Field Inhomogeneity Compensation in High Field Magnetic Resonance Imaging (MRI)

This thesis concentrates on the reduction of field (both main field B0 and RF field B1) inhomogeneity in MRI, especially at high B0 field. B0 and B1 field inhomogeneity are major hindrances in high B0 field MRI applications. B1 inhomogeneity will lead to spatially varying signal intensity in the MR images. B0 inhomogeneity produces blurring, distortion and signal loss at tissue interfaces. B0 artifacts are usually termed off-resonance or susceptibility artifacts. None of the existing methods can perfectly correct these inhomogeneity artifacts.This thesis aims at developing three-dimensional (3D) tailored RF (TRF) pulses to mitigate these artifacts. A current limitation in the use of 3D TRF techniques, however, is that pulses are often too long for practical clinical applications. Multiple transmission techniques are proposed to decrease pulse lengths and provide an inherent correction for B1 inhomogeneity. Shorter pulses are also more robust to profile distortions from susceptibility effects.Specifically, slice-selective 3D TRF pulses for multiple (or ¡°parallel¡±) transmitters were designed and validated in uniform phantom and human brain experiments at 3 Tesla. A pseudo-transmit sensitivity encoding (¡°transmit SENSE¡±) method was introduced using a body coil transmitter and multiple receivers to mimic the real parallel transmitter experiment. The kz-direction was controlled by fast switching of gradients in a fashion similar to Echo planar imaging (EPI). The transverse plane (kx-ky) was sampled sparsely with hexagonal trajectories, and accelerated with the transmit SENSE method. The transmit SENSE 3D TRF pulses reduced the B1 inhomogeneity compared to standard SINC pulses in human brain scans. The undersampled transmit SENSE pulses were only 4.3ms long and could excite a 5mm thick slice, which is very promising for clinical applications. Furthermore, these pulses are shown by numerical simulation to have promise in correcting through-plane susceptibility artifacts

Magnetic Resonance Imaging of the Brain in Moving Subjects. Application of Fetal, Neonatal and Adult Brain Studies

Imaging in the presence of subject motion has been an ongoing challenge for magnetic resonance imaging (MRI). Motion makes MRI data inconsistent, causing artifacts in conventional anatomical imaging as well as invalidating diffusion tensor imaging (DTI) reconstruction. In this thesis some of the important issues regarding the acquisition and reconstruction of anatomical and DTI imaging of moving subjects are addressed; methods to achieve high resolution and high signalto- noise ratio (SNR) volume data are proposed. An approach has been developed that uses multiple overlapped dynamic single shot slice by slice imaging combined with retrospective alignment and data fusion to produce self consistent 3D volume images under subject motion. We term this method as snapshot MRI with volume reconstruction or SVR. The SVR method has been performed successfully for brain studies on subjects that cannot stay still, and in some cases were moving substantially during scanning. For example, awake neonates, deliberately moved adults and, especially, on fetuses, for which no conventional high resolution 3D method is currently available. Fine structure of the in-utero fetal brain is clearly revealed for the first time with substantially improved SNR. The SVR method has been extended to correct motion artifacts from conventional multi-slice sequences when the subject drifts in position during data acquisition. Besides anatomical imaging, the SVR method has also been further extended to DTI reconstruction when there is subject motion. This has been validated successfully from an adult who was deliberately moving and then applied to inutero fetal brain imaging, which no conventional high resolution 3D method is currently available. Excellent fetal brain 3D apparent diffusion coefficient (ADC) maps in high resolution have been achieved for the first time as well as promising fractional Anisotropy (FA) maps. Pilot clinical studies using SVR reconstructed data to study fetal brain development in-utero have been performed. Growth curves for the normally developing fetal brain have been devised by the quantification of cerebral and cerebellar volumes as well as some one dimensional measurements. A Verhulst model is proposed to describe these growth curves, and this approach has achieved a correlation over 0.99 between the fitted model and actual data

Advances in diffusion MRI acquisition and processing in the Human Connectome Project

The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013

HYPERPOLARIZED CARBON-13 MAGNETIC RESONANCE MEASUREMENTS OF TISSUE PERFUSION AND METABOLISM

Hyperpolarized Magnetic Resonance Imaging (HP MRI) is an emerging modality that enables non-invasive interrogation of cells and tissues with unprecedented biochemical detail. This technology provides rapid imaging measurements of the activity of a small quantity of molecules with a strongly polarized nuclear magnetic moment. This polarization is created in a polarizer separate from the imaging magnet, and decays continuously towards a non-detectable thermal equilibrium once the imaging agent is removed from the polarizer and administered by intravenous injection. Specialized imaging strategies are therefore needed to extract as much information as possible from the HP signal during its limited lifetime. In this work, we present innovative strategies for measurement of tissue perfusion and metabolism with HP MRI. These techniques include the capacity to sensitize the imaging signal to the diffusive motion of HP molecules, providing improved accuracy and reproducibility for assessment of agent uptake in tissue. The proposed methods were evaluated in numerical simulations, implemented on a preclinical MRI system and demonstrated in vivo in rodents through imaging of HP 13C urea. Using the simulation and imaging infrastructure developed in this work, established methods for encoding HP chemical signals were compared quantitatively. Lastly, our method was adapted for imaging of [2-13C]dihydroxyacetone, a novel HP agent that probes enzymatic flux through multiple biochemical pathways in vivo. Our results demonstrate the capacity of HP MRI to measure tissue perfusion and metabolism in ways not possible with the imaging modalities currently available in the clinic. As the use of HP MRI advances in clinical investigations of human disease, these imaging measurements can offer real-time and individualized information on disease states for early detection and therapeutic guidance

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'

The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

The so-called “dot-compartment” is conjectured in diffusion MRI to represent small spherical spaces, such as cell bodies, in which the diffusion is restricted in all directions. Previous investigations inferred its existence from data acquired with directional diffusion encoding which does not permit a straightforward separation of signals from ‘sticks’ (axons) and signals from ‘dots’. Here we combine isotropic diffusion encoding with ultra-strong diffusion gradients (240 mT/m) to achieve high diffusion-weightings with high signal to noise ratio, while suppressing signal arising from anisotropic water compartments with significant mobility along at least one axis (e.g., axons). A dot-compartment, defined to have apparent diffusion coefficient equal to zero and no exchange, would result in a non-decaying signal at very high b-values (b 7000 s/mm2). With this unique experimental setup, a residual yet slowly decaying, signal above the noise floor for b-values as high as 15 000 s/mm2 was seen clearly in the cerebellar grey matter (GM), and in several white matter (WM) regions to some extent. Upper limits of the dot-signal-fraction were estimated to be 1.8% in cerebellar GM and 0.2% in WM. By relaxing the assumption of zero diffusivity, the signal at high b-values in cerebellar GM could be represented more accurately by an isotropic water pool with a low apparent diffusivity of 0.12 and a substantial signal fraction of 9.7%. The T2 of this component was estimated to be around 61 m s. This remaining signal at high b-values has potential to serve as a novel and simple marker for isotropically-restricted water compartments in cerebellar GM

Model-based reconstruction of accelerated quantitative magnetic resonance imaging (MRI)

Quantitative MRI refers to the determination of quantitative parameters (T1,T2,diffusion, perfusion etc.) in magnetic resonance imaging (MRI). The ’parameter maps’ are estimated from a set of acquired MR images using a parameter model, i.e. a set of mathematical equations that describes the MR images as a function of the parameter(s). A precise and accurate highresolution estimation of the parameters is needed in order to detect small changes and/or to visualize small structures. Particularly in clinical diagnostics, the method provides important information about tissue structures and respective pathologic alterations. Unfortunately, it also requires comparatively long measurement times which preclude widespread practical applications. To overcome such limitations, approaches like Parallel Imaging (PI) and Compressed Sensing (CS) along with the model-based reconstruction concept has been proposed. These methods allow for the estimation of quantitative maps from only a fraction of the usually required data. The present work deals with the model-based reconstruction methods that are applicable for the most widely available Cartesian (rectilinear) acquisition scheme. The initial implementation was based on accelerating the T*2 mapping using Maximum Likelihood estimation and Parallel Imaging (PI). The method was tested on a Multiecho Gradient Echo (MEGE) T*2 mapping experiment in a phantom and a human brain with retrospective undersampling. Since T*2 is very sensitive to phase perturbations as a result of magnetic field inhomogeneity further work was done to address this. The importance of coherent phase information in improving the accuracy of the accelerated T*2 mapping fitting was investigated. Using alternating minimization, the method extends the MLE approach based on complex exponential model fitting which avoids loss of phase information in recovering T*2 relaxation times. The implementation of this method was tested on prospective(real time) undersampling in addition to retrospective. Compared with fully sampled reference scans, the use of phase information reduced the error of the accelerated T*2 maps by up to 20% as compared to baseline magnitude-only method. The total scan time for the four times accelerated 3D T*2 mapping was 7 minutes which is clinically acceptable. The second main part of this thesis focuses on the development of a model-based super-resolution framework for the T2 mapping. 2D multi-echo spin-echo (MESE) acquisitions suffer from low spatial resolution in the slice dimension. To overcome this limitation while keeping acceptable scan times, we combined a classical super-resolution method with an iterative model-based reconstruction to reconstruct T2 maps from highly undersampled MESE data. Based on an optimal protocol determined from simulations, we were able to reconstruct 1mm3 isotropic T2 maps of both phantom and healthy volunteer data. Comparison of T2 values obtained with the proposed method with fully sampled reference MESE results showed good agreement. In summary, this thesis has introduced new approaches to employ signal models in different applications, with the aim of either accelerating an acquisition, or improving the accuracy of an existing method. These approaches may help to take the next step away from qualitative towards a fully quantitative MR imaging modality, facilitating precision medicine and personalized treatment

Robust Magnetic Resonance Imaging of Short T2 Tissues

Tissues with short transverse relaxation times are defined as ‘short T2 tissues’, and short T2 tissues often appear dark on images generated by conventional magnetic resonance imaging techniques. Common short T2 tissues include tendons, meniscus, and cortical bone. Ultrashort Echo Time (UTE) pulse sequences can provide morphologic contrasts and quantitative maps for short T2 tissues by reducing time-of-echo to the system minimum (e.g., less than 100 us). Therefore, UTE sequences have become a powerful imaging tool for visualizing and quantifying short T2 tissues in many applications. In this work, we developed a new Flexible Ultra Short time Echo (FUSE) pulse sequence employing a total of thirteen acquisition features with adjustable parameters, including optimized radiofrequency pulses, trajectories, choice of two or three dimensions, and multiple long-T2 suppression techniques. Together with the FUSE sequence, an improved analytical density correction and an auto-deblurring algorithm were incorporated as part of a novel reconstruction pipeline for reducing imaging artifacts. Firstly, we evaluated the FUSE sequence using a phantom containing short T2 components. The results demonstrated that differing UTE acquisition methods, improving the density correction functions and improving the deblurring algorithm could reduce the various artifacts, improve the overall signal, and enhance short T2 contrast. Secondly, we applied the FUSE sequence in bovine stifle joints (similar to the human knee) for morphologic imaging and quantitative assessment. The results showed that it was feasible to use the FUSE sequence to create morphologic images that isolate signals from the various knee joint tissues and carry out comprehensive quantitative assessments, using the meniscus as a model, including the mappings of longitudinal relaxation (T1) times, quantitative magnetization transfer parameters, and effective transverse relaxation (T2*) times. Lastly, we utilized the FUSE sequence to image the human skull for evaluating its feasibility in synthetic computed tomography (CT) generation and radiation treatment planning. The results demonstrated that the radiation treatment plans created using the FUSE-based synthetic CT and traditional CT data were able to present comparable dose calculations with the dose difference of mean less than a percent. In summary, this thesis clearly demonstrated the need for the FUSE sequence and its potential for robustly imaging short T2 tissues in various applications

Cerebral blood flow estimation from Arterial Spin Labeling MRI with Look-Locker readout: a bayesian approach

Arterial Spin Labeling (ASL) è una tecnica MRI che permette di misurare la perfusione in maniera completamente non invasiva. Diversi modelli sono stati proposti in letteratura per la quantificazione della perfusione (CBF) da acquisizioni ASL. In questo lavoro viene proposto un approccio bayesiano alla quantificazione, in grado di indirizzare al meglio le conoscenze disponibili sui parametri inclusi nel modello. Il modello standard, conosciuto anche come modello di Buxton, è stato consideratoopenEmbargo per motivi di priorità nella ricerca previo accordo con terze part