Real-time Feedback of B0 Shimming at Ultra High Field MRI

Magnetic resonance imaging(MRI) is moving towards higher and higher field strengths. After 1.5T MRI scanners became commonplace, 3T scanners were introduced and once 3T scanners became commonplace, ultra high field (UHF) scanners were introduced. UHF scanners typically refer to scanners with a field strength of 7T or higher. The number of sites that utilise UHF scanners is slowly growing and the first 7T MRI scanners were recently CE certified for clinical use. Although UHF scanners have the benefit of higher signal-to-noise ratio (SNR), they come with their own challenges. One of the many challenges is the problem of inhomogeneity of the main static magnetic field(B0 field). This thesis addresses multiple aspects associated with the problem of B0 inhomogeneity. The process of homogenising the field is called "shimming". The focus of this thesis is on active shimming where extra shim coils drive DC currents to generate extra magnetic fields superimposed on the main magnetic field to correct for inhomogeneities. In particular, we looked at the following issues: algorithms for calculating optimal shim currents; global static shimming using very high order/degree spherical harmonic-based (VHOS) coils; dynamic slice-wise shimming using VHOS coils compared to a localised multi-coil array shim system; B0 field monitoring using an NMR field camera; characterisation of the shim system using a field camera; and designing a controller based on the shim system model for real-time feedback

Fast high-resolution metabolite mapping in the rat brain using 1H-FID-MRSI at 14.1T

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous non-invasive acquisition of MR spectra from multiple spatial locations inside the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical settings, mostly because of difficulties specifically related to very small nominal voxel size in the rodent brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio SNR. In this context, we implemented a free induction decay 1H-MRSI sequence (1H-FID-MRSI) in the rat brain at 14.1T. We combined the advantages of 1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage and spatial resolution in the rodent brain, and developed a custom dedicated processing pipeline with a graphical user interface: MRS4Brain toolbox. LCModel fit, using the simulated metabolite basis-set and in-vivo measured MM, provided reliable fits for the data at acquisition delays of 1.3 and 0.94 ms. The resulting Cram\'er-Rao lower bounds were sufficiently low (<40%) for eight metabolites of interest, leading to highly reproducible metabolic maps. Similar spectral quality and metabolic maps were obtained between 1 and 2 averages, with slightly better contrast and brain coverage due to increased SNR in the latter case. Furthermore, the obtained metabolic maps were accurate enough to confirm the previously known brain regional distribution of some metabolites. The acquisitions proved high repeatability over time. We demonstrated that the increased SNR and spectral resolution at 14.1T can be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in 13 minutes, using the sequence and processing pipeline described herein. High-resolution 1H-FID-MRSI at 14.1T provided reproducible and high-quality metabolic mapping of brain metabolites with significantly reduced technical limitations.Comment: Dunja Simicic and Brayan Alves are joint first author

Noise-reduction techniques for 1H-FID-MRSI at 14.1T: Monte-Carlo validation & in vivo application

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high-resolution over the entire brain. The constant demand for higher spatial resolution in 1H-MRSI led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, the Marchenko-Pastur principal component analysis (MP-PCA) based denoising and the low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential and impact on preclinical 14.1T fast in vivo 1H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte-Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio SNR while preserving noise properties in each spectrum for both in vivo and Monte-Carlo datasets. Relative metabolite concentrations were not significantly altered by either methods and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted on lower concentrated metabolites. Our study provided a framework on how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care especially for low-concentrated metabolites.Comment: Brayan Alves and Dunja Simicic are joint first authors. Currently in revision for NMR in Biomedicin

ECCENTRIC: a fast and unrestrained approach for high-resolution in vivo metabolic imaging at ultra-high field MR

A novel method for fast and high-resolution metabolic imaging, called ECcentric Circle ENcoding TRajectorIes for Compressed sensing (ECCENTRIC), has been developed and implemented on 7 Tesla human MRI. ECCENTRIC is a non-Cartesian spatial-spectral encoding method optimized for random undersampling of magnetic resonance spectroscopic imaging (MRSI) at ultra-high field. The approach provides flexible and random (k,t) sampling without temporal interleaving to improve spatial response function and spectral quality. ECCENTRIC needs low gradient amplitudes and slew-rates that reduces electrical, mechanical and thermal stress of the scanner hardware, and is robust to timing imperfection and eddy-current delays. Combined with a model-based low-rank reconstruction, this approach enables simultaneous imaging of up to 14 metabolites over the whole-brain at 2-3mm isotropic resolution in 4-10 minutes with high signal-to-noise ratio. In 20 healthy volunteers and 20 glioma patients ECCENTRIC demonstrated unprecedented mapping of fine structural details of metabolism in healthy brains and an extended metabolic fingerprinting of glioma tumors.Comment: 20 pages, 7 figures,2 tables, 10 pages supplementary materia

MP-PCA denoising for diffusion MRS data: promises and pitfalls.

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4T in rat brain and at 3T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

Purpose: We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level. Methods: The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0–4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency. Results: The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout. Conclusions: We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems

Proton metabolic mapping of the brain at 7 T using a two-dimensional free induction decay-echo-planar spectroscopic imaging readout with lipid suppression

The increased signal-to-noise ratio (SNR) and chemical shift dispersion at high magnetic fields (≥7 T) have enabled neuro-metabolic imaging at high spatial resolutions. To avoid very long acquisition times with conventional magnetic resonance spectroscopic imaging (MRSI) phase-encoding schemes, solutions such as pulse-acquire or free induction decay (FID) sequences with short repetition time and inner volume selection methods with acceleration (echo-planar spectroscopic imaging [EPSI]), have been proposed. With the inner volume selection methods, limited spatial coverage of the brain and long echo times may still impede clinical implementation. FID-MRSI sequences benefit from a short echo time and have a high SNR per time unit; however, contamination from strong extra-cranial lipid signals remains a problem that can hinder correct metabolite quantification. L2-regularization can be applied to remove lipid signals in cases with high spatial resolution and accurate prior knowledge. In this work, we developed an accelerated two-dimensional (2D) FID-MRSI sequence using an echo-planar readout and investigated the performance of lipid suppression by L2-regularization, an external crusher coil, and the combination of these two methods to compare the resulting spectral quality in three subjects. The reduction factor of lipid suppression using the crusher coil alone varies from 2 to 7 in the lipid region of the brain boundary. For the combination of the two methods, the average lipid area inside the brain was reduced by 2% to 38% compared with that of unsuppressed lipids, depending on the subject's region of interest. 2D FID-EPSI with external lipid crushing and L2-regularization provides high in-plane coverage and is suitable for investigating brain metabolite distributions at high fields

Whole‐brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism

Deuterium metabolic imaging (DMI) is an emerging magnetic resonance technique, for non‐invasive mapping of human brain glucose metabolism following oral or intravenous administration of deuterium‐labeled glucose. Regional differences in glucose metabolism can be observed in various brain pathologies, such as Alzheimer's disease, cancer, epilepsy or schizophrenia, but the achievable spatial resolution of conventional phase‐encoded DMI methods is limited due to prolonged acquisition times rendering submilliliter isotropic spatial resolution for dynamic whole brain DMI not feasible. The purpose of this study was to implement non‐Cartesian spatial‐spectral sampling schemes for whole‐brain 2H FID‐MR Spectroscopic Imaging to assess time‐resolved metabolic maps with sufficient spatial resolution to reliably detect metabolic differences between healthy gray and white matter regions. Results were compared with lower‐resolution DMI maps, conventionally acquired within the same session. Six healthy volunteers (4 m/2 f) were scanned for ~90 min after administration of 0.8 g/kg oral [6,6′]‐2H glucose. Time‐resolved whole brain 2H FID‐DMI maps of glucose (Glc) and glutamate + glutamine (Glx) were acquired with 0.75 and 2 mL isotropic spatial resolution using density‐weighted concentric ring trajectory (CRT) and conventional phase encoding (PE) readout, respectively, at 7 T. To minimize the effect of decreased signal‐to‐noise ratios associated with smaller voxels, low‐rank denoising of the spatiotemporal data was performed during reconstruction. Sixty‐three minutes after oral tracer uptake three‐dimensional (3D) CRT‐DMI maps featured 19% higher (p = .006) deuterium‐labeled Glc concentrations in GM (1.98 ± 0.43 mM) compared with WM (1.66 ± 0.36 mM) dominated regions, across all volunteers. Similarly, 48% higher (p = .01) 2H‐Glx concentrations were observed in GM (2.21 ± 0.44 mM) compared with WM (1.49 ± 0.20 mM). Low‐resolution PE‐DMI maps acquired 70 min after tracer uptake featured smaller regional differences between GM‐ and WM‐dominated areas for 2H‐Glc concentrations with 2.00 ± 0.35 mM and 1.71 ± 0.31 mM, respectively (+16%; p = .045), while no regional differences were observed for 2H‐Glx concentrations. In this study, we successfully implemented 3D FID‐MRSI with fast CRT encoding for dynamic whole‐brain DMI at 7 T with 2.5‐fold increased spatial resolution compared with conventional whole‐brain phase encoded (PE) DMI to visualize regional metabolic differences. The faster metabolic activity represented by 48% higher Glx concentrations was observed in GM‐ compared with WM‐dominated regions, which could not be reproduced using whole‐brain DMI with the low spatial resolution protocol. Improved assessment of regional pathologic alterations using a fully non‐invasive imaging method is of high clinical relevance and could push DMI one step toward clinical applications

Quantitative Magnetic Resonance Spectroscopy of Brain Metabolites and Macromolecules at Ultra-High Field

Die Protonen-Magnetresonanzspektroskopie (1H-MRS) ist eine nicht-invasive Technik, die die Untersuchung der neurochemischen Zusammensetzung des menschlichen Gehirns ermöglicht. Bedeutende klinische Anwendungen von 1H-MRS ergaben sich in der Diagnose von Erkrankungen, in dem Verständnis von Krankheitsmechanismen oder in der Behandlungsüberwachung. Die zuverlässige Erkennung und Quantifizierung der Metaboliten ist von größter Bedeutung, um Biomarker für verschiedene neurologische Krankheiten zu etablieren. Zusätzlich enthalten Makromoleküle, die in dem Protonen-Spektrum breite Spektrallinien unter dem Metaboliten-Spektrum bilden, zahlreiche, wertvolle Informationen. Die Spektrallinien der Makromoleküle stammen von Aminosäuren aus Proteinen und Peptiden des Cytosols. Frühere Studien haben die klinische Relevanz von Makromolekülen in Erkrankungen wie Multiple Sklerose, Tumoren oder chronisch- traumatische Enzephalopathie gezeigt. Jedoch müssen mehrere Charakteristiken der Makromoleküle noch erforscht werden. Ein tiefgehendes Verständnis der Makromoleküle könnte dabei die Entdeckung neuer Biomarker für neurologische Krankheiten ermöglichen. Zusätzlich kann die Charakterisierung der makromolekularen Spektrallinien helfen folgende offene Fragen der MR Spektroskopie zu beantworten: den biologischen Ursprung der einzelnen makromolekularen Spektrallinien, die Zuordnung der makromolekularen Spektrallinien zu einzelnen Aminosäuren sowie die Untersuchung von anderen möglichen Beiträgen zum Signal der Makromoleküle wie z.B. verschiedene Zucker, DNA oder RNA. Die Sensitivität von MRS wurde durch stärkere Magnetfelder erheblich verbessert. MRS Messungen am Ultrahochfeld (≥7 T) profitieren von einem höheren Signal-Rausch- Verhältnis und einer höheren spektralen Auflösung. Zusätzlich wurden Lokalisierungsmethoden und Quantifizierungsmethoden weiterentwickelt, die es ermöglichen, die Konzentrationen auch der Metaboliten und Makromoleküle akkurat zu bestimmen, die ein kleines Signal-Rausch-Verhältnis haben oder komplexere spektrale Muster aufgrund von J-Kopplung aufweisen. Im Fokus des ersten Teils dieser Doktorarbeit steht die Charakterisierung der physikalischen Eigenschaften der makromolekularen Spektrallinien und die Frage, wie diese das Metaboliten-Spektrum beeinflussen. Dazu wurden Spektren am 9.4 T im menschlichen Gehirn aufgenommen, um hiermit T2 Relaxationszeiten zu bestimmen bzw. Linienbreiten quantitativ zu analysieren. Diese Analysen liefern Erkenntnisse über die spektrale Überlappung und J-Kopplungseffekte, die man in den makromolekularen Spektrallinien beobachtet. Zusätzlich wird eine neue „double inversion recovery“ Methode vorgestellt, um damit die T1 Relaxationszeiten von einzelnen makromolekularen Spektrallinien zu bestimmen. Der zweite Teil dieser Doktorarbeit beschäftigt sich mit der Quantifizierung von den Metaboliten des menschlichen Gehirns am 9.4 T mittels ein- und zweidimensionaler MRS Methoden. Die Konzentrationen der Metaboliten werden in mmol/kg berichtet. Hierbei wurden T1- und T2-Gewichtungen korrigiert sowie die Zusammensetzung des gemessenen Gewebes berücksichtigt. Die resultierenden Konzentrationen, die mittels der zwei Methoden gemessen wurden, werden untereinander sowie mit weiterer Literatur verglichen.Proton magnetic resonance spectroscopy (1H MRS) in the human brain is a non-invasive technique capable of aiding the investigation of the neurochemical composition. The clinical importance of 1H MRS can be seen in pathological diagnosis, understanding disease mechanisms or in treatment monitoring. Reliable detection and quantification of metabolites is of paramount importance in establishing potential biomarkers for several neurological pathologies. Furthermore, broad macromolecular resonances underlying metabolite peaks in a proton spectrum also hold a wealth of information. These macromolecular resonances originate from amino acids within cytosolic peptides and proteins. Some studies in the past have even discussed their clinical relevance in pathologies such as acute multiple sclerosis, glioma, and traumatic encephalopathy. However, the characteristics of these macromolecular resonances are yet to be fully explored. In-depth knowledge about the macromolecules could open up a new horizon of potential biomarkers for neurological diseases. In addition, characterizing macromolecular resonances may help the MR community answer some of the lingering research questions such as identifying the biological background of the individual macromolecular peaks, assigning macromolecular peaks to particular amino acids, and investigating other contributions to the macromolecular signal such as sugars, DNA or RNA. Detection capabilities of MRS have increased to a great extent with increasing static magnetic field. Ultra-high field (≥7 T) MRS benefits from increased signal-to-noise ratio (SNR) and improved spectral resolution. There is also constant development in localization techniques and quantification methods to accurately measure concentrations of metabolites and macromolecules with lower signal-to-noise ratio and complex spectral pattern due to J-coupling. The first part of the thesis focuses on characterizing the physical properties of macromolecular resonances in the human brain at 9.4 T and understanding their contribution to the metabolite spectrum. T2 relaxation times are calculated and a quantitative linewidth analysis is performed to understand the degree of overlap and J- coupling effects in the observed macromolecular peaks. Moreover, a novel double inversion recovery method is proposed to determine T1 relaxation times of individual macromolecular resonance lines. The second part of the thesis focuses on quantification of metabolites in the human brain at 9.4 T using one-dimensional and two-dimensional MRS techniques. Metabolite concentrations are reported in millimoles/kg after correcting for T1- and T2-weighting effects and the tissue composition. The concentration values measured from both the acquisition techniques were compared against each other and to literature

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders