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

ABSTRACT: OBJECTIVES:Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in a patient cohort of 23 high-grade gliomas (HGG). MATERIALS AND METHODS:We preoperatively measured 23 patients with histologically verified HGGs (17 male, 8 female, age 53 ± 15) with an MRSI sequence based on concentric ring trajectories with a 64 × 64 × 39 measurement matrix, and a 3.4 × 3.4 × 3.4 mm3 nominal voxel volume in 15 min. Quantification used a basis-set of 17 components including N-acetyl-aspartate (NAA), total choline (tCho), total creatine (tCr), glutamate (Glu), glutamine (Gln), glycine (Gly) and 2-hydroxyglutarate (2HG). The resultant metabolic images were evaluated for their reliability as well as their quality and compared to spatially segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast enhanced + edema, peritumoral) based on clinical data and also compared to histopathology (e.g., grade, IDH-status). RESULTS:Eighteen of the patient measurements were considered usable. In these patients, ten metabolites were quantified with acceptable quality. Gln, Gly, and tCho were increased and NAA and tCr decreased in nearly all tumor regions, with other metabolites such as serine, showing mixed trends. Overall, there was a reliable characterization of metabolic tumor areas. We also found heterogeneity in the metabolic images often continued into the peritumoral region. While 2HG could not be satisfyingly quantified, we found an increase of Glu in the contrast-enhancing region of IDH-wildtype HGGs and a decrease of Glu in IDH1-mutant HGGs. CONCLUSIONS:We successfully demonstrated high-resolution 7T 3D-MRSI in HGG patients, showing metabolic differences between tumor regions and peritumoral tissue for multiple metabolites. Increases of tCho, Gln (related to tumor metabolism), Gly (related to tumor proliferation), as well as decreases in NAA, tCr, and others, corresponded very well to clinical tumor segmentation, but were more heterogeneous and often extended into the peritumoral region.

SUBMITTER: Hangel G

PROVIDER: S-EPMC7511769 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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

Hangel Gilbert G Cadrien Cornelius C Lazen Philipp P Furtner Julia J Lipka Alexandra A Hečková Eva E Hingerl Lukas L Motyka Stanislav S Gruber Stephan S Strasser Bernhard B Kiesel Barbara B Mischkulnig Mario M Preusser Matthias M Roetzer Thomas T Wöhrer Adelheid A Widhalm Georg G Rössler Karl K Trattnig Siegfried S Bogner Wolfgang W

NeuroImage. Clinical 20200915

<h4>Objectives</h4>Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7 ...[more]

PMID: 32977210

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Project description: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 B 0 = 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.

Project description:PurposeA properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID-MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility.MethodsClinically feasible, high-resolution FID-MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test-retest reproducibility of MRSI scans was assessed voxel-wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model.ResultsThe full MM model provided the most reproducible quantification of total NAA, total Cho, myo-inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to -0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites.ConclusionClinically feasible FID-MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered.

Project description:Background and purposeAmyotrophic lateral sclerosis is a progressive motor neuron disorder that involves degeneration of both upper and lower motor neurons. In patients with amyotrophic lateral sclerosis, pathologic studies and ex vivo high-resolution MR imaging at ultra-high field strength revealed the co-localization of iron and activated microglia distributed in the deep layers of the primary motor cortex. The aims of the study were to measure the cortical thickness and evaluate the distribution of iron-related signal changes in the primary motor cortex of patients with amyotrophic lateral sclerosis as possible in vivo biomarkers of upper motor neuron impairment.Materials and methodsTwenty-two patients with definite amyotrophic lateral sclerosis and 14 healthy subjects underwent a high-resolution 2D multiecho gradient-recalled sequence targeted on the primary motor cortex by using a 7T scanner. Image analysis consisted of the visual evaluation and quantitative measurement of signal intensity and cortical thickness of the primary motor cortex in patients and controls. Qualitative and quantitative MR imaging parameters were correlated with electrophysiologic and laboratory data and with clinical scores.ResultsUltra-high field MR imaging revealed atrophy and signal hypointensity in the deep layers of the primary motor cortex of patients with amyotrophic lateral sclerosis with a diagnostic accuracy of 71%. Signal hypointensity of the deep layers of the primary motor cortex correlated with upper motor neuron impairment (r = -0.47; P < .001) and with disease progression rate (r = -0.60; P = .009).ConclusionsThe combined high spatial resolution and sensitivity to paramagnetic substances of 7T MR imaging demonstrate in vivo signal changes of the cerebral motor cortex that resemble the distribution of activated microglia within the cortex of patients with amyotrophic lateral sclerosis. Cortical thinning and signal hypointensity of the deep layers of the primary motor cortex could constitute a marker of upper motor neuron impairment in patients with amyotrophic lateral sclerosis.

Dataset Information

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

Publications

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

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