High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI

Hangel, Gilbert; Cadrien, Cornelius; Lazen, Philipp; Furtner, Julia; Lipka, Alexandra; Hečková, Eva; Hingerl, Lukas; Motyka, Stanislav; Gruber, Stephan; Strasser, Bernhard; Kiesel, Barbara; Mischkulnig, Mario; Preusser, Matthias; Roetzer, Thomas; Wöhrer, Adelheid; Widhalm, Georg; Rössler, Karl; Trattnig, Siegfried; Bogner, Wolfgang

doi:10.1016/j.nicl.2020.102433

Cited by 46 publications

(51 citation statements)

References 54 publications

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“…The increase in tP i intensity was dominated by the extracellular contribution, which is in line with our earlier observations ( 10 ) (3 of 5 patients with HGG were already presented). In a recently published high-resolution 1 H MRSI study on a larger cohort of patients with HGG ( 31 ), the tCr intensity showed varying trends across tumor subsegments and individual patients, with tCr reductions typically occurring in the necrosis. Our observation of an insignificant change of PCr intensities in tumor tissue across the cohort might correspond to this, despite the clear reduction of the PCr intensity in the central tumor region observed in examples Figures 1F , 3 .…”

Section: Discussionmentioning

confidence: 99%

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

et al. 2021

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Phosphorus magnetic resonance spectroscopic imaging (31P MRSI) is of particular interest for investigations of patients with brain tumors as it enables to non-invasively assess altered energy and phospholipid metabolism in vivo. However, the limited sensitivity of 31P MRSI hampers its broader application at clinical field strengths. This study aimed to identify the additional value of 31P MRSI in patients with glioma at ultra-high B0 = 7T, where the increase in signal-to-noise ratio may foster its applicability for clinical research. High-quality, 3D 31P MRSI datasets with an effective voxel size of 5.7 ml were acquired from the brains of seven patients with newly diagnosed glioma. An optimized quantification model was implemented to reliably extract an extended metabolic profile, including low-concentrated metabolites such as extracellular inorganic phosphate, nicotinamide adenine dinucleotide [NAD(H)], and uridine diphosphoglucose (UDPG), which may act as novel tumor markers; a background signal was extracted as well, which affected measures of phosphomonoesters beneficially. Application of this model to the MRSI datasets yielded high-resolution maps of 12 different 31P metabolites, showing clear metabolic differences between white matter (WM) and gray matter, and between healthy and tumor tissues. Moreover, differences between tumor compartments in patients with high-grade glioma (HGG), i.e., gadolinium contrast-enhancing/necrotic regions (C+N) and peritumoral edema, could also be suggested from these maps. In the group of patients with HGG, the most significant changes in metabolite intensities were observed in C+N compared to WM, i.e., for phosphocholine +340%, UDPG +54%, glycerophosphoethanolamine −45%, and adenosine-5′-triphosphate −29%. Furthermore, a prominent signal from mobile phospholipids appeared in C+N. In the group of patients with low-grade glioma, only the NAD(H) intensity changed significantly by −28% in the tumor compared to WM. Besides the potential of 31P MRSI at 7T to provide novel insights into the biochemistry of gliomas in vivo, the attainable spatial resolutions improve the interpretability of 31P metabolite intensities obtained from malignant tissues, particularly when only subtle differences compared to healthy tissues are expected. In conclusion, this pilot study demonstrates that 31P MRSI at 7T has potential value for the clinical research of glioma.

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Section: Discussionmentioning

confidence: 99%

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

et al. 2021

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“…Magnetic resonance spectroscopy (MRS) at higher field strengths improves SNR and spectral dispersion, leading to improved sensitivity and specificity, respectively, to different chemical species and metabolites. MRS has the potential to improve the detection of metabolites for tumor characterization; however, the technical challenges of increased SAR, magnetic field inhomogeneities, and fast T2*-relaxation can impose constraints on the acquisition of MRS data at 7 T [ 60 – 62 ]. Despite these limitations, earlier research at 7 T was able to demonstrate the application of a short-echo spin-echo MRS sequence to detect characteristic differences in regions of tumor versus normal appearing brain and successfully discriminate between short-echo metabolites, particularly glutamate and glutamine, although with low spatial resolutio n[ 63 ]; this differentiation remains elusive at field strengths of 3 T and below [ 60 ].…”

Section: Ultrahigh Field Mrimentioning

confidence: 99%

“…MRS has the potential to improve the detection of metabolites for tumor characterization; however, the technical challenges of increased SAR, magnetic field inhomogeneities, and fast T2*-relaxation can impose constraints on the acquisition of MRS data at 7 T [ 60 – 62 ]. Despite these limitations, earlier research at 7 T was able to demonstrate the application of a short-echo spin-echo MRS sequence to detect characteristic differences in regions of tumor versus normal appearing brain and successfully discriminate between short-echo metabolites, particularly glutamate and glutamine, although with low spatial resolutio n[ 63 ]; this differentiation remains elusive at field strengths of 3 T and below [ 60 ]. The last decade has seen different MRS acquisition approaches to offset some of the challenges at ultrahigh field imaging [ 60 , 64 – 67 ].…”

Section: Ultrahigh Field Mrimentioning

confidence: 99%

“…Despite these limitations, earlier research at 7 T was able to demonstrate the application of a short-echo spin-echo MRS sequence to detect characteristic differences in regions of tumor versus normal appearing brain and successfully discriminate between short-echo metabolites, particularly glutamate and glutamine, although with low spatial resolutio n[ 63 ]; this differentiation remains elusive at field strengths of 3 T and below [ 60 ]. The last decade has seen different MRS acquisition approaches to offset some of the challenges at ultrahigh field imaging [ 60 , 64 – 67 ]. For example, Hangel et al [ 66 ] used 7-T MRS combined with patch-based super-resolution (PBSR) reconstruction in ten glioma patients that resulted in the identification of complex metabolic activities, which were in topographic agreement with tracer uptake on PET.…”

Section: Ultrahigh Field Mrimentioning

confidence: 99%

“…For example, Hangel et al [ 66 ] used 7-T MRS combined with patch-based super-resolution (PBSR) reconstruction in ten glioma patients that resulted in the identification of complex metabolic activities, which were in topographic agreement with tracer uptake on PET. In a subsequent study, Hangel et al [ 60 ] successfully demonstrated metabolic differences between tumor regions and peritumoral tissues for multiple metabolites using a fast high-resolution whole-brain 3D MRS method in 23 patients with histologically verified high grade gliomas. Although 2-hydroxyglutarate (2HG) was not satisfactorily quantified in this study, other studies have demonstrated detection of 2HG at ultrahigh field [ 64 , 68 , 69 ].…”

Section: Ultrahigh Field Mrimentioning

confidence: 99%

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MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

Vachha

Huang

2021

Eur Radiol Exp

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Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.

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

Niess,

Strasser,

Hingerl

et al. 2024

Human Brain Mapping

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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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High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI

Abstract: Graphical abstract

Cited by 46 publications

References 54 publications

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

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

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