High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI
[Display omitted] •We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T.•tCho, Gln, and Gly were increased in contrast-enhancing tumor tissue.•Results corresponded well to clinical data, but show more differentiated images.•We found cases of heterogeneity in metabolic im...
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| Veröffentlicht in: | NeuroImage clinical Jg. 28; S. 102433 |
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| Abstract | [Display omitted]
•We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T.•tCho, Gln, and Gly were increased in contrast-enhancing tumor tissue.•Results corresponded well to clinical data, but show more differentiated images.•We found cases of heterogeneity in metabolic images not visible in clinical imaging.
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).
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).
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.
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. |
|---|---|
| AbstractList | Graphical 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. 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). 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 mm 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). 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. 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. 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).OBJECTIVESSuccessful 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).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).MATERIALS AND METHODSWe 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).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.RESULTSEighteen 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.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.CONCLUSIONSWe 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. • We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T. • tCho, Gln, and Gly were increased in contrast-enhancing tumor tissue. • Results corresponded well to clinical data, but show more differentiated images. • We found cases of heterogeneity in metabolic images not visible in clinical imaging. [Display omitted] •We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T.•tCho, Gln, and Gly were increased in contrast-enhancing tumor tissue.•Results corresponded well to clinical data, but show more differentiated images.•We found cases of heterogeneity in metabolic images not visible in clinical imaging. 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). 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). 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. 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. |
| ArticleNumber | 102433 |
| Author | Roetzer, Thomas Cadrien, Cornelius Lipka, Alexandra Mischkulnig, Mario Gruber, Stephan Strasser, Bernhard Widhalm, Georg Hingerl, Lukas Rössler, Karl Hangel, Gilbert Kiesel, Barbara Bogner, Wolfgang Lazen, Philipp Trattnig, Siegfried Furtner, Julia Motyka, Stanislav Hečková, Eva Wöhrer, Adelheid Preusser, Matthias |
| Author_xml | – sequence: 1 givenname: Gilbert surname: Hangel fullname: Hangel, Gilbert email: gilbert.hangel@meduniwien.ac.at organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 2 givenname: Cornelius surname: Cadrien fullname: Cadrien, Cornelius organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 3 givenname: Philipp surname: Lazen fullname: Lazen, Philipp organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 4 givenname: Julia surname: Furtner fullname: Furtner, Julia organization: Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 5 givenname: Alexandra surname: Lipka fullname: Lipka, Alexandra organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 6 givenname: Eva surname: Hečková fullname: Hečková, Eva organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 7 givenname: Lukas surname: Hingerl fullname: Hingerl, Lukas organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 8 givenname: Stanislav surname: Motyka fullname: Motyka, Stanislav organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 9 givenname: Stephan surname: Gruber fullname: Gruber, Stephan organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 10 givenname: Bernhard surname: Strasser fullname: Strasser, Bernhard organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 11 givenname: Barbara surname: Kiesel fullname: Kiesel, Barbara organization: Department of Neurosurgery, Medical University of Vienna, Vienna, Austria – sequence: 12 givenname: Mario surname: Mischkulnig fullname: Mischkulnig, Mario organization: Department of Neurosurgery, Medical University of Vienna, Vienna, Austria – sequence: 13 givenname: Matthias surname: Preusser fullname: Preusser, Matthias organization: Division of Oncology, Department of Inner Medicine I, Medical University of Vienna, Vienna, Austria – sequence: 14 givenname: Thomas surname: Roetzer fullname: Roetzer, Thomas organization: Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria – sequence: 15 givenname: Adelheid surname: Wöhrer fullname: Wöhrer, Adelheid organization: Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria – sequence: 16 givenname: Georg surname: Widhalm fullname: Widhalm, Georg organization: Department of Neurosurgery, Medical University of Vienna, Vienna, Austria – sequence: 17 givenname: Karl surname: Rössler fullname: Rössler, Karl organization: Department of Neurosurgery, Medical University of Vienna, Vienna, Austria – sequence: 18 givenname: Siegfried surname: Trattnig fullname: Trattnig, Siegfried organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria – sequence: 19 givenname: Wolfgang surname: Bogner fullname: Bogner, Wolfgang organization: High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32977210$$D View this record in MEDLINE/PubMed |
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| Keywords | tCr PT Gln Tau IDH Glu UHF Gly MP2RAGE Cys MRSI MM tCho HGG FOV ROI 7 Tesla 2HG NCE VOI Concentric circle trajectories FWHM GABA Metabolic imaging CRLB T1w iMUSICAL NAAG Magnetic resonance spectroscopic imaging Ser CRT SAR WET Glycine SVS SNR WM T2w FLAIR High-grade glioma GSH WT FID CE GM NAWM NEC TME NAA TE mIns Ctn PET TR macromolecules normal-appearing white matter isocitrate dehydrogenase non-contrast-enhanced echo time wildtype 2-hydroxyglutarate free induction decay glutamate (myo-)inositol repetition time necrotic field of view T1-weighted γ-aminobutyric acid full width at half maximum volume of interest glutamine white matter T2-weighted fluid-attenuated inversion recovery concentric ring trajectories gray matter region of interest signal-to-noise ratio tumor microenvironment serine N-acetyl-aspartyl glutamate cysteine magnetic resonance single-voxel spectroscopy cystathionine total creatine, creatine + phosphocreatine choline-containing compounds taurine specific absorption rate glutathione contrast-enhanced water suppression enhanced through T 1 effects interleaved multichannel spectroscopic data combined by matching image calibration data peritumoral ultra-high-field Cramér–Rao lower bound N-acetyl-aspartate positron emission tomography magnetization-prepared 2 rapid acquisition gradient echoes |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license. Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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•We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T.•tCho, Gln, and Gly were increased in contrast-enhancing... Graphical abstract Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum... • We demonstrated reliable and fast whole-brain 3D-MRSI of high-grade gliomas at 7T. • tCho, Gln, and Gly were increased in contrast-enhancing tumor tissue. •... Objectives: Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe... |
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| Title | High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI |
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