Real Blood Flow Research Articles

Enhancing flexibility of smart bioresorbable vascular scaffolds through 3D printing using polycaprolactone and polylactic acid

With the growing use of stent implantations, the risk of in-stent restenosis represents a major concern for cardiovascular patients. Herein, we propose a hybrid bioresorbable vascular scaffold (H-BVS) integrated with a wireless sensor that could enable significant advances in cardiovascular therapeutics. The H-BVS was carefully manufactured using a state-of-the-art customized 3D printer equipped with dual nozzles to achieve a synergistic combination of polycaprolactone (PCL) and polylactic acid (PLA), both of which are known for their bioresorbable properties. This characteristic is particularly valuable in medical applications where the scaffold is gradually absorbed by the body, eliminating the need for a second procedure to remove it. Furthermore, the H-BVS was integrated with a wireless, battery-less LC-type pressure sensor for real-time monitoring of in-stent restenosis. This wireless sensor was meticulously connected with the H-BVS framework through engineered microstructures, which not only ensured a robust bond but also significantly enhanced the overall integrity and functionality of the device. Additionally, the combination of the H-BVS and sensor was optimized to exhibit superior bending flexibility and radial strength, which are key factors in ensuring effectiveness and patient safety. The feasibility of the smart H-BVS (SH-BVS) was verified through comprehensive testing within a phantom system designed to simulate real blood flow conditions. We believe that the SH-BVS system holds strong potential to significantly improve patient monitoring and treatment strategies within the cardiovascular healthcare domain.

A new method to compute the blood flow equations using the physics-informed neural operator

Using the Navier-Stokes equation for real blood flow simulations in patients is a challenging task. Among many of the challenges, initial and boundary conditions are not directly measurable. Many parameters for the flow model are also not directly measurable and differ from patient to patient and over time. New machine learning techniques, like physics-informed neural networks (PINN), offer some new ways to handle these difficulties. In this work, we aim to learn the operator that maps some easily measurable physiological signals to the solution of the blood flow equation. We use our proposed model based on Navier-Stokes equation and PINN to fit real data on blood pressure. A Windkessel boundary condition is used to produce physically correct reflection waves. A time-periodic condition is used to capture the periodicity of blood flow and enables our model to simulate the blood flow without initial and boundary conditions. Furthermore, we allow the periods of each instance of solution to be different, which makes the training of neural operators computationally expensive, but more accuracy and physical correct towards real blood pressure data. Further more, we also propose an efficient implementation to incorporate the periodic condition into our model. Estimating the hyper-parameters in the Navier-Stokes equation is also difficult. We then introduce a hyper-parameter network to estimate these parameters during the training process as well. The blood flow data contains useful information for disease detection and diagnosis, but directly measuring the entire blood flow remains a significant challenge. We apply our proposed method to cuffless blood pressure estimation. More specifically, we aim to predict the blood pressure waveform (continuous blood pressure and velocity in both time and space) from Electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which can be easily measured using wearable devices. Compared to other methods, our method is the first one that can predict blood flow continuously, both with location and time which are valuable for cardio-vascular medical treatments and diagnoses.

A parametric study of the effect of 3D plaque shape on local hemodynamics and implications for plaque instability

The vast majority of heart attacks occur when vulnerable plaques rupture, releasing their lipid content into the blood stream leading to thrombus formation and blockage of a coronary artery. Detection of these unstable plaques before they rupture remains a challenge. Hemodynamic features including wall shear stress (WSS) and wall shear stress gradient (WSSG) near the vulnerable plaque and local inflammation are known to affect plaque instability. In this work, a computational workflow has been developed to enable a comprehensive parametric study detailing the effects of 3D plaque shape on local hemodynamics and their implications for plaque instability. Parameterized geometric 3D plaque models are created within a patient-specific coronary artery tree using a NURBS (non-uniform rational B-splines)-based vascular modeling pipeline. Realistic blood flow features are simulated by using a Navier–Stokes solver within an isogeometric finite-element analysis framework. Near wall hemodynamic quantities such as WSS and WSSG are quantified, and vascular distribution of an inflammatory marker (VCAM-1) is estimated. Results show that proximally skewed eccentric plaques have the most vulnerable combination of high WSS and high positive spatial WSSG, and the presence of multiple lesions increases risk of rupture. The computational tool developed in this work, in conjunction with clinical data, -could help identify surrogate markers of plaque instability, potentially leading to a noninvasive clinical procedure for the detection of vulnerable plaques before rupture.

Artificial intelligence-based speckle featurization and localization for ultrasound speckle tracking velocimetry

Deep learning-based super-resolution ultrasound (DL-SRU) framework has been successful in improving spatial resolution and measuring the velocity field information of a blood flows by localizing and tracking speckle signals of red blood cells (RBCs) without using any contrast agents. However, DL-SRU can localize only a small part of the speckle signals of blood flow owing to ambiguity problems encountered in the classification of blood flow signals from ultrasound B-mode images and the building up of suitable datasets required for training artificial neural networks, as well as the structural limitations of the neural network itself. An artificial intelligence-based speckle featurization and localization (AI-SFL) framework is proposed in this study. It includes a machine learning-based algorithm for classifying blood flow signals from ultrasound B-mode images, dimensionality reduction for featurizing speckle patterns of the classified blood flow signals by approximating them with quantitative values. A novel and robust neural network (ResSU-net) is trained using the online data generation (ODG) method and the extracted speckle features. The super-resolution performance of the proposed AI-SFL and ODG method is evaluated and compared with the results of previous U-net and conventional data augmentation methods under in silico conditions. The predicted locations of RBCs by the AI-SFL and DL-SRU for speckle patterns of blood flow are applied to a PTV algorithm to measure quantitative velocity fields of the flow. Finally, the feasibility of the proposed AI-SFL framework for measuring real blood flows is verified under in vivo conditions.

Fluid-structure interaction study for biomechanics and risk factors in Stanford type A aortic dissection.

Aortic dissection is a life-threatening condition with a rising prevalence in the elderly population, possibly as a consequence of the increasing population life expectancy. Untreated aortic dissection can lead to myocardial infarction, aortic branch malperfusion or occlusion, rupture, aneurysm formation and death. This study aims to assess the potential of a biomechanical model in predicting the risks of a non-dilated thoracic aorta with Stanford type A dissection. To achieve this, a fully coupled fluid-structure interaction model was developed under realistic blood flow conditions. This model of the aorta was developed by considering three-dimensional artery geometry, multiple artery layers, hyperelastic artery wall, in vivo-based physiological time-varying blood velocity profiles, and non-Newtonian blood behaviours. The results demonstrate that in a thoracic aorta with Stanford type A dissection, the wall shear stress (WSS) is significantly low in the ascending aorta and false lumen, leading to potential aortic dilation and thrombus formation. The results also reveal that the WSS is highly related to blood flow patterns. The aortic arch region near the brachiocephalic and left common carotid artery is prone to rupture, showing a good agreement with the clinical reports. The results have been translated into their potential clinical relevance by revealing the role of the stress state, WSS and flow characteristics as the main parameters affecting lesion progression, including rupture and aneurysm. The developed model can be tailored for patient-specific studies and utilised as a predictive tool to estimate aneurysm growth and initiation of wall rupture inside the human thoracic aorta.

Analysis of Blood Flow in the Macula and Optic Nerve Head in Healthy Young Volunteers Using Laser Speckle Flowgraphy.

To assess optic nerve head (ONH) and macular blood flow in young healthy volunteers using laser speckle flowgraphy (LSFG). This is a prospective single-center study conducted at the Department of Ophthalmology, University Hospital Zurich from May to November 2021. Young, healthy men aged ≥ 18 years without ocular or systemic diseases were included. A corrected visual acuity (VA) of 0.0 logMAR or better in both eyes and an intraocular pressure (IOP) of 21 mmHg or lower were required for inclusion. Subjects exceeding a spherical equivalent (SE) of ± 6 diopters (dpt) were excluded. Blood flow in the macula and the ONH was recorded using the Nidek LSFG RetFlow device (Nidek Company, Ltd., Hirioshi-cho, Japan). Laser power was set to 0.5 Millivolts (mV). Mean blur rate (MBR) was recorded as a parameter for blood flow. MBR is a calculated parameter that represents relative blood flow velocity correlated with the real anatomical blood flow rate. Colored heat maps of the recorded retinal area were generated automatically by the RetFlow device. Final analyses included 83 eyes of 43 male volunteers. Mean age was 21.9 years (SD ± 1.5, range: 20 to 29). Mean corrected VA was - 0.1 logMAR (SD ± 0.05, range: - 0.2 to 0.0), mean IOP was 15.4 mmHg (SD ± 2.5, range: 8.5 to 18.5), and mean SE was - 0.3 dpt (SD ± 1.2, range: - 5.0 to 1.2). Mean ONH MBR was 37.44 (SD ± 7.9, range: 22.5 to 53.5) and mean macular MBR was 27.8 (SD ± 9.7, range: 6.4 to 57.7). Pearson's Test showed a strong correlation between macular and papillary blood flow (p < 0.05, coefficient: 0.647). This study provides both ONH and macular blood flow data in a healthy young male population, showing a strong correlation between ONH and macular blood flow in the examined eyes. Further investigations are required to assess the validity of MBR as a parameter for the combined evaluation of retinal blood flow at the macula and ONH in healthy volunteers and patients with various diseases.

Abstract Number ‐ 54: First Fully Automated Robotic Transcranial Doppler Optimization of Cerebral Blood Flow During Cardiac Revascularization Surgery

Introduction Current technologies including EEG and near infrared pulse oximetry for non‐invasive monitoring of cerebral blood flow during cardiac surgery have proven inadequate for perioperative stroke risk mitigation. Cerebral arterial flow velocity is an excellent indicator of cerebral blood flow making transcranial doppler ultrasound (TCD) an excellent alternative technology for operating room continuous cerebral monitoring. To date, TCD utilization in the operating room has been limited due to frequent movement‐related loss of signal requiring nearly continuous manual probe readjustment. The recent development of fully autonomous robotic TCD (aTCD) has overcome these technical limitations, opening the door for real‐time continuous noninvasive cerebral blood flow monitoring with simultaneous emboli detection. Methods A 47‐year‐old female patient was found to have preoperative complete occlusion of the proximal brachiocephalic artery producing a double cerebral steal phenomenon with retrograde flow in the right internal carotid and vertebral arteries into the subclavian. A preoperative aTCD study disclosed baseline markedly diminished blood flow in the right middle cerebral artery (MCA) fed exclusively by small‐diameter collaterals via the circle of Willis.Intraoperatively, robotic aTCD was used to continuously monitor blood flow in the bilateral MCAs and perform emboli detection. In response to movement‐related signal loss, the robotic aTCD autonomously adjusted the probe position to maintain continuous MCA insonation. Results Shortly after intubation, a small drop in mean arterial pressure led to a near‐total loss of cerebral perfusion to the entire right hemisphere. This perfusion decrease was detected by aTCD, triggering the anesthesiologist to rapidly correct blood pressure to ensure adequate cerebral perfusion as confirmed by the robotic system. The patient was then placed on bypass pump with deployment of a temporary Y‐graft from the pump to the subclavian artery distal to the vertebral branch point and to the aorta to temporarily reverse the double cerebral steal. Coronary bypass was then performed, throughout which cerebral flow velocities were monitored continuously with aTCD and maintained in the safe cerebral perfusion range by adjusting pump pressures. Following a three‐vessel coronary bypass graft, permanent brachiocephalic artery bypass grafts were placed from the proximal aorta to the right subclavian and the proximal common carotid artery.Postoperative aTCD disclosed correction of the previously diminished blood flow detected in the right MCA preoperatively. Brain MRI postoperatively confirmed the absence of acute stroke. Conclusions This case represents the first use of robotic aTCD for real time continuous cerebral blood flow monitoring and optimization during complex cardiac surgery. Our experience suggests that aTCD may improve patient outcomes, particularly during high‐risk cardiac surgical and interventional procedures. Further studies of this promising technology are now needed.

Enhancing students' understanding of cardiac physiology by using 4D visualization.

Difficulties in achieving knowledge about physiology and anatomy of the beating heart highlight the challenges with more traditional pedagogical methods. Recent research regarding anatomy education has mainly focused on digital three-dimensional models. However, these pedagogical improvements may not be entirely applicable to cardiac anatomy and physiology due to the multidimensional complexity with moving anatomy and complex blood flow. The aim of this study was therefore to evaluate whether high quality time-resolved anatomical images combined with realistic blood flow simulations improve the understanding of cardiac structures and function. Three time-resolved datasets were acquired using time-resolved computed tomography and blood flow was computed using Computational Fluid Dynamics. The anatomical and blood flow information was combined and interactively visualized using volume rendering on an advanced stereo projection system. The setup was tested in interactive lectures for medical students. Ninety-seven students participated. Summative assessment of examinations showed significantly improved mean score (18.1 ± 4.5 vs 20.3 ± 4.9, p=0.002). This improvement was driven by knowledge regarding myocardial hypertrophy and pressure-velocity differences over a stenotic valve. Additionally, a supplementary formative assessment showed significantly more agreeing answers than disagreeing answers (p < 0.001) when the participants subjectively evaluated the contribution of the visualizations to their education and knowledge. In conclusion, the use of simultaneous visualization of time-resolved anatomy data and simulated blood flow improved medical students' results, with a particular effect on understanding of cardiac physiology and these simulations may be useful educational tools for teaching complex anatomical and physiological concepts.

Computing intracoronary blood flow rate under incomplete boundary conditions: Combing coronary anatomy and fractional flow reserve.

Accurate measurement of intracoronary blood flow rate is of great significance for the diagnosis of ischemic heart disease (IHD). Computational fluid dynamic (CFD) method, combining coronary angiography images and fractional flow reserve (FFR), provides a new way to calculate the mean flow rate. However, due to the incomplete boundary conditions obtained by FFR, side branches were ignored which was likely to have a significant impact on the accuracy. In this paper, a novel CFD based method for calculating the mean intracoronary flow rate under incomplete pressure boundary conditions was proposed, in order to improve the accuracy by including the side branches. A pressure-flow curve based flow resistance model was employed to model resistance of the epicardial arteries. A series of steady flow simulations were performed to extract the parameters of the flow resistance model, which implicitly specified constraints for splitting flow between branches and thus enabled the mean intracoronary blood flow rate to be calculated in two or more branches under incomplete pressure boundary conditions. Simulation experiments were designed to validate the proposed method in both idealized and reconstructed 3D models of coronary branches, and the impact of the assumed coefficient of the Murray's Law for splitting flow between branches was also investigated. The mean percentage error of the proposed method was +2.05%±0.04% for idealized models and +2.24%±0.01% for reconstructed models, and it was much lower than that of the method ignoring side branches (+38.48%±10.45% for idealized models and +30.54%±6.12% for reconstructed models). When the assumed coefficient of the Murray's Law was inconsistent with the real blood flow condition, the percentage errors still maintained less than about 3.00%. The proposed method provided an easy and accurate way to measure the mean intracoronary flow rate and would facilitate the accurate diagnosis of IHD.

Diagnostic biomarker kinetics: how brain-derived biomarkers distribute through the human body, and how this affects their diagnostic significance: the case of S100B

Blood biomarkers of neurological diseases are often employed to rule out or confirm the presence of significant intracranial or cerebrovascular pathology or for the differential diagnosis of conditions with similar presentations (e.g., hemorrhagic vs. embolic stroke). More widespread utilization of biomarkers related to brain health is hampered by our incomplete understanding of the kinetic properties, release patterns, and excretion of molecules derived from the brain. This is, in particular, true for S100B, an astrocyte-derived protein released across the blood–brain barrier (BBB). We developed an open-source pharmacokinetic computer model that allows investigations of biomarker’s movement across the body, the sources of biomarker’s release, and its elimination. This model was derived from a general in silico model of drug pharmacokinetics adapted for protein biomarkers. We improved the model’s predictive value by adding realistic blood flow values, organ levels of S100B, lymphatic and glymphatic circulation, and glomerular filtration for excretion in urine. Three key variables control biomarker levels in blood or saliva: blood–brain barrier permeability, the S100B partition into peripheral organs, and the cellular levels of S100B in astrocytes. A small contribution to steady-state levels of glymphatic drainage was also observed; this mechanism also contributed to the uptake of organs of circulating S100B. This open-source model can also mimic the kinetic behavior of other markers, such as GFAP or NF-L. Our results show that S100B, after uptake by various organs from the systemic circulation, can be released back into systemic fluids at levels that do not significantly affect the clinical significance of venous blood or salivary levels after an episode of BBB disruption.

Beyond Classic Anastomoses Training Models: Overview of Aneurysm Creation in Rodent Vessel Model.

Nowadays, due to the decline in the number of microsurgical clippings for cerebral aneurysms and revascularization procedures, young neurosurgeons have fewer opportunities to participate and train on this type of surgery. Vascular neurosurgery is a demanding subspecialty that requires skills that can only be acquired with technical experience. This background pushes the new generations to be ready for such challenging cases by training hard on different available models, such as synthetic tubes, chicken wings, or placenta vessels. Although many training models for vascular neurosurgery have been described worldwide, one of the best is the rodent vessels model. It offers pulsation, coagulation, and real blood flow conditions in a physiologic atmosphere that mimics perfectly the intracranial human vessels environment, especially in terms of size. However, the current differences in governmental different regulations about the use of living animals in medical experimentation and the social awareness, as well as the lack of financial support, cause more difficulties for neurosurgeons to start with that kind of training. In this review, we describe the tools and techniques as basic steps for vascular microsurgery training by using rodent models, that provide an accurate copy of brain vessels environment under stable conditions. The initial three classical known microanastomoses for neurosurgeons are end-to-end, end-to-side, and side-to-side, but in literature, there have been described other more complex exercises for training and investigation, such as aneurysm models. Although there is still little data available, we aim to summarize and discuss aneurysm's training models and reviewed the current literature on the subject and its applications, including a detailed description of the techniques.

Entropy and stability analysis on blood flow with nanoparticles through a stenosed artery having permeable walls.

In this research, the electro-osmotic effects are highlighted for a blood-based hybrid nanofluid flow across an artery infected with multiple stenosis. The artery has permeable walls together with slip boundary effects. The slip and permeable boundary conditions model the more realistic blood flow problems. The governing equations of the problem are converted into non-dimensional form by introducing adequate dimensionless variables and acquired the exact solutions. The detailed study of heat transfer is given by Joule heating and viscous dissipation effects. The disorder of fluid flow is investigated by the mathematical study of entropy generation. Analytically attained solutions are examined graphically for both symmetric and non-symmetric shapes of stenosis. Streamlines are analyzed for varying values of flow rate Q and electro-osmotic parameter m. The flow velocity has smallest values on the axis of channel and gets higher value near the boundary walls. The temperature profile delineates opposite behavior to the velocity, and it is parabolic in nature. The velocity reduces towards the non-uniform stenosis except for electroosmotic parameter m. The temperature has larger magnitude in the case of anti-symmetric stenosis. Moreover, the stability of velocity solution is also analyzed.

Self-Similar Functional Circuit Models of Arteries and Deterministic Fractal Operators: Theoretical Revelation for Biomimetic Materials.

In this paper, the self-similar functional circuit models of arteries are proposed for bioinspired hemodynamic materials design. Based on the mechanical-electrical analogous method, the circuit model can be utilized to mimic the blood flow of arteries. The theoretical mechanism to quantitatively simulate realistic blood flow is developed by establishing a fractal circuit network with an infinite number of electrical components. We have found that the fractal admittance operator obtained from the minimum repeating unit of the fractal circuit can simply and directly determine the blood-flow regulation mechanism. Furthermore, according to the operator algebra, the fractal admittance operator on the aorta can be represented by Gaussian-type convolution kernel function. Similarly, the arteriolar operator can be described by Bessel-type function. Moreover, by the self-similar assembly pattern of the proposed model, biomimetic materials which contain self-similar circuits can be designed to mimic physiological or pathological states of blood flow. Studies show that the self-similar functional circuit model can efficiently describe the blood flow and provide an available and convenient structural theoretical revelation for the preparation of in vitro hemodynamic bionic materials.

Local hemodynamic analysis after coronary stent implantation based on Euler-Lagrange method.

Coronary stents are deployed to treat the coronary artery disease (CAD) by reopening stenotic regions in arteries to restore blood flow, but the risk of the in-stent restenosis (ISR) is high after stent implantation. One of the reasons is that stent implantation induces changes in local hemodynamic environment, so it is of vital importance to study the blood flow in stented arteries. Based on regarding the red blood cell (RBC) as a rigid solid particle and regarding the blood (including RBCs and plasma) as particle suspensions, a non-Newtonian particle suspensions model is proposed to simulate the realistic blood flow in this work. It considers the blood's flow pattern and non-Newtonian characteristic, the blood cell-cell interactions, and the additional effects owing to the bi-concave shape and rotation of the RBC. Then, it is compared with other four common hemodynamic models (Newtonian single-phase flow model, Newtonian Eulerian two-phase flow model, non-Newtonian single-phase flow model, non-Newtonian Eulerian two-phase flow model), and the comparison results indicate that the models with the non-Newtonian characteristic are more suitable to describe the realistic blood flow. Afterwards, based on the non-Newtonian particle suspensions model, the local hemodynamic environment in stented arteries is investigated. The result shows that the stent strut protrusion into the flow stream would be likely to produce the flow stagnation zone. And the stent implantation can make the pressure gradient distribution uneven. Besides, the wall shear stress (WSS) of the region adjacent to every stent strut is lower than 0.5Pa, and along the flow direction, the low-WSS zone near the strut behind is larger than that near the front strut. What's more, in the regions near the struts in the proximal of the stent, the RBC particle stagnation zone is easy to be formed, and the erosion and deposition of RBCs are prone to occur. These hemodynamic analyses illustrate that the risk of ISR is high in the regions adjacent to the struts in the proximal and the distal ends of the stent when compared with struts in other positions of the stent. So the research can provide a suggestion on the stent design, which indicates that the strut structure in these positions of a stent should be optimized further.

Simulation of intravoxel incoherent perfusion signal using a realistic capillary network of a mouse brain.

To simulate the intravoxel incoherent perfusion magnetic resonance magnitude signal from the motion of blood particles in three realistic vascular network graphs from a mouse brain. In three networks generated from the cortex of a mouse scanned by two-photon laser microscopy, blood flow in each vessel was simulated using Poiseuille's law. The trajectories, flow speeds and phases acquired by a fixed number of simulated blood particles during a Stejskal-Tanner bipolar pulse gradient scheme were computed. The resulting magnitude signal was obtained by integrating all phases and the pseudo-diffusion coefficient D* was estimated by fitting an exponential signal decay. To better understand the anatomical source of the intravoxel incoherent motion (IVIM) perfusion signal, the above was repeated restricting the simulation to various types of vessel. The characteristics of the three microvascular networks were respectively vessel lengths (mean ± std. dev.) 67.2 ± 53.6 μm, 59.8 ± 46.2 μm and 64.5 ± 50.9 μm, diameters 6.0 ± 3.5 μm, 5.7 ± 3.6 μm and 6.1 ± 3.7 μm and simulated blood velocity 0.9 ± 1.7 μm/ms, 1.4 ± 2.5 μm/ms and 0.7 ± 2.1 μm/ms. Exponential fitting of the simulated signal decay as a function of b-value resulted in the following D*-values [10-3 mm2 /s]: 31.7, 40.4 and 33.4. The signal decay for low b-values was the largest in the larger vessels, but the smaller vessels and the capillaries accounted for more of the total volume of the networks. This simulation improves the theoretical understanding of the IVIM perfusion estimation method by directly linking the MR IVIM perfusion signal to an ultra-high resolution measurement of the microvascular network and a realistic blood flow simulation.

A Molecular Communication Detection Method for the Deformability of Erythrocyte Membrane in Blood Vessels.

Molecular communication (MC) inspired drug delivery holds considerable promise as a new design for targeted therapy with high efficiency and minimal toxicity. The process of drug delivery can be modelled in a blood flow-based MC system, where nanoparticles (NPs) carry therapeutic agents through the blood vessel channels to the targeted diseased tissue. Most previous studies in the flow-based MC consider a Newtonian fluid with a laminar flow, which ignores the influence of red blood cells (RBCs). However, the nature of blood flow is a complex and non-Newtonian fluid composed of proteins, platelets, plasma and deformable cells, especially RBCs. The ability to change their shapes is essential to the proper functioning of RBCs in the microvasculature. Different shapes of RBCs have a great impact on the performance of blood flow. Changes in the properties and shapes of RBCs are often associated with different diseases, such as sickle cell anemia, diabetes, and malaria. Thus, it is highly important to establish a more realistic blood flow MC model considering the deformable cells. According to our previous study, the motion and adhesion of individual NPs are modelled through the Brownian adhesion dynamics. Subsequently, this paper establishes a particle-cell hybrid model in the flow-based MC, which focuses on the RBC deformation, aggregation, and dispersion in the blood suspension. Based on the state of the RBC deformation and aggregation in the vessels with different flow rates, this paper proposes a novel methodology for detecting the deformability of the cells. The blood state in terms of RBC deformability is determined by the difference in NPs' concentration at the receiving end., this paper sheds some light on the influence of RBCs on the motion of NPs, which provides new insights on the design of targeted drug delivery and the detection of vascular diseases.

Performance of a Nitinol Honeycomb Stent for the Management of Atherosclerotic Aortic Plaque: Crimping, Sealing, and Fluid–Structure Interaction Analysis

Abstract We present the results of a computational study to investigate the performance of a nitinol honeycomb stent used in the management of an aortic atherosclerotic plaque with 70% stenosis. Such is considered severe and is associated with a higher risk of cardiovascular death. Traditionally, plaque size, composition, shape, and location are thought as important factors in determining the potential for the plaque to rupture (aka plaque vulnerability). The study looks at two plaque shapes and two plaque compositions. The stent used in the simulations is our own design. It compresses and expands due to nitinol’s superelastic property. The human aorta is represented by the Gasser–Ogden–Holzapfel (GOH) model, a sophisticated hyperelastic model which accounts for the dispersion of fibers present in the tissues. We proceed to investigate how the stent–aorta–plaque structure behaves under a physiological blood flow. Results indicate that the stent as designed can sustain realistic blood flow conditions and that hypocellular plaques are more prone to rupture, in agreement with results published in the literature. It also shows that neither plaque composition nor shape affect the wall shear stress (WSS). This study can be useful to surgeons to identify regions of stenotic aorta subjected to high stress, to select the appropriate stent diameter for aortae with plaques with various compositions and plaque shapes, and to decide on the optimal site for stent implantation.

Physical simulation of blood flow in a femoropopliteal artery graft

The paper describes a new experimental setup intended for simulation of blood flow through stenosis or distal end of anastomosis. The setup is able to reproduce flow rate pulsations with a wave form identical to the one of real blood flow during a cardiac cycle, including the high-amplitude antegrade peak and flow reversal. The design of experimental setup provides stable average flow rate in the test section and repeatability of simulated flow regimes.

A fluid–structure interaction analysis of anisotropic Dacron fabric used for aortic replacement

We present the results of a computational study aimed at capturing the behavior over time of Dacron fabric used for surgical correction of aortic aneurysms. The study concerns the problem of compliance mismatch between the graft and the native aorta and is very important to clinicians. The aorta is represented by a sophisticated anisotropic hyperelastic model (GOH), which takes into account the orientation of the collagen fibers. The corrugations present on the Dacron fabric are modeled geometrically using experimental data retrieved from the literature. The viscoelastic behavior of the Dacron graft reported by clinicians is also taken into account. Mechanical quantities experienced by the graft sewn to an aortic segment are obtained using fluid–structure interaction (FSI) simulations assuming realistic blood flow conditions. Both ascending and descending aorta with two curvatures are considered. Results of this study indicate that (i) the strains on the Dacron-aorta structure increase with increasing curvature and over time (ii) the simulations are capable of capturing stress concentrations at the junction of the graft and the aorta and (iii) the wall shear stresses (WSS) are substantially higher on the aortic segment than on the Dacron graft.

P1423INCREASED BLOOD FLOW RATE IN HIGH-FLUX HAEMODIALYSIS - IS IT RELEVANT FOR PHOSPHORUS REMOVAL IN HAEMODIALYSIS PATIENTS?

Abstract Background and Aims High-flux haemodialysis (HD), beside other uremic solutes harmful for patients, controls the level of phosphorus, major factor for HD-related morbidity and mortality. First line in phosphorus control in HD patients is dietary phosphorus intake reduction, whereas its’ removal is undervalued by hemodialysis. The primary objective was to analyse whether change in the rate of blood flow is relevant in phosphorus removal in HD patients. Second objective was to evaluate other variables impacted by higher blood flow rates. Method Retrospective study was conducted enrolling 80 patients from a single center in a period of 12 months. In the first six months, all patients were on lower blood flow rate (LBFR group) than the same patient group was switched to a higher blood flow rate in the following six months (HBFR group). Demographic, clinical and laboratory variables were collected and intra/inter-patient group analysis was performed. Results Forty-seven patients were male, and 41.3% were female. Mean age of the study population was 61.2±13.47 years (males 60.3±13.38, females 62.4±13.68). Mean dialysis vintage was 63.31±66.57 months. The average real blood flow rate in LBFR group was 290.75±19.65 ml/min (median 285.34 ml/min), 344.87±9.12 ml/min in HBFR group (median 339 ml/min), p=0.0002. The level of phosphorus in LBFR group was 1.52±0.03 mmol/L, and 1.45±0.04 in HBFR group, p=0.007. Other variables that significantly showed improvement following the increase of blood flow rate were eKT/V (p=0.0006), urea clearance (p=0.02) and transferrin saturation (p=0.04). The level of post-HD urea (p=0.02) and body surface area (p=0.04) were decreased. Weekly EPO dosage decrease in HBFR group (p=0.02) was not correlated with increased iron sucrose administration (LBFR group 59.99±36.18 mg/wk, HBFR group 65.8±28.7, p=0.45). There were no significant changes related to cardiac function; systolic (p=0.44) and diastolic pressure (p=0.36), mean arterial (p=0.43) and pulse pressure (p=0.26) remained in reference range. Also, the average dose of calcium-based phosphate binders did not change significantly (p=0.34). Conclusion This study showed that increased blood flow rate in HD patients reduces phosphorus and EPO consumption, improves urea clearance without significant impact on cardiac function and calcium overload with calcium-based phosphate binders.