Increasing the signal to noise ratio in MR spectroscopic imaging by coil combination at 7T

Das Ziel dieser Diplomarbeit war es das Signal zu Rausch Verhältnis (SNR) in der Magnetresonanz-Spektroskopiebildgebung (MRSI) bei 7 T durch die Benutzung von Mehrkanalspulen (AC) zu erhöhen. Mithilfe dieser Spulen kann das SNR stark verbessert werden, indem die einzelnen Kanäle der Spule aufsummiert werden. Es zeigt sich allerdings, dass diese Kanalkombination im Falle von spektroskopischen Daten problematisch ist, da das einfache Aufsummieren zu einer Signalauslöschung aufgrund von Phasendifferenzen der einzelnen Kanäle führt. Die Spektren der einzelnen Kanäle müssen daher vorher phasiert werden. Die gängige Methode um dies zu Erreichen benutzt den ersten Datenpunkt der FIDs, was bei guter Wasserunterdrückung aber zu unzuverlässigen Ergebnissen führen kann. Daher wurde die Phase mithilfe von schnellen Gradientenecho Bildgebungssequenzen (GRE) bestimmt. Mit deren Hilfe wurde jedes Voxel und jeder Kanal der MRSI Daten phasiert und gewichtet. Dies führt zu einer geringeren Signalauslöschung im Vergleich zur gängigen Methode. Die Realisierbarkeit der neuen Methode wurde durch das Messen der Gehirne von 7 gesunden Probanden und 3 Phantommessungen gezeigt. Dafür wurde im ersten Schritt nachgewiesen, dass das Phasieren von MRSI-Daten mithilfe von GRE-Daten grundsätzlich möglich ist. Im nachfolgenden zweiten Schritt wurde ein Algorithmus programmiert, mit dessen Hilfe spektroskopische Daten von AC-Kanälen mit oben genannter neuen Methode kombiniert werden können. Daraufhin wurde der SNR-Gewinn durch diese Methode im Vergleich zu einer Volumsspule mit den Messdaten ermittelt. Im letzten Schritt wurde gezeigt, dass diese neu entwickelte Methode zur Kanalkombination zu besseren Ergebnissen in Bezug auf SNR und Reproduzierbarkeit führt als die gängige Methode, insbesondere nahe der Oberfläche des Gehirns.The aim of this diploma thesis was to increase the Signal to Noise Ratio (SNR) in Magnetic Resonance Spectroscopic Imaging (MRSI) at 7 T by deploying Array Coils (AC). ACs can highly increase the SNR when summing up the individual channels. Yet, the combination of spectroscopic data is problematic due to phase differences between the channels, leading to signal cancellations if the channels are naively summed up. To prevent this, the signal of each channel has to be phased prior to summing. The phase information is typically obtained by the first FID data point. However, for good water suppression, this method can be unreliable. Therefore, a method is proposed with which the phase is estimated from fast Gradient Echo (GRE) imaging sequences. Each voxel and each channel is phased and weighted with these additional GRE data, leading to less signal cancellations in comparison to the conventional method. In order to show the feasibility of this method and its superiority over the established method, MRSI and GRE data of 7 healthy volunteers and 3 phantoms were measured. Thus, in the first step the possibility to phase MRSI data with GRE data was proven. In the subsequent step, an algorithm for combining the MRSI data of the AC-channels with the above mentioned new method was written. Then, the gain in the SNR using this method in comparison with the data of a Volume Coil was estimated using the measured data. Finally, the superiority of the new coil combination method over the established one was shown in terms of SNR and reproducibility, particularly at the surface of the brain

High frequency modulation and (quasi) single-sideband emission of mid-infrared ring and ridge quantum cascade lasers

We investigate the high frequency modulation characteristics of mid-infrared surface-emitting ring and edge-emitting ridge quantum cascade lasers (QCLs). In particular, a detailed comparison between circular ring devices and ridge-QCLs from the same laser material, which have a linear waveguide in a "Fabry-Perot (FP) type" cavity, reveals distinct similarities and differences. Both device types are single-mode emitting, based on either 2nd-(ring-QCL) or 1st-order (ridge-QCL) distributed feedback (DFB) gratings with an emission wavelength around 7.56 mum. Their modulation characteristics are investigated in the frequency-domain using an optical frequency-to-amplitude conversion technique based on the ro-vibrational absorptions of CH 4. We observe that the amplitude of frequency tuning Delta f over intensity modulation index in as function of the modulation frequency behaves similarly for both types of devices, while the ring-QCLs typically show higher values. The frequency-to-intensity modulation (FM-IM) phase shift shows a decrease starting from similar to 72 degrees at a modulation frequency of 800 kHz to about 0 degrees at 160 MHz. In addition, we also observe a quasi single-sideband (qSSB) regime for modulation frequencies above 100 MHz, which is identified by a vanishing-1 st-order sideband for both devices. This special FM-state can be observed in DFB QCLs and is in strong contrast to the behavior of regular DFB diode lasers, which do not achieve any significant sideband suppression. By analyzing these important high frequency characteristics of ring-QCLs and comparing them to ridge DFB-QCLs, it shows the potential of intersubband devices for applications in e.g. novel spectroscopic techniques and highly-integrated and high-bitrate free-space data communication. In addition, the obtained results close an existing gap in literature for high frequency modulation characteristics of QCLs

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

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

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

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

A comparison of 7 Tesla MR spectroscopic imaging and 3 Tesla MR fingerprinting for tumor localization in glioma patients

This paper investigates the correlation between magnetic resonance spectroscopic imaging (MRSI) and magnetic resonance fingerprinting (MRF) in glioma patients by comparing neuro-oncological markers obtained from MRSI to T1/T2 maps from MRF. Data from 12 consenting patients with gliomas were analyzed by defining hotspots for T1, T2 and various metabolic ratios, and comparing them using S{\o}rensen-Dice Similarity Coefficients (DSCs) and the distances between their centers of intensity (COIDs). Median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were highest for Gln/tNAA (T1: 0.75, T2: 0.80, tumor: 0.78), followed by Gly/tNAA (T1: 0.57, T2: 0.62, tumor: 0.54) and tCho/tNAA (T1: 0.61, T2: 0.58, tumor: 0.45). The median values in the tumor hotspot were T1=1724 ms, T2=86 ms, Gln/tNAA=0.61, Gly/tNAA=0.28, Ins/tNAA=1.15, and tCho/tNAA=0.48, and, in the peritumoral region, were T1=1756 ms, T2=102ms, Gln/tNAA=0.38, Gly/tNAA=0.20, Ins/tNAA=1.06, and tCho/tNAA=0.38, and, in the NAWM, were T1=950 ms, T2=43 ms, Gln/tNAA=0.16, Gly/tNAA=0.07, Ins/tNAA=0.54, and tCho/tNAA=0.20. The results of this study constitute the first comparison of 7T MRSI and 3T MRF, showing a good correspondence between these methods.Comment: Includes 3 tables, 6 figures, 3 supplementary tables, and 4 supplementary figure