PFG NMR and Bayesian analysis to characterise non-Newtonian fluids

Many industrial flow processes are sensitive to changes in the rheological behaviour of process fluids, and there therefore exists a need for methods that provide online, or inline, rheological characterisation necessary for process control and optimisation over timescales of minutes or less. Nuclear magnetic resonance (NMR) offers a non-invasive technique for this application, without limitation on optical opacity. We present a Bayesian analysis approach using pulsed field gradient (PFG) NMR to enable estimation of the rheological parameters of Herschel-Bulkley fluids in a pipe flow geometry, characterised by a flow behaviour index n, yield stress τ$_{0}$, and consistency factor k, by analysis of the signal in q-space. This approach eliminates the need for velocity image acquisition and expensive gradient hardware. We investigate the robustness of the proposed Bayesian NMR approach to noisy data and reduced sampling using simulated NMR data and show that even with a signal-to-noise ratio (SNR) of 100, only 16 points are required to be sampled to provide rheological parameters accurate to within 2% of the ground truth. Experimental validation is provided through an experimental case study on Carbopol 940 solutions (model Herschel-Bulkley fluids) using PFG NMR at a $^{1}$H resonance frequency of 85.2MHz; for SNR>1000, only 8 points are required to be sampled. This corresponds to a total acquisition time of <60s and represents an 88% reduction in acquisition time when compared to MR flow imaging. Comparison of the shear stress-shear rate relationship, quantified using Bayesian NMR, with non-Bayesian NMR methods demonstrates that the Bayesian NMR approach is in agreement with MR flow imaging to within the accuracy of the measurement. Furthermore, as we increase the concentration of Carbopol 940 we observe a change in rheological characteristics, probably due to shear history-dependent behaviour and the different geometries used. This behaviour highlights the need for online, or inline, rheological characterisation in industrial process applications.AJS and LFG wish to thank the EPSRC (Grant numbers EP/F047991/1 and EP/K039318/1) and TWB wishes to thank the EPSRC and Johnson Matthey plc for financial support

Taking Magnetic Resonance into Industrial Applications

Magnetic resonance (MR) is a highly versatile technique with great potential for use in industrial applications; from the in situ study of unit operations to the optimisation of product properties. This thesis, concerned with the latter, is divided into two parts. Firstly, dynamic MR is applied to characterise the flow behaviour, or rheology, of process fluids. Such characterisation is typically performed using conventional rheometry methods operating offline, with an online, or inline, method sought for process control and optimisation. Until recently, MR was an unlikely choice for this application due to the requirement of high-field MR hardware. However, recent developments in low-field MR hardware mean that the potential of MR in such applications can now be realised. Since the implementation of MR flow imaging is challenging on low-field MR hardware, two new approaches to MR rheometry are described using pulsed field gradient (PFG) MR. A cumulant analysis of the PFG MR signal is first used to characterise the rheology of model power-law fluids, namely xanthan gum-in-water solutions, accurate to within 5% of conventional rheometry, the data being acquired in only 6% of the time required when using MR flow imaging. The second approach utilises a Bayesian analysis of the PFG MR signal to characterise the rheology of model Herschel--Bulkley fluids, namely Carbopol 940-in-water solutions; data are acquired in only 12% of the time required for analysis using MR flow imaging. The suitability of the Bayesian MR approach to study process fluids is demonstrated through experimental study on an alumina-in-acetic acid slurry used by Johnson Matthey. Secondly, MR imaging is used to provide insights into the origins and mechanisms of colloidal gel collapse. Many industrial products are colloidal gels, a space-spanning network of attractive particles with a yield stress. Colloidal gels are, however, known to undergo gravitational collapse after a latency period, thus limiting the shelf-life of products. This remains poorly understood, with a more detailed understanding of both fundamental interest and practical importance. To this end, MR imaging is applied offline to investigate the phase behaviour of colloidal gels. In particular, a comparison of the simulated and experimental phase diagrams suggests gravitational gel collapse to be gravity-driven. Furthermore, measurement of the colloid volume fraction using MR imaging indicates the formation of clusters of colloids at the top of the samples. Whether such clusters initiate gravitational gel collapse is yield stress-dependent; the gravitational stress exerted by a cluster must be sufficient to yield the colloidal gel.Johnson Matthe

Magnetic Resonance Imaging and Velocity Mapping in Chemical Engineering Applications.

This review aims to illustrate the diversity of measurements that can be made using magnetic resonance techniques, which have the potential to provide insights into chemical engineering systems that cannot readily be achieved using any other method. Perhaps the most notable advantage in using magnetic resonance methods is that both chemistry and transport can be followed in three dimensions, in optically opaque systems, and without the need for tracers to be introduced into the system. Here we focus on hydrodynamics and, in particular, applications to rheology, pipe flow, and fixed-bed and gas-solid fluidized bed reactors. With increasing development of industrially relevant sample environments and undersampling data acquisition strategies that can reduce acquisition times to <1 s, magnetic resonance is finding increasing application in chemical engineering research

A Systematic Review and Discussion of the Clinical Potential

Funding Information: Funding by Portuguese Foundation for Science and Technology (FCT-MCTES) under the following projects: PTDC/EMD-EMD/1230/2021—Fluid-structure interaction for functional assessment of ascending aortic aneurysms: a biomechanical-based approach toward clinical practice ; UNIDEMI UIDB/00667/2020; A. Mourato PhD grant UI/BD/151212/2021; R. Valente PhD grant 2022.12223.BD. Publisher Copyright: © 2022 by the authors.Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.publishersversionpublishe

Mutual interferences and design principles for mechatronic devices in magnetic resonance imaging

Purpose: Robotic and mechatronic devices that work compatibly with magnetic resonance imaging (MRI) are applied in diagnostic MRI, image-guided surgery, neurorehabilitation and neuroscience. MRI-compatible mechatronic systems must address the challenges imposed by the scanner's electromagnetic fields. We have developed objective quantitative evaluation criteria for device characteristics needed to formulate design guidelines that ensure MRI-compatibility based on safety, device functionality and image quality. Methods: The mutual interferences between an MRI system and mechatronic devices working in its vicinity are modeled and tested. For each interference, the involved components are listed, and a numerical measure for "MRI-compatibility” is proposed. These interferences are categorized into an MRI-compatibility matrix, with each element representing possible interactions between one part of the mechatronic system and one component of the electromagnetic fields. Based on this formulation, design principles for MRI-compatible mechatronic systems are proposed. Furthermore, test methods are developed to examine whether a mechatronic device indeed works without interferences within an MRI system. Finally, the proposed MRI-compatibility criteria and design guidelines have been applied to an actual design process that has been validated by the test procedures. Results: Objective and quantitative MRI-compatibility measures for mechatronic and robotic devices have been established. Applying the proposed design principles, potential problems in safety, device functionality and image quality can be considered in the design phase to ensure that the mechatronic system will fulfill the MRI-compatibility criteria. Conclusion: New guidelines and test procedures for MRI instrument compatibility provide a rational basis for design and evaluation of mechatronic devices in various MRI applications. Designers can apply these criteria and use the tests, so that MRI-compatibility results can accrue to build an experiential databas

Ultrasound shear wave imaging for diagnosis of nonalcoholic fatty liver disease

Pour le diagnostic et la stratification de la fibrose hépatique, la rigidité du foie est un biomarqueur quantitatif estimé par des méthodes d'élastographie. L'élastographie par ondes de cisaillement (« shear wave », SW) utilise des ultrasons médicaux non invasifs pour évaluer les propriétés mécaniques du foie sur la base des propriétés de propagation des ondes de cisaillement. La vitesse des ondes de cisaillement (« shear wave speed », SWS) et l'atténuation des ondes de cisaillement (« shear wave attenuation », SWA) peuvent fournir une estimation de la viscoélasticité des tissus. Les tissus biologiques sont intrinsèquement viscoélastiques et un modèle mathématique complexe est généralement nécessaire pour calculer la viscoélasticité en imagerie SW. Le calcul précis de l'atténuation est essentiel, en particulier pour une estimation précise du module de perte et de la viscosité. Des études récentes ont tenté d'augmenter la précision de l'estimation du SWA, mais elles présentent encore certaines limites. Comme premier objectif de cette thèse, une méthode de décalage de fréquence revisitée a été développée pour améliorer les estimations fournies par la méthode originale de décalage en fréquence [Bernard et al 2017]. Dans la nouvelle méthode, l'hypothèse d'un paramètre de forme décrivant les caractéristiques spectrales des ondes de cisaillement, et assumé initialement constant pour tous les emplacements latéraux, a été abandonnée permettant un meilleur ajustement de la fonction gamma du spectre d'amplitude. En second lieu, un algorithme de consensus d'échantillons aléatoires adaptatifs (« adaptive random sample consensus », A-RANSAC) a été mis en œuvre pour estimer la pente du paramètre de taux variable de la distribution gamma afin d’améliorer la précision de la méthode. Pour valider ces changements algorithmiques, la méthode proposée a été comparée à trois méthodes récentes permettant d’estimer également l’atténuation des ondes de cisaillements (méthodes de décalage en fréquence, de décalage en fréquence en deux points et une méthode ayant comme acronyme anglophone AMUSE) à l'aide de données de simulations ou fantômes numériques. Également, des fantômes de gels homogènes in vitro et des données in vivo acquises sur le foie de canards ont été traités. Comme deuxième objectif, cette thèse porte également sur le diagnostic précoce de la stéatose hépatique non alcoolique (NAFLD) qui est nécessaire pour prévenir sa progression et réduire la mortalité globale. À cet effet, la méthode de décalage en fréquence revisitée a été testée sur des foies humains in vivo. La performance diagnostique de la nouvelle méthode a été étudiée sur des foies humains sains et atteints de la maladie du foie gras non alcoolique. Pour minimiser les sources de variabilité, une méthode d'analyse automatisée faisant la moyenne des mesures prises sous plusieurs angles a été mise au point. Les résultats de cette méthode ont été comparés à la fraction de graisse à densité de protons obtenue de l'imagerie par résonance magnétique (« magnetic resonance imaging proton density fat fraction », MRI-PDFF) et à la biopsie du foie. En outre, l’imagerie SWA a été utilisée pour classer la stéatose et des seuils de décision ont été établis pour la dichotomisation des différents grades de stéatose. Finalement, le dernier objectif de la thèse consiste en une étude de reproductibilité de six paramètres basés sur la technologie SW (vitesse, atténuation, dispersion, module de Young, viscosité et module de cisaillement). Cette étude a été réalisée chez des volontaires sains et des patients atteints de NAFLD à partir de données acquises lors de deux visites distinctes. En conclusion, une méthode robuste de calcul du SWA du foie a été développée et validée pour fournir une méthode de diagnostic de la NAFLD.For diagnosis and staging of liver fibrosis, liver stiffness is a quantitative biomarker estimated by elastography methods. Ultrasound shear wave (SW) elastography utilizes noninvasive medical ultrasound to assess the mechanical properties of the liver based on the monitoring of the SW propagation. SW speed (SWS) and SW attenuation (SWA) can provide an estimation of tissue viscoelasticity. Biological tissues are inherently viscoelastic in nature and a complex mathematical model is usually required to compute viscoelasticity in SW imaging. Accurate computation of attenuation is critical, especially for accurate loss modulus and viscosity estimation. Recent studies have made attempts to increase the precision of SWA estimation, but they still face some limitations. As a first objective of this thesis, a revisited frequency-shift method was developed to improve the estimates provided by the original implementation of the frequency-shift method [Bernard et al 2017]. In the new method, the assumption of a constant shape parameter of the gamma function describing the SW magnitude spectrum has been dropped for all lateral locations, allowing a better gamma fitting. Secondly, an adaptive random sample consensus algorithm (A-RANSAC) was implemented to estimate the slope of the varying rate parameter of the gamma distribution to improve the accuracy of the method. For the validation of these algorithmic changes, the proposed method was compared with three recent methods proposed to estimate SWA (frequency-shift, two-point frequency-shift and AMUSE methods) using simulation data or numerical phantoms. In addition, in vitro homogenous gel phantoms and in vivo animal (duck) liver data were processed. As a second objective, this thesis also aimed at improving the early diagnosis of nonalcoholic fatty liver disease (NAFLD), which is necessary to prevent its progression and decrease the overall mortality. For this purpose, the revisited frequency-shift method was tested on in vivo human livers. The new method's diagnosis performance was investigated with healthy and NAFLD human livers. To minimize sources of variability, an automated analysis method averaging measurements from several angles has been developed. The results of this method were compared to the magnetic resonance imaging proton density fat fraction (MRI-PDFF) and to liver biopsy. SWA imaging was used for grading steatosis and cut-off decision thresholds were established for dichotomization of different steatosis grades. As a third objective, this thesis is proposing a reproducibility study of six SW-based parameters (speed, attenuation, dispersion, Young’s modulus, viscosity and shear modulus). The assessment was performed in healthy volunteers and NAFLD patients using data acquired at two separate visits. In conclusion, a robust method for computing the liver’s SWA was developed and validated to provide a diagnostic method for NAFLD

Placenta microstructure and microcirculation imaging with diffusion MRI

PURPOSE: To assess which microstructural models best explain the diffusion-weighted MRI signal in the human placenta. METHODS: The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models were fit to the data, and ranked using the Bayesian information criterion. RESULTS: Anisotropic extensions to the intravoxel incoherent motion model, which consider the effect of coherent orientation in both microvascular structure and tissue microstructure, consistently had the lowest Bayesian information criterion values. Model parameter maps and model selection results were consistent with the physiology of the placenta and surrounding tissue. CONCLUSION: Anisotropic intravoxel incoherent motion models explain the placental diffusion signal better than apparent diffusion coefficient, intravoxel incoherent motion, and diffusion tensor models, in information theoretic terms, when using this protocol. Future work will aim to determine if model-derived parameters are sensitive to placental pathologies associated with disorders, such as fetal growth restriction and early-onset pre-eclampsia

Manual and automatic image analysis segmentation methods for blood flow studies in microchannels

In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic phenomena cell-free layer, two developed methods are presented and discussed in order to demonstrate their feasibility to obtain accurate data acquisition in such studies. Additionally, a comparison analysis between manual and automatic methods was performed.This project has been funded by Portuguese national funds of FCT/MCTES (PIDDAC) through the base funding from the following research units: UIDB/00532/2020 (Transport Phenomena Research Center—CEFT), UIDB/04077/2020 (Mechanical Engineering and Resource Sustainability Center—MEtRICs), UIDB/00690/2020 (CIMO). The authors are also grateful for the partial funding of FCT through the projects, NORTE-01-0145-FEDER-029394 (PTDC/EMD-EMD/29394/2017) and NORTE-01-0145-FEDER-030171 (PTDC/EMD-EMD/30171/2017) funded by COMPETE2020, NORTE2020, PORTUGAL2020 and FEDER. D. Bento acknowledges the PhD scholarship SFRH/BD/ 91192/2012 granted by FCT