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Pan F, Liu X, Wan J, Guo Y, Sun P, Zhang X, Wang J, Bao Q, Yang L. Advances and prospects in deuterium metabolic imaging (DMI): a systematic review of in vivo studies. Eur Radiol Exp 2024; 8:65. [PMID: 38825658 PMCID: PMC11144684 DOI: 10.1186/s41747-024-00464-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 04/02/2024] [Indexed: 06/04/2024] Open
Abstract
BACKGROUND Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo. METHODS A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution. RESULTS Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6'-2H2]glucose, [2,2,2'-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T). CONCLUSIONS Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability. RELEVANCE STATEMENT Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential. KEY POINTS • Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI's current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution.
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Affiliation(s)
- Feng Pan
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xinjie Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Jiayu Wan
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yusheng Guo
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Peng Sun
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Xiaoxiao Zhang
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Jiazheng Wang
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Qingjia Bao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.
| | - Lian Yang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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Niess F, Strasser B, Hingerl L, Bader V, Frese S, Clarke WT, Duguid A, Niess E, Motyka S, Krššák M, Trattnig S, Scherer T, Lanzenberger R, Bogner W. Whole-brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism. Hum Brain Mapp 2024; 45:e26686. [PMID: 38647048 PMCID: PMC11034002 DOI: 10.1002/hbm.26686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 03/13/2024] [Accepted: 04/04/2024] [Indexed: 04/25/2024] Open
Abstract
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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Affiliation(s)
- Fabian Niess
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Viola Bader
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Sabina Frese
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - William T. Clarke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Anna Duguid
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and MetabolismMedical University of ViennaViennaAustria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Institute for Clinical Molecular MRIKarl Landsteiner SocietySt. PöltenAustria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and MetabolismMedical University of ViennaViennaAustria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH)Medical University of ViennaViennaAustria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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MUW researcher of the month. Wien Klin Wochenschr 2024; 136:247-248. [PMID: 38598111 DOI: 10.1007/s00508-024-02352-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
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Bitencourt AGV, Bhowmik A, Marcal Filho EFDL, Lo Gullo R, Mazaheri Y, Kapetas P, Eskreis-Winkler S, Young R, Pinker K, Thakur SB. Deuterium MR spectroscopy: potential applications in oncology research. BJR Open 2024; 6:tzae019. [PMID: 39165295 PMCID: PMC11333568 DOI: 10.1093/bjro/tzae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 07/23/2024] [Accepted: 07/30/2024] [Indexed: 08/22/2024] Open
Abstract
Metabolic imaging in clinical practice has long relied on PET with fluorodeoxyglucose (FDG), a radioactive tracer. However, this conventional method presents inherent limitations such as exposure to ionizing radiation and potential diagnostic uncertainties, particularly in organs with heightened glucose uptake like the brain. This review underscores the transformative potential of traditional deuterium MR spectroscopy (MRS) when integrated with gradient techniques, culminating in an advanced metabolic imaging modality known as deuterium MRI (DMRI). While recent advancements in hyperpolarized MRS hold promise for metabolic analysis, their widespread clinical usage is hindered by cost constraints and the availability of hyperpolarizer devices or facilities. DMRI, also denoted as deuterium metabolic imaging (DMI), represents a pioneering, single-shot, and noninvasive paradigm that fuses conventional MRS with nonradioactive deuterium-labelled substrates. Extensively tested in animal models and patient cohorts, particularly in cases of brain tumours, DMI's standout feature lies in its seamless integration into standard clinical MRI scanners, necessitating only minor adjustments such as radiofrequency coil tuning to the deuterium frequency. DMRI emerges as a versatile tool for quantifying crucial metabolites in clinical oncology, including glucose, lactate, glutamate, glutamine, and characterizing IDH mutations. Its potential applications in this domain are broad, spanning diagnostic profiling, treatment response monitoring, and the identification of novel therapeutic targets across diverse cancer subtypes.
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Affiliation(s)
- Almir Galvão Vieira Bitencourt
- Imaging Department, A. C. Camargo Cancer Center, São Paulo, 01525-001, Brazil
- Diagnósticos da América S.A., São Paulo, 04321-120, Brazil
| | - Arka Bhowmik
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | | | - Roberto Lo Gullo
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | - Yousef Mazaheri
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | - Panagiotis Kapetas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Sarah Eskreis-Winkler
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | - Robert Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | - Katja Pinker
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
| | - Sunitha B Thakur
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, United States
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Montrazi ET, Sasson K, Agemy L, Peters DC, Brenner O, Scherz A, Frydman L. High-sensitivity deuterium metabolic MRI differentiates acute pancreatitis from pancreatic cancers in murine models. Sci Rep 2023; 13:19998. [PMID: 37968574 PMCID: PMC10652017 DOI: 10.1038/s41598-023-47301-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/11/2023] [Indexed: 11/17/2023] Open
Abstract
Deuterium metabolic imaging (DMI) is a promising tool for investigating a tumor's biology, and eventually contribute in cancer diagnosis and prognosis. In DMI, [6,6'-2H2]-glucose is taken up and metabolized by different tissues, resulting in the formation of HDO but also in an enhanced formation of [3,3'-2H2]-lactate at the tumor site as a result of the Warburg effect. Recent studies have shown DMI's suitability to highlight pancreatic cancer in murine models by [3,3'-2H2]-lactate formation; an important question is whether DMI can also differentiate between these tumors and pancreatitis. This differentiation is critical, as these two diseases are hard to distinguish today radiologically, but have very different prognoses requiring distinctive treatments. Recent studies have shown the limitations that hyperpolarized MRI faces when trying to distinguish these pancreatic diseases by monitoring the [1-13C1]-pyruvate→[1-13C1]-lactate conversion. In this work, we explore DMI's capability to achieve such differentiation. Initial tests used a multi-echo (ME) SSFP sequence, to identify any metabolic differences between tumor and acute pancreatitis models that had been previously elicited very similar [1-13C1]-pyruvate→[1-13C1]-lactate conversion rates. Although ME-SSFP provides approximately 5 times greater signal-to-noise ratio (SNR) than the standard chemical shift imaging (CSI) experiment used in DMI, no lactate signal was observed in the pancreatitis model. To enhance lactate sensitivity further, we developed a new, weighted-average, CSI-SSFP approach for DMI. Weighted-average CSI-SSFP improved DMI's SNR by another factor of 4 over ME-SSFP-a sensitivity enhancement that sufficed to evidence natural abundance 2H fat in abdominal images, something that had escaped the previous approaches even at ultrahigh (15.2 T) MRI fields. Despite these efforts to enhance DMI's sensitivity, no lactate signal could be detected in acute pancreatitis models (n = 10; [3,3'-2H2]-lactate limit of detection < 100 µM; 15.2 T). This leads to the conclusion that pancreatic tumors and acute pancreatitis may be clearly distinguished by DMI, based on their different abilities to generate deuterated lactate.
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Affiliation(s)
- Elton T Montrazi
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Keren Sasson
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Lilach Agemy
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Dana C Peters
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, USA
| | - Ori Brenner
- Department of Veterinary Resources, Weizmann Institute of Science, Rehovot, Israel
| | - Avigdor Scherz
- Department of Plant and Environmental Science, Weizmann Institute of Science, Rehovot, Israel
| | - Lucio Frydman
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.
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Niess F, Strasser B, Hingerl L, Niess E, Motyka S, Hangel G, Krššák M, Gruber S, Spurny-Dworak B, Trattnig S, Scherer T, Lanzenberger R, Bogner W. 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. Neuroimage 2023; 277:120250. [PMID: 37414233 PMCID: PMC11019874 DOI: 10.1016/j.neuroimage.2023.120250] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/25/2023] [Accepted: 06/23/2023] [Indexed: 07/08/2023] Open
Abstract
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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Affiliation(s)
- Fabian Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria.
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Department of Neurosurgery, Medical University of Vienna, Austria
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Austria
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Institute for Clinical Molecular MRI, Karl Landsteiner Society, Pölten 3100St, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
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Bednarik P, Goranovic D, Svatkova A, Niess F, Hingerl L, Strasser B, Deelchand DK, Spurny-Dworak B, Krssak M, Trattnig S, Hangel G, Scherer T, Lanzenberger R, Bogner W. 1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain. Nat Biomed Eng 2023; 7:1001-1013. [PMID: 37106154 PMCID: PMC10861140 DOI: 10.1038/s41551-023-01035-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 03/30/2023] [Indexed: 04/29/2023]
Abstract
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.
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Affiliation(s)
- Petr Bednarik
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark.
| | - Dario Goranovic
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alena Svatkova
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Fabian Niess
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Dinesh K Deelchand
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Martin Krssak
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
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Chen M, Zhou X, Cai H, Li D, Song C, You H, Ma R, Dong Z, Peng Z, Feng ST. Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances. J Magn Reson Imaging 2023; 58:12-25. [PMID: 36971442 DOI: 10.1002/jmri.28694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 03/29/2023] Open
Abstract
This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Meicheng Chen
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Xiaoqi Zhou
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Huasong Cai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Di Li
- Department of Medical Ultrasonics, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Chenyu Song
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Huayu You
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Ruixia Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Zhi Dong
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Zhenpeng Peng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Province Guangdong, People's Republic of China
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9
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Knutsson L, Xu X, van Zijl PCM, Chan KWY. Imaging of sugar-based contrast agents using their hydroxyl proton exchange properties. NMR IN BIOMEDICINE 2023; 36:e4784. [PMID: 35665547 PMCID: PMC9719573 DOI: 10.1002/nbm.4784] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/30/2022] [Accepted: 06/03/2022] [Indexed: 05/13/2023]
Abstract
The ability of CEST MRI to detect the presence of millimolar concentrations of non-metallic contrast agents has made it possible to study, non-invasively, important biological molecules such as proteins and sugars, as well as drugs already approved for clinical use. Here, we review efforts to use sugar and sugar polymers as exogenous contrast agents, which is possible based on the exchange of their hydroxyl protons with water protons. While this capability has raised early enthusiasm, for instance about the possibility of imaging D-glucose metabolism with MRI in a way analogous to PET, experience over the past decade has shown that this is not trivial. On the other hand, many studies have confirmed the possibility of imaging a large variety of sugar analogues, each with potentially interesting applications to assess tissue physiology. Some promising applications are the study of (i) sugar delivery and transport to assess blood-brain barrier integrity and (ii) sugar uptake by cells for their characterization (e.g., cancer versus healthy), as well as (iii) clearance of sugars to assess tissue drainage-for instance, through the glymphatic system. To judge these opportunities and their challenges, especially in the clinic, it is necessary to understand the technical aspects of detecting the presence of rapidly exchanging protons through the water signal in MRI, especially as a function of magnetic field strength. We expect that novel approaches in terms of MRI detection (both saturation transfer and relaxation based), MRI data analysis, and sugar design will push this young field forward in the next decade.
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Affiliation(s)
- Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, US
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Peter CM van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, US
| | - Kannie WY Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering, Hong Kong, China
- Tung Biomedical Sciences Centre, City University of Hong Kong
- City University of Hong Kong Shenzhen Institute, Shenzhen, China
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10
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Niess F, Hingerl L, Strasser B, Bednarik P, Goranovic D, Niess E, Hangel G, Krššák M, Spurny-Dworak B, Scherer T, Lanzenberger R, Bogner W. 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. Invest Radiol 2023; 58:431-437. [PMID: 36735486 PMCID: PMC10184811 DOI: 10.1097/rli.0000000000000953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/15/2022] [Indexed: 02/04/2023]
Abstract
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.
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Affiliation(s)
- Fabian Niess
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Petr Bednarik
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
| | - Dario Goranovic
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Eva Niess
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
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11
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Veeraiah P, Jansen JFA. Multinuclear Magnetic Resonance Spectroscopy at Ultra-High-Field: Assessing Human Cerebral Metabolism in Healthy and Diseased States. Metabolites 2023; 13:metabo13040577. [PMID: 37110235 PMCID: PMC10143499 DOI: 10.3390/metabo13040577] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/06/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023] Open
Abstract
The brain is a highly energetic organ. Although the brain can consume metabolic substrates, such as lactate, glycogen, and ketone bodies, the energy metabolism in a healthy adult brain mainly relies on glucose provided via blood. The cerebral metabolism of glucose produces energy and a wide variety of intermediate metabolites. Since cerebral metabolic alterations have been repeatedly implicated in several brain disorders, understanding changes in metabolite levels and corresponding cell-specific neurotransmitter fluxes through different substrate utilization may highlight the underlying mechanisms that can be exploited to diagnose or treat various brain disorders. Magnetic resonance spectroscopy (MRS) is a noninvasive tool to measure tissue metabolism in vivo. 1H-MRS is widely applied in research at clinical field strengths (≤3T) to measure mostly high abundant metabolites. In addition, X-nuclei MRS including, 13C, 2H, 17O, and 31P, are also very promising. Exploiting the higher sensitivity at ultra-high-field (>4T; UHF) strengths enables obtaining unique insights into different aspects of the substrate metabolism towards measuring cell-specific metabolic fluxes in vivo. This review provides an overview about the potential role of multinuclear MRS (1H, 13C, 2H, 17O, and 31P) at UHF to assess the cerebral metabolism and the metabolic insights obtained by applying these techniques in both healthy and diseased states.
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Affiliation(s)
- Pandichelvam Veeraiah
- Scannexus (Ultra-High-Field MRI Center), 6229 EV Maastricht, The Netherlands
- Faculty of Health Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
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12
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Niess F, Strasser B, Hingerl L, Niess E, Motyka S, Hangel G, Krššák M, Gruber S, Spurny-Dworak B, Trattnig S, Scherer T, Lanzenberger R, Bogner W. 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. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.17.23288672. [PMID: 37131634 PMCID: PMC10153308 DOI: 10.1101/2023.04.17.23288672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
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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Affiliation(s)
- Fabian Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Department of Neurosurgery, Medical University of Vienna
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, 3100 St. Pölten, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
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13
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Chen Ming Low J, Wright AJ, Hesse F, Cao J, Brindle KM. Metabolic imaging with deuterium labeled substrates. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 134-135:39-51. [PMID: 37321757 DOI: 10.1016/j.pnmrs.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 01/12/2023] [Accepted: 02/07/2023] [Indexed: 06/17/2023]
Abstract
Deuterium metabolic imaging (DMI) is an emerging clinically-applicable technique for the non-invasive investigation of tissue metabolism. The generally short T1 values of 2H-labeled metabolites in vivo can compensate for the relatively low sensitivity of detection by allowing rapid signal acquisition in the absence of significant signal saturation. Studies with deuterated substrates, including [6,6'-2H2]glucose, [2H3]acetate, [2H9]choline and [2,3-2H2]fumarate have demonstrated the considerable potential of DMI for imaging tissue metabolism and cell death in vivo. The technique is evaluated here in comparison with established metabolic imaging techniques, including PET measurements of 2-deoxy-2-[18F]fluoro-d-glucose (FDG) uptake and 13C MR imaging of the metabolism of hyperpolarized 13C-labeled substrates.
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Affiliation(s)
- Jacob Chen Ming Low
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Alan J Wright
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Friederike Hesse
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Jianbo Cao
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
| | - Kevin M Brindle
- Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
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14
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Sun P, Wu Z, Lin L, Hu G, Zhang X, Wang J. MR-Nucleomics: The study of pathological cellular processes with multinuclear magnetic resonance spectroscopy and imaging in vivo. NMR IN BIOMEDICINE 2023; 36:e4845. [PMID: 36259659 DOI: 10.1002/nbm.4845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 09/28/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
Clinical medicine has experienced a rapid development in recent decades, during which therapies targeting specific cellular signaling pathways, or specific cell surface receptors, have been increasingly adopted. While these developments in clinical medicine call for improved precision in diagnosis and treatment monitoring, modern medical imaging methods are restricted mainly to anatomical imaging, lagging behind the requirements of precision medicine. Although positron emission tomography and single photon emission computed tomography have been used clinically for studies of metabolism, their applications have been limited by the exposure risk to ionizing radiation, the subsequent limitation in repeated and longitudinal studies, and the incapability in assessing downstream metabolism. Magnetic resonance spectroscopy (MRS) or spectroscopic imaging (MRSI) are, in theory, capable of assessing molecular activities in vivo, although they are often limited by sensitivity. Here, we review some recent developments in MRS and MRSI of multiple nuclei that have potential as molecular imaging tools in the clinic.
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Affiliation(s)
- Peng Sun
- Clinical & Technical Support, Philips Healthcare, China
| | - Zhigang Wu
- Clinical & Technical Support, Philips Healthcare, China
| | - Liangjie Lin
- Clinical & Technical Support, Philips Healthcare, China
| | - Geli Hu
- Clinical & Technical Support, Philips Healthcare, China
| | | | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, China
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15
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Jiang S, Chai H, Tang Q. Advances in the intraoperative delineation of malignant glioma margin. Front Oncol 2023; 13:1114450. [PMID: 36776293 PMCID: PMC9909013 DOI: 10.3389/fonc.2023.1114450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/10/2023] [Indexed: 01/27/2023] Open
Abstract
Surgery plays a critical role in the treatment of malignant glioma. However, due to the infiltrative growth and brain shift, it is difficult for neurosurgeons to distinguish malignant glioma margins with the naked eye and with preoperative examinations. Therefore, several technologies were developed to determine precise tumor margins intraoperatively. Here, we introduced four intraoperative technologies to delineate malignant glioma margin, namely, magnetic resonance imaging, fluorescence-guided surgery, Raman histology, and mass spectrometry. By tracing their detecting principles and developments, we reviewed their advantages and disadvantages respectively and imagined future trends.
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16
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Andrew R, Stimson RH. Mapping endocrine networks by stable isotope tracing. CURRENT OPINION IN ENDOCRINE AND METABOLIC RESEARCH 2022; 26:100381. [PMID: 39185272 PMCID: PMC11344083 DOI: 10.1016/j.coemr.2022.100381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Hormones regulate metabolic homeostasis through interlinked dynamic networks of proteins and small molecular weight metabolites, and state-of-the-art chemical technologies have been developed to decipher these complex pathways. Stable-isotope tracers have largely replaced radiotracers to measure flux in humans, building on advances in nuclear magnetic resonance spectroscopy and mass spectrometry. These technologies are now being applied to localise molecules within tissues. Radiotracers are still highly valuable both preclinically and in 3D imaging by positron emission tomography. The coming of age of vibrational spectroscopy in conjunction with stable-isotope tracing offers detailed cellular insights to map complex biological processes. Together with computational modelling, these approaches are poised to coalesce into multi-modal platforms to provide hitherto inaccessible dynamic and spatial insights into endocrine signalling.
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Affiliation(s)
- Ruth Andrew
- University/ British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, 47, Little France Crescent, Edinburgh, EH16 4TJ, United Kingdom
| | - Roland H Stimson
- University/ British Heart Foundation Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, 47, Little France Crescent, Edinburgh, EH16 4TJ, United Kingdom
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17
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Theillet FX, Luchinat E. In-cell NMR: Why and how? PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2022; 132-133:1-112. [PMID: 36496255 DOI: 10.1016/j.pnmrs.2022.04.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/19/2022] [Accepted: 04/27/2022] [Indexed: 06/17/2023]
Abstract
NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.
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Affiliation(s)
- Francois-Xavier Theillet
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France.
| | - Enrico Luchinat
- Dipartimento di Scienze e Tecnologie Agro-Alimentari, Alma Mater Studiorum - Università di Bologna, Piazza Goidanich 60, 47521 Cesena, Italy; CERM - Magnetic Resonance Center, and Neurofarba Department, Università degli Studi di Firenze, 50019 Sesto Fiorentino, Italy
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18
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DeBerardinis RJ, Keshari KR. Metabolic analysis as a driver for discovery, diagnosis, and therapy. Cell 2022; 185:2678-2689. [PMID: 35839759 PMCID: PMC9469798 DOI: 10.1016/j.cell.2022.06.029] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 12/14/2022]
Abstract
Metabolic anomalies contribute to tissue dysfunction. Current metabolism research spans from organelles to populations, and new technologies can accommodate investigation across these scales. Here, we review recent advancements in metabolic analysis, including small-scale metabolomics techniques amenable to organelles and rare cell types, functional screening to explore how cells respond to metabolic stress, and imaging approaches to non-invasively assess metabolic perturbations in diseases. We discuss how metabolomics provides an informative phenotypic dimension that complements genomic analysis in Mendelian and non-Mendelian disorders. We also outline pressing challenges and how addressing them may further clarify the biochemical basis of human disease.
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Affiliation(s)
- Ralph J DeBerardinis
- Howard Hughes Medical Institute and Children's Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Kayvan R Keshari
- Department of Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
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19
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Martinez de Lizarrondo S, Jacqmarcq C, Naveau M, Navarro-Oviedo M, Pedron S, Adam A, Freis B, Allouche S, Goux D, Razafindrakoto S, Gazeau F, Mertz D, Vivien D, Bonnard T, Gauberti M. Tracking the immune response by MRI using biodegradable and ultrasensitive microprobes. SCIENCE ADVANCES 2022; 8:eabm3596. [PMID: 35857494 PMCID: PMC9278862 DOI: 10.1126/sciadv.abm3596] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 05/26/2022] [Indexed: 06/03/2023]
Abstract
Molecular magnetic resonance imaging (MRI) holds great promise for diagnosis and therapeutic monitoring in a wide range of diseases. However, the low intrinsic sensitivity of MRI to detect exogenous contrast agents and the lack of biodegradable microprobes have prevented its clinical development. Here, we synthetized a contrast agent for molecular MRI based on a previously unknown mechanism of self-assembly of catechol-coated magnetite nanocrystals into microsized matrix-based particles. The resulting biodegradable microprobes (M3P for microsized matrix-based magnetic particles) carry up to 40,000 times higher amounts of superparamagnetic material than classically used nanoparticles while preserving favorable biocompatibility and excellent water dispersibility. After conjugation to monoclonal antibodies, targeted M3P display high sensitivity and specificity to detect inflammation in vivo in the brain, kidneys, and intestinal mucosa. The high payload of superparamagnetic material, excellent toxicity profile, short circulation half-life, and widespread reactivity of the M3P particles provides a promising platform for clinical translation of immuno-MRI.
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Affiliation(s)
- Sara Martinez de Lizarrondo
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Charlene Jacqmarcq
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Mikael Naveau
- Normandie Université, UMS 3408 Cyceron, CNRS, University of Caen Normandy, GIP CYCERON, Caen, France
| | - Manuel Navarro-Oviedo
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Swannie Pedron
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Alexandre Adam
- Institut de Physique et de Chimie des Matériaux de Strasbourg (IPCMS), UMR-7504 CNRS—Université de Strasbourg, 23 rue du Lœss, 67034 Strasbourg, France
| | - Barbara Freis
- Institut de Physique et de Chimie des Matériaux de Strasbourg (IPCMS), UMR-7504 CNRS—Université de Strasbourg, 23 rue du Lœss, 67034 Strasbourg, France
| | - Stephane Allouche
- CHU Caen, Department of Biochemistry, CHU de Caen Côte de Nacre, Caen, France
| | - Didier Goux
- Centre de Microscopie Appliquée à la Biologie (CMAbio), UniCaen, Normandie University, SF4206 Icore, 14000 Caen, France
| | - Sarah Razafindrakoto
- MSC, Université de Paris CNRS, UMR7057, 45 rue des Saints Pères 75006, Paris, France
| | - Florence Gazeau
- MSC, Université de Paris CNRS, UMR7057, 45 rue des Saints Pères 75006, Paris, France
| | - Damien Mertz
- Institut de Physique et de Chimie des Matériaux de Strasbourg (IPCMS), UMR-7504 CNRS—Université de Strasbourg, 23 rue du Lœss, 67034 Strasbourg, France
| | - Denis Vivien
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
- CHU Caen, Clinical Research Department, CHU de Caen Côte de Nacre, Caen, France
| | - Thomas Bonnard
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
| | - Maxime Gauberti
- Normandie Université, UNICAEN, INSERM, PhIND (Physiopathology and Imaging of Neurological Disorders), Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
- CHU Caen, Department of Diagnostic Imaging and Interventional Radiology, CHU de Caen Côte de Nacre, Caen, France
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20
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Cember ATJ, Wilson NE, Rich LJ, Bagga P, Nanga RPR, Swago S, Swain A, Thakuri D, Elliot M, Schnall MD, Detre JA, Reddy R. Integrating 1H MRS and deuterium labeled glucose for mapping the dynamics of neural metabolism in humans. Neuroimage 2022; 251:118977. [PMID: 35143973 PMCID: PMC9166154 DOI: 10.1016/j.neuroimage.2022.118977] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 01/13/2022] [Accepted: 02/05/2022] [Indexed: 11/21/2022] Open
Abstract
In the technique presented here, dubbed 'qMRS', we quantify the change in 1H MRS signal following administration of 2H-labeled glucose. As in recent human DMRS studies, we administer [6,6'-2H2]-glucose orally to healthy subjects. Since 2H is not detectable by 1H MRS, the transfer of the 2H label from glucose to a downstream metabolite leads to a reduction in the corresponding 1H MRS resonance of the metabolite, even if the total concentration of both isoforms remains constant. Moreover, introduction of the deuterium label alters the splitting pattern of the proton resonances, making indirect detection of the deuterated forms- as well as the direct detection of the decrease in unlabeled form- possible even without a 2H coil. Because qMRS requires only standard 1H MRS acquisition methods, it can be performed using commonly implemented single voxel spectroscopy (SVS) and chemical shift imaging (CSI) sequences. In this work, we implement qMRS in semi-LASER based CSI, generating dynamic maps arising from the fitted spectra, and demonstrating the feasibility of using qMRS and qCSI to monitor dynamic metabolism in the human brain using a 7T scanner with no auxiliary hardware.
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Affiliation(s)
- Abigail T J Cember
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Graduate Group in Biochemistry and Biophysics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Neil E Wilson
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Siemens Medical Solutions USA, Malvern, PA, USA
| | - Laurie J Rich
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Puneet Bagga
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sophia Swago
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Anshuman Swain
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Deepa Thakuri
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Mark Elliot
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Mitchell D Schnall
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Ravinder Reddy
- Department of Radiology, Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
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21
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Kumar M, Nanga RPR, Verma G, Wilson N, Brisset JC, Nath K, Chawla S. Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism. Front Neurol 2022; 13:789355. [PMID: 35370872 PMCID: PMC8967433 DOI: 10.3389/fneur.2022.789355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.
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Affiliation(s)
- Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Neil Wilson
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | | | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Sanjeev Chawla
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22
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Hrovatin K, Fischer DS, Theis FJ. Toward modeling metabolic state from single-cell transcriptomics. Mol Metab 2022; 57:101396. [PMID: 34785394 PMCID: PMC8829761 DOI: 10.1016/j.molmet.2021.101396] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/21/2021] [Accepted: 11/09/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Single-cell metabolic studies bring new insights into cellular function, which can often not be captured on other omics layers. Metabolic information has wide applicability, such as for the study of cellular heterogeneity or for the understanding of drug mechanisms and biomarker development. However, metabolic measurements on single-cell level are limited by insufficient scalability and sensitivity, as well as resource intensiveness, and are currently not possible in parallel with measuring transcript state, commonly used to identify cell types. Nevertheless, because omics layers are strongly intertwined, it is possible to make metabolic predictions based on measured data of more easily measurable omics layers together with prior metabolic network knowledge. SCOPE OF REVIEW We summarize the current state of single-cell metabolic measurement and modeling approaches, motivating the use of computational techniques. We review three main classes of computational methods used for prediction of single-cell metabolism: pathway-level analysis, constraint-based modeling, and kinetic modeling. We describe the unique challenges arising when transitioning from bulk to single-cell modeling. Finally, we propose potential model extensions and computational methods that could be leveraged to achieve these goals. MAJOR CONCLUSIONS Single-cell metabolic modeling is a rising field that provides a new perspective for understanding cellular functions. The presented modeling approaches vary in terms of input requirements and assumptions, scalability, modeled metabolic layers, and newly gained insights. We believe that the use of prior metabolic knowledge will lead to more robust predictions and will pave the way for mechanistic and interpretable machine-learning models.
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Affiliation(s)
- Karin Hrovatin
- Institute of Computational Biology, Helmholtz Center Munich, Ingolstaedter Landstraße 1, Neuherberg, 85764, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, Freising, 85354, Germany.
| | - David S Fischer
- Institute of Computational Biology, Helmholtz Center Munich, Ingolstaedter Landstraße 1, Neuherberg, 85764, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, Freising, 85354, Germany.
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Ingolstaedter Landstraße 1, Neuherberg, 85764, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, Freising, 85354, Germany; Department of Mathematics, Technical University of Munich, Boltzmannstr. 3, Garching bei München, 85748, Germany.
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23
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Hangel G, Niess E, Lazen P, Bednarik P, Bogner W, Strasser B. Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain. Anal Biochem 2022; 638:114479. [PMID: 34838516 DOI: 10.1016/j.ab.2021.114479] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/15/2021] [Accepted: 11/16/2021] [Indexed: 12/21/2022]
Abstract
Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.
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Affiliation(s)
- Gilbert Hangel
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria; Department of Neurosurgery, Medical University of Vienna, Austria
| | - Eva Niess
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Philipp Lazen
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Petr Bednarik
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Bernhard Strasser
- High Field MR Centre, Department of Medical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria.
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24
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Taglang C, Batsios G, Mukherjee J, Tran M, Gillespie AM, Hong D, Ronen SM, Artee Luchman H, Pieper RO, Viswanath P. Deuterium magnetic resonance spectroscopy enables noninvasive metabolic imaging of tumor burden and response to therapy in low-grade gliomas. Neuro Oncol 2022; 24:1101-1112. [PMID: 35091751 PMCID: PMC9248401 DOI: 10.1093/neuonc/noac022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND The alternative lengthening of telomeres (ALT) pathway is essential for tumor proliferation in astrocytomas. The goal of this study was to identify metabolic alterations linked to the ALT pathway that can be exploited for noninvasive magnetic resonance spectroscopy (MRS)-based imaging of astrocytomas in vivo. METHODS Genetic and pharmacological methods were used to dissect the association between the ALT pathway and glucose metabolism in genetically engineered and patient-derived astrocytoma models. 2H-MRS was used for noninvasive imaging of ALT-linked modulation of glycolytic flux in mice bearing orthotopic astrocytomas in vivo. RESULTS The ALT pathway was associated with higher activity of the rate-limiting glycolytic enzyme phosphofructokinase-1 and concomitantly elevated flux of glucose to lactate in astrocytoma cells. Silencing the ALT pathway or treating with the poly(ADP-ribose) polymerase inhibitor niraparib that induces telomeric fusion in ALT-dependent astrocytoma cells abrogated glycolytic flux. Importantly, this metabolic reprogramming could be non-invasively visualized by 2H-MRS. Lactate production from [6,6'-2H]-glucose was higher in ALT-dependent astrocytoma tumors relative to the normal brain in vivo. Furthermore, treatment of orthotopic astrocytoma-bearing mice with niraparib reduced lactate production from [6,6'-2H]-glucose at early timepoints when alterations in tumor volume could not be detected by anatomical imaging, pointing to the ability of [6,6'-2H]-glucose to report on pseudoprogression in vivo. CONCLUSIONS We have mechanistically linked the ALT pathway to elevated glycolytic flux and demonstrated the ability of [6,6'-2H]-glucose to non-invasively assess tumor burden and response to therapy in astrocytomas. Our findings point to a novel, clinically translatable method for metabolic imaging of astrocytoma patients.
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Affiliation(s)
- Céline Taglang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Georgios Batsios
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Joydeep Mukherjee
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Meryssa Tran
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Anne Marie Gillespie
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Donghyun Hong
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Hema Artee Luchman
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute and Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Alberta, Canada
| | - Russell O Pieper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Pavithra Viswanath
- Corresponding Author: Pavithra Viswanath, PhD, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94143, USA ()
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25
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Wang X, Liu NM, Zhao YF, Yang F, Zhu ZJ, Song D. Research Progress in the Medical Application of Heavy Water, Especially in the Field of D 2O-Raman Spectroscopy. Int J Med Sci 2022; 19:1357-1363. [PMID: 35928718 PMCID: PMC9346379 DOI: 10.7150/ijms.73150] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/07/2022] [Indexed: 11/05/2022] Open
Abstract
Heavy water is an ideal contrast agent for metabolic activity and can be adapted to a wide range of biological systems owing to its non-invasiveness, universal applicability, and cost-effectiveness. As a new type of probe, the heavy isotope of water has been widely used in the study of cell development, metabolism, tissue homeostasis, aging, and tumor heterogeneity. Herein, we review findings supporting the applications of and research on heavy water in monitoring of bacterial metabolism, rapid detection of drug sensitivity, identification of tumor cells, precision medicine, and evaluation of skin barrier function and promote the use of heavy water as a suitable marker for the development of detection and treatment methodologies.
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Affiliation(s)
- Xin Wang
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
| | - Nai-Meng Liu
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
| | - Ya-Fei Zhao
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
| | - Fan Yang
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
| | - Zi-Jia Zhu
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
| | - Dong Song
- Department of Breast Surgery, First Hospital of Jilin University, Changchun, Jilin 130021
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26
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Li Y, Zhao Y, Guo R, Wang T, Zhang Y, Chrostek M, Low WC, Zhu XH, Liang ZP, Chen W. Machine Learning-Enabled High-Resolution Dynamic Deuterium MR Spectroscopic Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3879-3890. [PMID: 34319872 PMCID: PMC8675063 DOI: 10.1109/tmi.2021.3101149] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Deuterium magnetic resonance spectroscopic imaging (DMRSI) has recently been recognized as a potentially powerful tool for noninvasive imaging of brain energy metabolism and tumor. However, the low sensitivity of DMRSI has significantly limited its utility for both research and clinical applications. This work presents a novel machine learning-based method to address this limitation. The proposed method synergistically integrates physics-based subspace modeling and data-driven deep learning for effective denoising, making high-resolution dynamic DMRSI possible. Specifically, a novel subspace model was used to represent the dynamic DMRSI signals; deep neural networks were trained to capture the low-dimensional manifolds of the spectral and temporal distributions of practical dynamic DMRSI data. The learned subspace and manifold structures were integrated via a regularization formulation to remove measurement noise. Theoretical analysis, computer simulations, and in vivo experiments have been conducted to demonstrate the denoising efficacy of the proposed method which enabled high-resolution imaging capability. The translational potential was demonstrated in tumor-bearing rats, where the Warburg effect associated with cancer metabolism and tumor heterogeneity were successfully captured. The new method may not only provide an effective tool to enhance the sensitivity of DMRSI for basic research and clinical applications but also provide a framework for denoising other spatiospectral data.
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27
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Ruhm L, Avdievich N, Ziegs T, Nagel AM, De Feyter HM, de Graaf RA, Henning A. Deuterium metabolic imaging in the human brain at 9.4 Tesla with high spatial and temporal resolution. Neuroimage 2021; 244:118639. [PMID: 34637905 PMCID: PMC8591372 DOI: 10.1016/j.neuroimage.2021.118639] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/10/2021] [Accepted: 10/05/2021] [Indexed: 01/09/2023] Open
Abstract
PURPOSE To present first highly spatially resolved deuterium metabolic imaging (DMI) measurements of the human brain acquired with a dedicated coil design and a fast chemical shift imaging (CSI) sequence at an ultrahigh field strength of B0 = 9.4 T. 2H metabolic measurements with a temporal resolution of 10 min enabled the investigation of the glucose metabolism in healthy human subjects. METHODS The study was performed with a double-tuned coil with 10 TxRx channels for 1H and 8TxRx/2Rx channels for 2H and an Ernst angle 3D CSI sequence with a nominal spatial resolution of 2.97 ml and a temporal resolution of 10 min. RESULTS The metabolism of [6,6'-2H2]-labeled glucose due to the TCA cycle could be made visible in high resolution metabolite images of deuterated water, glucose and Glx over the entire human brain. CONCLUSION X-nuclei MRSI as DMI can highly benefit from ultrahigh field strength enabling higher temporal and spatial resolutions.
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Affiliation(s)
- Loreen Ruhm
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany; IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tübingen, Germany.
| | - Nikolai Avdievich
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Theresia Ziegs
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany; IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tübingen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany; Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Henk M De Feyter
- Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States
| | - Robin A de Graaf
- Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States
| | - Anke Henning
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas/Texas, United States
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28
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Cepeda E, Narváez K. Molecular Photoacoustic Imaging. BIONATURA 2021. [DOI: 10.21931/rb/2021.06.04.34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Medicine has gone through several challenges to make it much more accurate and thus prolong the human being's life. A large part of this challenge is diseased, so early detection can help carry out treatment on time. There is a technology that allows detecting an abnormality within the body without using an invasive method. Ultrasound is a diagnostic test used to scan organs and tissues through sound waves. Although this technique has been widely used, the results are not desired because the images generated are not high resolution.
On the other hand, X-rays are used because it presents an image with a much higher resolution than other techniques based on light waves or ultrasound; despite this, they are harmful to cells. In consequence of this problem, another method called molecular photoacoustic imaging has been implemented. This technique bridges the traditional depth limits of ballistic optical imaging and diffuse optical imaging's resolution limits, using the acoustic waves generated in response to laser light absorption, which has now shown potential for molecular imaging, allowing the visualization of biological processes in a non-invasive way. The purpose of this article is to give a critically scoped review of the physical, chemical, and biochemical characteristics of existing photoacoustic contrast agents, highlighting the pivotal applications and current challenges for molecular photoacoustic imaging.
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Affiliation(s)
- Eduardo Cepeda
- School of Biological Sciences and Engineering, Yachay Tech University, Urcuquí 100650, Ecuador
| | - Katherine Narváez
- School of Biological Sciences and Engineering, Yachay Tech University, Urcuquí 100650, Ecuador
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29
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Polvoy I, Qin H, Flavell RR, Gordon J, Viswanath P, Sriram R, Ohliger MA, Wilson DM. Deuterium Metabolic Imaging-Rediscovery of a Spectroscopic Tool. Metabolites 2021; 11:570. [PMID: 34564385 PMCID: PMC8470013 DOI: 10.3390/metabo11090570] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 08/18/2021] [Indexed: 01/31/2023] Open
Abstract
The growing demand for metabolism-specific imaging techniques has rekindled interest in Deuterium (2H) Metabolic Imaging (DMI), a robust method based on administration of a substrate (glucose, acetate, fumarate, etc.) labeled with the stable isotope of hydrogen and the observation of its metabolic fate in three-dimensions. This technique allows the investigation of multiple metabolic processes in both healthy and diseased states. Despite its low natural abundance, the short relaxation time of deuterium allows for rapid radiofrequency (RF) pulses without saturation and efficient image acquisition. In this review, we provide a comprehensive picture of the evolution of DMI over the course of recent decades, with a special focus on its potential clinical applications.
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Affiliation(s)
- Ilona Polvoy
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Hecong Qin
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Robert R. Flavell
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Jeremy Gordon
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Pavithra Viswanath
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Renuka Sriram
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
| | - Michael A. Ohliger
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
- Department of Radiology, Zuckerberg San Francisco General Hospital, San Francisco, CA 94110, USA
| | - David M. Wilson
- Department of Radiology and Biomedical Imaging, University of California, 185 Berry St., San Francisco, CA 94158, USA; (I.P.); (H.Q.); (R.R.F.); (J.G.); (P.V.); (R.S.); (M.A.O.)
- Department of Radiology and Biomedical Imaging, University of California, 505 Parnassus Ave, San Francisco, CA 94143, USA
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van Zijl PCM, Brindle K, Lu H, Barker PB, Edden R, Yadav N, Knutsson L. Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo. Curr Opin Chem Biol 2021; 63:209-218. [PMID: 34298353 PMCID: PMC8384704 DOI: 10.1016/j.cbpa.2021.06.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/12/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022]
Abstract
Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.
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Affiliation(s)
- Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA.
| | - Kevin Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Nirbhay Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Medical Radiation Physics, Lund University, Lund, Sweden
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De Feyter HM, de Graaf RA. Deuterium metabolic imaging - Back to the future. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 326:106932. [PMID: 33902815 PMCID: PMC8083995 DOI: 10.1016/j.jmr.2021.106932] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/29/2021] [Accepted: 02/02/2021] [Indexed: 05/07/2023]
Abstract
Deuterium metabolic spectroscopy (DMS) and imaging (DMI) have recently been described as simple and robust MR-based methods to map metabolism with high temporal and/or spatial resolution. The metabolic fate of a wide range of suitable deuterated substrates, including glucose and acetate, can be monitored with deuterium MR methods in which the favorable MR characteristics of deuterium prevent many of the complications that hamper other techniques. The short T1 relaxation times lead to good MR sensitivity, while the low natural abundance prevents the need for water or lipid suppression. The sparsity of the deuterium spectra in combination with the low resonance frequency provides relative immunity to magnetic field inhomogeneity. Taken together, these features combine into a highly robust metabolic imaging method that has strong potential to become a dominant MR research tool and a viable clinical imaging modality. This perspective reviews the history of deuterium as a metabolic tracer, the use of NMR as a detection method for deuterium in vitro and in vivo and the recent development of DMS and DMI. Following a review of the NMR characteristics and the biological effects of deuterium, the promising future of DMI is outlined.
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Affiliation(s)
- Henk M De Feyter
- Departments of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA.
| | - Robin A de Graaf
- Departments of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA.
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Bednarik P, Spurny B, Silberbauer LR, Svatkova A, Handschuh PA, Reiter B, Konadu ME, Stimpfl T, Spies M, Bogner W, Lanzenberger R. Effect of Ketamine on Human Neurochemistry in Posterior Cingulate Cortex: A Pilot Magnetic Resonance Spectroscopy Study at 3 Tesla. Front Neurosci 2021; 15:609485. [PMID: 33841073 PMCID: PMC8024494 DOI: 10.3389/fnins.2021.609485] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 02/23/2021] [Indexed: 12/28/2022] Open
Abstract
Ketamine is a powerful glutamatergic long-lasting antidepressant, efficient in intractable major depression. Whereas ketamine's immediate psychomimetic side-effects were linked to glutamate changes, proton MRS (1H-MRS) showed an association between the ratio of glutamate and glutamine and delayed antidepressant effect emerging ∼2 h after ketamine administration. While most 1H-MRS studies focused on anterior cingulate, recent functional MRI connectivity studies revealed an association between ketamine's antidepressant effect and disturbed connectivity patterns to the posterior cingulate cortex (PCC), and related PCC dysfunction to rumination and memory impairment involved in depressive pathophysiology. The current study utilized the state-of-the-art single-voxel 3T sLASER 1H-MRS methodology optimized for reproducible measurements. Ketamine's effects on neurochemicals were assessed before and ∼3 h after intravenous ketamine challenge in PCC. Concentrations of 11 neurochemicals, including glutamate (CRLB ∼ 4%) and glutamine (CRLB ∼ 13%), were reliably quantified with the LCModel in 12 healthy young men with between-session coefficients of variation (SD/mean) <8%. Also, ratios of glutamate/glutamine and glutamate/aspartate were assessed as markers of synaptic function and activated glucose metabolism, respectively. Pairwise comparison of metabolite profiles at baseline and 193 ± 4 min after ketamine challenge yielded no differences. Minimal detectable concentration differences estimated with post hoc power analysis (power = 80%, alpha = 0.05) were below 0.5 μmol/g, namely 0.39 μmol/g (∼4%) for glutamate, 0.28 μmol/g (∼10%) for Gln, ∼14% for glutamate/glutamine and ∼8% for glutamate/aspartate. Despite the high sensitivity to detect between-session differences in glutamate and glutamine concentrations, our study did not detect delayed glutamatergic responses to subanesthetic ketamine doses in PCC.
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Affiliation(s)
- Petr Bednarik
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI in Musculoskeletal System, Karl Landsteiner Society, Vienna, Austria
| | - Benjamin Spurny
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Leo R. Silberbauer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Alena Svatkova
- Department of Medicine III, Clinical Division of Endocrinology and Metabolism, Medical University of Vienna, Vienna, Austria
| | - Patricia A. Handschuh
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Birgit Reiter
- Clinical Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Melisande E. Konadu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Stimpfl
- Clinical Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Marie Spies
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI in Musculoskeletal System, Karl Landsteiner Society, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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Masmudi-Martín M, Zhu L, Sanchez-Navarro M, Priego N, Casanova-Acebes M, Ruiz-Rodado V, Giralt E, Valiente M. Brain metastasis models: What should we aim to achieve better treatments? Adv Drug Deliv Rev 2021; 169:79-99. [PMID: 33321154 DOI: 10.1016/j.addr.2020.12.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 11/16/2020] [Accepted: 12/04/2020] [Indexed: 02/07/2023]
Abstract
Brain metastasis is emerging as a unique entity in oncology based on its particular biology and, consequently, the pharmacological approaches that should be considered. We discuss the current state of modelling this specific progression of cancer and how these experimental models have been used to test multiple pharmacologic strategies over the years. In spite of pre-clinical evidences demonstrating brain metastasis vulnerabilities, many clinical trials have excluded patients with brain metastasis. Fortunately, this trend is getting to an end given the increasing importance of secondary brain tumors in the clinic and a better knowledge of the underlying biology. We discuss emerging trends and unsolved issues that will shape how we will study experimental brain metastasis in the years to come.
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Ruiz-Rodado V, Brender JR, Cherukuri MK, Gilbert MR, Larion M. Magnetic resonance spectroscopy for the study of cns malignancies. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2021; 122:23-41. [PMID: 33632416 PMCID: PMC7910526 DOI: 10.1016/j.pnmrs.2020.11.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 11/20/2020] [Accepted: 11/22/2020] [Indexed: 05/04/2023]
Abstract
Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.
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Affiliation(s)
- Victor Ruiz-Rodado
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States.
| | - Jeffery R Brender
- Radiation Biology Branch, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Murali K Cherukuri
- Radiation Biology Branch, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Mioara Larion
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States.
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35
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Affiliation(s)
- Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Kevin M Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
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