Computational fluid dynamics modelling in cardiovascular medicine

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

Blood Flow Quantification in Peripheral Arterial Disease: Emerging Diagnostic Techniques in Vascular Surgery

The assessment of local blood flow patterns in patients with peripheral arterial disease is clinically relevant, since these patterns are related to atherosclerotic disease progression and loss of patency in stents placed in peripheral arteries, through mechanisms such as recirculating flow and low wall shear stress (WSS). However, imaging of vascular flow in these patients is technically challenging due to the often complex flow patterns that occur near atherosclerotic lesions. While several flow quantification techniques have been developed that could improve the outcomes of vascular interventions, accurate 2D or 3D blood flow quantification is not yet used in clinical practice. This article provides an overview of several important topics that concern the quantification of blood flow in patients with peripheral arterial disease. The hemodynamic mechanisms involved in the development of atherosclerosis and the current clinical practice in the diagnosis of this disease are discussed, showing the unmet need for improved and validated flow quantification techniques in daily clinical practice. This discussion is followed by a showcase of state-of-the-art blood flow quantification techniques and how these could be used before, during and after treatment of stenotic lesions to improve clinical outcomes. These techniques include novel ultrasound-based methods, Phase-Contrast Magnetic Resonance Imaging (PC-MRI) and Computational Fluid Dynamics (CFD). The last section discusses future perspectives, with advanced (hybrid) imaging techniques and artificial intelligence, including the implementation of these techniques in clinical practice.

The new role of diagnostic angiography in coronary physiological assessment

The role of 'stand-alone' coronary angiography (CAG) in the management of patients with chronic coronary syndromes is the subject of debate, with arguments for its replacement with CT angiography on the one hand and its confinement to the interventional cardiac catheter laboratory on the other. Nevertheless, it remains the standard of care in most centres. Recently, computational methods have been developed in which the laws of fluid dynamics can be applied to angiographic images to yield 'virtual' (computed) measures of blood flow, such as fractional flow reserve. Together with the CAG itself, this technology can provide an 'all-in-one' anatomical and functional investigation, which is particularly useful in the case of borderline lesions. It can add to the diagnostic value of CAG by providing increased precision and reduce the need for further non-invasive and functional tests of ischaemia, at minimal cost. In this paper, we place this technology in context, with emphasis on its potential to become established in the diagnostic workup of patients with suspected coronary artery disease, particularly in the non-interventional setting. We discuss the derivation and reliability of angiographically derived fractional flow reserve (CAG-FFR) as well as its limitations and how CAG-FFR could be integrated within existing national guidance. The assessment of coronary physiology may no longer be the preserve of the interventional cardiologist.

The Hemodynamics of Patent Ductus Arteriosus in Patients after Central Shunt Operation

A central shunt (CS) was an important surgery of systemic-to-pulmonary shunt (SPS) for the treatment of complex congenital heart diseases with decreased pulmonary blood flow (CCHDs-DPBF). There was no clear conclusion on how to deal with unclosed patent ductus arteriosus (PDA) during CS surgery. This study expanded the knowledge base on PDA by exploring the influence of the closing process of the PDA on the hemodynamic parameters for the CS model. The initial three-dimensional (3D) geometry was reconstructed based on the patient's computed tomography (CT) data. Then, a CS configuration with three typical pulmonary artery (PA) dysplasia structures and different sizes of PDA was established. The three-element windkessel (3WK) multiscale coupling model was used to define boundary conditions for transient simulation through computational fluid dynamics (CFD). The results showed that the larger size of PDA led to a greater systemic-to-pulmonary shunt ratio (Q _S/A), and the flow ratio of the left pulmonary artery (LPA) to right pulmonary artery (RPA) (Q _L/R) was more close to 1, while both the proportion of high wall shear stress (WSS) areas and power loss decreased. The case of PDA nonclosure demonstrates that the aortic oxygen saturation (Sao₂) increased, while the systemic oxygen delivery (Do₂) decreased. In general, for the CS model with three typical PA dysplasia, the changing trends of hemodynamic parameters during the spontaneous closing process of PDA were roughly identical, and nonclosure of PDA had a series of hemodynamic advantages, but a larger PDA may cause excessive PA perfusion and was not conducive to reducing cyanosis symptoms.

Agreement of Angiography-Derived and Wire-Based Fractional Flow Reserves in Percutaneous Coronary Intervention

Background: Coronary angiography-derived fractional flow reserve (caFFR) measurements have shown good correlations and agreement with invasive wire-based fractional flow reserve (FFR) measurements. However, few studies have examined the diagnostic performance of caFFR measurements before and after percutaneous coronary intervention (PCI). This study sought to compare the diagnostic performance of caFFR measurements against wire-based FFR measurements in patients before and after PCI.

Methods: Patients who underwent FFR-guided PCI were eligible for the acquisition of caFFR measurements. Offline caFFR measurements were performed by blinded hospital operators in a core laboratory. The primary endpoint was the vessel-oriented composite endpoint (VOCE), defined as a composite of vessel-related cardiovascular death, vessel-related myocardial infarction, and target vessel revascularization.

Results: A total of 105 pre-PCI caFFR measurements and 65 post-PCI caFFR measurements were compared against available wire-based FFR measurements. A strong linear correlation was found between wire-based FFR and caFFR measurements (r = 0.77; p < 0.001) before PCI, and caFFR measurements also showed a high correlation (r = 0.82; p < 0.001) with wire-based FFR measurements after PCI. A total of 6 VOCEs were observed in 61 patients during follow-up. Post-PCI FFR values (≤0.82) in the target vessel was the strongest predictor of VOCE [hazard ratio (HR): 5.59; 95% confidence interval (CI): 1.12–27.96; p = 0.036). Similarly, patients with low post-PCI caFFR values (≤0.83) showed an 8-fold higher risk of VOCE than those with high post-PCI caFFR values (>0.83; HR: 8.83; 95% CI: 1.46–53.44; p = 0.017).

Conclusion: The study showed that the caFFR measurements were well-correlated and in agreement with invasive wire-based FFR measurements before and after PCI. Similar to wire-based FFR measurements, post-PCI caFFR measurements can be used to identify patients with a higher risk for adverse events associated with PCI.

Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function

In order to simulate the cardiac function for a patient-specific geometry, the generation of the computational mesh is crucially important. In practice, the input is typically a set of unprocessed polygonal surfaces coming either from a template geometry or from medical images. These surfaces need ad-hoc processing to be suitable for a volumetric mesh generation. In this work we propose a set of new algorithms and tools aiming to facilitate the mesh generation process. In particular, we focus on different aspects of a cardiac mesh generation pipeline: (1) specific polygonal surface processing for cardiac geometries, like connection of different heart chambers or segmentation outputs; (2) generation of accurate boundary tags; (3) definition of mesh-size functions dependent on relevant geometric quantities; (4) processing and connecting together several volumetric meshes. The new algorithms-implemented in the open-source software vmtk-can be combined with each other allowing the creation of personalized pipelines, that can be optimized for each cardiac geometry or for each aspect of the cardiac function to be modeled. Thanks to these features, the proposed tools can significantly speed-up the mesh generation process for a large range of cardiac applications, from single-chamber single-physics simulations to multi-chambers multi-physics simulations. We detail all the proposed algorithms motivating them in the cardiac context and we highlight their flexibility by showing different examples of cardiac mesh generation pipelines.

Computational Analysis of the Pulmonary Arteries in Congenital Heart Disease: A Review of the Methods and Results

With the help of computational fluid dynamics (CFD), hemodynamics of the pulmonary arteries (PA's) can be studied in detail and varying physiological circumstances and treatment options can be simulated. This offers the opportunity to improve the diagnostics and treatment of PA stenosis in biventricular congenital heart disease (CHD). The aim of this review was to evaluate the methods of computational studies for PA's in biventricular CHD and the level of validation of the numerical outcomes. A total of 34 original research papers were selected. The literature showed a great variety in the used methods for (re) construction of the geometry as well as definition of the boundary conditions and numerical setup. There were 10 different methods identified to define inlet boundary conditions and 17 for outlet boundary conditions. A total of nine papers verified their CFD outcomes by comparing results to clinical data or by an experimental mock loop. The diversity in used methods and the low level of validation of the outcomes result in uncertainties regarding the reliability of numerical studies. This limits the current clinical utility of CFD for the study of PA flow in CHD. Standardization and validation of the methods are therefore recommended.

On the relevance of boundary conditions and viscosity models in blood flow simulations in patient-specific aorto-coronary bypass models

Physiologically realistic results are the aim of every blood flow simulation. This is not different in aorto-coronary bypasses where the properties of the coronary circulation may significantly affect the relevance of the performed simulations. By considering three patient-specific bypass geometries, the present article focuses on two aspects of the coronary blood flow - its phasic flow pattern and its behaviour affected by blood rheology. For the phasic flow property, a multiscale modelling approach is chosen as a means to assess the ability of five different types of coronary boundary conditions (mean arterial pressure, Windkessel model and three lumped parameter models) to attain realistic coronary haemodynamics. From the analysed variants of boundary conditions, the best option in terms of physiological characteristics and its potential for use in patient-based simulations, is utilised to account for the effect of shear-dependent viscosity on the resulting haemodynamics and wall shear stress stimulation. Aside from the Newtonian model, the blood rheology is approximated by two non-Newtonian models in order to determine whether the choice of a viscosity model is important in simulations involving coronary circulation. A comprehensive analysis of obtained results demonstrated notable superiority of all lumped parameter models, especially in comparison to the constant outlet pressure, which regardless of bypass type gave overestimated and physiologically misleading results. In terms of rheology, it was noted that blood in undamaged coronary arteries behaves as a Newtonian fluid, whereas in vessels with atypical lumen geometry, such as that of anastomosis or stenosis, its shear-thinning behaviour should not be ignored.

Mending a broken heart: In vitro, in vivo and in silico models of congenital heart disease

Birth defects contribute to ∼0.3% of global infant mortality in the first month of life, and congenital heart disease (CHD) is the most common birth defect among newborns worldwide. Despite the significant impact on human health, most treatments available for this heterogenous group of disorders are palliative at best. For this reason, the complex process of cardiogenesis, governed by multiple interlinked and dose-dependent pathways, is well investigated. Tissue, animal and, more recently, computerized models of the developing heart have facilitated important discoveries that are helping us to understand the genetic, epigenetic and mechanobiological contributors to CHD aetiology. In this Review, we discuss the strengths and limitations of different models of normal and abnormal cardiogenesis, ranging from single-cell systems and 3D cardiac organoids, to small and large animals and organ-level computational models. These investigative tools have revealed a diversity of pathogenic mechanisms that contribute to CHD, including genetic pathways, epigenetic regulators and shear wall stresses, paving the way for new strategies for screening and non-surgical treatment of CHD. As we discuss in this Review, one of the most-valuable advances in recent years has been the creation of highly personalized platforms with which to study individual diseases in clinically relevant settings.

Wall Shear Stress Topological Skeleton Analysis in Cardiovascular Flows: Methods and Applications

A marked interest has recently emerged regarding the analysis of the wall shear stress (WSS) vector field topological skeleton in cardiovascular flows. Based on dynamical system theory, the WSS topological skeleton is composed of fixed points, i.e., focal points where WSS locally vanishes, and unstable/stable manifolds, consisting of contraction/expansion regions linking fixed points. Such an interest arises from its ability to reflect the presence of near-wall hemodynamic features associated with the onset and progression of vascular diseases. Over the years, Lagrangian-based and Eulerian-based post-processing techniques have been proposed aiming at identifying the topological skeleton features of the WSS. Here, the theoretical and methodological bases supporting the Lagrangian- and Eulerian-based methods currently used in the literature are reported and discussed, highlighting their application to cardiovascular flows. The final aim is to promote the use of WSS topological skeleton analysis in hemodynamic applications and to encourage its application in future mechanobiology studies in order to increase the chance of elucidating the mechanistic links between blood flow disturbances, vascular disease, and clinical observations.

Digital Twins for Tissue Culture Techniques—Concepts, Expectations, and State of the Art

Techniques to provide in vitro tissue culture have undergone significant changes during the last decades, and current applications involve interactions of cells and organoids, three-dimensional cell co-cultures, and organ/body-on-chip tools. Efficient computer-aided and mathematical model-based methods are required for efficient and knowledge-driven characterization, optimization, and routine manufacturing of tissue culture systems. As an alternative to purely experimental-driven research, the usage of comprehensive mathematical models as a virtual in silico representation of the tissue culture, namely a digital twin, can be advantageous. Digital twins include the mechanistic of the biological system in the form of diverse mathematical models, which describe the interaction between tissue culture techniques and cell growth, metabolism, and the quality of the tissue. In this review, current concepts, expectations, and the state of the art of digital twins for tissue culture concepts will be highlighted. In general, DT’s can be applied along the full process chain and along the product life cycle. Due to the complexity, the focus of this review will be especially on the design, characterization, and operation of the tissue culture techniques.

Application of physics-based flow models in cardiovascular medicine: Current practices and challenges

Personalized physics-based flow models are becoming increasingly important in cardiovascular medicine. They are a powerful complement to traditional methods of clinical decision-making and offer a wealth of physiological information beyond conventional anatomic viewing using medical imaging data. These models have been used to identify key hemodynamic biomarkers, such as pressure gradient and wall shear stress, which are associated with determining the functional severity of cardiovascular diseases. Importantly, simulation-driven diagnostics can help researchers understand the complex interplay between geometric and fluid dynamic parameters, which can ultimately improve patient outcomes and treatment planning. The possibility to compute and predict diagnostic variables and hemodynamics biomarkers can therefore play a pivotal role in reducing adverse treatment outcomes and accelerate development of novel strategies for cardiovascular disease management.

Characterization of Vortex Flow in a Mouse Model of Ventricular Dyssynchrony by Plane-Wave Ultrasound Using Hexplex Processing

The rodent heart is frequently used to study human cardiovascular disease (CVD). Although advanced cardiovascular ultrasound imaging methods are available for human clinical practice, application of these techniques to small animals remains limited due to the temporal and spatial-resolution demands. Here, an ultrasound vector-flow workflow is demonstrated that enables visualization and quantification of the complex hemodynamics within the mouse heart. Wild type (WT) and fibroblast growth factor homologous factor 2 (FHF2)-deficient mice (Fhf2 ^KO/Y ), which present with hyperthermia-induced ECG abnormalities highly reminiscent of Brugada syndrome, were used as a mouse model of human CVD. An 18-MHz linear array was used to acquire high-speed (30 kHz), plane-wave data of the left ventricle (LV) while increasing core body temperature up to 41.5 °C. Hexplex (i.e., six output) processing of the raw data sets produced the output of vector-flow estimates (magnitude and phase); B-mode and color-Doppler images; Doppler spectrograms; and local time histories of vorticity and pericardium motion. Fhf2 ^WT/Y mice had repeatable beat-to-beat cardiac function, including vortex formation during diastole, at all temperatures. In contrast, Fhf2 ^KO/Y mice displayed dyssynchronous contractile motion that disrupted normal inflow vortex formation and impaired LV filling as temperature rose. The hexplex processing approach demonstrates the ability to visualize and quantify the interplay between hemodynamic and mechanical function in a mouse model of human CVD.

Healthy and diseased in vitro models of vascular systems

Irregular hemodynamics affects the progression of various vascular diseases, such atherosclerosis or aneurysms. Despite the extensive hemodynamics studies on animal models, the inter-species differences between humans and animals hamper the translation of such findings. Recent advances in vascular tissue engineering and the suitability of in vitro models for interim analysis have increased the use of in vitro human vascular tissue models. Although the effect of flow on endothelial cell (EC) pathophysiology and EC-flow interactions have been vastly studied in two-dimensional systems, they cannot be used to understand the effect of other micro- and macro-environmental parameters associated with vessel wall diseases. To generate an ideal in vitro model of the vascular system, essential criteria should be included: 1) the presence of smooth muscle cells or perivascular cells underneath an EC monolayer, 2) an elastic mechanical response of tissue to pulsatile flow pressure, 3) flow conditions that accurately mimic the hemodynamics of diseases, and 4) geometrical features required for pathophysiological flow. In this paper, we review currently available in vitro models that include flow dynamics and discuss studies that have tried to address the criteria mentioned above. Finally, we critically review in vitro fluidic models of atherosclerosis, aneurysm, and thrombosis.

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.

Hemodynamic Modeling of Biological Aortic Valve Replacement Using Preoperative Data Only

Objectives: Prediction of aortic hemodynamics after aortic valve replacement (AVR) could help optimize treatment planning and improve outcomes. This study aims to demonstrate an approach to predict postoperative maximum velocity, maximum pressure gradient, secondary flow degree (SFD), and normalized flow displacement (NFD) in patients receiving biological AVR.

Methods: Virtual AVR was performed for 10 patients, who received actual AVR with a biological prosthesis. The virtual AVRs used only preoperative anatomical and 4D flow MRI data. Subsequently, computational fluid dynamics (CFD) simulations were performed and the abovementioned hemodynamic parameters compared between postoperative 4D flow MRI data and CFD results.

Results: For maximum velocities and pressure gradients, postoperative 4D flow MRI data and CFD results were strongly correlated (R² = 0.75 and R² = 0.81) with low root mean square error (0.21 m/s and 3.8 mmHg). SFD and NFD were moderately and weakly correlated at R² = 0.44 and R² = 0.20, respectively. Flow visualization through streamlines indicates good qualitative agreement between 4D flow MRI data and CFD results in most cases.

Conclusion: The approach presented here seems suitable to estimate postoperative maximum velocity and pressure gradient in patients receiving biological AVR, using only preoperative MRI data. The workflow can be performed in a reasonable time frame and offers a method to estimate postoperative valve prosthesis performance and to identify patients at risk of patient-prosthesis mismatch preoperatively. Novel parameters, such as SFD and NFD, appear to be more sensitive, and estimation seems harder. Further workflow optimization and validation of results seems warranted.

4D flow evaluation of blood non-Newtonian behavior in left ventricle flow analysis

Blood is generally modeled as a Newtonian fluid, assuming a standard and constant viscosity; however, this assumption may not hold for the highly pulsatile and recirculating intracavitary flow in the left ventricle (LV), hampering the quantification of fluid dynamic indices of potential clinical relevance. Herein, we investigated the effect of three viscosity models on the patient-specific quantification of LV blood energetics, namely on viscous energy loss (EL), from 4D Flow magnetic resonance imaging: I) Newtonian with standard viscosity (3.7 cP), II) Newtonian with subject-specific hematocrit-dependent viscosity, III) non-Newtonian accounting for the effect of hematocrit and shear rate. Analyses were performed on 5 controls and 5 patients with cardiac light-chain amyloidosis. In Model II, viscosity ranged between 3.0 (-19%) and 4.3 cP (+16%), mildly deviating from the standard value. In the non-Newtonian model, this effect was emphasized: viscosity ranged from 3.2 to 6.0 cP, deviating maximally from the standard value in low shear rate (i.e., <100 s^-1) regions. This effect reflected on EL quantifications: in particular, as compared to Model I, Model III yielded markedly higher EL values (up to +40%) or markedly lower (down to -21%) for subjects with hematocrit higher than 39.5% and lower than 30%, respectively. Accounting for non-Newtonian blood behavior on a patient-specific basis may enhance the accuracy of intracardiac energetics assessment by 4D Flow, which may be explored as non-invasive index to discriminate between healthy and pathologic LV.

Review of Current Advances in the Mechanical Description and Quantification of Aortic Dissection Mechanisms

Aortic dissection is a life-threatening event associated with a very poor outcome. A number of complex phenomena are involved in the initiation and propagation of the disease. Advances in the comprehension of the mechanisms leading to dissection have been made these last decades, thanks to improvements in imaging and experimental techniques. However, the micro-mechanics involved in triggering such rupture events remains poorly described and understood. It constitutes the primary focus of the present review. Towards the goal of detailing the dissection phenomenon, different experimental and modeling methods were used to investigate aortic dissection, and to understand the underlying phenomena involved. In the last ten years, research has tended to focus on the influence of microstructure on initiation and propagation of the dissection, leading to a number of multiscale models being developed. This review brings together all these materials in an attempt to identify main advances and remaining questions.

Testing a Patient-Specific In-Silico Model to Noninvasively Estimate Central Blood Pressure

PURPOSE

To show some preliminary results about the possibility to exploit a cardiovascular mathematical model-made patient-specific by noninvasive data routinely measured during ordinary clinical examinations-in order to obtain sufficiently accurate central blood pressure (BP) estimates.

METHODS

A closed-loop multiscale (0D and 1D) model of the cardiovascular system is made patient-specific by using as model inputs the individual mean heart rate and left-ventricular contraction time, weight, height, age, sex and mean/pulse brachial BPs. The resulting framework is used to determine central systolic, diastolic, mean and pulse pressures, which are compared with the beat-averaged invasive pressures of 12 patients aged 72 ± 6.61 years.

RESULTS

Errors in central systolic, diastolic, mean and pulse pressures by the model are 4.26 ± 2.81, 5.86 ± 4.38, 4.98 ± 3.95 and 3.51±2.38 mmHg, respectively.

CONCLUSION

The proposed modeling approach shows a good patient-specific response and appears to be potentially useful in clinical practice. However, this approach needs to be evaluated in a larger cohort of patients and could possibly be improved through more accurate oscillometric BP measurement methods.

Novel CFD modeling approaches to assessing urine flow in prostatic urethra after transurethral surgery

Assessment of the pressure and velocity of urine flow for different diameter ratios of prostatic urethra (RPU) after transurethral surgery using computational fluid dynamics (CFD). A standardized and idealized two-dimensional CFD model after transurethral surgery (CATS-1st) was developed for post-surgery mid-voiding. Using CATS-1st, 210 examples were amplified according to an array of size [3][5][14], which contained three groups of longitudinal diameters of prostatic urethra (LD-PU). Each of these groups contained five subgroups of transverse diameters of the bladder neck (TD-BN), each with 14 examples of transverse diameters of PU (TD-PU). The pressure and velocity of urine flow were monitored through flow dynamics simulation, and the relationship among RPU-1 (TD-PU/TD-BN), RPU-2 (RPU-1/LD-PU), the transverse diameter of the vortex, and the midpoint velocity of the external urethral orifice (MV-EUO) was determined. A total of 210 CATS examples, including CATS-1st examples, were analyzed. High (bladder and PU) and medium/low (the rest of the urethra) pressure zones, and low (bladder), medium (PU), and high (the rest of the urethra) velocity zones were determined. The rapid changes in the velocity were concentrated in and around the PU. Laminar flow was present in all the examples. The vortices appeared and then gradually shrank with reducing RPU on both the sides of PU in 182 examples. In the vortex examples, minimum RPU-1 and RPU-2 reached close to the values of 0.79 and 0.02, respectively. MV-EUO increased gradually with decreasing RPU. In comparison to the vortex examples, the non-vortex examples exhibited a significantly higher (p < 0.01) MV-EUO. The developed CFD models (CATS) presented an effective simulation of urine flow behavior within the PU after transurethral surgery for benign prostatic hyperplasia (BPH). These models could prove to be useful for morphological repair in PU after transurethral surgery.

An Introduction to Biomedical Computational Fluid Dynamics

Computational fluid dynamics (CFD) is a tool that has been used by engineers for over 50 years to analyse heat transfer and fluid flow phenomena. In recent years, there have been rapid developments in biomedical and health research applications of CFD. It has been used to evaluate drug delivery systems, analyse physiological flows (e.g. laryngeal jet flow), facilitate surgical planning (e.g. management of intracranial aneurysms), and develop medical devices (e.g. vascular stents and valve prostheses). Due to the complexity of these fluid flows, it demands an interdisciplinary approach consisting of engineers, computer scientists, and mathematicians to develop the computer programs and software used to solve the mathematical equations. Advances in technology and decreases in computational cost are allowing CFD to be more widely accessible and therefore used in more varied contexts. Cardiovascular medicine is the most common area of biomedical research in which CFD is currently being used, followed closely by upper and lower respiratory tract medicine. CFD is also being used in research investigating cerebrospinal fluid, synovial joints, and intracellular fluid. Although CFD can provide meaningful and aesthetically pleasing outputs, interpretation of the data can be challenging for those without a strong understanding of mathematical and engineering principles. Future development and evolution of computational medicine will therefore require close collaboration between experts in engineering, computer science, and biomedical research. This chapter aims to introduce computational fluid dynamics and present the reader with the basics of biological fluid properties, the CFD method, and its applications within biomedical research through published examples, in hope of bridging knowledge gaps in this rapidly emerging method of biomedical analysis.

Big Data and Actuarial Science

This article investigates the impact of big data on the actuarial sector. The growing fields of applications of data analytics and data mining raise the ability for insurance companies to conduct more accurate policy pricing by incorporating a broader variety of data due to increased data availability. The analyzed areas of this paper span from automobile insurance policy pricing, mortality and healthcare modeling to estimation of harvest-, climate- and cyber risk as well as assessment of catastrophe risk such as storms, hurricanes, tornadoes, geomagnetic events, earthquakes, floods, and fires. We evaluate the current use of big data in these contexts and how the utilization of data analytics and data mining contribute to the prediction capabilities and accuracy of policy premium pricing of insurance companies. We find a high penetration of insurance policy pricing in almost all actuarial fields except in the modeling and pricing of cyber security risk due to lack of data in this area and prevailing data asymmetries, for which we identify the application of artificial intelligence, in particular machine learning techniques, as a possible solution to improve policy pricing accuracy and results.

Novel measurement tool and model for aberrant urinary stream in 3D printed urethras derived from human tissue

Background

An estimated 10% of male adults have split or dribbled stream leading to poor hygiene, embarrassment, and inconvenience. There is no current metric that measures male stream deviation.

Objective

To develop a novel method to measure spray in normal and abnormal anatomical conformations.

Design, setting, and participants

We developed a novel platform to reliably describe spray. We used cadaveric tissues and 3D Printed models to study the impact of meatal shape on the urinary stream. Cadaveric penile tissue and 3D printed models were affixed to a fluid pump and used to simulate micturition. Dye captured on fabric allowed for spray detection.

Outcome measurements and statistical analysis

Spray pattern area, deviation from normal location, and flowrates were recorded. Computational fluid dynamic models were created to study fluid vorticity.

Results and limitations

Obstructions at the penile tip worsened spray dynamics and reduced flow. Ventral meatotomy improved flowrate (p<0.05) and reduced spray (p<0.05) compared to tips obstructed ventrally, dorsally or in the fossa navicularis. 3D models do not fully reproduce parameters of their parent cadaver material. The average flowrate from 3D model was 10ml/sec less than that of the penis from which it was derived (p = 0.03). Nonetheless, as in cadavers, increasing obstruction in 3D models leads to the same pattern of reduced flowrate and worse spray. Dynamic modeling revealed increasing distal obstruction was correlated to higher relative vorticity observed at the urethral tip.

Conclusions

We developed a robust method to measure urine spray in a research setting. Dynamic 3D printed models hold promise as a methodology to study common pathologies in the urethra and corrective surgeries on the urine stream that would not be feasible in patients. These novel methods require further validation, but offer promise as a research and clinical tool.

Effect of microcirculatory resistance on coronary blood flow and instantaneous wave-free ratio: A computational study

BACKGROUND AND OBJECTIVE

The instantaneous wave-free ratio (iFR) has been proposed to estimate the hemodynamic severity of atherosclerotic stenosis in coronary arteries. The atherosclerotic stenosis in a proximal coronary artery could change its distal microcirculatory resistance (MR). However, there is a lack of investigation about the effect of MR variation on the blood flow and iFR of stenotic coronary arteries. We aim to investigate the changes of blood flow and iFR caused by distal MR variation.

METHODS

Four three-dimensional models of coronary arteries were reconstructed from the computed tomography images of two normal cases and two cases with 74.9% and 96.4% (in area) stenoses in a large branch of left anterior descending artery (LAD). Computational fluid dynamics simulation was performed on each model under 6 MR situations: hyperemia as the reference situation, resting when MR was multiplied by 8/3 in all outlet branches, h-one-1.5 and h-one-2 when MR was multiplied by 1.5 and 2.0 in one branch (the stenotic, or the corresponding branch in normal case) of LAD, h-branches-1.5 and h-branches-2 when MR was multiplied by 1.5 and 2.0 in the stenotic/corresponding and its cognate branches. Flow rate and iFR of each outlet branch were then calculated and compared between different MR situations to investigate the effect of MR variation on flow rate and iFR.

RESULTS

In the 74.9% stenosed and normal cases, referring to the hyperemia situation, the increase of MR in any branch significantly decreased its flow rate and increased its iFR, with limited effect on the flow rate (<3%) and iFR (<0.01) of other branches. However, in the 96.4% stenosed case, the doubled MR in the stenosed branch (h-one-2) significantly increased the flow rate (>10%) and iFR (>0.05) of its cognate branches.

CONCLUSION

The increase of MR in a normal or mildly stenosed branch of coronary artery decreases its blood flow and increases its iFR, with limited effect on other branches. Whereas, the increase of MR in a severely stenotic large branch could significantly increase the flow velocity and iFR of its cognate branches.

Retrograde branched extension limb assembling stent of pararenal abdominal aortic aneurysm: A longitudinal hemodynamic analysis for stent graft migration

PURPOSE

Pararenal abdominal aortic aneurysms (PRAAAs) are a life-threatening disease, and hemodynamic analysis may provide greater insight into the effectiveness and long-term outcomes of endovascular aneurysm repair (EVAR). However, the lack of patient-specific boundary conditions on the periphery compromises the accuracy. Windkessel (WK) boundary conditions coupled to hemodynamic follow-up models of a PRAAA patient, aims to provide insights into the link between hemodynamics and poor prognosis.

METHOD

One PRAAA patient underwent EVAR and reintervention after one branch of stent-graft (SG) had migrated. Totally five computational follow-up models were studied. Patient-specific flow data acquired via ultrasound were used to define the boundary conditions in the ascending aorta and the following three branches. Coupled zero-dimensional WK models representing the distal vasculature were used to define the outlet boundary conditions under the abdomen.

RESULTS

Flow divisions of the main SG branches were 40.7% and 24.7%, respectively. Time-averaged wall shear stress and oscillatory shear index (OSI) increased at the junction connected the SG branch and the stent leading to the right common iliac artery (RCIA) where the stent migrated. The OSI and relative residence time (RRT) value in superior mesenteric artery increased notably after the migration, the RRT continuously increased following the reintervention.

CONCLUSION

Unbalanced flow, resulting in locally high-speed flow, high WSS and OSI might significantly affect stent stability. Results suggest that diameters and interconnection design of stents in complex cases should take the flow division into consideration and computational simulations might be considered as a tool for intervention protocol design.

An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

Cardiovascular diseases account for the number one cause of deaths in the world. Part of the reason for such grim statistics is our limited understanding of the underlying mechanisms causing these devastating pathologies, which is made difficult by the invasiveness of the procedures associated with their diagnosis (e.g., inserting catheters into the coronal artery to measure blood flow to the heart). Likewise, it is also difficult to design and test assistive devices without implanting them in vivo. However, with the recent advancements made in biomedical scanning technologies and computer simulations, image-based modeling (IBM) has arisen as the next logical step in the evolution of non-invasive patient-specific cardiovascular medicine. Yet, due to its novelty, it is still relatively unknown outside of the niche field. Therefore, the goal of this manuscript is to review the current state-of-the-art and the limitations of the methods used in this area of research, as well as their applications to personalized cardiovascular investigations and treatments. Specifically, the modeling of three different physics – electrophysiology, biomechanics and hemodynamics – used in the cardiovascular IBM is discussed in the context of the physiology that each one of them describes and the mechanisms of the underlying cardiac diseases that they can provide insight into. Only the “bare-bones” of the modeling approaches are discussed in order to make this introductory material more accessible to an outside observer. Additionally, the imaging methods, the aspects of the unique cardiac anatomy derived from them, and their relation to the modeling algorithms are reviewed. Finally, conclusions are drawn about the future evolution of these methods and their potential toward revolutionizing the non-invasive diagnosis, virtual design of treatments/assistive devices, and increasing our understanding of these lethal cardiovascular diseases.

Combining statistical shape modeling, CFD, and meta-modeling to approximate the patient-specific pressure-drop across the aortic valve in real-time

BACKGROUND

Advances in medical imaging, segmentation techniques, and high performance computing have stimulated the use of complex, patient-specific, three-dimensional Computational Fluid Dynamics (CFD) simulations. Patient-specific, CFD-compatible geometries of the aortic valve are readily obtained. CFD can then be used to obtain the patient-specific pressure-flow relationship of the aortic valve. However, such CFD simulations are computationally expensive, and real-time alternatives are desired.

AIM

The aim of this work is to evaluate the performance of a meta-model with respect to high-fidelity, three-dimensional CFD simulations of the aortic valve.

METHODS

Principal component analysis was used to build a statistical shape model (SSM) from a population of 74 iso-topological meshes of the aortic valve. Synthetic meshes were created with the SSM, and steady-state CFD simulations at flow-rates between 50 and 650 mL/s were performed to build a meta-model. The meta-model related the statistical shape variance, and flow-rate to the pressure-drop.

RESULTS

Even though the first three shape modes account for only 46% of shape variance, the features relevant for the pressure-drop seem to be captured. The three-mode shape-model approximates the pressure-drop with an average error of 8.8% to 10.6% for aortic valves with a geometric orifice area below 150 mm² . The proposed methodology was least accurate for aortic valve areas above 150 mm² . Further reduction to a meta-model introduces an additional 3% error.

CONCLUSIONS

Statistical shape modeling can be used to capture shape variation of the aortic valve. Meta-models trained by SSM-based CFD simulations can provide an estimate of the pressure-flow relationship in real-time.

Haemodynamic assessment of bicuspid aortic valve aortopathy: a systematic review of the current literature

Both genetic and haemodynamic theories explain the aetiology, progression and optimal management of bicuspid aortic valve aortopathy. In recent years, the haemodynamic theory has been explored with the help of magnetic resonance imaging and computational fluid dynamics. The objective of this review was to summarize the findings of these investigations with focus on the blood flow pattern and associated variables, including flow eccentricity, helicity, flow displacement, cusp opening angle, systolic flow angle, wall shear stress (WSS) and oscillatory shear index. A structured literature review was performed from January 1990 to January 2018 and revealed the following 3 main findings: (i) the bicuspid aortic valve is associated with flow eccentricity and helicity in the ascending aorta compared to healthy and diseased tricuspid aortic valve, (ii) flow displacement is easier to obtain than WSS and has been shown to correlate with valve morphology and type of aortopathy and (iii) the stenotic bicuspid aortic valve is associated with elevated WSS along the greater curvature of the ascending aorta, where aortic dilatation and aortic wall thinning are commonly found. We conclude that new haemodynamic variables should complement ascending aorta diameter as an indicator for disease progression and the type and timing of intervention. WSS describes the force that blood flow exerts on the vessel wall as a function of viscosity and geometry of the vessel, making it a potentially more reliable marker of disease progression.

Heritability of haemodynamics in the ascending aorta

Blood flow in the vasculature can be characterised by dimensionless numbers commonly used to define the level of instabilities in the flow, for example the Reynolds number, Re. Haemodynamics play a key role in cardiovascular disease (CVD) progression. Genetic studies have identified mechanosensitive genes with causal roles in CVD. Given that CVD is highly heritable and abnormal blood flow may increase risk, we investigated the heritability of fluid metrics in the ascending aorta calculated using patient-specific data from cardiac magnetic resonance (CMR) imaging. 341 participants from 108 British Caucasian families were phenotyped by CMR and genotyped for 557,124 SNPs. Flow metrics were derived from the CMR images to provide some local information about blood flow in the ascending aorta, based on maximum values at systole at a single location, denoted max, and a 'peak mean' value averaged over the area of the cross section, denoted pm. Heritability was estimated using pedigree-based (QTDT) and SNP-based (GCTA-GREML) methods. Estimates of Reynolds number based on spatially averaged local flow during systole showed substantial heritability ([Formula: see text], [Formula: see text]), while the estimated heritability for Reynolds number calculated using the absolute local maximum velocity was not statistically significant (12-13%; [Formula: see text]). Heritability estimates of the geometric quantities alone; e.g. aortic diameter ([Formula: see text], [Formula: see text]), were also substantially heritable, as described previously. These findings indicate the potential for the discovery of genetic factors influencing haemodynamic traits in large-scale genotyped and phenotyped cohorts where local spatial averaging is used, rather than instantaneous values. Future Mendelian randomisation studies of aortic haemodynamic estimates, which are swift to derive in a clinical setting, will allow for the investigation of causality of abnormal blood flow in CVD.

Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning

The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR, CT-myocardial perfusion and how developments in machine learning can supplement these techniques.

Influence of malformation of right coronary artery originating from the left sinus in hemodynamic environment

Background

The anomalous origin of the right coronary artery (RCA) from the left coronary artery sinus (AORL) is one of the abnormal origins of the coronary arteries. Most of these issues rarely have any effects on human health, but some individuals may exhibit symptoms, such as myocardial ischemia or even sudden death. Recently, researchers have investigated the AORL through clinical cases, but studies based on computational fluid dynamics (CFD) have rarely been reported. In this study, the hemodynamic changes between the normal origin of the RCA and the AORL are compared based on numerical simulation results.

Methods

Realistic three-dimensional (3D) models of the 16 normal right coronary arteries and 26 abnormal origins of the RCAs were constructed, respectively. The blood flow was numerically simulated using the ANSYS software. This study used a one-way fluid–solid coupling finite element model, wherein the blood is assumed to be an incompressible Newtonian fluid, and the vessel is assumed to be made of an isotropic linear elastic material.

Results

The cross-sectional area differences between the inlet of the normal group and that of the abnormal group were significant (P < 0.0001). Moreover, there were significant differences in the volumetric flow (P = 0.0001) and pressure (P = 0.0002). Positive correlation exists for the ratio of the cross-sectional area of the RCA to the inlet area of the ascending aorta (AAO), and the ratio of the inlet volumetric flow of the RCA to the volumetric flow of the AAO, in the normal (P = 0.0001, r = 0.8178) and abnormal (P = 0.0033, r = 0.6107) groups.

Conclusion

This study demonstrates that the cross-sectional area of the AORL inlet may cause ischemia symptoms. The results obtained by this study may contribute to the further understanding of the clinical symptoms of the AORL based on the hemodynamics.

In silico clinical trials: concepts and early adoptions

Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach.

Data-Driven Pulsatile Blood Flow Physics with Dynamic Mode Decomposition

Dynamic mode decomposition (DMD) is a purely data-driven and equation-free technique for reduced-order modeling of dynamical systems and fluid flow. DMD finds a best fit linear reduced-order model that represents any given spatiotemporal data. In DMD, each mode evolves with a fixed frequency and therefore DMD modes represent physically meaningful structures that are ranked based on their dynamics. The application of DMD to patient-specific cardiovascular flow data is challenging. First, the input flow rate is unsteady and pulsatile. Second, the flow topology can change significantly in different phases of the cardiac cycle. Finally, blood flow in patient-specific diseased arteries is complex and often chaotic. The objective of this study was to overcome these challenges using our proposed multistage dynamic mode decomposition with control (mDMDc) method and use this technique to study patient-specific blood flow physics. The inlet flow rate was considered as the controller input to the systems. Blood flow data were divided into different stages based on the inlet flow waveform and DMD with control was applied to each stage. The system was augmented to consider both velocity and wall shear stress (WSS) vector data, and therefore study the interaction between the coherent structures in velocity and near-wall coherent structures in WSS. First, it was shown that DMD modes can exactly represent the analytical Womersley solution for incompressible pulsatile flow in tubes. Next, our method was applied to image-based coronary artery stenosis and cerebral aneurysm models where complex blood flow patterns are anticipated. The flow patterns were studied using the mDMDc modes and the reconstruction errors were reported. Our augmented mDMDc framework could capture coherent structures in velocity and WSS with a fewer number of modes compared to the traditional DMD approach and demonstrated a close connection between the velocity and WSS modes.

Does the inflow velocity profile influence physiologically relevant flow patterns in computational hemodynamic models of left anterior descending coronary artery?

Patient-specific computational fluid dynamics is a powerful tool for investigating the hemodynamic risk in coronary arteries. Proper setting of flow boundary conditions in computational hemodynamic models of coronary arteries is one of the sources of uncertainty weakening the findings of in silico experiments, in consequence of the challenging task of obtaining in vivo 3D flow measurements within the clinical framework. Accordingly, in this study we evaluated the influence of assumptions on inflow velocity profile shape on coronary artery hemodynamics. To do that, (1) ten left anterior descending coronary artery (LAD) geometries were reconstructed from clinical angiography, and (2) eleven velocity profiles with realistic 3D features such as eccentricity and differently shaped (single- and double-vortex) secondary flows were generated analytically and imposed as inflow boundary conditions. Wall shear stress and helicity-based descriptors obtained prescribing the commonly used parabolic velocity profile were compared with those obtained with the other velocity profiles. Our findings indicated that the imposition of idealized velocity profiles as inflow boundary condition is acceptable as long the results of the proximal vessel segment are not considered, in LAD coronary arteries. As a pragmatic rule of thumb, a conservative estimation of the length of influence of the shape of the inflow velocity profile on LAD local hemodynamics can be given by the theoretical entrance length for cylindrical conduits in laminar flow conditions.

Experimental Assessment of Two Non-Contrast MRI Sequences Used for Computational Fluid Dynamics: Investigation of Consistency Between Techniques

Purpose

Recent studies have noted a degree of variance between the geometries segmented by different groups from 3D medical images that are used in computational fluid dynamics (CFD) simulations of patient-specific cardiovascular systems. The aim of this study was to determine if the applied sequence of magnetic resonance imaging (MRI) also introduced observable variance in CFD results.

Methods

Using a series of phantoms MR images of vessels of known diameter were assessed for the time-of-flight and multi-echo data image combination sequences. Following this, patient images of arterio-venous fistulas were acquired using the same sequences. Comparisons of geometry were made using the phantom and patient images, and of wall shear stress quantities using the CFD results from the patient images.

Results

Phantom images showed deviations in diameter between 0 and 15% between the sequences, depending on vessel diameter. Patient images showed different geometrical features such as narrowings that were not present on both sequences. Distributions of wall shear stress (WSS) quantities differed from simulations between the geometries obtained from the sequences.

Conclusion

In conclusion, choosing different MRI sequences resulted in slightly different geometries of the same anatomy, which led to compounded errors in WSS quantities from CFD simulation.

Electronic supplementary material

The online version of this article (10.1007/s13239-020-00473-z) contains supplementary material, which is available to authorized users.

Myocardial Fluid Balance and Pathophysiology of Myocardial Edema in Coronary Artery Bypass Grafting

Myocardial edema is one of the most common complications of coronary artery bypass grafting (CABG) that is linearly related to many coronary artery diseases. Myocardial edema can cause several consequences including systolic dysfunction, diastolic dysfunction, arrhythmia, and cardiac tissue fibrosis that can increase mortality in CABG. Understanding myocardial fluid balance and tissue and systemic fluid regulation is crucial in order to ultimately link how coronary artery bypass grafting can cause myocardial edema in such a setting. The identification of susceptible patients by using imaging modalities is still challenging. Future studies about the technique of imaging modalities, examination protocols, prevention, and treatment of myocardial edema should be carried out, in order to limit myocardial edema occurrence and prevent complications.

Opportunities and challenges of implementing computed tomography fractional flow reserve into clinical practice

CT-derived fractional flow reserve (CT-FFR) uses computational fluid dynamics to derive non-invasive FFR to determine the haemodynamic significance of coronary artery lesions. Studies have demonstrated good diagnostic accuracy of CT-FFR and reassuring short-term clinical outcome data.As a prerequisite, high-quality CT coronary angiography (CTCA) images are required with good heart rate control and pre-treatment with glyceryl trinitrate, which would otherwise render CTCA as unsuitable for CT-FFR. CT-FFR can determine the functional significance of CAD lesions, and there are supportive data for its use in clinical decision-making. However, the downstream impact on myocardial ischaemic burden or viability cannot be obtained.Several challenges remain with implementation of CT-FFR, including interpretation, training, availability, resource utilisation and funding. Further research is required to determine which cases should be considered for clinical CT-FFR analysis, with additional practical guidance on how to implement this emerging technique in clinical practice. Furthermore, long-term prognostic data are required before widespread clinical implementation of CT-FFR can be recommended.While there are several potential opportunities for CT-FFR, at present there remain important systemic and technical limitations and challenges that need to be overcome prior to routine integration of CT-FFR into clinical practice.

Low shear stress regulates vascular endothelial cell pyroptosis through miR-181b-5p/STAT-3 axis

Low shear stress and pyroptosis both play an important role in the onset and development of atherosclerosis (AS). MicroRNAs (miRNAs) are a kind of short (18-22) nucleotide sequences that can bind to the 3'-untranslated region (3'-UTR) of messenger RNA, thereby regulating programmed cell death including pyroptosis. However, the function of miRNAs in cells subjected to shear stress conditions is unknown. Therefore, we conducted the current study to demonstrate the effect of low shear stress on pyroptosis and the underlying mechanism. Human umbilical vein endothelial cells (HUVECs) stimulated by undisturbed shear stress (5 dynes/cm² ) were the experimental group while HUVECs without shear stress treatment were the control group in our experiments. We observed that shear stress can suppress mechanosensitive miR-181b-5p expression, accompanying the elevated expression of NLRP3 inflammasome-dependent pyroptosis. Introduction of miR-181b-5p could alleviate NLRP3 inflammasome-dependent pyroptosis. Luciferase assay showed specific binding of miR-181b-5p to the 3'-UTR of signal transduction and transcriptional activation factor 3 (STAT-3) gene. Inhibition of STAT-3 gene expression at the posttranscriptional level results in the alleviation of NLRP3 inflammasome-dependent pyroptosis. Besides, the silencing of STAT-3 reduced anti-miR-181b-5p-mediated HUVEC pyroptosis via regulating NLRP3 inflammasome activation. Given the role of mechanosensitive miR-181b-5p and STAT-3 in the shear stress-induced pyroptosis, regulation of their expression levels may be a promising strategy to control AS.

Synthetic PPG generation from haemodynamic model with baroreflex autoregulation: a Digital twin of cardiovascular system

Synthetic data generation has recently emerged as a substitution technique for handling the problem of bulk data needed in training machine learning algorithms. Healthcare, primarily cardiovascular domain is a major area where synthetic physiological data like Photoplethysmogram (PPG), Electrocardiogram (ECG), Phonocardiogram (PCG), etc. are being used to improve accuracy of machine learning algorithm. Conventional synthetic data generation approach using mathematical formulations lack interpretability. Hence, aim of this paper is to generate synthetic PPG signal from a Digital twin platform replicating cardiovascular system. Such system can serve the dual purpose of replicating the physical system, so as to simulate specific `what if' scenarios as well as to generate large scale synthetic data with patho-physiological interpretability. Cardio-vascular Digital twin is modeled with a two chambered heart, haemodynamic equations and a baroreflex based pressure control mechanism to generate blood pressure and flow variations. Synthetic PPG signal is generated from the model for healthy and Atherosclerosis condition. Initial validation of the platform has been made on the basis of efficiency of the platform in clustering Coronary Artery Disease (CAD) and non CAD PPG data by extracting features from the synthetically generated PPG and comparing that with PPG obtained from Physionet data.

Computational optimization of a novel atraumatic catheter for local drug delivery in coronary atherosclerotic plaques

Early identification and treatment of high-risk plaques before they rupture, and precipitate adverse events constitute a major challenge in cardiology today. Computational simulations are a time- and cost-effective way to study the performance, and to optimize a system. The main objective of this work is to optimize the flow of a novel atraumatic local drug delivery catheter for the treatment of coronary atherosclerosis. The mixing and spreading effectiveness of a drug fluid was analyzed utilizing computational fluid dynamics (CFD) in a coronary artery model. The optimum infusion flow of the nanoparticle-carrying drug fluid was found by maximizing the drug volume fraction and minimizing drug velocity at the artery wall, while maintaining acceptable wall shear stress (WSS). Drug velocities between 15 m/s and 20 m/s are optimum for local drug delivery. The resulting parameters from this study will be used to fabricate customized prototypes for future in-vivo experiments.

Combining Volumetric and Wall Shear Stress Analysis from CT to Assess Risk of Abdominal Aortic Aneurysm Progression

Background Despite known limitations, the decision to operate on abdominal aortic aneurysm (AAA) is primarily on the basis of measurement of maximal aneurysm diameter. Purpose To identify volumetric and computational fluid dynamics parameters to predict AAAs that are likely to progress in size. Materials and Methods This study, part of a multicenter prospective registry (NCT01599533), included 126 patients with AAA. Patients were sorted into stable (≤10-mL increase in aneurysm volume) and progression (>10-mL increase in aneurysm volume) groups. Initial AAA characteristics of the derivation cohort were analyzed (maximal diameter and surface, thrombus and lumen volumes, maximal wall pressure, and wall shear stress [WSS]) to identify relevant parameters for a logistic regression model. Model and maximal diameter diagnostic performances were assessed in both cohorts and for AAAs smaller than 50 mm by using area under the receiver operating characteristic curve (AUC). Results Eighty-one patients were included (mean age, 73 years ± 7 years [standard deviation]; 78 men). The derivation and validation cohorts included, respectively, 50 and 31 participants. In the derivation cohort, there was higher mean lumen volume and lower mean WSS in the progression group compared with the stable group (60 mL ± 14 vs 46 mL ± 18 [P = .005] and 66% ± 6 vs 53% ± 9 [P = .02], respectively). Mean lumen volume and mean WSS at baseline were correlated to total volume growth (r = 0.47 [P = .002] and -0.42 [P = .006], respectively). In the derivation cohort, a regression model including lumen volume and WSS to predict aneurysm enlargement was superior to maximal diameter alone (AUC, 0.78 vs 0.52, respectively; P = .003); although no difference was found in the validation cohort (AUC, 0.79 vs 0.71, respectively; P = .51). For AAAs smaller than 50 mm, a regression model that included both baseline WSS and lumen volume performed better than maximal diameter (AUC, 0.79 vs 0.53, respectively; P = .01). Conclusion Combined analysis of lumen volume and wall shear stress was associated with enlargement of abdominal aortic aneurysms at 1 year, particularly in aneurysms smaller than 50 mm in diameter. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Mitsouras and Leach in this issue.

Simulation of Unit Operations in Formulation Development of Tablets Using Computational Fluid Dynamics

Tablets are the most customarily used solid oral unit dosage form for its better patient compliance. Preparation of these tablets include granulation, granule drying, die filling, and tablet coating as few unit operations and evaluation tests like dissolution test and disintegration test. These are the most crucial segments influencing the quality of the tablet. Critical analysis of the impact of factors like flow pattern, temperature, velocity, and other properties of fluid affecting the unit operations is obligatory to enhance their efficiency. Computational fluid dynamics (CFD), a combined mathematical and numerical approach, is used to analyze the process parameters of fluid affecting the abovementioned processes during tablet formulation. The equations governing the laws of conservation of energy, mass, and momentum are solved numerically utilizing CFD software for better understanding of the role of fluids within the tablet processing steps. This review not only focuses on discrete explanations on how CFD is utilized in formulation and evaluation of tablet but it is also a compilation of multiple research works performed on each unit operation by applying CFD.

Personalized Interventions: A Reality in the Next 20 Years or Pie in the Sky

There is no better representation of the need for personalization of care than the breadth and complexity of congenital heart disease. Advanced imaging modalities are now standard of care in the field, and the advancements being made to three-dimensional visualization technologies are growing as a means of pre-procedural preparation. Incorporating emerging modeling approaches, such as computational fluid dynamics, will push the limits of our ability to predict outcomes, and this information may be both obtained and utilized during a single procedure in the future. Artificial intelligence and customized devices may soon surface as realistic tools for the care of patients with congenital heart disease, as they are showing growing evidence of feasibility within other fields. This review illustrates the great strides that have been made and the persistent challenges that exist within the field of congenital interventional cardiology, a field which must continue to innovate and push the limits to achieve personalization of the interventions it provides.