Patient-Specific Haemodynamic Analysis of Virtual Grafting Strategies in Type-B Aortic Dissection: Impact of Compliance Mismatch

INTRODUCTION

Compliance mismatch between the aortic wall and Dacron Grafts is a clinical problem concerning aortic haemodynamics and morphological degeneration. The aortic stiffness introduced by grafts can lead to an increased left ventricular (LV) afterload. This study quantifies the impact of compliance mismatch by virtually testing different Type-B aortic dissection (TBAD) surgical grafting strategies in patient-specific, compliant computational fluid dynamics (CFD) simulations.

MATERIALS AND METHODS

A post-operative case of TBAD was segmented from computed tomography angiography data. Three virtual surgeries were generated using different grafts; two additional cases with compliant grafts were assessed. Compliant CFD simulations were performed using a patient-specific inlet flow rate and three-element Windkessel outlet boundary conditions informed by 2D-Flow MRI data. The wall compliance was calibrated using Cine-MRI images. Pressure, wall shear stress (WSS) indices and energy loss (EL) were computed.

RESULTS

Increased aortic stiffness and longer grafts increased aortic pressure and EL. Implementing a compliant graft matching the aortic compliance of the patient reduced the pulse pressure by 11% and EL by 4%. The endothelial cell activation potential (ECAP) differed the most within the aneurysm, where the maximum percentage difference between the reference case and the mid (MDA) and complete (CDA) descending aorta replacements increased by 16% and 20%, respectively.

CONCLUSION

This study suggests that by minimising graft length and matching its compliance to the native aorta whilst aligning with surgical requirements, the risk of LV hypertrophy may be reduced. This provides evidence that compliance-matching grafts may enhance patient outcomes.

Ultrasonic irrigation flows in root canals: effects of ultrasound power and file insertion depth

Ultrasonic irrigation during root canal treatment can enhance biofilm disruption. The challenge is to improve the fluid flow so that the irrigant reaches areas inaccessible to hand instrumentation. The aim of this study is to experimentally investigate how the flow field and hydrodynamic forces induced by ultrasonic irrigation are influenced by the ultrasound power and file insertion depth. A root canal phantom was 3D printed and used as a mold for the fabrication of a PDMS channel. An ultrasonic instrument with a #15K-file provided the irrigation. The flow field was studied by means of Particle Image Velocimetry (PIV). The time averaged velocity and shear stress distributions were found to vary significantly with ultrasound power. Their maximum values increase sharply for low powers and up to a critical power level. At and above this setting, the flow pattern changes, from the high velocity and shear stress region confined in the vicinity of the tip, to one covering the whole root canal domain. Exceeding this threshold also induces a moderate increase in the maximum velocities and shear stresses. The insertion depth was found to have a smaller effect on the measured velocity and shear stresses. Due to the oscillating nature of the flow, instantaneous maximum velocities and shear stresses can reach much higher values than the mean, especially for high powers. Ultrasonic irrigation will benefit from using a higher power setting as this does produce greater shear stresses near the walls of the root canal leading to the potential for increased biofilm removal.

Partitioning of dense RBC suspensions in single microfluidic bifurcations: role of cell deformability and bifurcation angle

Red blood cells (RBCs) are a key determinant of human physiology and their behaviour becomes extremely heterogeneous as they navigate in narrow, bifurcating vessels in the microvasculature, affecting local haemodynamics. This is due to partitioning in bifurcations which is dependent on the biomechanical properties of RBCs, especially deformability. We examine the effect of deformability on the haematocrit distributions of dense RBC suspensions flowing in a single, asymmetric Y-shaped bifurcation, experimentally. Human RBC suspensions (healthy and artificially hardened) at 20% haematocrit (Ht) were perfused through the microchannels at different flow ratios between the outlet branches, and negligible inertia, and imaged to infer cell distributions. Notable differences in the shape of the haematocrit distributions were observed between healthy and hardened RBCs near the bifurcation apex. These lead to more asymmetric distributions for healthy RBCs in the daughter and outlet branches with cells accumulating near the inner channel walls, exhibiting distinct hematocrit peaks which are sharper for healthy RBCs. Although the hematocrit distributions differed locally, similar partitioning characteristics were observed for both suspensions. Comparisons with RBC distributions measured in a T-shaped bifurcation showed that the bifurcation angle affects the haematocrit characteristics of the healthy RBCs and not the hardened ones. The extent of RBC partitioning was found similar in both geometries and suspensions. The study highlights the differences between local and global characteristics which impact RBC distribution in more complex, multi-bifurcation networks.

A systematic review of clinical and biomechanical engineering perspectives on the prediction of restenosis in coronary and peripheral arteries

Objective

Restenosis is a significant complication of revascularization treatments in coronary and peripheral arteries, sometimes necessitating repeated intervention. Establishing when restenosis will happen is extremely difficult due to the interplay of multiple variables and factors. Standard clinical and Doppler ultrasound scans surveillance follow-ups are the only tools clinicians can rely on to monitor intervention outcomes. However, implementing efficient surveillance programs is hindered by health care system limitations, patients' comorbidities, and compliance. Predictive models classifying patients according to their risk of developing restenosis over a specific period will allow the development of tailored surveillance, prevention programs, and efficient clinical workflows. This review aims to: (1) summarize the state-of-the-art in predictive models for restenosis in coronary and peripheral arteries; (2) compare their performance in terms of predictive power; and (3) provide an outlook for potentially improved predictive models.

Methods

We carried out a comprehensive literature review by accessing the PubMed/MEDLINE database according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search strategy consisted of a combination of keywords and included studies focusing on predictive models of restenosis published between January 1993 and April 2023. One author independently screened titles and abstracts and checked for eligibility. The rest of the authors independently confirmed and discussed in case of any disagreement. The search of published literature identified 22 studies providing two perspectives-clinical and biomechanical engineering-on restenosis and comprising distinct methodologies, predictors, and study designs. We compared predictive models' performance on discrimination and calibration aspects. We reported the performance of models simulating reocclusion progression, evaluated by comparison with clinical images.

Results

Clinical perspective studies consider only routinely collected patient information as restenosis predictors. Our review reveals that clinical models adopting traditional statistics (n = 14) exhibit only modest predictive power. The latter improves when machine learning algorithms (n = 4) are employed. The logistic regression models of the biomechanical engineering perspective (n = 2) show enhanced predictive power when hemodynamic descriptors linked to restenosis are fused with a limited set of clinical risk factors. Biomechanical engineering studies simulating restenosis progression (n = 2) are able to capture its evolution but are computationally expensive and lack risk scoring for individual patients at specific follow-ups.

Conclusions

Restenosis predictive models, based solely on routine clinical risk factors and using classical statistics, inadequately predict the occurrence of restenosis. Risk stratification models with increased predictive power can be potentially built by adopting machine learning techniques and incorporating critical information regarding vessel hemodynamics arising from biomechanical engineering analyses.

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to capture personalised aortic haemodynamics

Data driven, reduced order modelling has shown promise in tackling the challenges associated with computational and experimental haemodynamic models. In this work, we focus on the use of Reduced Order Models (ROMs) to reconstruct velocity fields in a patient-specific dissected aorta, with the objective being to compare the ROMs obtained from Robust Proper Orthogonal Decomposition (RPOD) to those obtained from the traditional Proper Orthogonal Decomposition (POD). POD and RPOD are applied to in vitro, haemodynamic data acquired by Particle Image Velocimetry and compare the decomposed flows to those derived from Computational Fluid Dynamics (CFD) data for the same geometry and flow conditions. In this work, PIV and CFD results act as surrogates for clinical haemodynamic data e.g. MR, helping to demonstrate the potential use of ROMS in real clinical scenarios. The flow is reconstructed using different numbers of POD modes and the flow features obtained throughout the cardiac cycle are compared to the original Full Order Models (FOMs). Robust Principal Component Analysis (RPCA), the first step of RPOD, has been found to enhance the quality of PIV data, allowing POD to capture most of the kinetic energy of the flow in just two modes similar to the numerical data that are free from measurement noise. The reconstruction errors differ along the cardiac cycle with diastolic flows requiring more modes for accurate reconstruction. In general, modes 1-10 are found sufficient to represent the flow field. The results demonstrate that the coherent structures that characterise this aortic dissection flow are described by the first few POD modes suggesting that it is possible to represent the macroscale behaviour of aortic flow in a low-dimensional space; thus significantly simplifying the problem, and allowing for more computationally efficient flow simulations or machine learning based flow predictions that can pave the way for translation of such models to the clinic.

Aneurysmal growth in type-B aortic dissection: assessing the impact of patient-specific inlet conditions on key haemodynamic indices

Type-B aortic dissection is a cardiovascular disease in which a tear develops in the intimal layer of the descending aorta, allowing pressurized blood to delaminate the layers of the vessel wall. In medically managed patients, long-term aneurysmal dilatation of the false lumen (FL) is considered virtually inevitable and is associated with poorer disease outcomes. While the pathophysiological mechanisms driving FL dilatation are not yet understood, haemodynamic factors are believed to play a key role. Computational fluid dynamics (CFD) and 4D-flow MRI (4DMR) analyses have revealed correlations between flow helicity, oscillatory wall shear stress and aneurysmal dilatation of the FL. In this study, we compare CFD simulations using a patient-specific, three-dimensional, three-component inlet velocity profile (4D IVP) extracted from 4DMR data against simulations with flow rate-matched uniform and axial velocity profiles that remain widely used in the absence of 4DMR. We also evaluate the influence of measurement errors in 4DMR data by scaling the 4D IVP to the degree of imaging error detected in prior studies. We observe that oscillatory shear and helicity are highly sensitive to inlet velocity distribution and flow volume throughout the FL and conclude that the choice of IVP may greatly affect the future clinical value of simulations.

Machine Learning in Predicting Printable Biomaterial Formulations for Direct Ink Writing

Three-dimensional (3D) printing is emerging as a transformative technology for biomedical engineering. The 3D printed product can be patient-specific by allowing customizability and direct control of the architecture. The trial-and-error approach currently used for developing the composition of printable inks is time- and resource-consuming due to the increasing number of variables requiring expert knowledge. Artificial intelligence has the potential to reshape the ink development process by forming a predictive model for printability from experimental data. In this paper, we constructed machine learning (ML) algorithms including decision tree, random forest (RF), and deep learning (DL) to predict the printability of biomaterials. A total of 210 formulations including 16 different bioactive and smart materials and 4 solvents were 3D printed, and their printability was assessed. All ML methods were able to learn and predict the printability of a variety of inks based on their biomaterial formulations. In particular, the RF algorithm has achieved the highest accuracy (88.1%), precision (90.6%), and F1 score (87.0%), indicating the best overall performance out of the 3 algorithms, while DL has the highest recall (87.3%). Furthermore, the ML algorithms have predicted the printability window of biomaterials to guide the ink development. The printability map generated with DL has finer granularity than other algorithms. ML has proven to be an effective and novel strategy for developing biomaterial formulations with desired 3D printability for biomedical engineering applications.

The Influence of Minor Aortic Branches in Patient-Specific Flow Simulations of Type-B Aortic Dissection

Type-B aortic dissection (TBAD) is a disease in which a tear develops in the intimal layer of the descending aorta forming a true lumen and false lumen (FL). Because disease outcomes are thought to be influenced by haemodynamic quantities such as pressure and wall shear stress (WSS), their analysis via numerical simulations may provide valuable clinical insights. Major aortic branches are routinely included in simulations but minor branches are virtually always neglected, despite being implicated in TBAD progression and the development of complications. As minor branches are estimated to carry about 7-21% of cardiac output, neglecting them may affect simulation accuracy. We present the first simulation of TBAD with all pairs of intercostal, subcostal and lumbar arteries, using 4D-flow MRI (4DMR) to inform patient-specific boundary conditions. Compared to an equivalent case without minor branches, their inclusion improved agreement with 4DMR velocities, reduced time-averaged WSS (TAWSS) and transmural pressure and elevated oscillatory shear in regions where FL dilatation and calcification were observed in vivo. Minor branch inclusion resulted in differences of 60-75% in these metrics of potential clinical relevance, indicating a need to account for minor branch flow loss if simulation accuracy is sought.

Experimental insights into elasto-inertial transitions in Taylor-Couette flows

Since the seminal work of Taylor in 1923, Taylor-Couette (TC) flow has served as a paradigm to study hydrodynamic instabilities and bifurcation phenomena. Transitions of Newtonian TC flows to inertial turbulence have been extensively studied and are well understood, while in the past few years, there has been an increasing interest in TC flows of complex, viscoelastic fluids. The transitions to elastic turbulence (ET) or elasto-inertial turbulence (EIT) have revealed fascinating dynamics and flow states; depending on the rheological properties of the fluids, a broad spectrum of transitions has been reported, including rotating standing waves, flame patterns (FP), and diwhirls (DW). The nature of these transitions and the relationship between ET and EIT are not fully understood. In this review, we discuss experimental efforts on TC flows of viscoelastic fluids. We outline the experimental methods employed and the non-dimensional parameters of interest, followed by an overview of inertia, elasticity and elasto-inertia-driven transitions to turbulence and their modulation through shear thinning or particle suspensions. The published experimental data are collated, and a map of flow transitions to EIT as a function of the key fluid parameters is provided, alongside perspectives for the future work. This article is part of the theme issue 'Taylor-Couette and related flows on the centennial of Taylor's seminal Philosophical Transactions paper (part 1)'.

A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations

PURPOSE

Peripheral arteriovenous malformations (pAVMs) are congenital lesions characterised by abnormal high-flow, low-resistance vascular connections-the so-called nidus-between arteries and veins. The mainstay treatment typically involves the embolisation of the nidus, however the complexity of pAVMs often leads to uncertain outcomes. This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of pAVMs using routinely acquired clinical data.

METHODS

A computational model was developed to simulate the pre-, intra-, and post-intervention haemodynamics of a patient-specific pAVM. A porous medium of varying permeability was employed to simulate the sclerosant effect on the nidus haemodynamics. Results were compared against clinical data (digital subtraction angiography, DSA, images) and experimental flow-visualization results in a 3D-printed phantom of the same pAVM.

RESULTS

The computational model allowed the simulation of the pAVM haemodynamics and the sclerotherapy-induced changes at different interventional stages. The predicted inlet flow rates closely matched the DSA-derived data, although the post-intervention one was overestimated, probably due to vascular system adaptations not accounted for numerically. The nidus embolization was successfully captured by varying the nidus permeability and increasing its hydraulic resistance from 0.330 to 3970 mmHg s ml-1. The nidus flow rate decreased from 71% of the inlet flow rate pre-intervention to 1%: the flow completely bypassed the nidus post-intervention confirming the success of the procedure.

CONCLUSION

The study demonstrates that the haemodynamic effects of the embolisation procedure can be simulated from routinely acquired clinical data via a porous medium with varying permeability as evidenced by the good qualitative agreement between numerical predictions and both in vivo and in vitro data. It provides a fundamental building block towards a computational treatment-planning framework for AVM embolisation.

Experimental evaluation of the patient-specific haemodynamics of an aortic dissection model using particle image velocimetry

Aortic Dissection (AD) is a complex pathology that affects the aorta. Diagnosis, management and treatment remain a challenge as it is a highly patient-specific pathology and there is still a limited understanding of the fluid-mechanics phenomena underlying clinical outcomes. Although in vitro models can allow the accurate study of AD flow fields in physical phantoms, they are currently scarce and almost exclusively rely on over simplifying assumptions. In this work, we present the first experimental study of a patient-specific case of AD. An anatomically correct phantom was produced and combined with a state-of-the-art in vitro platform, informed by clinical data, employed to accurately reproduce personalised conditions. The complex AD haemodynamics reproduced by the platform was characterised by flow rate and pressure acquisitions as well as Particle Image Velocimetry (PIV) derived velocity fields. Clinically relevant haemodynamic indices, that can be correlated with AD prognosis - such as velocity, shear rate, turbulent kinetic energy distributions - were extracted in two regions of interest in the aortic domain. The acquired data highlighted the complex nature of the flow (e.g. recirculation regions, low shear rate in the false lumen) and was in very good agreement with the available clinical data and the CFD results of a study conducted alongside, demonstrating the accuracy of the findings. These results demonstrate that the described platform constitutes a powerful, unique tool to reproduce in vitro personalised haemodynamic conditions, which can be used to support the evaluation of surgical procedures, medical devices testing and to validate state-of-the-art numerical models.

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

We present a novel, cost-efficient methodology to simulate aortic haemodynamics in a patient-specific, compliant aorta using an MRI data fusion process. Based on a previously-developed Moving Boundary Method, this technique circumvents the high computational cost and numerous structural modelling assumptions required by traditional Fluid-Structure Interaction techniques. Without the need for Computed Tomography (CT) data, the MRI images required to construct the simulation can be obtained during a single imaging session. Black Blood MR Angiography and 2D Cine-MRI data were used to reconstruct the luminal geometry and calibrate wall movement specifically to each region of the aorta. 4D-Flow MRI and non-invasive pressure measurements informed patient-specific inlet and outlet boundary conditions. Luminal area closely matched 2D Cine-MRI measurements with a mean error of less than 4.6% across the cardiac cycle, while physiological pressure and flow distributions were simulated to within 3.3% of patient-specific targets. Moderate agreement with 4D-Flow MRI velocity data was observed. Despite lower peak velocity, an equivalent rigid-wall simulation predicted a mean Time-Averaged Wall Shear Stress (TAWSS) 13% higher than the compliant simulation. The agreement observed between compliant simulation results and MRI data is testament to the accuracy and efficiency of this MRI-based simulation technique.

Effect of Particle Specific Surface Area on the Rheology of Non-Brownian Silica Suspensions

Industrial formulations very often involve particles with a broad range of surface characteristics and size distributions. Particle surface asperities (roughness) and porosity increase particle specific surface area and significantly alter suspension rheology, which can be detrimental to the quality of the end product. We examine the rheological properties of two types of non-Brownian, commercial precipitated silicas, with varying specific surface area, namely PS52 and PS226, suspended in a non-aqueous solvent, glycerol, and compare them against those of glass sphere suspensions (GS2) with a similar size distribution. A non-monotonic effect of the specific surface area (S) on suspension rheology is observed, whereby PS52 particles in glycerol are found to exhibit strong shear thinning response, whereas such response is suppressed for glass sphere and PS226 particle suspensions. This behaviour is attributed to the competing mechanisms of particle-particle and particle-solvent interactions. In particular, increasing the specific surface area beyond a certain value results in the repulsive interparticle hydration forces (solvation forces) induced by glycerol overcoming particle frictional contacts and suppressing shear thinning; this is evidenced by the response of the highest specific surface area particles PS226. The study demonstrates the potential of using particle specific surface area as a means to tune the rheology of non-Brownian silica particle suspensions.

A Combined In Vivo, In Vitro, In Silico Approach for Patient-Specific Haemodynamic Studies of Aortic Dissection

The optimal treatment of Type-B aortic dissection (AD) is still a subject of debate, with up to 50% of the cases developing late-term complications requiring invasive intervention. A better understanding of the patient-specific haemodynamic features of AD can provide useful insights on disease progression and support clinical management. In this work, a novel in vitro and in silico framework to perform personalised studies of AD, informed by non-invasive clinical data, is presented. A Type-B AD was investigated in silico using computational fluid dynamics (CFD) and in vitro by means of a state-of-the-art mock circulatory loop and particle image velocimetry (PIV). Both models not only reproduced the anatomical features of the patient, but also imposed physiologically-accurate and personalised boundary conditions. Experimental flow rate and pressure waveforms, as well as detailed velocity fields acquired via PIV, are extensively compared against numerical predictions at different locations in the aorta, showing excellent agreement. This work demonstrates how experimental and numerical tools can be developed in synergy to accurately reproduce patient-specific AD blood flow. The combined platform presented herein constitutes a powerful tool for advanced haemodynamic studies for a range of vascular conditions, allowing not only the validation of CFD models, but also clinical decision support, surgical planning as well as medical device innovation.

Highly integrated workflows for exploring cardiovascular conditions: Exemplars of precision medicine in Alzheimer's disease and aortic dissection

For precision medicine to be implemented through the lens of in silico technology, it is imperative that biophysical research workflows offer insight into treatments that are specific to a particular illness and to a particular subject. The boundaries of precision medicine can be extended using multiscale, biophysics-centred workflows that consider the fundamental underpinnings of the constituents of cells and tissues and their dynamic environments. Utilising numerical techniques that can capture the broad spectrum of biological flows within complex, deformable and permeable organs and tissues is of paramount importance when considering the core prerequisites of any state-of-the-art precision medicine pipeline. In this work, a succinct breakdown of two precision medicine pipelines developed within two Virtual Physiological Human (VPH) projects are given. The first workflow is targeted on the trajectory of Alzheimer's Disease, and caters for novel hypothesis testing through a multicompartmental poroelastic model which is integrated with a high throughput imaging workflow and subject-specific blood flow variability model. The second workflow gives rise to the patient specific exploration of Aortic Dissections via a multi-scale and compliant model, harnessing imaging, computational fluid-dynamics (CFD) and dynamic boundary conditions. Results relating to the first workflow include some core outputs of the multiporoelastic modelling framework, and the representation of peri-arterial swelling and peri-venous drainage solution fields. The latter solution fields were statistically analysed for a cohort of thirty-five subjects (stratified with respect to disease status, gender and activity level). The second workflow allowed for a better understanding of complex aortic dissection cases utilising both a rigid-wall model informed by minimal and clinically common datasets as well as a moving-wall model informed by rich datasets.

A Preliminary Computational Investigation Into the Flow of PEG in Rat Myocardial Tissue for Regenerative Therapy

Myocardial infarction (MI), a type of cardiovascular disease, affects a significant proportion of people around the world. Traditionally, non-communicable chronic diseases were largely associated with aging populations in higher income countries. It is now evident that low- to middle-income countries are also affected and in these settings, younger individuals are at high risk. Currently, interventions for MI prolong the time to heart failure. Regenerative medicine and stem cell therapy have the potential to mitigate the effects of MI and to significantly improve the quality of life for patients. The main drawback with these therapies is that many of the injected cells are lost due to the vigorous motion of the heart. Great effort has been directed toward the development of scaffolds which can be injected alongside stem cells, in an attempt to improve retention and cell engraftment. In some cases, the scaffold alone has been seen to improve heart function. This study focuses on a synthetic polyethylene glycol (PEG) based hydrogel which is injected into the heart to improve left ventricular function following MI. Many studies in literature characterize PEG as a Newtonian fluid within a specified shear rate range, on the macroscale. The aim of the study is to characterize the flow of a 20 kDa PEG on the microscale, where the behavior is likely to deviate from macroscale flow patterns. Micro particle image velocimetry (μPIV) is used to observe flow behavior in microchannels, representing the gaps in myocardial tissue. The fluid exhibits non-Newtonian, shear-thinning behavior at this scale. Idealized two-dimensional computational fluid dynamics (CFD) models of PEG flow in microchannels are then developed and validated using the μPIV study. The validated computational model is applied to a realistic, microscopy-derived myocardial tissue model. From the realistic tissue reconstruction, it is evident that the myocardial flow region plays an important role in the distribution of PEG, and therefore, in the retention of material.

Testosterone Therapy: An Assessment of the Clinical Consequences of Changes in Hematocrit and Blood Flow Characteristics

INTRODUCTION

Clinical guidelines indicate that hematocrit should be monitored during testosterone replacement therapy (TTh), with action taken if a level of 0.54 is exceeded.

AIM

To consider the extent of changes in hematocrit and putative effects on viscosity, blood flow, and mortality rates after TTh.

METHODS

We focused on literature describing benefits and possible pitfalls of TTh, including increased hematocrit. We used data from the BLAST RCT to determine change in hematocrit after 30 weeks of TTh and describe a clinical case showing the need for monitoring. We consider the validity of the current hematocrit cutoff value at which TTh may be modified. Ways in which hematocrit alters blood flow in the micro- and macro-vasculature are also considered.

MAIN OUTCOME MEASURES

The following measures were assessed: (i) change in hematocrit, (ii) corresponding actions taken in clinical practice, and (iii) possible blood flow changes following change in hematocrit.

RESULTS

Analysis of data from the BLAST RCT showed a significant increase in mean hematocrit of 0.01, the increase greater in men with lower baseline values. Although 0 of 61 men given TTh breached the suggested cutoff of 0.54 after 30 weeks, a clinical case demonstrates the need to monitor hematocrit. An association between hematocrit and morbidity and mortality appears likely but not proven and may be evident only in patient subgroups. The consequences of an increased hematocrit may be mediated by alterations in blood viscosity, oxygen delivery, and flow. Their relative impact may vary in different vascular beds.

CONCLUSIONS

TTh can effect an increased hematocrit via poorly understood mechanisms and may have harmful effects on blood flow that differ in patient subgroups. At present, there appears no scientific basis for using a hematocrit of 0.54 to modify TTh; other values may be more appropriate in particular patient groups. König CS, Balabani S, Hackett GI, et al. Testosterone Therapy: An Assessment of the Clinical Consequences of Changes in Hematocrit and Blood Flow Characteristics. Sex Med Rev 2019;7:650-660.

Virtual TEVAR: Overcoming the Roadblocks of In-Silico Tools for Aortic Dissection Treatment

The use of in silico tools for the interventional planning of complex vascular conditions, such as Aortic Dissections has been often limited by high computational cost, involving long timescales for accurate results to be produced and low numbers of patients, precluding the use of statistical analyses to inform individual-level models. In the paper [Theranostics 2018; 8(20):5758-5771. doi:10.7150/thno.28944], Chen et al. proposed a novel algorithm to compute patient-specific 'virtual TEVAR' that will help clinicians to approach individual treatment and decision-making based on objective and quantifiable metrics and validated on a cohort of 66 patients in real time. This research will significantly impact the field and has the potential to transform the way clinical interventions will be approached in the future.

Computational tools for clinical support: a multi-scale compliant model for haemodynamic simulations in an aortic dissection based on multi-modal imaging data

Aortic dissection (AD) is a vascular condition with high morbidity and mortality rates. Computational fluid dynamics (CFD) can provide insight into the progression of AD and aid clinical decisions; however, oversimplified modelling assumptions and high computational cost compromise the accuracy of the information and impede clinical translation. To overcome these limitations, a patient-specific CFD multi-scale approach coupled to Windkessel boundary conditions and accounting for wall compliance was developed and used to study a patient with AD. A new moving boundary algorithm was implemented to capture wall displacement and a rich in vivo clinical dataset was used to tune model parameters and for validation. Comparisons between in silico and in vivo data showed that this approach successfully captures flow and pressure waves for the patient-specific AD and is able to predict the pressure in the false lumen (FL), a critical variable for the clinical management of the condition. Results showed regions of low and oscillatory wall shear stress which, together with higher diastolic pressures predicted in the FL, may indicate risk of expansion. This study, at the interface of engineering and medicine, demonstrates a relatively simple and computationally efficient approach to account for arterial deformation and wave propagation phenomena in a three-dimensional model of AD, representing a step forward in the use of CFD as a potential tool for AD management and clinical support.

A simplified method to account for wall motion in patient-specific blood flow simulations of aortic dissection: Comparison with fluid-structure interaction

Aortic dissection (AD) is a complex and highly patient-specific vascular condition difficult to treat. Computational fluid dynamics (CFD) can aid the medical management of this pathology, yet its modelling and simulation are challenging. One aspect usually disregarded when modelling AD is the motion of the vessel wall, which has been shown to significantly impact simulation results. Fluid-structure interaction (FSI) methods are difficult to implement and are subject to assumptions regarding the mechanical properties of the vessel wall, which cannot be retrieved non-invasively. This paper presents a simplified 'moving-boundary method' (MBM) to account for the motion of the vessel wall in type-B AD CFD simulations, which can be tuned with non-invasive clinical images (e.g. 2D cine-MRI). The method is firstly validated against the 1D solution of flow through an elastic straight tube; it is then applied to a type-B AD case study and the results are compared to a state-of-the-art, full FSI simulation. Results show that the proposed method can capture the main effects due to the wall motion on the flow field: the average relative difference between flow and pressure waves obtained with the FSI and MBM simulations was less than 1.8% and 1.3%, respectively and the wall shear stress indices were found to have a similar distribution. Moreover, compared to FSI, MBM has the advantage to be less computationally expensive (requiring half of the time of an FSI simulation) and easier to implement, which are important requirements for clinical translation.

Semi-interpenetrating network hyaluronic acid microgel delivery systems in micro-flow

Macroscopic hydrogels are commonly used as injectable scaffolds or fillers, however they may easily obstruct blood vessels, which poses risks and limits their clinical use. In the present study, three types of hyaluronic acid (HA)-based hydrogel micro-particles with non-covalent, covalent semi-interpenetrating and conventional 3D molecular networks, have been designed, fabricated and characterized. The micro-particles are spherical, biconcave or irregular in shape and their diameter ranged between 2.5 and 3.5 µm; their suspensions exhibit a tuneable viscosity, shear-thinning behaviour, dynamic stability and dispersity in microfluidic flow as a result of their specific particulate nature, providing thus a well-controlled injectable platform. Hydrogel particle suspensions also demonstrate an enhanced safety profile, in terms of the dispersity, cell safety, and hemocompatibility. In addition, Rhodamine 6G has successfully been loaded and released from the particles as a model for drug delivery. Functionalisation of hydrogel microparticles using synthetic polymers has been proven to be a cost-effective way to achieve desirable rheological properties and flow dynamic stability with improved physicochemical properties and biocompatibility in vitro, showing promise as a multifunctional biomedical material for various advanced surgical devices and therapies.

Processing methods for photoacoustic Doppler flowmetry with a clinical ultrasound scanner

Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17 MHz. Measurements were performed on a flow phantom consisting of a tube (580  μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25  mm  /  s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.

Partitioning of red blood cell aggregates in bifurcating microscale flows

Microvascular flows are often considered to be free of red blood cell aggregates, however, recent studies have demonstrated that aggregates are present throughout the microvasculature, affecting cell distribution and blood perfusion. This work reports on the spatial distribution of red blood cell aggregates in a T-shaped bifurcation on the scale of a large microvessel. Non-aggregating and aggregating human red blood cell suspensions were studied for a range of flow splits in the daughter branches of the bifurcation. Aggregate sizes were determined using image processing. The mean aggregate size was marginally increased in the daughter branches for a range of flow rates, mainly due to the lower shear conditions and the close cell and aggregate proximity therein. A counterintuitive decrease in the mean aggregate size was apparent in the lower flow rate branches. This was attributed to the existence of regions depleted by aggregates of certain sizes in the parent branch, and to the change in the exact flow split location in the T-junction with flow ratio. The findings of the present investigation may have significant implications for microvascular flows and may help explain why the effects of physiological RBC aggregation are not deleterious in terms of in vivo vascular resistance.

Deformation of double emulsions under conditions of flow cytometry hydrodynamic focusing

Water-in-oil-in-water (w/o/w) microfluidics double emulsions offer a new route to compartmentalise reagents into isolated aqueous microenvironments while maintaining an aqueous carrier fluid phase; this enables compatibility with commercial flow cytometry systems such as fluorescence-activated cell sorting (FACS). Double emulsion (inner core) deformation under hydrodynamic focusing conditions that mimic the environment double emulsions experience in flow cytometry applications is of particular importance for droplet stability and cell viability. This paper reports on an experimental study of the dynamic deformation of aqueous cores of w/o/w double emulsions under hydrodynamic focusing, with the sheath flow directed at 45° to the sample flow. A number of factors affecting the inner core deformation and recovery were examined. Deformation was found to depend significantly on the core or shell viscosity, the droplet-to-sheath flow velocity ratio, and core and shell sizes. Core deformation was found to depend more on the type of surfactant rather concentration with high molecular weight surfactant exhibiting a negligible effect on deformation whereas low molecular weight surfactant enhancing deformation at low concentrations due to their lateral mobility at the interface.

The microenvironment of double emulsions in rectangular microchannels

The flow environment in inner cores of water-in-oil-in-water (w/o/w) microfluidic double emulsions has a significant impact on industrial applications of such systems. For example, in the case of shear sensitive cells compartmentalised in the cores, high shear conditions may be deleterious. This study reports on the flow characteristics of w/o/w inner cores in comparison to those in single water-in-oil (w/o) microdroplets of equal size moving in the same microchannel, resolved by means of micro-particle image velocimetry (μPIV). The multiphase flow system employed in the study had a viscosity ratio, λ, between aqueous and oil phase of the order of unity (λ = 0.78) and both single droplets and inner cores of double emulsions filled the channel. This configuration resulted in a weak recirculating flow inside the w/o single droplet: the measured flow field exhibited a uniform low velocity flow field in the central region surrounded by small regions of reversed flow near the channel walls. This flow topology was maintained in the inner cores of w/o/w double emulsions for intermediate capillary numbers (Ca) ranging from 10(-3) to 10(-2), and core morphologies varying from large plugs to pancake cores. The core morphology affected the magnitude and distribution of the velocity in the droplets. The similarity in the flow topology resulted from the fact that inner cores were located at the back of the outer droplet in such a way that inner and outer interfaces were in contact for over half of core surface area and separated only by a thin lubricating film. Both single droplets and inner cores exhibited a narrow shear rate distribution characterised by small regions of maximum shear confined near the channel walls. Shear rate magnitude values were found to be an order of magnitude lower than those in the channel and hence capable of reducing stresses in flow cytometry to far below reported values for cell damage. Hence, it can be concluded that double emulsions are suitable candidates to substitute single droplets in flow cytometry to protect the screened items and are compatible with the commercial flow cytometry systems.

Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models

BACKGROUND

The management and prognosis of aortic dissection (AD) is often challenging and the use of personalised computational models is being explored as a tool to improve clinical outcome. Including vessel wall motion in such simulations can provide more realistic and potentially accurate results, but requires significant additional computational resources, as well as expertise. With clinical translation as the final aim, trade-offs between complexity, speed and accuracy are inevitable. The present study explores whether modelling wall motion is worth the additional expense in the case of AD, by carrying out fluid-structure interaction (FSI) simulations based on a sample patient case.

METHODS

Patient-specific anatomical details were extracted from computed tomography images to provide the fluid domain, from which the vessel wall was extrapolated. Two-way fluid-structure interaction simulations were performed, with coupled Windkessel boundary conditions and hyperelastic wall properties. The blood was modelled using the Carreau-Yasuda viscosity model and turbulence was accounted for via a shear stress transport model. A simulation without wall motion (rigid wall) was carried out for comparison purposes.

RESULTS

The displacement of the vessel wall was comparable to reports from imaging studies in terms of intimal flap motion and contraction of the true lumen. Analysis of the haemodynamics around the proximal and distal false lumen in the FSI model showed complex flow structures caused by the expansion and contraction of the vessel wall. These flow patterns led to significantly different predictions of wall shear stress, particularly its oscillatory component, which were not captured by the rigid wall model.

CONCLUSIONS

Through comparison with imaging data, the results of the present study indicate that the fluid-structure interaction methodology employed herein is appropriate for simulations of aortic dissection. Regions of high wall shear stress were not significantly altered by the wall motion, however, certain collocated regions of low and oscillatory wall shear stress which may be critical for disease progression were only identified in the FSI simulation. We conclude that, if patient-tailored simulations of aortic dissection are to be used as an interventional planning tool, then the additional complexity, expertise and computational expense required to model wall motion is indeed justified.

On the flow topology inside droplets moving in rectangular microchannels

The flow topology in moving microdroplets has a significant impact on the behaviour of encapsulated objects and hence on applications of the technology. This study reports on a systematic investigation of the flow field inside droplets moving in a rectangular microchannel, by means of micro-particle image velocimetry (μPIV). Various water/oil (w/o) fluid mixtures were studied in order to elucidate the effects of a number of parameters such as capillary number (Ca), droplet geometry, viscosity ratio and interfacial tension. A distinct change in flow topology was observed at intermediate Ca ranging from 10(-3) to 10(-1), in surfactant-laden droplets, which was attributed primarily to the viscosity ratio of the two phases rather than the Marangoni effect expected in such systems. W/o droplet systems of lower inner-to-outer viscosity ratios tend to exhibit the well-known flow pattern characterised by a parabola-like profile in the droplet bulk-volume, surrounded by two counter rotating recirculation zones on either side of the droplet axis. As the viscosity ratio between the two phases is increased, the flow pattern becomes more uniform, exhibiting low velocities in the droplet bulk-volume and higher-reversed velocities along the w/o interface. The Ca and droplet geometry had no effect on the observed flow topology change. The study highlights the complex, three-dimensional (3D) nature of the flow inside droplets in rectangular microchannels and demonstrates the ability to control the droplet flow environment by adjusting the viscosity ratio between the two phases.

Spatial distributions of red blood cells significantly alter local haemodynamics

Although bulk changes in red blood cell concentration between vessels have been well characterised, local distributions are generally overlooked. Red blood cells aggregate, deform and migrate within vessels, forming heterogeneous distributions which have considerable effect on local haemodynamics. The present study reports data on the local distribution of human red blood cells in a sequentially bifurcating microchannel, representing the branching geometry of the microvasculature. Imaging methodologies with simple extrapolations are used to infer three dimensional, time-averaged velocity and haematocrit distributions under a range of flow conditions. Strong correlation between the bluntness of the velocity and haematocrit profiles in the parent branch of the geometry is observed and red blood cell aggregation has a notable effect on the observed trends. The two branches of the first bifurcation show similar characteristics in terms of the shapes of the profiles and the extent of plasma skimming, despite the difference in geometric configuration. In the second bifurcation, considerable asymmetry between the branches in the plasma skimming relationship is observed, and elucidated by considering individual haematocrit profiles. The results of the study highlight the importance of considering local haematocrit distributions in the analysis of blood flow and could lead to more accurate computational models of blood flow in microvascular networks. The experimental approaches developed in this work provide a foundation for further examining the characteristics of microhaemodynamics.

Development of a patient-specific simulation tool to analyse aortic dissections: assessment of mixed patient-specific flow and pressure boundary conditions

Aortic dissection has high morbidity and mortality rates and guidelines regarding surgical intervention are not clearly defined. The treatment of aortic dissection varies with each patient and detailed knowledge of haemodynamic and mechanical forces would be advantageous in the process of choosing a course of treatment. In this study, a patient-specific dissected aorta geometry is constructed from computed tomography scans. Dynamic boundary conditions are implemented by coupling a three element Windkessel model to the 3D domain at each outlet, in order to capture the essential behaviour of the downstream vasculature. The Windkessel model parameters are defined based on clinical data. The predicted minimum and maximum pressures are close to those measured invasively. Malperfusion is indicated and complex flow patterns are observed. Pressure, flow and wall shear stress distributions are analysed. The methodology presented here provides insight into the haemodynamics in a patient-specific dissected aorta and represents a development towards the use of CFD simulations as a diagnostic tool for aortic dissection.

The effect of red blood cell aggregation on velocity and cell-depleted layer characteristics of blood in a bifurcating microchannel

Red blood cell (RBC) aggregation is a multifaceted phenomenon, and whether it is generally beneficial or deleterious remains unclear. In order to better understand its effect on microvascular blood flow, the phenomenon must be studied in complex geometries, as it is strongly dependent on time, flow, and geometry. The cell-depleted layer (CDL) which forms at the walls of microvessels has been observed to be enhanced by aggregation; however, details of the characteristics of the CDL in complex regions, such as bifurcations, require further investigation. In the present study, a microchannel with a T-junction was used to analyze the influence of aggregation on the flow field and the CDL. Micro-PIV using RBCs as tracers provided high resolution cell velocity data. CDL characteristics were measured from the same data using a newly developed technique based on motion detection. Skewed and sharpened velocity profiles in the daughter branches were observed, contrary to the behavior of a continuous Newtonian fluid. RBC aggregation was observed to increase the skewness, but decrease the sharpening, of the velocity profiles in the daughter branches. The CDL width was found to be significantly greater, with a wider distribution, in the presence of aggregation and the mean width increased proportionally with the reciprocal of the fraction of flow entering the daughter branch. Aggregation also significantly increased the roughness of the interface between the CDL and the RBC core. The present results provide further insight into how RBC aggregation may affect the flow in complex geometries, which is of importance in both understanding its functions invivo, and utilizing it as a tool in microfluidic devices.

Detecting the early onset of shear-induced fibril formation of insulin in situ

A new approach is presented for detecting the early onset of amyloid fibril formation of insulin in a fluidic environment. The fibrillogenesis of insulin in a well-characterized Taylor-Couette flow cell was analyzed in situ using Raman spectroscopy in combination with principal components analysis (PCA). Raman spectra recorded using a 532.5 nm excitation laser revealed a more rapid fibrillogenesis process during the first 90 min of shearing than previously reported for samples exposed to flow. Bands corresponding to intermolecular H-bonded β-sheet structure of insulin at 1678, 1630, and 1625 cm(-1) observed in the Raman difference spectra between unsheared insulin and sheared insulin show an increase in intensity as a function of shear exposure time, which is characteristic of fibril formation, with the first changes detected after 10 min. Additional analysis of samples removed from the flow cell after specific time periods provided conformation of the flow-enhanced fibrillogenesis process, including the detection of early fibril formation after only 1 min of shearing. FT-IR spectra of the insulin solutions showed evolution of bands at 1673 and 1633 cm(-1) from an increase in H-bonded β-turn and β-sheet structures, respectively, while fluorescence emission spectra detected the presence of a new emission band at 482 nm. TEM images confirmed the early onset of fibril formation at 1 min shear exposure, before a maturation and concentration increase of fibrils with further shearing. This study highlights the ability of fluid flows to accelerate insulin fibril formation, which has important implications for biotechnology applications such as the purification process of insulin therapeutic drugs in the pharmaceutical industry, as well as the use of optical-based methods for detecting fibrillogenesis.

Spatial variation of blood viscosity: modelling using shear fields measured by a μPIV based technique

The spatial characteristics of blood viscosity were investigated by combining a newly developed constitutive equation with shear deformation fields calculated from velocity measurements obtained by a μPIV based technique. Blood at physiological hematocrit levels and in the presence of aggregation was sheared in a narrow gap plate-plate geometry and the velocity and aggregation characteristics were determined from images captured using a high resolution camera. Changes in the microstructure of blood caused by aggregation were observed to affect the flow characteristics. At low shear rates, high aggregation and network formation caused the RBC motion to become essentially two-dimensional. The measured velocity fields were used to estimate the magnitude of shear which was subsequently used in conjunction with the new model to assess the spatial variation of viscosity across the flow domain. It was found that the non-uniform microstructural characteristics of blood influence its viscosity distribution accordingly. The viscosity of blood estimated in the core of the examined flow, using a zero-gradient core velocity profile assumption, was found to be significantly higher than the overall effective viscosity determined using other velocity profile assumptions.

Susceptibility of different proteins to flow-induced conformational changes monitored with Raman spectroscopy

By directly monitoring stirred protein solutions with Raman spectroscopy, the reversible unfolding of proteins caused by fluid shear is examined for several natural proteins with varying structural properties and molecular weight. While complete denaturation is not observed, a wide range of spectral variances occur for the different proteins, indicating subtle conformational changes that appear to be protein-specific. A number of significant overall trends are apparent from the study. For globular proteins, the overall extent of spectral variance increases with protein size and the proportion of beta-structure. For two less structured proteins, fetuin and alpha-casein, the observed changes are of relatively low magnitude, despite the greater molecular structural mobility of these proteins. This implies that other protein-specific factors, such as posttranslational modifications, may also be significant. Individual band changes occurring in the spectral profiles of each individual protein are also discussed in detail.

Shear-induced unfolding of lysozyme monitored in situ

Conformational changes due to externally applied physiochemical parameters, including pH, temperature, solvent composition, and mechanical forces, have been extensively reported for numerous proteins. However, investigations on the effect of fluid shear flow on protein conformation remain inconclusive despite its importance not only in the research of protein dynamics but also for biotechnology applications where processes such as pumping, filtration, and mixing may expose protein solutions to changes in protein structure. By combining particle image velocimetry and Raman spectroscopy, we have successfully monitored reversible, shear-induced structural changes of lysozyme in well-characterized flows. Shearing of lysozyme in water altered the protein's backbone structure, whereas similar shear rates in glycerol solution affected the solvent exposure of side-chain residues located toward the exterior of the lysozyme alpha-domain. The results demonstrate the importance of measuring conformational changes in situ and of quantifying fluid stresses by the three-dimensional shear tensor to establish reversible unfolding or misfolding transitions occurring due to flow exposure.

Coupled human erythrocyte velocity field and aggregation measurements at physiological haematocrit levels

Simultaneous measurement of erythrocyte (RBC) velocity fields and aggregation properties has been successfully performed using an optical shearing microscope and Particle Image Velocimetry (PIV). Blood at 45% haematocrit was sheared at rates of 5.4< or =gamma < or = 252 s(-1) and imaged using a high speed camera. The images were then processed to yield aggregation indices and flow velocities. Negligible levels of aggregation were observed for gamma > or = 54.0 s(-1), while high levels of aggregation and network formation occurred for gamma < or = 11.7 s(-1). The results illustrate that the velocity measurements are dependent on the extent of RBC aggregation. High levels of network formation cause the velocities at gamma > or = 5.4 s(-1) to deviate markedly from the expected solid body rotation profile. The effect of aggregation level on the PIV accuracy was assessed by monitoring the two-dimensional (2D) correlation coefficients. Lower levels of aggregation result in poorer image correlation, from which it can be inferred that PIV accuracy is reduced. Moreover, aggregation is time-dependent, and consequently PIV accuracy may decrease during recording as the cells break up. It is therefore recommended that aggregation and its effects are taken into account in future when undertaking blood flow studies using PIV. The simplicity of the technique, which requires no lasers, filters, or special pretreatments, demonstrates the potential wide-spread applicability of the data acquisition system for accurate blood flow PIV and aggregation measurement.