failure and with invasive data measured in a large animal (pig). In all cases the activation of the C-Pulse was discernible by the presence of a diastolic augmentation in the pressure and flow waveforms. Activation of the device initiates a forward traveling compression wave, whereas a forward traveling expansion wave is associated to the device relaxation, with waves exerting an action in the coronary and the carotid vascular beds. We also found that the stiffness of the arterial tree is an important determinant of action of the device. In settings with reduced arterial compliance, the same level of aortic compression demands higher values of external pressure, leading to stronger hemodynamic effects and enhanced perfusion. We conclude that the 1-D model may be used as an efficient tool for predicting the hemodynamic impact of the C-Pulse system in the entire arterial tree, complementing in vivo observations.

1-D blood flow modelling in a running human body.

In this paper an attempt was made to simulate blood flow in a mobile human arterial network, specifically, in a running human subject. In order to simulate the effect of motion, a previously published immobile 1-D model was modified by including an inertial force term into the momentum equation. To calculate inertial force, gait analysis was performed at different levels of speed. Our results show that motion has a significant effect on the amplitudes of the blood pressure and flow rate but the average values are not effected significantly.

A one-dimensional arterial network model for bypass graft assessment.

We propose an arterial network model based on one-dimensional hemodynamic equations to study the behavior of different vascular surgical bypass grafts in the case of an arterial occlusive pathology: a stenosis of the Right Iliac artery. We investigate the performances of three different bypass grafts (Aorto-Femoral, Axillo-Femoral and cross-over Femoral) depending on the degree of obstruction of the stenosis. Numerical simulations show that all bypass grafts are efficient since we retrieve in each case the healthy hemodynamics downstream of the stenosed region while ensuring at the same time a global healthy circulation. We analyze in detail the behavior of the Axillo-Femoral bypass graft by performing hundreds of simulations where we vary the values of its Young's modulus [0.1-50 MPa] and radius [0.01-5 cm]. Our analysis shows that Young's modulus and radius of commercial bypass grafts are optimal in terms of hemodynamic considerations. Our numerical findings prove that this model approach can be used to optimize or plan patient-specific surgeries, to numerically assess the viability of bypass grafts and to perform parametric analysis and error propagation evaluations by running extensive simulations.

Vascular mapping of the retroauricular skin - proposal for a posterior superior surgical incision for transcutaneous bone-conduction hearing implants.

BACKGROUND: Passive transcutaneous osseointegrated hearing implant systems have become increasingly popular more recently. The area over the implant is vulnerable due to vibration and pressure from the externally worn sound processor. Good perfusion and neural integrity has the potential to reduce complications. The authors' objective was to determine the ideal surgical exposure to maintain perfusion and neural integrity and decrease surgical time as a result of reduced bleeding. METHODS: The vascular anatomy of the temporal-parietal soft tissue was examined in a total of 50 subjects. Imaging diagnostics included magnetic resonance angiography in 12 and Doppler ultrasound in 25 healthy subjects to reveal the arterial network. Cadaver dissection of 13 subjects formed the control group. The prevalence of the arteries were statistically analyzed with sector analysis in the surgically relevant area. RESULTS: The main arterial branches of this region could be well identified with each method. Statistical analysis showed that the arterial pattern was similar in all subjects. The prevalence of major arteries is low in the upper posterior area though large in proximity to the auricle region. CONCLUSIONS: Diverse methods indicate the advantages of a posterior superior incision because the major arteries and nerves are at less risk of damage and best preserved. Although injury to these structures is rare, when it occurs, the distal flow is compromised and the peri-implant area is left intact. Hand-held Doppler is efficient and cost-effective in finding the best position for incision, if necessary, in subjects with a history of surgical stress to the retroauricular skin. TRIAL REGISTRATION: This was a non-interventional study.

Disruption of Cortical Arterial Network is Associated with the Severity of Transient Neurologic Events After Direct Bypass Surgery in Adult Moyamoya Disease.

OBJECTIVE: Transient neurologic events (TNEs) frequently occur after revascularization in adult moyamoya disease (MMD). In the present study, we hypothesized that cortical arterial network disruption may be associated with TNE severity after bypass surgery. METHODS: This retrospective study included 76 hemispheres in 45 consecutive adult patients with MMD who underwent direct revascularization surgery at our institution. We classified cortical arterial network disruption grade (NDG) into the following 4 categories based on angiography: NDG 0, >90% of suprasylvian cortical branches of the middle cerebral artery showed anterograde filling; NDG 1, 50%-90%; NDG 2, <50%; and NDG 3, none. TNE severity was assigned 1 of 4 grades based on symptom duration and clinical features: grade 0, none; grade 1, mild; grade 2, moderate; and grade 3, severe. We evaluated multiple clinical characteristics, including NDG, to identify factors that have a significant association with TNE severity. RESULTS: Of the 73 hemispheres without perioperative ischemic or hemorrhagic complications, the following degrees of TNEs were developed: grade 0, 33%; grade 1, 30%; grade 2, 22%; and grade 3, 15%. We determined that NDG and left-side surgery were significantly associated with TNE severity (P < 0.01 and P = 0.04, respectively). The NDG had excellent interobserver reliability (weighted κ value = 0.96). There were no significant correlations between TNE severity and other clinical backgrounds. CONCLUSIONS: NDG is useful for the prediction of severity of TNEs after revascularization. Disturbed bypass flow spreading may lead to the development of TNEs in adult MMD.

An implicit solver for 1D arterial network models.

In this study, the 1D blood flow equations are solved using a newly proposed enhanced trapezoidal rule method (ETM), which is an extension to the simplified trapezoidal rule method. At vessel junctions, the conservation of mass and conservation of total pressure are held as system constraints using Lagrange multipliers that can be physically interpreted as external flow rates. The ETM scheme is compared with published arterial network benchmark problems and a dam break problem. Strengths of the ETM scheme include being simple to implement, intuitive connection to lumped parameter models, and no restrictive stability criteria such as the Courant-Friedrichs-Lewy (CFL) number. The ETM scheme does not require the use of characteristics at vessel junctions, or for inlet and outlet boundary conditions. The ETM forms an implicit system of equations, which requires only one global solve per time step for pressure, followed by flow rate update on the elemental system of equations; thus, no iterations are required per time step. Consistent results are found for all benchmark cases, and for a 56-vessel arterial network problem, it gives very satisfactory solutions at a spatial and time discretization that results in a maximum CFL of 3, taking 4.44 seconds per cardiac cycle. By increasing the time step and element size to produce a maximum CFL number of 15, the method takes only 0.39 second per cardiac cycle with only a small compromise on accuracy.

Heterogeneous mechanics of the mouse pulmonary arterial network.

Individualized modeling and simulation of blood flow mechanics find applications in both animal research and patient care. Individual animal or patient models for blood vessel mechanics are based on combining measured vascular geometry with a fluid structure model coupling formulations describing dynamics of the fluid and mechanics of the wall. For example, one-dimensional fluid flow modeling requires a constitutive law relating vessel cross-sectional deformation to pressure in the lumen. To investigate means of identifying appropriate constitutive relationships, an automated segmentation algorithm was applied to micro-computerized tomography images from a mouse lung obtained at four different static pressures to identify the static pressure-radius relationship for four generations of vessels in the pulmonary arterial network. A shape-fitting function was parameterized for each vessel in the network to characterize the nonlinear and heterogeneous nature of vessel distensibility in the pulmonary arteries. These data on morphometric and mechanical properties were used to simulate pressure and flow velocity propagation in the network using one-dimensional representations of fluid and vessel wall mechanics. Moreover, wave intensity analysis was used to study effects of wall mechanics on generation and propagation of pressure wave reflections. Simulations were conducted to investigate the role of linear versus nonlinear formulations of wall elasticity and homogeneous versus heterogeneous treatments of vessel wall properties. Accounting for heterogeneity, by parameterizing the pressure/distention equation of state individually for each vessel segment, was found to have little effect on the predicted pressure profiles and wave propagation compared to a homogeneous parameterization based on average behavior. However, substantially different results were obtained using a linear elastic thin-shell model than were obtained using a nonlinear model that has a more physiologically realistic pressure versus radius relationship.

Rational macromodeling of 1D blood flow in the human cardiovascular system.

In this paper, we present a novel rational macromodeling approach for the description of 1D blood flow in the human cardiovascular system, which is suitable for time-domain simulations. Using the analogy of the blood flow propagation problem with transmission lines and considering the hypothesis of linearized Navier-Stokes equations, a frequency-domain rational macromodel for each arterial segment has been built. The poles and the residues of each arterial segment macromodel have been calculated by means of the Vector Fitting technique. Finally, the rational macromodel of the whole cardiovascular system is obtained by properly combining the macromodels of the single arterial segments using an interconnect matrix. The rational form of the proposed cardiovascular model leads to a state-space or electrical circuit model suitable for time-domain analysis. The stability and passivity properties of the global cardiovascular model are discussed to guarantee stable time-domain simulations. The proposed macromodeling approach has been validated by pertinent numerical results. Copyright © 2015 John Wiley & Sons, Ltd.

An integrative model of the cardiovascular system coupling heart cellular mechanics with arterial network hemodynamics.

The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements.

An Integrative Model of the Cardiovascular System Coupling Heart Cellular Mechanics with Arterial Network Hemodynamics

The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements.