Transient Anomalous Diffusion MRI in Excised Mouse Spinal Cord: Comparison Among Different Diffusion Metrics and Validation With Histology

Neural tissue is a hierarchical multiscale system with intracellular and extracellular diffusion compartments at different length scales. The normal diffusion of bulk water in tissues is not able to detect the specific features of a complex system, providing nonlocal, diffusion measurement averaged on a 10-20 mm length scale. Being able to probe tissues with sub-micrometric diffusion length and quantify new local parameters, transient anomalous diffusion (tAD) would dramatically increase the diagnostic potential of diffusion MRI (DMRI) in detecting collective and sub-micro architectural changes of human tissues due to pathological damage. In DMRI, the use of tAD parameters quantified using specific DMRI acquisition protocols and their interpretation has often aroused skepticism. Although the derived formulas may accurately fit experimental diffusion-weighted data, the relationships between the postulated dynamical feature and the underlying geometrical structure remains elusive, or at most only suggestive. This work aimed to elucidate and validate the image contrast and information that can be obtained using the tAD model in white matter (WM) through a direct comparison between different diffusion metrics and histology. Towards this goal, we compared tAD metrics extracted from pure subdiffusion (a-imaging) and superpseudodiffusion (g-imaging) in excised mouse spinal cord WM, together with T2 and T2  relaxometry, conventional (normal diffusion-based) diffusion tensor imaging (DTI) and q-space imaging (QSI), with morphologic measures obtained by optical microscopy, to determine which structural and topological characteristics of myelinated axons influenced tAD contrast. Axon diameter (AxDiam), the standard deviation of diameters (SDax:diam), axonal density (AxDens) and effective local density (ELD) were extracted from optical images in several WM tracts. Among all the diffusion parameters obtained at 9.4 T, g-metrics confirmed a strong dependence on magnetic in-homogeneities quantified by R2  = 1/T2  and showed the strongest associations with AxDiam and ELD. On the other hand, a-metrics showed strong associations with SDax:diam and was significantly related to AxDens, suggesting its ability to quantify local heterogeneity degree in neural tissue. These results elucidate the biophysical mechanism underpinning tAD parameters and show the clinical potential of tAD-imaging, considering that both physiologic and pathologic neurodegeneration translate into alterations of WM morphometry and topology

A novel mechanism of contrast in MRI: pseudo super-diffusion of water molecules unveils microstructural details in biological tissues

The goal of this work is to investigate the properties of the contrast provided by Anomalous Diffusion (AD) γ-imaging technique and to test its potential in detecting tissue microstructure. The collateral purpose is to implement this technique by optimizing data acquisition and data processing, with the long term perspective of adoption in massive in vitro, in vivo and clinical studies. The AD γ-imaging technique is a particular kind of Diffusion Weighted- Magnetic Resonance Imaging (DW-MRI). It represents a refinement of conventionally used DW-MRI methods, sharing with them the advantage of being non invasive, since it uses water as an endogenous contrast agent. Besides, it is more suitable to the study of complex tissues, because it is based on a theoretical model that overcomes the simplistic Gaussian assumption. While the Gaussian assumption predicates the linearity between the average molecular displacement of water and the diffusing time, as in case of diffusion in isotropic, homogeneous and infinite environments, a number of experiments performed in vitro and in vivo on both animals and humans showed an anomalous behavior of water molecules, with a non linear relation between the distance travelled and the elapsed time. In particular, the γ-parameter quantifies water pseudo super-diffusion, a peculiarity due to the fact that water diffusion occurs in multi-compartments and it is probed by means of MRI. In fact, a restricted diffusion is rather predicted for water diffusing in biological tissues. Recently, the trick that allows to make the traditional DW-MRI acquisition sequence suitable for pseudo super-diffusion quantification has been unveiled, and in short it consists in performing DW experiments varying the diffusion gradient strengths, at a constant diffusive time. The γ-parameter is extracted by fitting DW-data to a stretched-exponential function. Finally, probing water diffusion in different directions allows to reconstruct a γ-tensor, with scalar invariants that quantify the entity of AD and its anisotropy in a given volume element. In vitro results on inert materials revealed that γ correlates with internal gradients arising from magnetic susceptibility differences (Δ) between neighboring compartments, and that it reflects the multi-compartmentalization of the space explored by diffusing molecules. Furthermore, values of γ compatible with a description of super-diffusive motion were found. This anomaly can be explained considering that the presence of Δ induce an additional attenuation to the signal, simulating a pseudo super-diffusion. Finally, In vivo results on human brain showed that γ is more effective in discriminating among different brain regions compared to conventional DWMRI parameters. These studies suggest that the contrast provided by AD γ-imaging is influenced by an interplay of two factors, Δ -effects on one hand, multicompartmentalization on the other hand, through which γ could reflect tissue microstructure. With the aim to shed some light on this issue I performed AD γ-imaging in excised mouse spinal cord (MSC) at 9.4 T and healthy human brain at 3.0 T. The adoption of MSC was motivated by its current use in studies of demyelination due to an induced pathology that mimics Multiple Sclerosis alterations, and by its simplified geometry. I acquired DW-data with parameters optimized for the particular system chosen: the MSC was scanned along 3 orthogonal directions, thus an apparent γ was derived; for the in vivo studies I used more directions and I extracted a γ-tensor. I found that γ and its anisotropy reflected the microstructure of spinal cord tracts (such as the axon diameters and the axonal density). I investigated both in MSC and human brain the relation between γ and the rate of relaxation (R2*), a parameter well-known to reflect Δ, and found significant linear correlations. Because of this γ was able to differentiate white matter regions on the basis of their spatial orientation, and gray matter regions on the basis of their intrinsic iron content in human brain imaged at 3.0 T. These results suggest that AD γ-imaging could be an alternative or complementary technique to DW-MRI in the field of neuroscience. Indeed it could be useful for the assessment of the bulk susceptibility inhomogeneity, which reflects iron deposition, the hallmark of several neurodegenerative diseases. The part of this thesis work concerning the in vivo experiment in human brain gave rise to a paper published on NeuroImage, a relevant scientific journal in the field of MRI applied to brain investigation

Mini review on anomalous diffusion by MRI: Potential advantages, pitfalls, limitations, nomenclature, and correct interpretation of literature

In this mini-review, we addressed the transient-anomalous diffusion by MRI, starting from the assumption that transient-anomalous diffusion is ubiquitously observed in biological tissues, as demonstrated by different single-particle-tracking optical experiments. The purpose of this review is to identify the main pitfalls that can be encountered when venturing into the field of anomalous diffusion quantified by diffusion-MRI methods. Therefore, the theory of anomalous diffusion deriving from its mathematical definition was reported and connected with the consolidated description and the established procedures of conventional diffusion-MRI of tissues. We highlighted the two different modalities for quantifying subdiffusion and superdiffusion parameters of anomalous diffusion. Then we showed that most of the papers concerning anomalous diffusion, actually deal with pseudo-superdiffusion due to the use of a superdiffusion signal representation. Pseudo-superdiffusion depends on water diffusion multi-compartmentalization and local magnetic in-homogeneities that mimic the superdiffusion of spins. In addition to the relatively large production of pseudosuperdiffusion images, anomalous diffusion research is still in its early stages due to the limited flexibility of conventional clinical MRI scanners that currently prevent the acquisition of diffusion-weighted images by varying the diffusion time (the necessary acquisition modality to quantify transient-subdiffusion in human tissues). Moreover, the wide diffusion gradient pulses complicates the definition of a reliable function representative of anomalous diffusion signal behavior to fit data. Nevertheless, it is important and possible to address these limitations, as one of the potentialities of anomalous diffusion imaging is to increase the resolution, sensitivity, and specificity of MRI

Can anomalous diffusion models in magnetic resonance imaging be used to characterise white matter tissue microstructure?

During the time window of diffusion weighted magnetic resonance imaging experiments (DW-MRI), water diffusion in tissue appears to be anomalous as a transient effect, with a mean squared displacement that is not a linear function of time. A number of statistical models have been proposed to describe water diffusion in tissue, and parameters describing anomalous as well as Gaussian diffusion have previously been related to measures of tissue microstructure such as mean axon radius. We analysed the relationship between white matter tissue characteristics and parameters of existing statistical diffusion models.A white matter tissue model (ActiveAx) was used to generate multiple b-value diffusion-weighted magnetic resonance imaging signals. The following models were evaluated to fit the diffusion signal: 1) Gaussian models - 1a) mono-exponential decay and 1b) bi-exponential decay; 2) Anomalous diffusion models - 2a) stretched exponential, 2b) continuous time random walk and 2c) space fractional Bloch-Torrey equation. We identified the best candidate model based on the relationship between the diffusion-derived parameters and mean axon radius and axial diffusivity, and applied it to the in vivo DW-MRI data acquired at 7.0 T from five healthy participants to estimate the same selected tissue characteristics. Differences between simulation parameters and fitted parameters were used to assess accuracy and in vivo findings were compared to previously reported observations.The space fractional Bloch-Torrey model was found to be the best candidate in characterising white matter on the base of the ActiveAx simulated DW-MRI data. Moreover, parameters of the space fractional Bloch-Torrey model were sensitive to mean axon radius and axial diffusivity and exhibited low noise sensitivity based on simulations. We also found spatial variations in the model parameter β to reflect changes in mean axon radius across the mid-sagittal plane of the corpus callosum.Simulations have been used to define how the parameters of the most common statistical magnetic resonance imaging diffusion models relate to axon radius and diffusivity. The space fractional Bloch-Torrey equation was identified as the best model for the characterisation of axon radius and diffusivity. This model allows changes in mean axon radius and diffusivity to be inferred from spatially resolved maps of model parameters

Double diffusion encoding and applications for biomedical imaging

Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The majority of dMRI techniques employ standard single diffusion encoding (SDE) measurements, covering different sequence parameter ranges depending on the complexity of the method. Although many signal representations and biophysical models have been proposed for SDE data, they are intrinsically limited by a lack of specificity. Advanced dMRI methods have been proposed to provide additional microstructural information beyond what can be inferred from SDE. These enhanced contrasts can play important roles in characterizing biological tissues, for instance upon diseases (e.g. neurodegenerative, cancer, stroke), aging, learning, and development. In this review we focus on double diffusion encoding (DDE), which stands out among other advanced acquisitions for its versatility, ability to probe more specific diffusion correlations, and feasibility for preclinical and clinical applications. Various DDE methodologies have been employed to probe compartment sizes (Section 3), decouple the effects of microscopic diffusion anisotropy from orientation dispersion (Section 4), probe displacement correlations, study exchange, or suppress fast diffusing compartments (Section 6). DDE measurements can also be used to improve the robustness of biophysical models (Section 5) and study intra-cellular diffusion via magnetic resonance spectroscopy of metabolites (Section 7). This review discusses all these topics as well as important practical aspects related to the implementation and contrast in preclinical and clinical settings (Section 9) and aims to provide the readers a guide for deciding on the right DDE acquisition for their specific application

Mri Methods For Imaging The Feto-Placental Vasculature And Blood

Fetal magnetic resonance imaging (MRI) in recent times has become a well-established adjunct to ultrasound (US) in routine clinical prenatal care and diagnostics. The majority of fetal MRI is restricted to T2-weighted scans, where the diagnosis is based on the appearance of normal and abnormal tissue. Although there have been many advancements in MRI and a plethora of sequences, that probe different anatomical and different physiological process, the adaptation of these in fetal imaging has been rather slow. Many of these can extract quantitative parameters that can throw light on the underlying tissue’s normal/patho-physiology. But the use of such quantitative MRI methods has been extremely limited in fetal imaging due to its unique and dynamic physiological milieu that pose several technical challenges including low signal to noise and/or resolution, artifacts associated with abdominal imaging and most importantly fetal motion. These limitations are expected to be overcome by (a) optimizing and (b) developing novel MR imaging sequences, both of which constitute the primary aim of my work. This work develops a framework that allows for vascular imaging in the fetus and placenta. This includes both qualitative vascular imaging and blood flow quantification. Towards this, three broad directions were explored (a) Moving to higher field imaging, while optimizing parameters for low energy deposition and (b) application of non-gated phase contrast MRI and (c) optimization of conventional time-of-flight angiography for fetal applications

Optimized non-invasive MRI protocols for characterizing tissue microstructures: applications in humans to prostate cancer and fetal brain development

This PhD project was aimed to optimize MRI protocols for pelvis imaging, in particular for the diagnosis of prostate cancer (PCa) and for the fetal brain development. Different non-invasive MRI techniques were employed to investigate biological tissues, with the purpose to obtain information on microstructures and potentially metabolism. Prostate cancer is the second most common malignancy and the fifth leading cause of death in men worldwide. Due to the high incidence of PCa and the limitations of current diagnostic methods, the primary goal of this work was to develop an MRI protocol able to improve the sensitivity of the diagnostic. The investigation of prostate cancer started with ex-vivo experiments conducted on specimens of human prostate gland, obtained after radical prostatectomy, with the 9.4T scanner at the NMR and Medical Physics Laboratory of CNR-ISC (Sapienza). Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI) were performed at high-resolution (70x70 micrometers in plane) to evaluate diffusion metrics in the different prostate compartment and directly compare measurements with the histopathology results. This study proceeded with in-vivo experiments with a 3T clinical MR scanner (Philips Achieva at Policlinico Tor Vergata) on subjects with diagnosed PCa. DTI was performed with the purpose to assess its diagnostic ability in individuating and classifying PCa with different ranges of diffusion weightings, i.e. b-values. Our results showing that the diagnostic accuracy of DTI is improved with high diffusion weightings motivated our interest in performing DKI, a technique that captures water diffusion features when high b-values are employed, providing additional information on tissue microstructures, inaccessible to DTI technique. The second part of this PhD project was conducted at the Center for Magnetic Resonance Research (CMRR) in Minneapolis and was funded by the European Union's Horizon 2020 research and innovation program under the Marie Curie grant agreement No 691110 (MICROBRADAM). The study was dedicated to perform prostate cancer imaging with new contrast mechanisms, based on T1rho and T2rho relaxation times. T1rho and T2rho characterize the relaxation of the nuclear magnetization in the rotating frame and they are sensitive to molecular dynamics occurring at frequencies in the range of kHz, characteristic of several in-vivo processes, enabling the access to important information on tissue microenvironment. T1rho and T2rho imaging is limited by the intensive energy deposited by the acquisition sequence, which it is usually overcome by increasing the acquisition time, preventing the possibility of diagnostic applications. Therefore the aim of this work was to develop a new approach to perform imaging in the rotating frame with a three-dimensional acquisition method, recently developed at the CMRR, in order to address the aforementioned shortcomings. Given the incidence of PCa, this research has international interest and potentially contributes to improve not only the sensitivity of PCa diagnostic but also the knowledge of the tissue micro-changing caused by the tumor development. A part of this project was dedicated to Diffusion MRI application in woman pelvis to image fetuses during gestation. The aim of this work was to develop a fast and reliable protocol for fetal imaging to minimize mother-fetal motion artifact and perfusion effects. The protocol designed for acquisition and post-processing was employed to successfully study fetal brain development during the second and third trimester of gestation, in normal cases and in fetuses affected by ventriculomegaly disease. These preliminary data can contribute to delineate a reference standard to assess the normal progress of sulcation and myelination as well as the normative biometry of the fetal brain, improving the knowledge of brain maturation. Globally, the impact of this research lies in having demonstrated that the sensitivity of DMRI for microstructural changes in body tissue caused by cancer, brain disease or normal condition like brain maturation can be fruitfully utilized in combination with artifact correction methods. Moreover, new strategy of image reconstruction, such as 3D gradient echo, can be successfully employed to perform abdominal imaging, enriching the investigation of in-vivo systems with information on tissue microenvironment and metabolism

Imaging Iron Content In Patients With Multiple Sclerosis Using Magnetic Resonance Imaging

The importance of iron in maintaining normal physiological processes in the human body has been well emphasized in the literature. However, when iron behaves badly , its abnormal presence might lead to a spectrum of pathologies depending on what function has been altered. In the brain, for instance, abnormal iron content is thought to be associated with neurodegenerative diseases. In this dissertation, we study iron involvement in one of the most debilitating neurological diseases, multiple sclerosis (MS), using in vivo magnetic resonance imaging. We first test the sensitivity and specificity of the MR method used, known as susceptibility weighted imaging (SWI) compared to other conventional MR techniques and rapid-scanning X-ray fluorescence in MS cadaver brains. Then, we use SWI phase images to assess iron content in the deep gray matter structures of MS patients compared to normal controls. Finally, we assess the possibility of developing a new MS vascular animal model to study the link between vascular abnormalities, iron deposition and sclerotic lesions. As a result of this work, we show that SWI provides a better contrast to image the structures and substructures of the brain based on their iron content compared to conventional MR techniques. The power of SWI in imaging iron content was validated by the use of X-Ray fluorescence (which is known to be an element specific imaging method), showing similar contrast and making SWI the method of choice to image iron content in vivo. Using SWI, we show a clear separation between MS patients and normal subjects, when we assessed iron content in the midbrain, thalamus and basal ganglia. We report that out of the seven structures studied, two were more susceptible to abnormal iron deposition (the pulvinar thalamus in young adults, and the red nucleus in elderly people). Finally, in an MR based study, we show that the swine and the human share a similar cerebrovascular drainage system starting from the superficial cerebral veins and deep cervical veins all the way to the heart, as a means to test the vascular involvement in MS

Advanced parallel magnetic resonance imaging methods with applications to MR spectroscopic imaging

Parallel magnetic resonance imaging offers a framework for acceleration of conventional MRI encoding using an array of receiver coils with spatially-varying sensitivities. Novel encoding and reconstruction techniques for parallel MRI are investigated in this dissertation. The main goal is to improve the actual reconstruction methods and to develop new approaches for massively parallel MRI systems that take advantage of the higher information content provided by the large number of small receivers. A generalized forward model and inverse reconstruction with regularization for parallel MRI with arbitrary k-space sub-sampling is developed. Regularization methods using the singular value decomposition of the encoding matrix and pre-conditioning of the forward model are proposed to desensitize the solution from data noise and model errors. Variable density k-space sub-sampling is presented to improve the reconstruction with the common uniform sub-sampling. A novel method for massively parallel MRI systems named Superresolution Sensitivity Encoding (SURE-SENSE) is proposed where acceleration is performed by acquiring the low spatial resolution representation of the object being imaged and the stronger sensitivity variation from small receiver coils is used to perform intra-pixel reconstruction. SURE-SENSE compares favorably the performance of standard SENSE reconstruction for low spatial resolution imaging such as spectroscopic imaging. The methods developed in this dissertation are applied to Proton Echo Planar Spectroscopic Imaging (PEPSI) for metabolic imaging in human brain with high spatial and spectral resolution in clinically feasible acquisition times. The contributions presented in this dissertation are expected to provide methods that substantially enhance the utility of parallel MRI for clinical research and to offer a framework for fast MRSI of human brain with high spatial and spectral resolution

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