Development of magnetic resonance imaging techniques for mouse models of Alzheimer's Disease

Due to increasing life expectancy in western societies, a rise in the prevalence of Alzheimer’s Disease (AD) is expected to have adverse social and economic consequences. The success of emerging treatments for AD relies heavily on the ability to test their efficacy. Sensitive biomarkers are required that provide information specific to the therapeutic targets. Through manipulation of the genome, transgenic mice have been bred to exhibit particular pathological features of AD in isolation. Magnetic Resonance Imaging (MRI) of these mouse models can be used to observe phenotypic abnormalities in-vivo in a controlled environment. As summarised in the introductory chapter, the aim of this work was to develop MRI techniques for inclusion in multi-parametric protocols to characterise AD models in-vivo. Structural MRI has become an increasingly popular tool in the measurement of atrophy of brain tissue over time and requires both accuracy and stability of the imaging system. In chapter 3, a protocol for the calibration of system gradients for high resolution, pre-clinical MRI is described. A structural phantom has been designed and 3D printed for use in a 9.4T small bore MRI and micro CT system. Post processing software is used to monitor gradient stability and provide corrections for scaling errors and non-linearity. Diffusion Tensor Imaging (DTI) and Quantitative Susceptibility Mapping (QSM) are MRI techniques that have shown sensitivity to changes in white matter regions of the brain. QSM may also provide a non invasive method for measurement of increased iron concentration in grey matter tissue observed in AD. Chapters 4 and 5 evaluate the utility of these measurements as imaging biomarkers in a mouse model that exhibits tau pathology associated with AD. Discrepancies between transgenic and wild-type groups were identified for both MRI techniques indicating the potential benefit of their inclusion in a multi-parametric in-vivo protocol

On Nature of the Gradient Echo MR Signal and Its Application to Monitoring Multiple Sclerosis

Multiple Sclerosis is a common disease, affecting 2.5 million people world-wide. The clinical course is heterogeneous, ranging from benign disease in which patients live an almost normal life to severe and devastating disease that may shorten life. Despite much research, a fully effective treatment for MS is still unavailable and diagnostic techniques for monitoring MS disease evolution are much needed. As a non-invasive tool, Magnetic resonance imaging: MRI) plays a key role in MS diagnosis. Numerous MRI techniques have been proposed over the years. Among most widely used are conventional T1-weighted: T1W), T2-weighted: T2W) and FLuid Attenuated Inversion Recovery: FLAIR) imaging techniques. However their results do not correlate well with neurological findings. Several advanced MRI techniques are also used as research tools to study MS. Among them are magnetization transfer contrast imaging: MT), MR spectroscopy: MRS), and Diffusion Tensor Imaging: DTI) but they have not penetrated to clinical arena yet. Gradient Echo Plural Contrast Imaging: GEPCI) developed in our laboratory is a post processing technique based on multi-echo gradient echo sequence. It offers basic contrasts such as T1W images and T2* maps obtained from magnitude of GEPCI signal, and frequency maps obtained from GEPCI signal phase. Phase information of Gradient Echo MR signal has recently attracted much attention of the MR community since it manifests superior gray matter/ white matter contrast and sub-cortical contrast, especially at high field: 7 T) MRI. However the nature of this contrast is under intense debates. Our group proposed a theoretical framework - Generalized Lorentzian Approach - which emphasizes that, contrary to a common-sense intuition, phase contrast in brain tissue is not directly proportional to the tissue bulk magnetic susceptibility but is rather determined by the geometrical arrangement of brain tissue components: lipids, proteins, iron, etc.) at the cellular and sub-cellular levels - brain tissue magnetic architecture . In this thesis we have provide first direct prove of this hypothesis by measurement of phase contrast in isolated optic nerve. We have also provided first quantitative measurements of the contribution to phase contrast from the water-macromolecule exchange effect. Based on our measurement in protein solutions, we demonstrated that the magnitude of exchange effect is 1/2 of susceptibility effect and to the opposite sign. GEPCI technique also offers a scoring method for monitoring Multiple Sclerosis based on the quantitative T2* maps generated from magnitude information of gradient echo signal. Herein we demonstrated a strong agreement between GEPCI quantitative scores and traditional lesion load assessment. We also established a correlation between GEPCI scores and clinical tests for MS patients. We showed that this correlation is stronger than that found between traditional lesion load and clinical tests. Such studies will be carried out for longer period and on MS subjects with broader range of disease severity in the future. We have also demonstrated that the magnitude and phase information available from GEPCI experiment can be combined in multiple ways to generate novel contrasts that can help with visualization of neurological brain abnormalities beyond Multiple Sclerosis. In summary, in this study, we 1) propose novel contrasts for GEPCI from its basic images; 2) investigate the biophysical mechanisms behind phase contrast; 3) evaluate the benefits of quantitative T2* map offered by GEPCI in monitoring disease of Multiple Sclerosis by comparing GEPCI results to clinical standard techniques; 4) apply our theoretical framework - Generalized Lorentzian Approach - to better understand phase contrast in MS lesions

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI

Correction of spatial distortion in magnetic resonance imaging

Dissertation to Obtain the Degree of Master in Biomedical EngineeringMagnetic Resonance Imaging (MRI) has been a major investigation and research focus among scientific and medical communities. So, new hardware with superior magnetic fields and faster sequences has been developed. However, these improvements result in intensity and spatial distortions, particularly in fast sequences, as Echo Plana Imaging (EPI), used in functional and diffusion-weighed MRI (fMRI and DW-MRI). Therefore, correction of spatial distortion is useful to obtain a higher quality in this kind of images. This project contains two major parts. The first part consists in simulating MRI data required for assessing the performance of Registration methods and optimizing parameters. To assess the methods five evaluation metrics were calculated between the corrected data and an undistorted EPI, namely: Root Mean Square (RMS); Normalized Mutual Information (NMI), Squared Correlation Coefficient(SCC); Euclidean Distance of Centres of Mass (CM) and Dice Coefficient of segmented images. In brief, this part validates the applied Registration correction method. The project’s second part includes correction of real images, obtained at a Clinical Partner. Real images are diffusion weighted MRI data with different b-values (gradient strength coefficient), allowing performance assessment of different methods on images with increasing b-values and decreasing SNR. The methods tested on real data were Registration, Field Map correction and a new proposed pipeline, which consists in performing a Field Map correction after a registration process. To assess the accuracy of these methods on real data, we used the same evaluation metrics, as for simulated data, except RMS and Dice Coefficient. At the end, it was concluded that Registration-based methods are better than Field Map, and that the new proposed pipeline produces some improvements in the registration. Regarding the influence of b-value on the correction, it is important to say that the methods performed using images with higher b’s showed more improvements in regarding metric values, but the behaviour is similar for all b-values

Quantitative MRI of the human brain: Magnetisation transfer and magnetic field mapping.

The ultimate goal of this thesis was to identify ways of combining the parametric maps produced by the use of multiple quantitative Magnetic Resonance Imaging (MRI) techniques. As a first stage towards this goal, this thesis focuses on magnetisation transfer (MT) imaging, and on the use of field mapping techniques to improve the reliability of other quantitative techniques such as functional MRI (fMRI) and diffusion tensor (DT) MRI. After summarising the basic principles of MRI, the MT phenomenon is described and a quantitative MT model is reviewed. A set of experiments is then described aiming at optimising the acquisition parameters for the measurement of the MT ratio (MTR). The interaction between T and MT is investigated, confirming that MTR acquisition protocols should be designed to minimize T -weighting. Next, the quantitative model of MT is used to optimise the white-to-grey matter contrast to noise ratio of a pulse sequence for MTR measurement, at both 1.5 T and 3.0 T. The following chapter is focused on the optimisation of quantitative MT for in vivo applications. First, the sensitivity to noise of the technique is investigated using simulations. Second, the implementation of a 3D pulse sequence for quantitative MT is described. The sequence is used at 1.5 T and at 3.0 T to collect data from healthy volunteers, providing normative values. Finally, the set of sampling points used to measure MT parameters is optimised using the Cramer-Rao lower bound, showing dramatic improvements in both precision and accuracy. Next, after a review of static field inhomogeneities and field mapping, the consequences of field inhomogeneities on quantitative MT are evaluated. The use of novel acquisition sequences for field mapping is investigated, the application of field-map based correction for fMRI and DT MRI data is considered, and its effects are discussed. Finally, an attempt to combine different parameters through multivariate analysis is presented, by using principal component analysis to identify patterns of association between MT parameters. Finally, an attempt to combine different tialysis is presented, by using principal componen ssociation between MT parameters

Development and optimization of high resolution multi-shot magnetic resonance acquisitions for diffusion weighted imaging

Diffusion Weighted Imaging (DWI) has become a valuable tool for imaging tissue microstructure, finding use in both clinical and research settings. In order to better resolve finer structures it is desirable to acquire images with higher resolutions. Achieving higher resolutions in diffusion imaging faces several challenges with the primary challenges being low signal to noise ratio and motion induced phase errors. The work in this thesis aims at creating an acquisition that is able to image with a high SNR efficiency in order to achieve higher resolutions. This is accomplished through the use 3D excitations in order to optimize the repetition time in order to operate in a signal to noise ratio efficient regime. High SNR efficiency is also achieved by minimizing TE through the use of spiral readouts. In conjunction with the signal to noise ratio efficiency is the need for motion correction in high resolution diffusion imaging. In this work, the requirements for performing motion correction are analyzed through simulation and in-vivo experiments. The work on motion correction demonstrated the impact that b-value, gradient strength, and cardiac pulsation have on motion induced phase error correction. Results show that a 6 mm resolution navigator is sufficient for correction of motion induced phase errors due to cardiac pulsation at a b-value of 1000 s/mm2 on most current hardware systems. By combining all the methods used in this dissertation, a high quality diffusion weighted imaging approach that uses a novel pulse sequence was developed that has produced high quality diffusion weighted images at a 0.8 mm isotropic resolution. Additionally this work takes several of the advances used in diffusion weighted imaging and applies them to magnet resonance elastography in order to improve the resolution and spatial coverage achievable with magnetic resonance elastography

Investigating the effects of microstructure and magnetic susceptibility in MRI

Over the last decade, phase measurements derived from gradient echo MRI have increasingly been used as a source of quantitative information, allowing tissue composition and microstructure to be probed in vivo and opening up many new avenues of research. However, the non-local nature of phase contrast and the complexity of the underlying sources of phase variation mean that care must be taken in the interpretation and exploitation of phase information. The work described in this thesis explores the application of phase-based quantitative susceptibility measurements in vivo, and uses theory, experiment, and simulation to investigate the contribution of local structural effects to measurements of MRI signal phase. In initial work, the use of phase imaging and quantitative susceptibility mapping (QSM) is compared in the analysis of white matter lesions in multiple sclerosis, demonstrating in vivo the dipolar distortions inherent in phase images, and the correction of such artefacts through the application of QSM, based on a thresholded k-space division method . Visual analysis of the lesions with a focus on the presence of the peripheral rings that occur in some white matter lesions allows comparison of our data with previous studies. A theoretical description of effects of magnetic susceptibility anisotropy using a susceptibility tensor model is then presented, and its predictions tested using macroscopic phantoms composed of pyrolytic graphite sheet, a highly anisotropic and diamagnetic material. The results of these experiments confirm that the full tensor model must be used to predict the effects of structures composed of such materials on the magnetic field. Finally, Monte Carlo simulation is used to demonstrate the effects of perturber shape and diffusion on the MRI signal phase measured from a volume containing oriented, NMR-invisible, spheroidal perturbers with constant bulk magnetic susceptibility. The rate of phase accumulation over time is shown to be highly dependent on perturber shape and diffusion, and the possible implication of these results on real MRI measurements are discussed

Quantitative susceptibility mapping and susceptibility-based distortion correction of echo planar images

Thesis (Ph. D. in Medical Engineering)--Harvard-MIT Program in Health Sciences and Technology, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 143-153).The field of medical image analysis continues to expand as magnetic resonance imaging (MRI) technology advances through increases in field strength and the development of new image acquisition and reconstruction methods. The advent of echo planar imaging (EPI) has allowed volumetric data sets to be obtained in a few seconds, making it possible to image dynamic physiological processes in the brain. In order to extract meaningful information from functional and diffusion data, clinicians and neuroscientists typically combine EPI data with high resolution structural images. Image registration is the process of determining the correct correspondence. Registration of EPI and structural images is difficult due to distortions in EPI data. These distortions are caused by magnetic field perturbations that arise from changes in magnetic susceptibility throughout the object of interest. Distortion is typically corrected by acquiring an additional scan called a fieldmap. A fieldmap provides a direct measure of the magnetic perturbations, allowing distortions to be easily computed and corrected. Fieldmaps, however, require additional scan time, may not be reliable in the presence of significant motion or respiration effects, and are often omitted from clinical protocols. In this thesis, we develop a novel method for correcting distortions in EPI data and registering the EPI to structural MRI. A synthetic fieldmap is computed from a tissue/air segmentation of a structural image using a perturbation method and subsequently used to unwarp the EPI data. Shim and other missing parameters are estimated by registration. We obtain results that are similar to those obtained using fieldmnaps, however, neither fieldmaps nor knowledge of shim coefficients is required. In addition, we describe a method for atlas-based segmentation of structural images for calculation of synthetic fieldmaps. CT data sets are used to construct a probabilistic atlas of the head and corresponding MRI is used to train a classifier that segments soft tissue, air, and bone. Synthetic fieldmap results agree well with acquired fieldmaps: 90% of voxel shifts show subvoxel disagreement with those computed from acquired fieldmaps. In addition, synthetic fieldmaps show statistically significant improvement following inclusion of the atlas. In the second part of this thesis, we focus on the inverse problem of reconstructing quantitative magnetic susceptibility maps from acquired fieldmaps. Iron deposits change the susceptibility of tissue, resulting in magnetic perturbations that are detectable with high resolution fieldmaps. Excessive iron deposition in specific regions of the brain is associated with neurodegenerative disorders such as Alzheimer's and Parkinson's disease. In addition, iron is known to accumulate at varying rates throughout the brain in normal aging. Developing a non-invasive method to calculate iron concentration may provide insight into the role of iron in the pathophysiology of neurodegenerative disease. Calculating susceptibility maps from measured fieldmaps is difficult, however, since iron-related field inhomogeneity may be obscured by larger field perturbations, or 'biasfields', arising from adjacent tissue/air boundaries. In addition, the inverse problem is ill-posed, and fieldmap measurements are only valid in limited anatomical regions. In this dissertation, we develop a novel atlas-based susceptibility mapping (ASM) technique that requires only a single fieldmap acquisition and successfully inverts a spatial formulation of the forward field model. We derive an inhomogeneous wave equation that relates the Laplacian of the observed field to the D'Alembertian of susceptibility, and eliminates confounding biasfields. The tissue/air atlas we constructed for susceptibility-based distortion correction is applied to resolve ambiquity in the forward model arising from the ill-posed inversion. We include fourier-based modeling of external susceptibility sources and the associated biasfield in a variational approach, allowing for simultaneous susceptibility estimation and biasfield elimination. Results show qualitative improvement over two methods commonly used to infer underlying susceptibility values and quantitative susceptibility estimates show stronger correlation with postmortem iron concentrations than competing methods.by Clare Poynton.Ph.D.in Medical Engineerin

Investigating the effects of microstructure and magnetic susceptibility in MRI

Over the last decade, phase measurements derived from gradient echo MRI have increasingly been used as a source of quantitative information, allowing tissue composition and microstructure to be probed in vivo and opening up many new avenues of research. However, the non-local nature of phase contrast and the complexity of the underlying sources of phase variation mean that care must be taken in the interpretation and exploitation of phase information. The work described in this thesis explores the application of phase-based quantitative susceptibility measurements in vivo, and uses theory, experiment, and simulation to investigate the contribution of local structural effects to measurements of MRI signal phase. In initial work, the use of phase imaging and quantitative susceptibility mapping (QSM) is compared in the analysis of white matter lesions in multiple sclerosis, demonstrating in vivo the dipolar distortions inherent in phase images, and the correction of such artefacts through the application of QSM, based on a thresholded k-space division method . Visual analysis of the lesions with a focus on the presence of the peripheral rings that occur in some white matter lesions allows comparison of our data with previous studies. A theoretical description of effects of magnetic susceptibility anisotropy using a susceptibility tensor model is then presented, and its predictions tested using macroscopic phantoms composed of pyrolytic graphite sheet, a highly anisotropic and diamagnetic material. The results of these experiments confirm that the full tensor model must be used to predict the effects of structures composed of such materials on the magnetic field. Finally, Monte Carlo simulation is used to demonstrate the effects of perturber shape and diffusion on the MRI signal phase measured from a volume containing oriented, NMR-invisible, spheroidal perturbers with constant bulk magnetic susceptibility. The rate of phase accumulation over time is shown to be highly dependent on perturber shape and diffusion, and the possible implication of these results on real MRI measurements are discussed

Quantitative Susceptibility Imaging of Tissue Microstructure Using Ultra-High Field MRI

This thesis has used ultra-high field (UHF) magnetic resonance imaging (MRI) to investigate the fundamental relationships between tissue microstructure and such susceptibility-based contrast parameters as the apparent transverse relaxation rate (R2*), the local Larmor frequency shift (LFS) and quantitative volume magnetic susceptibility (QS). The interaction of magnetic fields with biological tissues results in shifts in the LFS which can be used to distinguish underlying cellular architecture. The LFS is also linked to the relaxation properties of tissues in a gradient echo MRI sequence. Equally relevant, histological analysis has identified iron and myelin as two major sources of the LFS. As a result, computation of LFS and the associated volume magnetic susceptibility from MRI phase data may serve as a significant method for in vivo monitoring of changes in iron and myelin associated with normal, healthy aging, as well as neurological disease processes. In this research, the cellular level underpinnings of the R2* and LFS signals were examined in a model rat brain system using 9.4 T MRI. The study was carried out using biophysical modeling and correlation with quantitative histology. For the first time, multiple biophysical modeling schemes were compared in both gray and white matter of excised rat brain tissue. Suprisingly, R2* dependence on tissue orientation has not been fully understood. Accordingly, scaling relations were derived for calculating the reversible, mesoscopic magnetic field component, R2\u27, of the apparent transverse relaxation rate from the orientation dependence in gray and white matter. Our results demonstrate that the orientation dependence of R2* and LFS in both white and cortical gray matter has a sinusoidal dependence on tissue orientation and a linear dependence on the volume fraction of myelin in the tissue. A susceptibility processing pipeline was also developed and applied to the calculation of phase-combined LFS and QS maps. The processing pipeline was subsequently used to monitor myelin and iron changes in multiple sclerosis (MS) patients compared to healthy, age and gender-matched controls. With the use of QS and R2* mapping, evidence of statistically significant increases in iron deposition in sub-cortical gray matter, as well as myelin degeneration along the white matter skeleton, were identified in MS patients. The magnetic susceptibility-based MRI methods were then employed as potential clinical biomarkers for disease severity monitoring of MS. It was demonstrated that the combined use of R2* and QS, obtained from multi-echo gradient echo MRI, could serve as an improved metric for monitoring both gray and white matter changes in early MS