A modular motion compensation pipeline for prospective respiratory motion correction of multi-nuclear MR spectroscopy.

Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner's reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.

7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading.

INTRODUCTION: With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients. METHODS: We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status. RESULTS: Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy. CONCLUSIONS: We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.

Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory.

Purpose: 1.1 Proton ( 1 H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency due to their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time. Methods: 1.2Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory. Results: 1.3Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in-vivo and phantom data. The CRLBs improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar. Conclusion: 1.4By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality.

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.

A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients.

This paper investigated 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 Sørensen-Dice similarity coefficients (DSCs) and the distances between their centers of intensity (COIDs). The median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were the 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 = 102 ms, 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.

Predicting dynamic, motion-related changes in B0 field in the brain at a 7T MRI using a subject-specific fine-trained U-net.

PURPOSE: Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B0 ), which is a prerequisite for high quality data. Thus, characterization of changes to B0 , for example induced by patient movement, is important for MR applications that are prone to B0 inhomogeneities. METHODS: We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction. A 3D U-net was trained on in vivo gradient-echo brain 7T MRI data. The input consisted of B0 maps and anatomical images at an initial position, and anatomical images at a different head position (obtained by applying a rigid-body transformation on the initial anatomical image). The output consisted of B0 maps at the new head positions. We further fine-trained the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data. RESULTS: Our approach was compared to established dynamic B0 field mapping via interleaved navigators, which suffer from limited spatial resolution and the need for undesirable sequence modifications. Qualitative and quantitative comparison showed similar performance between an interleaved navigator-equivalent method and proposed method. CONCLUSION: It is feasible to predict B0 maps from rigid subject movement and, when combined with external tracking hardware, this information could be used to improve the quality of MR acquisitions without the use of navigators.

Implementation of a 7T Epilepsy Task Force consensus imaging protocol for routine presurgical epilepsy work-up: effect on diagnostic yield and lesion delineation.

OBJECTIVE: Recently, the 7 Tesla (7 T) Epilepsy Task Force published recommendations for 7 T magnetic resonance imaging (MRI) in patients with pharmaco-resistant focal epilepsy in pre-surgical evaluation. The objective of this study was to implement and evaluate this consensus protocol with respect to both its practicability and its diagnostic value/potential lesion delineation surplus effect over 3 T MRI in the pre-surgical work-up of patients with pharmaco-resistant focal onset epilepsy. METHODS: The 7 T MRI protocol consisted of T1-weighted, T2-weighted, high-resolution-coronal T2-weighted, fluid-suppressed, fluid-and-white-matter-suppressed, and susceptibility-weighted imaging, with an overall duration of 50 min. Two neuroradiologists independently evaluated the ability of lesion identification, the detection confidence for these identified lesions, and the lesion border delineation at 7 T compared to 3 T MRI. RESULTS: Of 41 recruited patients > 12 years of age, 38 were successfully measured and analyzed. Mean detection confidence scores were non-significantly higher at 7 T (1.95 ± 0.84 out of 3 versus 1.64 ± 1.19 out of 3 at 3 T, p = 0.050). In 50% of epilepsy patients measured at 7 T, additional findings compared to 3 T MRI were observed. Furthermore, we found improved border delineation at 7 T in 88% of patients with 3 T-visible lesions. In 19% of 3 T MR-negative cases a new potential epileptogenic lesion was detected at 7 T. CONCLUSIONS: The diagnostic yield was beneficial, but with 19% new 7 T over 3 T findings, not major. Our evaluation revealed epilepsy outcomes worse than ILAE Class 1 in two out of the four operated cases with new 7 T findings.

Metabolic Insights into Iron Deposition in Relapsing-Remitting Multiple Sclerosis via 7 T Magnetic Resonance Spectroscopic Imaging.

OBJECTIVE: To investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition. METHODS: 7 T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 ± 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), "non-iron" (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions ("rim": distinct rim-shaped iron accumulation; "area": iron deposition across the entire lesions; "transition": transition between "area" and "rim" accumulation shape), and for lesion layers of "non-iron" and "rim" lesions. Furthermore, newly emerging "non-iron" and "iron" lesions were compared longitudinally, as measured before their appearance and one year later. RESULTS: Thirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, "area" lesions exhibited a 65% higher mIns/tNAA (p = 0.035) than "rim" lesions. Comparing lesion layers of both "non-iron" and "rim" lesions, a steeper metabolic gradient of mIns/tNAA ("non-iron" +15%, "rim" +40%) and tNAA/tCr ("non-iron" -15%, "rim" -35%) was found in "iron" lesions, with the lesion core showing +22% higher mIns/tNAA (p = 0.005) and -23% lower tNAA/tCr (p = 0.048) in "iron" compared to "non-iron" lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in "iron" lesions (year 0: p = 0.013, year 1: p = 0.041) as opposed to "non-iron" lesions (year 0: p = 0.022, year 1: p = 0.231). CONCLUSION: 7 T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T.

INTRODUCTION: Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. METHODS: Five volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6'-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. RESULTS: One hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). CONCLUSION: This study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

Evaluation of Gliomas with Magnetic Resonance Fingerprinting with PET Correlation-A Comparative Study.

OBJECTIVES: Advanced MR imaging of brain tumors is still mainly based on qualitative imaging. PET imaging offers additive metabolic information, and MR fingerprinting (MRF) offers a novel approach to quantitative data acquisition. The purpose of this study was to evaluate the ability of MRF to predict tumor regions and grading in combination with PET. METHODS: Seventeen patients with histologically verified infiltrating gliomas and available amino-acid PET data were enrolled. ROIs for solid tumor parts (SPo), perifocal edema (ED1), and normal-appearing white matter (NAWM) were selected on conventional MRI sequences and aligned to the MRF and PET images. The predictability of gliomas by region and grading as well as intermodal correlations were assessed. RESULTS: For MRF, we calculated an overall predictability by region (SPo, ED1, and NAWM) for all of the MRF parameters of 76.5%, 47.1%, and 94.1%, respectively. The overall ability to distinguish low- from high-grade gliomas using MRF was 88.9% for LGG and 75% for HGG, with an accuracy of 82.4%, a ppV of 85.71%, and an npV of 80%. PET positivity was found in 13/17 patients for solid tumor parts, and in 3/17 patients for the edema region. However, there was no significant difference in region-specific MRF values between PET positive and PET negative patients. CONCLUSIONS: MRF and PET provide quantitative measurements of the tumor tissue characteristics of gliomas, with good predictability. Nonetheless, the results are dissimilar, reflecting the different underlying mechanisms of each method.

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 at 7 Tesla MRI. ECCENTRIC is a non-Cartesian spatial-spectral encoding method optimized to accelerate magnetic resonance spectroscopic imaging (MRSI) with high signal-to-noise 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. In healthy volunteers ECCENTRIC demonstrated unprecedented spatial mapping of fine structural details of human brain neurochemistry. This innovative tool introduces a novel approach to neuroscience, providing new insights into the exploration of brain activity and physiology.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct ( 2 H) and indirect ( 1 H) detection of deuterium labeled compounds at 7T and clinical 3T.

Introduction: Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'- 2 H 2 ]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2 H MRSI (DMI) and 1 H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. Methods: Five volunteers (4m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8g/kg oral [6,6'- 2 H 2 ]-glucose administration using time-resolved 3D 2 H FID-MRSI with elliptical phase encoding at 7T and 3D 1 H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. Results: One hour after oral tracer administration regionally averaged deuterium labeled Glx 4 concentrations and the dynamics were not significantly different over all participants between 7T 2 H DMI and 3T 1 H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc 6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2 H and 1 H data points a weak to moderate negative correlation was observed for Glx 4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc 6 data GM (r=- 0.61, p<0.001) and WM (r=-0.70, p<0.001). Conclusion: This study demonstrates that indirect detection of deuterium labeled compounds using 1 H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2 H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain.

Impaired glucose metabolism in the brain has been linked to several neurological disorders. Positron emission tomography and carbon-13 magnetic resonance spectroscopic imaging (MRSI) can be used to quantify the metabolism of glucose, but these methods involve exposure to radiation, cannot quantify downstream metabolism, or have poor spatial resolution. Deuterium MRSI (2H-MRSI) is a non-invasive and safe alternative for the quantification of the metabolism of 2H-labelled substrates such as glucose and their downstream metabolic products, yet it can only measure a limited number of deuterated compounds and requires specialized hardware. Here we show that proton MRSI (1H-MRSI) at 7 T has higher sensitivity, chemical specificity and spatiotemporal resolution than 2H-MRSI. We used 1H-MRSI in five volunteers to differentiate glutamate, glutamine, γ-aminobutyric acid and glucose deuterated at specific molecular positions, and to simultaneously map deuterated and non-deuterated metabolites. 1H-MRSI, which is amenable to clinically available magnetic-resonance hardware, may facilitate the study of glucose metabolism in the brain and its potential roles in neurological disorders.

Noninvasive 3-Dimensional 1 H-Magnetic Resonance Spectroscopic Imaging of Human Brain Glucose and Neurotransmitter Metabolism Using Deuterium Labeling at 3T : Feasibility and Interscanner Reproducibility.

OBJECTIVES: Noninvasive, affordable, and reliable mapping of brain glucose metabolism is of critical interest for clinical research and routine application as metabolic impairment is linked to numerous pathologies, for example, cancer, dementia, and depression. A novel approach to map glucose metabolism noninvasively in the human brain has been presented recently on ultrahigh-field magnetic resonance (MR) scanners (≥7T) using indirect detection of deuterium-labeled glucose and downstream metabolites such as glutamate, glutamine, and lactate. The aim of this study was to demonstrate the feasibility to noninvasively detect deuterium-labeled downstream glucose metabolites indirectly in the human brain via 3-dimensional (3D) proton ( 1 H) MR spectroscopic imaging on a clinical 3T MR scanner without additional hardware. MATERIALS AND METHODS: This prospective, institutional review board-approved study was performed in 7 healthy volunteers (mean age, 31 ± 4 years, 5 men/2 women) after obtaining written informed consent. After overnight fasting and oral deuterium-labeled glucose administration, 3D metabolic maps were acquired every ∼4 minutes with ∼0.24 mL isotropic spatial resolution using real-time motion-, shim-, and frequency-corrected echo-less 3D 1 H-MR spectroscopic Imaging on a clinical routine 3T MR system. To test the interscanner reproducibility of the method, subjects were remeasured on a similar 3T MR system. Time courses were analyzed using linear regression and nonparametric statistical tests. Deuterium-labeled glucose and downstream metabolites were detected indirectly via their respective signal decrease in dynamic 1 H MR spectra due to exchange of labeled and unlabeled molecules. RESULTS: Sixty-five minutes after deuterium-labeled glucose administration, glutamate + glutamine (Glx) signal intensities decreased in gray/white matter (GM/WM) by -1.63 ± 0.3/-1.0 ± 0.3 mM (-13% ± 3%, P = 0.02/-11% ± 3%, P = 0.02), respectively. A moderate to strong negative correlation between Glx and time was observed in GM/WM ( r = -0.64, P < 0.001/ r = -0.54, P < 0.001), with 60% ± 18% ( P = 0.02) steeper slopes in GM versus WM, indicating faster metabolic activity. Other nonlabeled metabolites showed no significant changes. Excellent intrasubject repeatability was observed across scanners for static results at the beginning of the measurement (coefficient of variation 4% ± 4%), whereas differences were observed in individual Glx dynamics, presumably owing to physiological variation of glucose metabolism. CONCLUSION: Our approach translates deuterium metabolic imaging to widely available clinical routine MR scanners without specialized hardware, offering a safe, affordable, and versatile (other substances than glucose can be labeled) approach for noninvasive imaging of glucose and neurotransmitter metabolism in the human brain.

Lesion-Specific Metabolic Alterations in Relapsing-Remitting Multiple Sclerosis Via 7 T Magnetic Resonance Spectroscopic Imaging.

BACKGROUND: Magnetic resonance spectroscopic imaging (MRSI) of the brain enables in vivo assessment of metabolic alterations in multiple sclerosis (MS). This provides complementary insights into lesion pathology that cannot be obtained via T1- and T2-weighted conventional magnetic resonance imaging (cMRI). PURPOSE: The aims of this study were to assess focal metabolic alterations inside and at the periphery of lesions that are visible or invisible on cMRI, and to correlate their metabolic changes with T1 hypointensity and the distance of lesions to cortical gray matter (GM). METHODS: A 7 T MRSI was performed on 51 patients with relapsing-remitting MS (30 female/21 male; mean age, 35.4 ± 9.9 years). Mean metabolic ratios were calculated for segmented regions of interest (ROIs) of normal-appearing white matter, white matter lesions, and focal regions of increased mIns/tNAA invisible on cMRI. A subgroup analysis was performed after subdividing based on T1 relaxation and distance to cortical GM. Metabolite ratios were correlated with T1 and compared between different layers around cMRI-visible lesions. RESULTS: Focal regions of, on average, 2.8-fold higher mIns/tNAA than surrounding normal-appearing white matter and with an appearance similar to that of MS lesions were found, which were not visible on cMRI (ie, ~4% of metabolic hotspots). T1 relaxation was positively correlated with mIns/tNAA ( P ≤ 0.01), and negatively with tNAA/tCr ( P ≤ 0.01) and tCho/tCr ( P ≤ 0.01). mIns/tCr was increased outside lesions, whereas tNAA/tCr distributions resembled macroscopic tissue damage inside the lesions. mIns/tCr was -21% lower for lesions closer to cortical GM ( P ≤ 0.05). CONCLUSIONS: 7 T MRSI allows in vivo visualization of focal MS pathology not visible on cMRI and the assessment of metabolite levels in the lesion center, in the active lesion periphery and in cortical lesions. This demonstrated the potential of MRSI to image mIns as an early biomarker in lesion development.

Three-dimensional, 2.5-minute, 7T phosphorus magnetic resonance spectroscopic imaging of the human heart using concentric rings.

A three-dimensional (3D), density-weighted, concentric rings trajectory (CRT) magnetic resonance spectroscopic imaging (MRSI) sequence is implemented for cardiac phosphorus (31 P)-MRS at 7 T. The point-by-point k-space sampling of traditional phase-encoded chemical shift imaging (CSI) sequences severely restricts the minimum scan time at higher spatial resolutions. Our proposed CRT sequence implements a stack of concentric rings, with a variable number of rings and planes spaced to optimise the density of k-space weighting. This creates flexibility in acquisition time, allowing acquisitions substantially faster than traditional phase-encoded CSI sequences, while retaining high signal-to-noise ratio (SNR). We first characterise the SNR and point-spread function of the CRT sequence in phantoms. We then evaluate it at five different acquisition times and spatial resolutions in the hearts of five healthy participants at 7 T. These different sequence durations are compared with existing published 3D acquisition-weighted CSI sequences with matched acquisition times and spatial resolutions. To minimise the effect of noise on the short acquisitions, low-rank denoising of the spatiotemporal data was also performed after acquisition. The proposed sequence measures 3D localised phosphocreatine to adenosine triphosphate (PCr/ATP) ratios of the human myocardium in 2.5 min, 2.6 times faster than the minimum scan time for acquisition-weighted phase-encoded CSI. Alternatively, in the same scan time, a 1.7-times smaller nominal voxel volume can be achieved. Low-rank denoising reduced the variance of measured PCr/ATP ratios by 11% across all protocols. The faster acquisitions permitted by 7-T CRT 31 P-MRSI could make cardiac stress protocols or creatine kinase rate measurements (which involve repeated scans) more tolerable for patients without sacrificing spatial resolution.

The Impact of Theta-Burst Stimulation on Cortical GABA and Glutamate in Treatment-Resistant Depression: A Surface-Based MRSI Analysis Approach.

Background: Theta burst stimulation (TBS) belongs to one of the biological antidepressant treatment options. When applied bilaterally, excitatory intermittent TBS (iTBS) is commonly targeted to the left and inhibitory continuous TBS (cTBS) to the right dorsolateral prefrontal cortex. TBS was shown to influence neurotransmitter systems, while iTBS is thought to interfere with glutamatergic circuits and cTBS to mediate GABAergic neurotransmission. Objectives: We aimed to expand insights into the therapeutic effects of TBS on the GABAergic and glutamatergic system utilizing 3D-multivoxel magnetic resonance spectroscopy imaging (MRSI) in combination with a novel surface-based MRSI analysis approach to investigate changes of cortical neurotransmitter levels in patients with treatment-resistant depression (TRD). Methods: Twelve TRD patients (five females, mean age ± SD = 35 ± 11 years) completed paired MRSI measurements, using a GABA-edited 3D-multivoxel MEGA-LASER sequence, before and after 3 weeks of bilateral TBS treatment. Changes in cortical distributions of GABA+/tNAA (GABA+macromolecules relative to total N-acetylaspartate) and Glx/tNAA (Glx = mixed signal of glutamate and glutamine), were investigated in a surface-based region-of-interest (ROI) analysis approach. Results: ANCOVAs revealed a significant increase in Glx/tNAA ratios in the left caudal middle frontal area (p corr. = 0.046, F = 13.292), an area targeted by iTBS treatment. Whereas, contralateral treatment with cTBS evoked no alterations in glutamate or GABA concentrations. Conclusion: This study demonstrates surface-based adaptions in the stimulation area to the glutamate metabolism after excitatory iTBS but not after cTBS, using a novel surface-based analysis of 3D-MRSI data. The reported impact of facilitatory iTBS on glutamatergic neurotransmission provides further insight into the neurobiological effects of TBS in TRD.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors.

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

MR Fingerprinting-A Radiogenomic Marker for Diffuse Gliomas.

(1) Background: Advanced MR imaging (MRI) of brain tumors is mainly based on qualitative contrast images. MR Fingerprinting (MRF) offers a novel approach. The purpose of this study was to use MRF-derived T1 and T2 relaxation maps to differentiate diffuse gliomas according to isocitrate dehydrogenase (IDH) mutation. (2) Methods: Twenty-four patients with histologically verified diffuse gliomas (14 IDH-mutant, four 1p/19q-codeleted, 10 IDH-wildtype) were enrolled. MRF T1 and T2 relaxation times were compared to apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV) within solid tumor, peritumoral edema, and normal-appearing white matter (NAWM), using contrast-enhanced MRI, diffusion-, perfusion-, and susceptibility-weighted imaging. For perfusion imaging, a T2* weighted perfusion sequence with leakage correction was used. Correlations of MRF T1 and T2 times with two established conventional sequences for T1 and T2 mapping were assessed (a fast double inversion recovery-based MR sequence ('MP2RAGE') for T1 quantification and a multi-contrast spin echo-based sequence for T2 quantification). (3) Results: MRF T1 and T2 relaxation times were significantly higher in the IDH-mutant than in IDH-wildtype gliomas within the solid part of the tumor (p = 0.024 for MRF T1, p = 0.041 for MRF T2). MRF T1 and T2 relaxation times were significantly higher in the IDH-wildtype than in IDH-mutant gliomas within peritumoral edema less than or equal to 1cm adjacent to the tumor (p = 0.038 for MRF T1 mean, p = 0.010 for MRF T2 mean). In the solid part of the tumor, there was a high correlation between MRF and conventionally measured T1 and T2 values (r = 0.913, p < 0.001 for T1, r = 0.775, p < 0.001 for T2), as well as between MRF and ADC values (r = 0.813, p < 0.001 for T2, r = 0.697, p < 0.001 for T1). The correlation was weak between the MRF and rCBV values (r = -0.374, p = 0.005 for T2, r = -0.181, p = 0.181 for T1). (4) Conclusions: MRF enables fast, single-sequence based, multi-parametric, quantitative tissue characterization of diffuse gliomas and may have the potential to differentiate IDH-mutant from IDH-wildtype gliomas.