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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 has 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, Marchenko-Pastur principal component analysis (MP-PCA) based denoising and low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T 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 method 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 for lower-concentration metabolites. Our study provided a framework for how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low-concentration metabolites.
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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.
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Neoplasias Encefálicas , Glioma , Isocitrato Deshidrogenasa , Espectroscopía de Resonancia Magnética , Mutación , Clasificación del Tumor , Humanos , Glioma/genética , Glioma/diagnóstico por imagen , Glioma/patología , Isocitrato Deshidrogenasa/genética , Neoplasias Encefálicas/diagnóstico por imagen , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patología , Femenino , Masculino , Persona de Mediana Edad , Adulto , Espectroscopía de Resonancia Magnética/métodos , Estudios Prospectivos , Anciano , Imagen por Resonancia Magnética/métodos , Colina/metabolismo , Colina/análisisRESUMEN
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.
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Encéfalo , Deuterio , Glucosa , Humanos , Glucosa/metabolismo , Adulto , Masculino , Femenino , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Imagen por Resonancia Magnética/métodos , Adulto Joven , Espectroscopía de Resonancia Magnética/métodos , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/metabolismo , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/metabolismoRESUMEN
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.
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A 46-year-old male patient presented with inflammatory diseases over more than 3 years. The patient suffered from recurrent pleuritis, polychondritis, orbital phlegmon, fever, and skin lesions. A bone marrow puncture added myelodysplastic syndrome to the patient's history. A focused cytomorphological reinvestigation of the archived bone marrow aspirate smears detected significant vacuolization of erythroid and myeloid precursor cells. Target sequencing revealed the UBA1 (p.Met41Thr) hotspot mutation that established the diagnosis of VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome.
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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.
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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.
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Encéfalo , Imagen por Resonancia Magnética , Humanos , Estudios Retrospectivos , Imagen por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Movimiento (Física) , Movimiento , Procesamiento de Imagen Asistido por Computador/métodos , ArtefactosRESUMEN
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.
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Esclerosis Múltiple Recurrente-Remitente , Esclerosis Múltiple , Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Esclerosis Múltiple Recurrente-Remitente/diagnóstico por imagen , Esclerosis Múltiple Recurrente-Remitente/patología , Esclerosis Múltiple/patología , Encéfalo/patología , Imagen por Resonancia Magnética/métodos , Espectroscopía de Resonancia Magnética/métodos , Hierro/metabolismo , Receptores de Antígenos de Linfocitos T/metabolismoRESUMEN
Myelodysplastic/myeloproliferative neoplasm with neutrophilia (MDS/MPN-N; previously referred to as atypical chronic myeloid leukemia) is a type of myelodysplastic syndrome/myeloproliferative neoplasm. A molecular genetic precondition for diagnosis is BCR::ABL negativity; further diagnostic criteria include clinicopathological assessments, such as peripheral blood leukocyte counts, the number of neutrophils and their precursors, and the presence of dysgranulopoiesis. The present case report highlights the importance of differential diagnoses with a stringent diagnostic workup according to the 5th Edition of the World Health Organization Classification of Hematolymphoid Tumors. A systematic review of the literature from 2013 to 2022 covering the mutational landscape of MDS/MPN-N was also performed to highlight recent improvements in the molecular genetic diagnostics of this disease.
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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.
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Encéfalo , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Deuterio/metabolismo , Reproducibilidad de los Resultados , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Glucosa/metabolismoRESUMEN
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.
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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.
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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.