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

Separation of fluid and solid shear wave fields and quantification of coupling density by magnetic resonance poroelastography

Purpose: Biological soft tissues often have a porous architecture comprising fluid and solid compartments. Upon displacement through physiological or externally induced motion, the relative motion of these compartments depends on poroelastic parameters, such as coupling density (rho 12) and tissue porosity. This study introduces inversion recovery MR elastography (IR-MRE) (1) to quantify porosity defined as fluid volume over total volume, (2) to separate externally induced shear strain fields of fluid and solid compartments, and (3) to quantify coupling density assuming a biphasic behavior of in vivo brain tissue. Theory and Methods: Porosity was measured in eight tofu phantoms and gray matter (GM) and white matter (WM) of 21 healthy volunteers. Porosity of tofu was compared to values obtained by fluid draining and microscopy. Solid and fluid shear-strain amplitudes and rho 12were estimated both in phantoms and in in vivo brain. Results T-1-based measurement of tofu porosity agreed well with reference values (R = 0.99,P < .01). Brain tissue porosity was 0.14 ± 0.02 in GM and 0.05 ± 0.01 in WM (P < .001). Fluid shear strain was found to be phase-locked with solid shear strain but had lower amplitudes in both tofu phantoms and brain tissue (P < .05). In accordance with theory, tofu and brain rho 12were negative. Conclusion: IR-MRE allowed for the first time separation of shear strain fields of solid and fluid compartments for measuring coupling density according to the biphasic theory of poroelasticity. Thus, IR-MRE opens horizons for poroelastography-derived imaging markers that can be used in basic research and diagnostic applications

Inversion‐recovery MR elastography of the human brain for improved stiffness quantification near fluid–solid boundaries

Purpose: In vivo MR elastography (MRE) holds promise as a neuroimaging marker. In cerebral MRE, shear waves are introduced into the brain, which also stimulate vibrations in adjacent CSF, resulting in blurring and biased stiffness values near brain surfaces. We here propose inversion-recovery MRE (IR-MRE) to suppress CSF signal and improve stiffness quantification in brain surface areas. Methods: Inversion-recovery MRE was demonstrated in agar-based phantoms with solid-fluid interfaces and 11 healthy volunteers using 31.25-Hz harmonic vibrations. It was performed by standard single-shot, spin-echo EPI MRE following 2800-ms IR preparation. Wave fields were acquired in 10 axial slices and analyzed for shear wave speed (SWS) as a surrogate marker of tissue stiffness by wavenumber-based multicomponent inversion. Results: Phantom SWS values near fluid interfaces were 7.5 ± 3.0% higher in IR-MRE than MRE (P = .01). In the brain, IR-MRE SNR was 17% lower than in MRE, without influencing parenchymal SWS (MRE: 1.38 ± 0.02 m/s; IR-MRE: 1.39 ± 0.03 m/s; P = .18). The IR-MRE tissue-CSF interfaces appeared sharper, showing 10% higher SWS near brain surfaces (MRE: 1.01 ± 0.03 m/s; IR-MRE: 1.11 ± 0.01 m/s; P < .001) and 39% smaller ventricle sizes than MRE (P < .001). Conclusions: Our results show that brain MRE is affected by fluid oscillations that can be suppressed by IR-MRE, which improves the depiction of anatomy in stiffness maps and the quantification of stiffness values in brain surface areas. Moreover, we measured similar stiffness values in brain parenchyma with and without fluid suppression, which indicates that shear wavelengths in solid and fluid compartments are identical, consistent with the theory of biphasic poroelastic media

Reduction of breathing artifacts in multifrequency magnetic resonance elastography of the abdomen

Purpose: With abdominal magnetic resonance elastography (MRE) often suffering from breathing artifacts, it is recommended to perform MRE during breath-hold. However, breath-hold acquisition prohibits extended multifrequency MRE examinations and yields inconsistent results when patients cannot hold their breath. The purpose of this work was to analyze free-breathing strategies in multifrequency MRE of abdominal organs. Methods: Abdominal MRE with 30, 40, 50, and 60 Hz vibration frequencies and single-shot, multislice, full wave-field acquisition was performed four times in 11 healthy volunteers: once with multiple breath-holds and three times during free breathing with ungated, gated, and navigated slice adjustment. Shear wave speed maps were generated by tomoelastography inversion. Image registration was applied for correction of intrascan misregistration of image slices. Sharpness of features was quantified by the variance of the Laplacian. Results: Total scan times ranged from 120 seconds for ungated free-breathing MRE to 376 seconds for breath-hold examinations. As expected, free-breathing MRE resulted in larger organ displacements (liver, 4.7 ± 1.5 mm; kidneys, 2.4 ± 2.2 mm; spleen, 3.1 ± 2.4 mm; pancreas, 3.4 ± 1.4 mm) than breath-hold MRE (liver, 0.7 ± 0.2 mm; kidneys, 0.4 ± 0.2 mm; spleen, 0.5 ± 0.2 mm; pancreas, 0.7 ± 0.5 mm). Nonetheless, breathing-related displacement did not affect mean shear wave speed, which was consistent across all protocols (liver, 1.43 ± 0.07 m/s; kidneys, 2.35 ± 0.21 m/s; spleen, 2.02 ± 0.15 m/s; pancreas, 1.39 ± 0.15 m/s). Image registration before inversion improved the quality of free-breathing examinations, yielding no differences in image sharpness to uncorrected breath-hold MRE in most organs (P > .05). Conclusion: Overall, multifrequency MRE is robust to breathing when considering whole-organ values. Respiration-related blurring can readily be corrected using image registration. Consequently, ungated free-breathing MRE combined with image registration is recommended for multifrequency MRE of abdominal organs

Changes in Liver Mechanical Properties and Water Diffusivity During Normal Pregnancy Are Driven by Cellular Hypertrophy

During pregnancy, the body's hyperestrogenic state alters hepatic metabolism and synthesis. While biochemical changes related to liver function during normal pregnancy are well understood, pregnancy-associated alterations in biophysical properties of the liver remain elusive. In this study, we investigated 26 ex vivo fresh liver specimens harvested from pregnant and non-pregnant rats by diffusion-weighted imaging (DWI) and magnetic resonance elastography (MRE) in a 0.5-Tesla compact magnetic resonance imaging (MRI) scanner. Water diffusivity and viscoelastic parameters were compared with histological data and blood markers. We found livers from pregnant rats to have (i) significantly enlarged hepatocytes (26 ± 15%, p < 0.001), (ii) increased liver stiffness (12 ± 15%, p = 0.012), (iii) decreased viscosity (-23 ± 14%, p < 0.001), and (iv) increased water diffusivity (12 ± 11%, p < 0.001). In conclusion, increased stiffness and reduced viscosity of the liver during pregnancy are mainly attributable to hepatocyte enlargement. Hypertrophy of liver cells imposes fewer restrictions on intracellular water mobility, resulting in a higher hepatic water diffusion coefficient. Collectively, MRE and DWI have the potential to inform on structural liver changes associated with pregnancy in a clinical context

A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: From current barriers to future adoption

Photoacoustic imaging (PAI), also referred to as optoacoustic imaging, has shown promise in early-stage clinical trials in a range of applications from inflammatory diseases to cancer. While the first PAI systems have recently received regulatory approvals, successful adoption of PAI technology into healthcare systems for clinical decision making must still overcome a range of barriers, from education and training to data acquisition and interpretation. The International Photoacoustic Standardisation Consortium (IPASC) undertook an community exercise in 2022 to identify and understand these barriers, then develop a roadmap of strategic plans to address them. Here, we outline the nature and scope of the barriers that were identified, along with short-, medium- and longterm community efforts required to overcome them, both within and beyond the IPASC group

Assimilation of magnetic resonance elastography data in an in silico brain model

This paper investigates a data assimilation approach for non-invasive quantification of intracranial pressure from partial displacement data, acquired through magnetic resonance elastography. Data assimilation is based on a parametrized-background data weak methodology, in which the state of the physical system -- tissue displacements and pressure fields -- is reconstructed from partially available data assuming an underlying poroelastic biomechanics model. For this purpose, a physics-informed manifold is built by sampling the space of parameters describing the tissue model close to their physiological ranges, to simulate the corresponding poroelastic problem, and compute a reduced basis. Displacements and pressure reconstruction is sought in a reduced space after solving a minimization problem that encompasses both the structure of the reduced-order model and the available measurements. The proposed pipeline is validated using synthetic data obtained after simulating the poroelastic mechanics on a physiological brain. The numerical experiments demonstrate that the framework can exhibit accurate joint reconstructions of both displacement and pressure fields. The methodology can be formulated for an arbitrary resolution of available displacement data from pertinent images. It can also inherently handle uncertainty on the physical parameters of the mechanical model by enlarging the physics-informed manifold accordingly. Moreover, the framework can be used to characterize, in silico, biomarkers for pathological conditions, by appropriately training the reduced-order model. A first application for the estimation of ventricular pressure as an indicator of abnormal intracranial pressure is shown in this contribution

Displacement and pressure reconstruction from magnetic resonance elastography images: Application to an in silico brain model

This paper investigates a data assimilation approach for non-invasive quantification of intracranial pressure from partial displacement data, acquired through magnetic resonance elastography. Data assimilation is based on a parametrized-background data weak methodology, in which the state of the physical system tissue displacements and pressure fields is reconstructed from partially available data assuming an underlying poroelastic biomechanics model. For this purpose, a physics-informed manifold is built by sampling the space of parameters describing the tissue model close to their physiological ranges, to simulate the corresponding poroelastic problem, and compute a reduced basis. Displacements and pressure reconstruction is sought in a reduced space after solving a minimization problem that encompasses both the structure of the reduced-order model and the available measurements. The proposed pipeline is validated using synthetic data obtained after simulating the poroelastic mechanics on a physiological brain. The numerical experiments demonstrate that the framework can exhibit accurate joint reconstructions of both displacement and pressure fields. The methodology can be formulated for an arbitrary resolution of available displacement data from pertinent images. It can also inherently handle uncertainty on the physical parameters of the mechanical model by enlarging the physics-informed manifold accordingly. Moreover, the framework can be used to characterize, in silico, biomarkers for pathological conditions, by appropriately training the reduced-order model. A first application for the estimation of ventricular pressure as an indicator of abnormal intracranial pressure is shown in this contribution

Inversion-recovery MR elastography of the human brain for improved stiffness quantification near fluid-solid boundaries

Purpose: In vivo MR elastography (MRE) holds promise as a neuroimaging marker. In cerebral MRE, shear waves are introduced into the brain, which also stimulate vibrations in adjacent CSF, resulting in blurring and biased stiffness values near brain surfaces. We here propose inversion-recovery MRE (IR-MRE) to suppress CSF signal and improve stiffness quantification in brain surface areas. Methods: Inversion-recovery MRE was demonstrated in agar-based phantoms with solid-fluid interfaces and 11 healthy volunteers using 31.25-Hz harmonic vibrations. It was performed by standard single-shot, spin-echo EPI MRE following 2800-ms IR preparation. Wave fields were acquired in 10 axial slices and analyzed for shear wave speed (SWS) as a surrogate marker of tissue stiffness by wavenumber-based multicomponent inversion. Results: Phantom SWS values near fluid interfaces were 7.5 ± 3.0% higher in IR-MRE than MRE (P =.01). In the brain, IR-MRE SNR was 17% lower than in MRE, without influencing parenchymal SWS (MRE: 1.38 ± 0.02 m/s; IR-MRE: 1.39 ± 0.03 m/s; P =.18). The IR-MRE tissue–CSF interfaces appeared sharper, showing 10% higher SWS near brain surfaces (MRE: 1.01 ± 0.03 m/s; IR-MRE: 1.11 ± 0.01 m/s; P <.001) and 39% smaller ventricle sizes than MRE (P <.001). Conclusions: Our results show that brain MRE is affected by fluid oscillations that can be suppressed by IR-MRE, which improves the depiction of anatomy in stiffness maps and the quantification of stiffness values in brain surface areas. Moreover, we measured similar stiffness values in brain parenchyma with and without fluid suppression, which indicates that shear wavelengths in solid and fluid compartments are identical, consistent with the theory of biphasic poroelastic media. © 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicin

A review of a strategic roadmapping exercise to advance clinical translation of photoacoustic imaging: From current barriers to future adoption.

Photoacoustic imaging (PAI), also referred to as optoacoustic imaging, has shown promise in early-stage clinical trials in a range of applications from inflammatory diseases to cancer. While the first PAI systems have recently received regulatory approvals, successful adoption of PAI technology into healthcare systems for clinical decision making must still overcome a range of barriers, from education and training to data acquisition and interpretation. The International Photoacoustic Standardisation Consortium (IPASC) undertook an community exercise in 2022 to identify and understand these barriers, then develop a roadmap of strategic plans to address them. Here, we outline the nature and scope of the barriers that were identified, along with short-, medium- and long-term community efforts required to overcome them, both within and beyond the IPASC group