Design of a Transceive Coil Array for Parallel Imaging at 9.4T

The main goal of this thesis is to design and develop a transmit/receive (transceive) coil array for small animal imaging at 9.4T. The goal is achieved by following basic RF design principles with a methodical construction approach and demonstrating viable applications. As operational frequencies increase linearly with higher static fields, the wavelength approaches the size of the sample being imaged. The resulting standing wave mode deteriorates image homogeneity. Fortunately, with multi-channel coil arrays, the produced Bi field can be tailored to produce a homogeneous excitation in the region of interest, thus overcoming the so called dielectric resonance effect. We examined a solution to achieve a higher level of Bx homogeneity and we compared the improvement of RF wavelength effects reduction against the results obtained with a similar-sized conventional birdcage coil. An additional benefit of this design lies in the fact that the use of multiple receiving coil elements is necessary for the implementation of fast imaging acquisition techniques such as parallel imaging. This is possible because the distinct element sensitivities are used to reconstruct conventional images from undersampled (or accelerated) data. The greatest advantage of parallel imaging is thus the reduction of total acquisition time. In functional MRI (fMRI), single-shot EPI is one of the standard imaging technique. Unfortunately, EPI suffers from significant limitations, precisely because all of the data is acquired following a single RF excitation. As a result EPI images can manifest artifacts and blurring due to susceptibility mismatch, off-resonance effects and reduced signal at the edges of k-space. Fortunately, parallel imaging can be used to decrease such unwanted effects by reducing the total k-space data acquired. Presented in this thesis is the logical progression of the construction of a transceive coil from surface coil fundamentals to high field applications such as field focusing and parallel imaging techniques

Compressed Sensing Accelerated Magnetic Resonance Spectroscopic Imaging

abstract: Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker. However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

Advanced sparse sampling techniques for accelerating structural and quantitative MRI

Magnetic Resonance Imaging (MRI) has become a routine clinical procedure for the screening, diagnosis and treatment monitoring of various clinical conditions. Although MRI has highly desirable properties such as being completely non-ionizing and providing excellent soft tissue contrast which has resulted in its widespread usage across the gamut of clinical applications, it is limited by a slow data acquisition process. Several techniques have been developed over the years that have considerably improved the speed of MRI but there is still a clinical need to further accelerate MRI for many clinical applications. This thesis focuses on two recent advances in MRI acceleration to reduce the overall patient scan time. The first part of the thesis describes the development of a fast 3D neuroimaging methodology that has been implemented in a clinical Magnetic Resonance (MR) sequence which was accelerated using a combination of compressed sensing and sampling order optimization of acquired measurements. This methodology reduced the overall scan time by more than 60% compared to the normal scan time while also producing images of acceptable quality for clinical diagnosis. The clinical utility of accelerated neuroimaging is demonstrated by conducting a healthy volunteer study on eight subjects using this fast 3D MRI method. The results of the radiological diagnostic quality assessments that were carried out on the accelerated human brain MR images by four experienced neuroradiologists are presented. The results show that accelerated MR neuroimaging retained sufficient clinical diagnostic value for certain clinical applications. The second part of the thesis describes the development of an accelerated Cartesian sampling scheme for a rapid quantitative MR method called Magnetic Resonance Fingerprinting (MRF). This method was able to simultaneously generate quantitative multi-parametric maps such as T1, T2 and proton density (PD) maps in a very short scan duration that is clinically acceptable. The developed Cartesian sampling method using Echo Planar Imaging (EPI) is compared with conventional spiral sampling that is generally used for MR fingerprinting. The ability of novel iterative reconstruction techniques to improve the multi-parametric estimation accuracy is also demonstrated. The results show that accelerated Cartesian MR fingerprinting can be an alternative to conventional spiral MR fingerprinting

Neural Representations of Visual Motion Processing in the Human Brain Using Laminar Imaging at 9.4 Tesla

During natural behavior, much of the motion signal falling into our eyes is due to our own movements. Therefore, in order to correctly perceive motion in our environment, it is important to parse visual motion signals into those caused by self-motion such as eye- or head-movements and those caused by external motion. Neural mechanisms underlying this task, which are also required to allow for a stable perception of the world during pursuit eye movements, are not fully understood. Both, perceptual stability as well as perception of real-world (i.e. objective) motion are the product of integration between motion signals on the retina and efference copies of eye movements. The central aim of this thesis is to examine whether different levels of cortical depth or distinct columnar structures of visual motion regions are differentially involved in disentangling signals related to self-motion, objective, or object motion. Based on previous studies reporting segregated populations of voxels in high level visual areas such as V3A, V6, and MST responding predominantly to either retinal or extra- retinal (‘real’) motion, we speculated such voxels to reside within laminar or columnar functional units. We used ultra-high field (9.4T) fMRI along with an experimental paradigm that independently manipulated retinal and extra-retinal motion signals (smooth pursuit) while controlling for effects of eye-movements, to investigate whether processing of real world motion in human V5/MT, putative MST (pMST), and V1 is associated to differential laminar signal intensities. We also examined motion integration across cortical depths in human motion areas V3A and V6 that have strong objective motion responses. We found a unique, condition specific laminar profile in human area V6, showing reduced mid-layer responses for retinal motion only, suggestive of an inhibitory retinal contribution to motion integration in mid layers or alternatively an excitatory contribution in deep and superficial layers. We also found evidence indicating that in V5/MT and pMST, processing related to retinal, objective, and pursuit motion are either integrated or colocalized at the scale of our resolution. In contrast, in V1, independent functional processes seem to be driving the response to retinal and objective motion on the one hand, and to pursuit signals on the other. The lack of differential signals across depth in these regions suggests either that a columnar rather than laminar segregation governs these functions in these areas, or that the methods used were unable to detect differential neural laminar processing. Furthermore, the thesis provides a thorough analysis of the relevant technical modalities used for data acquisition and data analysis at ultra-high field in the context of laminar fMRI. Relying on our technical implementations we were able to conduct two high-resolution fMRI experiments that helped us to further investigate the laminar organization of self-induced and externally induced motion cues in human high-level visual areas and to form speculations about the site and the mechanisms of their integration

Applications of MRI Magnetic Susceptibility Mapping in PET-MRI Brain Studies

Magnetic susceptibility mapping (SM) uses magnetic resonance imaging (MRI) phase images to produce maps of the magnetic susceptibility (χ) of tissues. This work focuses on the applications of SM-based imaging to PET-MRI, the hybrid imaging modality which combines positron emission tomography (PET) with MRI. First, the potential of using SM to aid PET attenuation correction (AC) is explored. AC for PET-MRI is challenging as PET-MRI provides no information regarding the electron density of tissues. Recently proposed SM methods for calculating the χ in regions of no MRI signal are used to segment air, bone and soft tissue in order to create AC maps. In the head, SM methods are found to produce inferior air/bone segmentations to high-performing AC methods, but result in more accurate AC than ultrashort-echo (UTE)-based air/bone segmentations, and may be able to provide additional information in subjects with atypical anatomy. Secondly, a SM pipeline for inclusion in a PET-MRI study into biomarkers for Alzheimer’s disease (AD) is developed. In the Insight46 study 500 healthy subjects from the 1946 MRC National Survey of Health and Development are undergoing a comprehensive PET-MRI protocol at two time-points. SM processing methods are compared and optimised, and a method for processing images with oblique imaging planes is developed. The effect of using different tools for automated segmentation of regions of interest (ROIs) on reported regional χ values is analysed. The ROIs resulting from different tools are found to result in large differences in χ values. FIRST is chosen as the most appropriate ROI segmentation tool for this study based on anatomical accuracy as assessed by a neuroradiologist. Initial analysis of χ values from 100 subjects using data from the first time-point is carried out. No significant association with regional χ values is found for amyloid status, PET radiotracer uptake, or APOE genotype

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

© 2019 International Society for Magnetic Resonance in Medicine Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use

Imagerie de diffusion en temps-réel (correction du bruit et inférence de la connectivité cérébrale)

La plupart des constructeurs de systèmes d'imagerie par résonance magnétique (IRM) proposent un large choix d'applications de post-traitement sur les données IRM reconstruites a posteriori, mais très peu de ces applications peuvent être exécutées en temps réel pendant l'examen. Mises à part certaines solutions dédiées à l'IRM fonctionnelle permettant des expériences relativement simples ainsi que d'autres solutions pour l'IRM interventionnelle produisant des scans anatomiques pendant un acte de chirurgie, aucun outil n'a été développé pour l'IRM pondérée en diffusion (IRMd). Cependant, comme les examens d'IRMd sont extrêmement sensibles à des perturbations du système hardware ou à des perturbations provoquées par le sujet et qui induisent des données corrompues, il peut être intéressant d'investiguer la possibilité de reconstruire les données d'IRMd directement lors de l'examen. Cette thèse est dédiée à ce projet innovant. La contribution majeure de cette thèse a consisté en des solutions de débruitage des données d'IRMd en temps réel. En effet, le signal pondéré en diffusion peut être corrompu par un niveau élevé de bruit qui n'est plus gaussien, mais ricien ou chi non centré. Après avoir réalisé un état de l'art détaillé de la littérature sur le bruit en IRM, nous avons étendu l'estimateur linéaire qui minimise l'erreur quadratique moyenne (LMMSE) et nous l'avons adapté à notre cadre de temps réel réalisé avec un filtre de Kalman. Nous avons comparé les performances de cette solution à celles d'un filtrage gaussien standard, difficile à implémenter car il nécessite une modification de la chaîne de reconstruction pour y être inséré immédiatement après la démodulation du signal acquis dans l'espace de Fourier. Nous avons aussi développé un filtre de Kalman parallèle qui permet d'appréhender toute distribution de bruit et nous avons montré que ses performances étaient comparables à celles de notre méthode précédente utilisant un filtre de Kalman non parallèle. Enfin, nous avons investigué la faisabilité de réaliser une tractographie en temps-réel pour déterminer la connectivité structurelle en direct, pendant l'examen. Nous espérons que ce panel de développements méthodologiques permettra d'améliorer et d'accélérer le diagnostic en cas d'urgence pour vérifier l'état des faisceaux de fibres de la substance blanche.Most magnetic resonance imaging (MRI) system manufacturers propose a huge set of software applications to post-process the reconstructed MRI data a posteriori, but few of them can run in real-time during the ongoing scan. To our knowledge, apart from solutions dedicated to functional MRI allowing relatively simple experiments or for interventional MRI to perform anatomical scans during surgery, no tool has been developed in the field of diffusion-weighted MRI (dMRI). However, because dMRI scans are extremely sensitive to lots of hardware or subject-based perturbations inducing corrupted data, it can be interesting to investigate the possibility of processing dMRI data directly during the ongoing scan and this thesis is dedicated to this challenging topic. The major contribution of this thesis aimed at providing solutions to denoise dMRI data in real-time. Indeed, the diffusion-weighted signal may be corrupted by a significant level of noise which is not Gaussian anymore, but Rician or noncentral chi. After making a detailed review of the literature, we extended the linear minimum mean square error (LMMSE) estimator and adapted it to our real-time framework with a Kalman filter. We compared its efficiency to the standard Gaussian filtering, difficult to implement, as it requires a modification of the reconstruction pipeline to insert the filter immediately after the demodulation of the acquired signal in the Fourier space. We also developed a parallel Kalman filter to deal with any noise distribution and we showed that its efficiency was quite comparable to the non parallel Kalman filter approach. Last, we addressed the feasibility of performing tractography in real-time in order to infer the structural connectivity online. We hope that this set of methodological developments will help improving and accelerating a diagnosis in case of emergency to check the integrity of white matter fiber bundles.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF