Novel applications, model, and methods in magnetic resonance elastography

Magnetic Resonance Elastography (MRE) is a non-invasive imaging technique that maps and quantifies the mechanical properties of soft tissue related to the propagation and attenuation of shear waves. There is considerable interest in whether MRE can bring new insight into pathologies. Brain in particular has been of utmost interest in the recent years. Brain tumors, Alzheimer's disease, and Multiple Sclerosis have all been subjects of MRE studies. This thesis addresses four aspects of MRE, ranging from novel applications in brain MRE, to physiological interpretation of measured mechanical properties, to improvements in MRE technology. First, we present longitudinal measurements of the mechanical properties of glioblastoma tumorigenesis and progression in a mouse model. Second, we present a new finding from our group regarding a localized change in mechanical properties of neural tissue when functionally stimulated. Third, we address contradictory results in the literature regarding the effects of vascular pressure on shear wave speed in soft tissues. To reconcile these observations, a mathematical model based on poro-hyperelasticity is used. Finally, we consider a part of MRE that requires inferring mechanical properties from MR measurements of vibration patterns in tissue. We present improvements to MRE reconstruction methods by developing and using an advanced variational formulation of the forward problem for shear wave propagation

Simplification of Mathematical Models for Medical Ultrasound Poroelasticity Imaging

The use of an understanding of mechanical properties of tissues for the purposes of medical diagnosis has been going on since the foundation of the medical field as a science. In recent decades, medical ultrasound elastography techniques have been developed and improved and have helped the medical community improve the state of diagnosis and tracking of various diseases like cancer, and lymphedema. Poroelastography, refers to the extension of ultrasound elastography techniques towards imaging the mechanical properties of tissues that are modeled as poroelastic. Currently, the field of poroelastography is stuck, largely due to the complication in the mathematical models surrounding poroelastic materials. This dissertation focuses on the investigation of the suitability of a simplified equation involving a single saturating exponential (i.e. time constant curve) to describe the local time-dependent strain response of non-homogeneous poroelastic materials placed under creep compression. A new algorithm of measuring how precisely a non-linear equation fits a set of data samples from an experiment, the Resimulation of Noise (RoN) algorithm, was developed and implemented for the time constant curve case. The RoN algorithm was shown to track the precision of the fit in a more intuitive and accurate manner than previously used quality of fit metrics. The RoN algorithm coupled with an in-depth FEM simulation study was conducted to see how well the single exponential time-constant curve fit the localized strain samples of a simulated prismatic phantom with a cylindrical inclusion under different permeability and stiffness contrasts. The study showed that, on average, the single exponential time constant curve was suitable within 10% precision for 90% of the phantom's area so long as a mean-mask filter was applied the localized strain images before attempting the curve-fit. Future work in the field of poroelasticity imaging should center around the use of the single exponential time constant curve. This will require the development of a full understanding of how poroelastic material parameter contrast affects the contrast of the measured time constants. Procedures that will help this endeavor: such as the parallelization of the RoN algorithm as well as the development of novel nonhomogeneous poroelastic phantoms with the aid of 3-D printers are also proposed

A numerical framework for interstitial fluid pressure imaging in poroelastic MRE

A numerical framework for interstitial fluid pressure imaging (IFPI) in biphasic materials is investigated based on three-dimensional nonlinear finite element poroelastic inversion. The objective is to reconstruct the time-harmonic pore-pressure field from tissue excitation in addition to the elastic parameters commonly associated with magnetic resonance elastography (MRE). The unknown pressure boundary conditions (PBCs) are estimated using the available full-volume displacement data from MRE. A subzone-based nonlinear inversion (NLI) technique is then used to update mechanical and hydrodynamical properties, given the appropriate subzone PBCs, by solving a pressure forward problem (PFP). The algorithm was evaluated on a single-inclusion phantom in which the elastic property and hydraulic conductivity images were recovered. Pressure field and material property estimates had spatial distributions reflecting their true counterparts in the phantom geometry with RMS errors around 20% for cases with 5% noise, but degraded significantly in both spatial distribution and property values for noise levels > 10%. When both shear moduli and hydraulic conductivity were estimated along with the pressure field, property value error rates were as high as 58%, 85% and 32% for the three quantities, respectively, and their spatial distributions were more distorted. Opportunities for improving the algorithm are discussed

Quantifizierung von Porosität, getrennten Scherwellenfelder der festen und flüssigen Phasen sowie Kopplungsdichte mittels Inversion-Recovery-Magnetresonanzelastographie in porösen Phantomen und In-vivo-Gehirnen

Magnetic resonance elastography (MRE) is an emerging noninvasive technique based on magnetic resonance imaging (MRI) and shear waves that depicts biomechanical properties of biological tissues. In MRE, quantitative parameter maps are usually reconstructed under the assumption of monophasic viscoelastic media. Conversely, the poroelastic model, consisting of a solid porous matrix permeated by a fluid, can better describe the behavior of multiphasic soft tissues, e.g., the brain. However, the assumption of two media and their interactions increases the complexity of the underlying motion equations, impeding their solution without independent information on fluid and solid wavefields and prior porosity quantification. Therefore, the aim of this thesis was threefold: 1) to develop an MRI method for determining porosity; 2) to develop an MRE method for separately encoding shear wave fields of fluid and solid fractions in biphasic tissues; and 3) to estimate coupling density ρ12 and thus experimentally validate the poroelastic model equations. Methods Inversion recovery MRI (IR-MRI) and IR-MRE are introduced for voxel-wise quantification of porosity, shear strain of solid and fluid compartments, and ρ12. Porosity was estimated in fluid phantoms of different relaxation times, fluid-solid tofu phantoms, and in in vivo, in the brains of 21 healthy volunteers. Reference values of phantom porosity were obtained by microscopy and draining the fluid from the matrix. Solid and fluid shear-strain amplitudes and ρ12 were quantified in three tofu phantoms and seven healthy volunteers. Results Phantom porosity measured by IR-MRI agreed well with reference values (R=0.99, P<.01). Average brain tissue porosity was 0.14–0.02 in grey matter and 0.05–0.01 in white matter (P<.001). Fluid shear strain was phase-locked with solid shear strain but had lower amplitudes in both phantoms and brains (P<.05). ρ12 was negative in all materials and biological tissues investigated. Conclusions IR-MRI for the first time allowed noninvasive mapping of in vivo brain porosity and yielded consistent results in tissue-mimicking phantoms. IR-MRI combined with IR-MRE allowed us to separately encode shear strain fields of solid and fluid motion in phantoms and human brain. This led to the quantification of coupling density ρ12, which was negative, as predicted. IR-MRE opens horizons for the development and application of novel imaging markers based on the poroelastic behavior of soft biological tissues. Moreover, quantification of subvoxel multicompartmental interactions provides insight into multiscale mechanical properties, which are potentially relevant for various diagnostic applications.Die Magnetresonanz-Elastographie (MRE) ist eine neuartige Technik, welche die Magnetresonanztomographie (MRT) mit Scherwellen kombiniert, um so die nichtinvasive Darstellung der biomechanischen Gewebeeigenschaften zu ermöglichen. In der MRE werden quantitative Parameterkarten von Weichgewebe unter der Annahme monophasischer, viskoelastischer Materialeigenschaften rekonstruiert. Das in dieser Arbeit verwendete poroelastische Modell hingegen berücksichtigt bei Weichgewebe wie dem Gehirn die Mehrphasigkeit des Gewebe bestehend aus einer festen porösen Matrix und flüssigen Kompartimenten. Deren unabhängige mechanische Eigenschaften und ihre Wechselwirkungen erhöhen die Komplexität der zugrundeliegenden Bewegungsgleichungen in der Poroelastographie, wodurch die Lösung ohne zusätzliche Informationen über die Wellenfelder und vorherige Quantifizierung der Gewebeporosität erschwert wird. Diese Arbeit hatte daher drei Ziele: 1) eine MRT-Methode zur Messung der Gewebeporosität zu entwickeln, 2) eine MRE-Methode zur getrennten Kodierung der Scherwellenfelder von flüssigen und festen Anteilen in biphasischen Geweben zu entwickeln, und 3) die Kopplungsdichte p12 zu bestimmen um so die biphasischen Modellgleichungen experimentell zu validieren. Methoden: Diese Arbeit stellt die Inversion-Recovery-MRT (IR-MRI) sowie die neuartige Inversion-Recovery-MRE (IR-MRE) vor, womit sich die Porosität, die Scherwellenauslenkung der festen und porösen flüssigen Phasen sowie die Kopplungsdichte p12 in Weichgeweben quantifizieren lassen. Porosität wurde in Flüssig-Phantomen unterschiedlicher Relaxationszeiten, Flüssig- Festkörper-Phantomen auf Tofubasis sowie in vivo im Gehirn bei 21 gesunden Probanden ermittelt. Referenzwerte der Porosität wurden in Phantomen durch Mikroskopie sowie Flüssigkeitsdrainage bestimmt. Feste und flüssige Scherauslenkungsamplituden und p12 wurden in drei Tofuphantomen und bei sieben gesunden Probanden quantifiziert. Ergebnisse: Die mittels IR-MRI gemessene Porosität der Phantome stimmte gut mit den Referenzwerten überein (R=0.99, P<.01). Die durchschnittliche Porosität der grauen und weißen Substanz betrug 0.14±0.02 und 0.05±0.01 (P<.001). Die Scherwellenamplituden der flüssigen Anteile und der festen Matrix waren phasengekoppelt, jedoch geringer in den flüssigen Anteilen (P<.05). p12 war in allen untersuchten Materialien und Geweben negativ. Schlussfolgerung: Mittels der IR-MRI konnten erstmals die Porosität von Hirngewebe in vivo nichtinvasiv abgebildet und die Konsistenz der Werte in gewebeähnlichen, porösen Phantomen nachgewiesen werden. Die Kombination von IR-MRI mit IR-MRE ermöglichte die getrennte Kodierung von Scherwellenfeldern fester und flüssiger Phasen und damit die Quantifizierung der Kopplungsdichte p12, welche, wie theoretisch vorhergesagt, negative Werte aufwies. Die IR-MRE eröffnet vielfältige Möglichkeiten zur Entwicklung und Anwendung neuartiger Bildgebungsmarker auf der Grundlage poroelastischer Kenngrößen von Weichgeweben und ermöglicht somit potenziell eine Vielzahl diagnostischer Anwendungen

Viscoelasticity Imaging of Biological Tissues and Single Cells Using Shear Wave Propagation

Changes in biomechanical properties of biological soft tissues are often associated with physiological dysfunctions. Since biological soft tissues are hydrated, viscoelasticity is likely suitable to represent its solid-like behavior using elasticity and fluid-like behavior using viscosity. Shear wave elastography is a non-invasive imaging technology invented for clinical applications that has shown promise to characterize various tissue viscoelasticity. It is based on measuring and analyzing velocities and attenuations of propagated shear waves. In this review, principles and technical developments of shear wave elastography for viscoelasticity characterization from organ to cellular levels are presented, and different imaging modalities used to track shear wave propagation are described. At a macroscopic scale, techniques for inducing shear waves using an external mechanical vibration, an acoustic radiation pressure or a Lorentz force are reviewed along with imaging approaches proposed to track shear wave propagation, namely ultrasound, magnetic resonance, optical, and photoacoustic means. Then, approaches for theoretical modeling and tracking of shear waves are detailed. Following it, some examples of applications to characterize the viscoelasticity of various organs are given. At a microscopic scale, a novel cellular shear wave elastography method using an external vibration and optical microscopy is illustrated. Finally, current limitations and future directions in shear wave elastography are presented

Why Are Viscosity and Nonlinearity Bound to Make an Impact in Clinical Elastographic Diagnosis?

The contributions by Antonio Gomez, Monica Contreras and Francisca S. Molina are gratefully acknowledged.The adoption of multiscale approaches by the biomechanical community has caused a major improvement in quality in the mechanical characterization of soft tissues. The recent developments in elastography techniques are enabling in vivo and non-invasive quantification of tissues’ mechanical properties. Elastic changes in a tissue are associated with a broad spectrum of pathologies, which stems from the tissue microstructure, histology and biochemistry. This knowledge is combined with research evidence to provide a powerful diagnostic range of highly prevalent pathologies, from birth and labor disorders (prematurity, induction failures, etc.), to solid tumors (e.g., prostate, cervix, breast, melanoma) and liver fibrosis, just to name a few. This review aims to elucidate the potential of viscous and nonlinear elastic parameters as conceivable diagnostic mechanical biomarkers. First, by providing an insight into the classic role of soft tissue microstructure in linear elasticity; secondly, by understanding how viscosity and nonlinearity could enhance the current diagnosis in elastography; and finally, by compounding preliminary investigations of those elastography parameters within different technologies. In conclusion, evidence of the diagnostic capability of elastic parameters beyond linear stiffness is gaining momentum as a result of the technological and imaging developments in the field of biomechanics.This research was funded by Ministerio de Educación, Cultura y Deporte grant numbers DPI2017-83859-R, DPI2014-51870-R, UNGR15-CE-3664 and EQC2018-004508-P; Ministerio de Sanidad, Servicios Sociales e Igualdad grant numbers DTS15/00093 and PI16/00339; Instituto de Salud Carlos III y Fondos Feder; Junta de Andalucía grant numbers PI-0107-2017, PIN-0030-2017 and IE2017-5537; Juan de la Cierva Incorporación IJC2018-037167-I, Ministerio de Ciencia, Innovación y Universidades grant number PRE2018-086085

Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography

Objective. Magnetic resonance elastography (MRE) of the brain has shown promise as a sensitive neuroimaging biomarker for neurodegenerative disorders; however, the accuracy of performing MRE of the cerebral cortex warrants investigation due to the unique challenges of studying thinner and more complex geometries. Approach. A series of realistic, whole-brain simulation experiments are performed to examine the accuracy of MRE to measure the viscoelasticity (shear stiffness, μ, and damping ratio, ξ) of cortical structures predominantly effected in aging and neurodegeneration. Variations to MRE spatial resolution and the regularization of a nonlinear inversion (NLI) approach are examined. Main results. Higher-resolution MRE displacement data (1.25 mm isotropic resolution) and NLI with a low soft prior regularization weighting provided minimal measurement error compared to other studied protocols. With the optimized protocol, an average error in μ and ξ was 3% and 11%, respectively, when compared with the known ground truth. Mid-line structures, as opposed to those on the cortical surface, generally display greater error. Varying model boundary conditions and reducing the thickness of the cortex by up to 0.67 mm (which is a realistic portrayal of neurodegenerative pathology) results in no loss in reconstruction accuracy. Significance. These experiments establish quantitative guidelines for the accuracy expected of in vivo MRE of the cortex, with the proposed method providing valid MRE measures for future investigations into cortical viscoelasticity and relationships with health, cognition, and behavior

Effect of Temporal Acquisition Parameters on the Image Quality of Ultrasound Axial Strain Time-constant Elastograms

Recent developments in ultrasound elastography have suggested the possibility of using elastographic methods to estimate the temporal mechanical properties of complex tissues. In this context, elastographic methods to image the axial strain time constant (TC) have been developed. The axial strain TC is a parameter that is related to the viscoelastic and poroelastic behavior of tissues. Estimation of this parameter can be done using curve fitting methods. However, the effect of temporal ultrasonic acquisition parameters, such as window of observation, acquisition rate, and input noise, on the image quality of the resultant TC elastograms has not been investigated yet. Elucidating such effects could be useful for diagnostic applications. This work explores the effects of varying windows of observation, acquisition rate, and input noise on the image quality (accuracy and signal-to-noise ratio (SNR)) of axial strain TC estimates and elastograms using a previously developed simulation model. By varying the amount of data collected as a percentage of the expected TC, the algorithms were able to compute a minimum threshold collection time for an accurate TC estimation as a percentage of the expected TC. The effect of acquisition parameters such as acquisition rate and input noise on the minimum threshold collection time was assessed. Experimental data, collected for previous experiments, were used as a proof of principle to corroborate the simulation findings. The results of this work suggest that there is a linear dependence of the total acquisition time necessary for accurate TC estimates on the true time constant value. The simulation results also indicate that it might be possible to make accurate estimates of the axial strain TC using small windows of observation (as small as 20% of the expected TC) with fast acquisition rates and high input SNR levels. Experimental results suggest that, in practice, a larger window of observation should be used to account for multiple noise sources typically not considered in simulations. This work also suggests that the minimum window of observation necessary for an accurate TC estimate is highly dependent on the acquisition frame rate and the input SNR level. Therefore, use of imaging systems with fast acquisition rates is recommended for studies aiming at measuring time-dependent phenomena in tissues

On the Validation of a Multiple-Network Poroelastic Model Using Arterial Spin Labeling MRI Data

The Multiple-Network Poroelastic Theory (MPET) is a numerical model to characterize the transport of multiple fluid networks in the brain, which overcomes the problem of conducting separate analyses on individual fluid compartments and losing the interactions between tissue and fluids, in addition to the interaction between the different fluids themselves. In this paper, the blood perfusion results from MPET modeling are partially validated using cerebral blood flow (CBF) data obtained from arterial spin labeling (ASL) magnetic resonance imaging (MRI), which uses arterial blood water as an endogenous tracer to measure CBF. Two subjects—one healthy control and one patient with unilateral middle cerebral artery (MCA) stenosis are included in the validation test. The comparison shows several similarities between CBF data from ASL and blood perfusion results from MPET modeling, such as higher blood perfusion in the gray matter than in the white matter, higher perfusion in the periventricular region for both the healthy control and the patient, and asymmetric distribution of blood perfusion for the patient. Although the partial validation is mainly conducted in a qualitative way, it is one important step toward the full validation of the MPET model, which has the potential to be used as a testing bed for hypotheses and new theories in neuroscience research

Entwicklung der multifrequenten Magnetresonanz-Elastographie zur Quantifizierung der biophysikalischen Eigenschaften von menschlichem Hirngewebe

Magnetic resonance elastography (MRE) is an emerging technique for the quantitative imaging of the biophysical properties of soft tissues in humans. Following its successful clinical application in detecting and characterizing liver fibrosis, the scientific community is investigating the use of viscoelasticity as a biomarker for neurological diseases. Clinical implementation requires a thorough understanding of brain tissue mechanics in conjunction with innovative techniques in new research areas. Therefore, three in vivo studies were conducted to analyze the inherent stiffness dispersion of brain tissue over a wide frequency range, to investigate real-time MRE in monitoring the viscoelastic response of brain tissue during the Valsalva maneuver (VM), and to study mechanical alterations of small lesions in multiple sclerosis (MS). Ultra-low frequency MRE with profile-based wave analysis was developed in 14 healthy subjects to determine large-scale brain stiffness, from pulsation-induced shear waves (1 Hz) to ultra-low frequencies (5 – 10 Hz) to the conventional range (20 – 40 Hz). Furthermore, multifrequency real-time MRE with a frame rate of 5.4 Hz was introduced to analyze stiffness and fluidity changes in response to respiratory challenges and cerebral autoregulation in 17 healthy subjects. 2D and 3D wavenumber-based stiffness reconstruction of the brain was established for conventional MRE in 12 MS patients. MS lesions were analyzed in terms of mechanical contrast with surrounding tissue in relation to white matter (WM) heterogeneity. We found superviscous properties of brain tissue at large scales with a strong stiffness dispersion and a relatively high model-based viscosity of η = 6.6 ± 0.3 Pa∙s. The brain’s viscoelasticity was affected by perfusion changes during VM, which was associated with an increase in brain stiffness of 6.7% ± 4.1% (p<.001), whereas fluidity decreased by -2.1 ± 1.4% (p<.001). In the diseased brain, the analysis of 147 MS lesions revealed 46% of lesions to be softer and 54% of lesions to be stiffer than surrounding tissue. However, due to the heterogeneity of WM stiffness, the results provide no significant evidence for a systematic pattern of mechanical variations in MS. Nevertheless, the results may explain, for the first time, the gap between static ex vivo and dynamic in vivo methods. Fluidity-induced dispersion provides rich information on the structure of tissue compartments. Moreover, viscoelasticity is affected by perfusion during cerebral autoregulation and thus may be sensitive to intracranial pressure modulation. The overall heterogeneity of stiffness obscures changes in MS lesions, and MS may not exhibit sclerosis as a mechanical signature. In summary, this thesis contributes to the field of human brain MRE by presenting new methods developed in studies conducted in new research areas using state-of-the-art technology. The results advance clinical applications and open exciting possibilities for future in vivo studies of human brain tissue.Die Magnetresonanz-Elastographie (MRE) ist ein Verfahren zur quantitativen Darstellung der viskoelastischen Eigenschaften von Weichgewebe. Nach der erfolgreichen klinischen Anwendung in der Leberdiagnostik wird versucht, Viskoelastizität als Biomarker für neurologische Krankheiten zu nutzen. Hierzu bedarf es einer genauen Analyse der Gewebemechanik und innovativen Anwendungsgebieten. Daher, wurden drei Studien durchgeführt, um die Steifigkeitsdispersion von Hirngewebe zu analysieren, das viskoelastische Verhalten während des Valsalva Manövers (VM) abzubilden, und die mechanischen Veränderungen in Läsionen bei Multipler Sklerose (MS) zu untersuchen. Niedrigfrequenz-MRE mit profilbasierter Wellenanalyse wurde in 14 Probanden entwickelt, um die Steifigkeit des Gesamthirns von pulsationsinduzierten Scherwellen (1 Hz) über ultraniedrige Frequenzen (5 – 10 Hz) bis hin zum konventionellen Bereich (20 – 40 Hz) zu bestimmen. Außerdem wurde die multifrequente Echtzeit-MRE mit einer Bildfrequenz von 6.4 Hz eingeführt, um die viskoelastische Antwort des Gehirns auf respiratorische Herausforderungen bei 17 gesunden Probanden zu untersuchen. Neue 2D- und 3D-Wellenzahl-basierte Steifigkeitsrekonstruktionen für das Gehirn wurden in 12 MS Patienten und konventioneller MRE entwickelt. Die Steifigkeitsänderungen in MS-Läsionen wurden mit umliegender weißer Substanz und dessen Heterogenität verglichen. Wir fanden superviskose Eigenschaften des Hirngewebes mit einer starken Dispersion und relativ hohen, modellbasierten Viskosität von η = 6,6 ± 0,3 Pa∙s. Die mechanischen Gewebeeigenschaften wurden durch Perfusionsänderungen während VM beeinflusst und die Hirnsteifigkeit erhöhte sich um 6,7 ± 4,1% (p<.001) wobei sich die Fluidität um -2,1 ± 1,4% (p<.001) verringerte. Die Analyse von 147 MS-Läsionen ergab, dass 54% bzw. 46% der Läsionen steifer bzw. weicher sind als das umgebende Gewebe. Aufgrund der Heterogenität der WM-Steifigkeit konnte jedoch kein Hinweis auf ein systematisches Muster mechanischer Veränderungen in MS-Läsionen gefunden werden. Die Ergebnisse können zum ersten Mal die Lücke zwischen statischen ex vivo und dynamischen in vivo Methoden erklären. Die fluiditätsinduzierte Dispersion liefert interessante Informationen über die zugrundeliegende Gewebestruktur. Darüber hinaus wird die Viskoelastizität durch die Perfusion während der zerebralen Autoregulation beeinflusst und kann daher empfindlich auf intrakranielle Druckschwankungen reagieren. Die allgemeine Heterogenität der Steifigkeit überschattet die Veränderungen in MS-Läsionen, und somit ist Sklerose möglicherweise kein prominentes Merkmal von MS. Zusammenfassend lässt sich festhalten, dass diese Dissertation einen Beitrag zum Gebiet der MRE leistet, indem neue Methoden und Anwendungen in neuen Forschungsgebieten mit modernster Technologie dargestellt werden. Hierdurch wird die klinische Translation gefördert und spannende Möglichkeiten für zukünftige Studien eröffnet