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Larson PEZ, Bernard JML, Bankson JA, Bøgh N, Bok RA, Chen AP, Cunningham CH, Gordon J, Hövener JB, Laustsen C, Mayer D, McLean MA, Schilling F, Slater J, Vanderheyden JL, von Morze C, Vigneron DB, Xu D. Current methods for hyperpolarized [1- 13C]pyruvate MRI human studies. Magn Reson Med 2024; 91:2204-2228. [PMID: 38441968 PMCID: PMC10997462 DOI: 10.1002/mrm.29875] [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: 05/13/2023] [Revised: 08/12/2023] [Accepted: 09/06/2023] [Indexed: 03/07/2024]
Abstract
MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of HP agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate-by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation; (2) MRI system setup and calibrations; (3) data acquisition and image reconstruction; and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the "HP 13C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods and Equipment study groups. It further aims to provide a comprehensive reference for future consensus, building as the field continues to advance human studies with this metabolic imaging modality.
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Affiliation(s)
- Peder EZ Larson
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley, CA
94143, USA
| | - Jenna ML Bernard
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
| | - James A Bankson
- Department of Imaging Physics, MD Anderson Medical Center,
Houston, TX, USA
| | - Nikolaj Bøgh
- The MR Research Center, Department of Clinical Medicine,
Aarhus University, Aarhus, Denmark
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
| | | | - Charles H Cunningham
- Physical Sciences, Sunnybrook Research Institute, Toronto,
Ontario, Canada
- Department of Medical Biophysics, University of Toronto,
Toronto, Ontario, Canada
| | - Jeremy Gordon
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
| | - Jan-Bernd Hövener
- Section Biomedical Imaging, Molecular Imaging North
Competence Center (MOIN CC), Department of Radiology and Neuroradiology, University
Medical Center Schleswig-Holstein (UKSH), Kiel University, Am Botanischen Garten 14,
24118, Kiel, Germany
| | - Christoffer Laustsen
- The MR Research Center, Department of Clinical Medicine,
Aarhus University, Aarhus, Denmark
| | - Dirk Mayer
- Department of Diagnostic Radiology and Nuclear Medicine,
University of Maryland School of Medicine, Baltimore, MD, USA
- Greenebaum Cancer Center, University of Maryland School
of Medicine, Baltimore, MD, USA
| | - Mary A McLean
- Department of Radiology, University of Cambridge,
Cambridge, United Kingdom
- Cancer Research UK Cambridge Institute, University of
Cambridge, Li Ka Shing Center, Cambridge, United Kingdom
| | - Franz Schilling
- Department of Nuclear Medicine, School of Medicine,
Klinikum Rechts der Isar, Technical University of Munich, 81675 Munich,
Germany
| | - James Slater
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
| | | | | | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley, CA
94143, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University
of California, San Francisco, CA 94143, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley, CA
94143, USA
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Wang Z, Luo G, Li Y, Cao P. Using a deep learning prior for accelerating hyperpolarized 13 C MRSI on synthetic cancer datasets. Magn Reson Med 2024. [PMID: 38440832 DOI: 10.1002/mrm.30053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/30/2024] [Accepted: 01/30/2024] [Indexed: 03/06/2024]
Abstract
PURPOSE We aimed to incorporate a deep learning prior with k-space data fidelity for accelerating hyperpolarized carbon-13 MRSI, demonstrated on synthetic cancer datasets. METHODS A two-site exchange model, derived from the Bloch equation of MR signal evolution, was firstly used in simulating training and testing data, that is, synthetic phantom datasets. Five singular maps generated from each simulated dataset were used to train a deep learning prior, which was then employed with the fidelity term to reconstruct the undersampled MRI k-space data. The proposed method was assessed on synthetic human brain tumor images (N = 33), prostate cancer images (N = 72), and mouse tumor images (N = 58) for three undersampling factors and 2.5% additive Gaussian noise. Furthermore, varied levels of Gaussian noise with SDs of 2.5%, 5%, and 10% were added on synthetic prostate cancer data, and corresponding reconstruction results were evaluated. RESULTS For quantitative evaluation, peak SNRs were approximately 32 dB, and the accuracy was generally improved for 5 to 8 dB compared with those from compressed sensing with L1-norm regularization or total variation regularization. Reasonable normalized RMS error were obtained. Our method also worked robustly against noise, even on a data with noise SD of 10%. CONCLUSION The proposed singular value decomposition + iterative deep learning model could be considered as a general framework that extended the application of deep learning MRI reconstruction to metabolic imaging. The morphology of tumors and metabolic images could be measured robustly in six times acceleration using our method.
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Affiliation(s)
- Zuojun Wang
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, People's Republic of China
| | - Guanxiong Luo
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Ye Li
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology of Chinese Academy of Sciences, Shenzhen, People's Republic of China
| | - Peng Cao
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, People's Republic of China
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Chen HY, Gordon JW, Dwork N, Chung BT, Riselli A, Sivalokanathan S, Bok RA, Slater JB, Vigneron DB, Abraham MR, Larson PEZ. Probing human heart TCA cycle metabolism and response to glucose load using hyperpolarized [2- 13 C]pyruvate MRS. NMR IN BIOMEDICINE 2024; 37:e5074. [PMID: 38054254 DOI: 10.1002/nbm.5074] [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: 08/10/2023] [Revised: 10/22/2023] [Accepted: 10/24/2023] [Indexed: 12/07/2023]
Abstract
INTRODUCTION The healthy heart has remarkable metabolic flexibility that permits rapid switching between mitochondrial glucose oxidation and fatty acid oxidation to generate ATP. Loss of metabolic flexibility has been implicated in the genesis of contractile dysfunction seen in cardiomyopathy. Metabolic flexibility has been imaged in experimental models, using hyperpolarized (HP) [2-13 C]pyruvate MRI, which enables interrogation of metabolites that reflect tricarboxylic acid (TCA) cycle flux in cardiac myocytes. This study aimed to develop methods, demonstrate feasibility for [2-13 C]pyruvate MRI in the human heart for the first time, and assess cardiac metabolic flexibility. METHODS Good manufacturing practice [2-13 C]pyruvic acid was polarized in a 5 T polarizer for 2.5-3 h. Following dissolution, quality control parameters of HP pyruvate met all safety and sterility criteria for pharmacy release, prior to administration to study subjects. Three healthy subjects each received two HP injections and MR scans, first under fasting conditions, followed by oral glucose load. A 5 cm axial slab-selective spectroscopy approach was prescribed over the left ventricle and acquired at 3 s intervals on a 3 T clinical MRI scanner. RESULTS The study protocol, which included HP substrate injection, MR scanning, and oral glucose load, was performed safely without adverse events. Key downstream metabolites of [2-13 C]pyruvate metabolism in cardiac myocytes include the glycolytic derivative [2-13 C]lactate, TCA-associated metabolite [5-13 C]glutamate, and [1-13 C]acetylcarnitine, catalyzed by carnitine acetyltransferase (CAT). After glucose load, 13 C-labeling of lactate, glutamate, and acetylcarnitine from 13 C-pyruvate increased by an average of 39.3%, 29.5%, and 114% respectively in the three subjects, which could result from increases in lactate dehydrogenase, pyruvate dehydrogenase, and CAT enzyme activity as well as TCA cycle flux (glucose oxidation). CONCLUSIONS HP [2-13 C]pyruvate imaging is safe and permits noninvasive assessment of TCA cycle intermediates and the acetyl buffer, acetylcarnitine, which is not possible using HP [1-13 C]pyruvate. Cardiac metabolite measurement in the fasting/fed states provides information on cardiac metabolic flexibility and the acetylcarnitine pool.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Nicholas Dwork
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Brian T Chung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Andrew Riselli
- School of Pharmacy, University of California, San Francisco, California, USA
| | | | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - James B Slater
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - M Roselle Abraham
- Division of Cardiology, University of California, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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Autry AW, Vaziri S, Gordon JW, Chen HY, Kim Y, Dang D, LaFontaine M, Noeske R, Bok R, Villanueva-Meyer JE, Clarke JL, Oberheim Bush NA, Chang SM, Xu D, Lupo JM, Larson PEZ, Vigneron DB, Li Y. Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach. Cancers (Basel) 2024; 16:354. [PMID: 38254844 PMCID: PMC10814348 DOI: 10.3390/cancers16020354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.
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Affiliation(s)
- Adam W. Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Duy Dang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Marisa LaFontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | | | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Javier E. Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jennifer L. Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Susan M. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Janine M. Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
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Adamson PM, Datta K, Watkins R, Recht LD, Hurd RE, Spielman DM. Deuterium metabolic imaging for 3D mapping of glucose metabolism in humans with central nervous system lesions at 3T. Magn Reson Med 2024; 91:39-50. [PMID: 37796151 PMCID: PMC10841984 DOI: 10.1002/mrm.29830] [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: 05/23/2023] [Revised: 07/19/2023] [Accepted: 07/28/2023] [Indexed: 10/06/2023]
Abstract
PURPOSE To explore the potential of 3T deuterium metabolic imaging (DMI) using a birdcage 2 H radiofrequency (RF) coil in both healthy volunteers and patients with central nervous system (CNS) lesions. METHODS A modified gradient filter, home-built 2 H volume RF coil, and spherical k-space sampling were employed in a three-dimensional chemical shift imaging acquisition to obtain high-quality whole-brain metabolic images of 2 H-labeled water and glucose metabolic products. These images were acquired in a healthy volunteer and three subjects with CNS lesions of varying pathologies. Hardware and pulse sequence experiments were also conducted to improve the signal-to-noise ratio of DMI at 3T. RESULTS The ability to quantify local glucose metabolism in correspondence to anatomical landmarks across patients with varying CNS lesions is demonstrated, and increased lactate is observed in one patient with the most active disease. CONCLUSION DMI offers the potential to examine metabolic activity in human subjects with CNS lesions with DMI at 3T, promising for the potential of the future clinical translation of this metabolic imaging technique.
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Affiliation(s)
- Philip M. Adamson
- Department of Electrical Engineering, Stanford University, Stanford, California USA
| | - Keshav Datta
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Ron Watkins
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Lawrence D. Recht
- Department of Neurology, Stanford University, Stanford, California, USA
| | - Ralph E. Hurd
- Department of Radiology, Stanford University, Stanford, California, USA
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Wodtke P, Grashei M, Schilling F. Quo Vadis Hyperpolarized 13C MRI? Z Med Phys 2023:S0939-3889(23)00120-4. [PMID: 38160135 DOI: 10.1016/j.zemedi.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/16/2023] [Accepted: 10/20/2023] [Indexed: 01/03/2024]
Abstract
Over the last two decades, hyperpolarized 13C MRI has gained significance in both preclinical and clinical studies, hereby relying on technologies like PHIP-SAH (ParaHydrogen-Induced Polarization-Side Arm Hydrogenation), SABRE (Signal Amplification by Reversible Exchange), and dDNP (dissolution Dynamic Nuclear Polarization), with dDNP being applied in humans. A clinical dDNP polarizer has enabled studies across 24 sites, despite challenges like high cost and slow polarization. Parahydrogen-based techniques like SABRE and PHIP offer faster, more cost-efficient alternatives but require molecule-specific optimization. The focus has been on imaging metabolism of hyperpolarized probes, which requires long T1, high polarization and rapid contrast generation. Efforts to establish novel probes, improve acquisition techniques and enhance data analysis methods including artificial intelligence are ongoing. Potential clinical value of hyperpolarized 13C MRI was demonstrated primarily for treatment response assessment in oncology, but also in cardiology, nephrology, hepatology and CNS characterization. In this review on biomedical hyperpolarized 13C MRI, we summarize important and recent advances in polarization techniques, probe development, acquisition and analysis methods as well as clinical trials. Starting from those we try to sketch a trajectory where the field of biomedical hyperpolarized 13C MRI might go.
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Affiliation(s)
- Pascal Wodtke
- Department of Nuclear Medicine, TUM School of Medicine and Health, Klinikum rechts der Isar of Technical University of Munich, 81675 Munich, Germany; Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, United Kingdom; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge UK
| | - Martin Grashei
- Department of Nuclear Medicine, TUM School of Medicine and Health, Klinikum rechts der Isar of Technical University of Munich, 81675 Munich, Germany
| | - Franz Schilling
- Department of Nuclear Medicine, TUM School of Medicine and Health, Klinikum rechts der Isar of Technical University of Munich, 81675 Munich, Germany; Munich Institute of Biomedical Engineering, Technical University of Munich, 85748 Garching, Germany; German Cancer Consortium (DKTK), Partner Site Munich and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany.
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Hu JY, Vaziri S, Bøgh N, Kim Y, Autry AW, Bok RA, Li Y, Laustsen C, Xu D, Larson PEZ, Chang S, Vigneron DB, Gordon JW. Investigating cerebral perfusion with high resolution hyperpolarized [1- 13 C]pyruvate MRI. Magn Reson Med 2023; 90:2233-2241. [PMID: 37665726 PMCID: PMC10543485 DOI: 10.1002/mrm.29844] [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: 03/24/2023] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 09/06/2023]
Abstract
PURPOSE To investigate high-resolution hyperpolarized (HP) 13 C pyruvate MRI for measuring cerebral perfusion in the human brain. METHODS HP [1-13 C]pyruvate MRI was acquired in five healthy volunteers with a multi-resolution EPI sequence with 7.5 × 7.5 mm2 resolution for pyruvate. Perfusion parameters were calculated from pyruvate MRI using block-circulant singular value decomposition and compared to relative cerebral blood flow calculated from arterial spin labeling (ASL). To examine regional perfusion patterns, correlations between pyruvate and ASL perfusion were performed for whole brain, gray matter, and white matter voxels. RESULTS High resolution 7.5 × 7.5 mm2 pyruvate images were used to obtain relative cerebral blood flow (rCBF) values that were significantly positively correlated with ASL rCBF values (r = 0.48, 0.20, 0.28 for whole brain, gray matter, and white matter voxels respectively). Whole brain voxels exhibited the highest correlation between pyruvate and ASL perfusion, and there were distinct regional patterns of relatively high ASL and low pyruvate normalized rCBF found across subjects. CONCLUSION Acquiring HP 13 C pyruvate metabolic images at higher resolution allows for finer spatial delineation of brain structures and can be used to obtain cerebral perfusion parameters. Pyruvate perfusion parameters were positively correlated to proton ASL perfusion values, indicating a relationship between the two perfusion measures. This HP 13 C study demonstrated that hyperpolarized pyruvate MRI can assess cerebral metabolism and perfusion within the same study.
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Affiliation(s)
- Jasmine Y. Hu
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley,
California, USA
| | - Sana Vaziri
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
| | - Nikolaj Bøgh
- MR Research Center, Department of Clinical Medicine, Aarhus
University, Aarhus, Denmark
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
| | - Adam W. Autry
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley,
California, USA
| | - Christoffer Laustsen
- MR Research Center, Department of Clinical Medicine, Aarhus
University, Aarhus, Denmark
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley,
California, USA
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley,
California, USA
| | - Susan Chang
- Department of Neurological Surgery, University of
California San Francisco, San Francisco, California, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering,
University of California, San Francisco and University of California, Berkeley,
California, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University
of California San Francisco, San Francisco, California, USA
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Larson PE, Bernard JM, Bankson JA, Bøgh N, Bok RA, Chen AP, Cunningham CH, Gordon J, Hövener JB, Laustsen C, Mayer D, McLean MA, Schilling F, Slater J, Vanderheyden JL, von Morze C, Vigneron DB, Xu D, Group THCMC. Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human Studies. ARXIV 2023:arXiv:2309.04040v2. [PMID: 37731660 PMCID: PMC10508833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the HP 13C MRI Consensus Group as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.
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9
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Chen HY, Gordon JW, Dwork N, Chung BT, Riselli A, Sivalokanathan S, Bok RA, Slater JB, Vigneron DB, Abraham MR, Larson PE. Probing Human Heart TCA Cycle Metabolism and Response to Glucose Load using Hyperpolarized [2- 13C]Pyruvate MR Spectroscopy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.16.23297053. [PMID: 37905131 PMCID: PMC10615004 DOI: 10.1101/2023.10.16.23297053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Introduction The normal heart has remarkable metabolic flexibility that permits rapid switching between mitochondrial glucose oxidation and fatty acid (FA) oxidation to generate ATP. Loss of metabolic flexibility has been implicated in the genesis of contractile dysfunction seen in cardiomyopathy. Metabolic flexibility has been imaged in experimental models, using hyperpolarized (HP) [2-13C]pyruvate MRI, which enables interrogation of metabolites that reflect tricarboxylic acid (TCA) cycle flux in cardiac myocytes. This study aimed to develop methods, demonstrate feasibility for [2-13C]pyruvate MRI in the human heart for the first time, and assess cardiac metabolic flexibility. Methods Good Manufacturing Practice [2-13C]pyruvic acid was polarized in a 5T polarizer for 2.5-3 hours. Following dissolution, QC parameters of HP pyruvate met all safety and sterility criteria for pharmacy release, prior to administration to study subjects. Three healthy subjects each received two HP injections and MR scans, first under fasting conditions, followed by oral glucose load. A 5cm axial slab-selective spectroscopy approach was prescribed over the left ventricle and acquired at 3s intervals on a 3T clinical MRI scanner. Results The study protocol which included HP substrate injection, MR scanning and oral glucose load, was performed safely without adverse events. Key downstream metabolites of [2-13C]pyruvate metabolism in cardiac myocytes include the glycolytic derivative [2-13C]lactate, TCA-associated metabolite [5-13C]glutamate, and [1-13C]acetylcarnitine, catalyzed by carnitine acetyltransferase (CAT). After glucose load, 13C-labeling of lactate, glutamate, and acetylcarnitine from 13C-pyruvate increased by 39.3%, 29.5%, and 114%, respectively in the three subjects, that could result from increases in lactate dehydrogenase (LDH), pyruvate dehydrogenase (PDH), and CAT enzyme activity as well as TCA cycle flux (glucose oxidation). Conclusions HP [2-13C]pyruvate imaging is safe and permits non-invasive assessment of TCA cycle intermediates and the acetyl buffer, acetylcarnitine, which is not possible using HP [1-13C]pyruvate. Cardiac metabolite measurement in the fasting/fed states provides information on cardiac metabolic flexibility and the acetylcarnitine pool.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Nicholas Dwork
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Brian T. Chung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Andrew Riselli
- School of Pharmacy, University of California, San Francisco, United States
| | | | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - James B. Slater
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - M. Roselle Abraham
- Division of Cardiology, University of California, San Francisco, United States
| | - Peder E.Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
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10
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Chung BT, Kim Y, Gordon JW, Chen HY, Autry AW, Lee PM, Hu JY, Tan CT, Suszczynski C, Chang SM, Villanueva-Meyer JE, Bok RA, Larson PEZ, Xu D, Li Y, Vigneron DB. Hyperpolarized [2- 13C]pyruvate MR molecular imaging with whole brain coverage. Neuroimage 2023; 280:120350. [PMID: 37634883 PMCID: PMC10530049 DOI: 10.1016/j.neuroimage.2023.120350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/20/2023] [Accepted: 08/24/2023] [Indexed: 08/29/2023] Open
Abstract
Hyperpolarized (HP) 13C Magnetic Resonance Imaging (MRI) was applied for the first time to image and quantify the uptake and metabolism of [2-13C]pyruvate in the human brain to provide new metabolic information on cerebral energy metabolism. HP [2-13C]pyruvate was injected intravenously and imaged in 5 healthy human volunteer exams with whole brain coverage in a 1-minute acquisition using a specialized spectral-spatial multi-slice echoplanar imaging (EPI) pulse sequence to acquire 13C-labeled volumetric and dynamic images of [2-13C]pyruvate and downstream metabolites [5-13C]glutamate and [2-13C]lactate. Metabolic ratios and apparent conversion rates of pyruvate-to-lactate (kPL) and pyruvate-to-glutamate (kPG) were quantified to investigate simultaneously glycolytic and oxidative metabolism in a single injection.
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Affiliation(s)
- Brian T Chung
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA.
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Philip M Lee
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Chou T Tan
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Chris Suszczynski
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA; Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
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11
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Deen SS, Rooney C, Shinozaki A, McGing J, Grist JT, Tyler DJ, Serrão E, Gallagher FA. Hyperpolarized Carbon 13 MRI: Clinical Applications and Future Directions in Oncology. Radiol Imaging Cancer 2023; 5:e230005. [PMID: 37682052 PMCID: PMC10546364 DOI: 10.1148/rycan.230005] [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: 01/24/2023] [Revised: 06/16/2023] [Accepted: 08/02/2023] [Indexed: 09/09/2023]
Abstract
Hyperpolarized carbon 13 MRI (13C MRI) is a novel imaging approach that can noninvasively probe tissue metabolism in both normal and pathologic tissues. The process of hyperpolarization increases the signal acquired by several orders of magnitude, allowing injected 13C-labeled molecules and their downstream metabolites to be imaged in vivo, thus providing real-time information on kinetics. To date, the most important reaction studied with hyperpolarized 13C MRI is exchange of the hyperpolarized 13C signal from injected [1-13C]pyruvate with the resident tissue lactate pool. Recent preclinical and human studies have shown the role of several biologic factors such as the lactate dehydrogenase enzyme, pyruvate transporter expression, and tissue hypoxia in generating the MRI signal from this reaction. Potential clinical applications of hyperpolarized 13C MRI in oncology include using metabolism to stratify tumors by grade, selecting therapeutic pathways based on tumor metabolic profiles, and detecting early treatment response through the imaging of shifts in metabolism that precede tumor structural changes. This review summarizes the foundations of hyperpolarized 13C MRI, presents key findings from human cancer studies, and explores the future clinical directions of the technique in oncology. Keywords: Hyperpolarized Carbon 13 MRI, Molecular Imaging, Cancer, Tissue Metabolism © RSNA, 2023.
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Affiliation(s)
- Surrin S Deen
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Catriona Rooney
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Ayaka Shinozaki
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Jordan McGing
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - James T Grist
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Damian J Tyler
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Eva Serrão
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
| | - Ferdia A Gallagher
- From the Department of Radiology, Cambridge University Hospitals, Biomedical Campus, Cambridge, CB2 0QQ, England (S.S.D., E.S., F.A.G.); Department of Physiology, Anatomy, and Genetics (C.R., A.S., J.T.G., D.J.T.) and the Oxford Centre for Clinical Magnetic Resonance Research (A.S., J.T.G., D.J.T.), University of Oxford, Oxford, England; Department of Radiology, Oxford University Hospitals, Oxford, England (J.M., J.T.G.); Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England (J.T.G.); Department of Radiology, University of Cambridge, Cambridge, England (E.S., F.A.G.); Cancer Research UK Cambridge Centre, Cambridge, England (F.A.G.); and Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Canada (E.S.)
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12
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Autry AW, Vaziri S, LaFontaine M, Gordon JW, Chen HY, Kim Y, Villanueva-Meyer JE, Molinaro A, Clarke JL, Oberheim Bush NA, Xu D, Lupo JM, Larson PEZ, Vigneron DB, Chang SM, Li Y. Multi-parametric hyperpolarized 13C/ 1H imaging reveals Warburg-related metabolic dysfunction and associated regional heterogeneity in high-grade human gliomas. Neuroimage Clin 2023; 39:103501. [PMID: 37611371 PMCID: PMC10470324 DOI: 10.1016/j.nicl.2023.103501] [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: 05/04/2023] [Revised: 07/29/2023] [Accepted: 08/16/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Dynamic hyperpolarized (HP)-13C MRI has enabled real-time, non-invasive assessment of Warburg-related metabolic dysregulation in glioma using a [1-13C]pyruvate tracer that undergoes conversion to [1-13C]lactate and [13C]bicarbonate. Using a multi-parametric 1H/HP-13C imaging approach, we investigated dynamic and steady-state metabolism, together with physiological parameters, in high-grade gliomas to characterize active tumor. METHODS Multi-parametric 1H/HP-13C MRI data were acquired from fifteen patients with progressive/treatment-naïve glioblastoma [prog/TN GBM, IDH-wildtype (n = 11)], progressive astrocytoma, IDH-mutant, grade 4 (G4AIDH+, n = 2) and GBM manifesting treatment effects (n = 2). Voxel-wise regional analysis of the cohort with prog/TN GBM assessed imaging heterogeneity across contrast-enhancing/non-enhancing lesions (CEL/NEL) and normal-appearing white matter (NAWM) using a mixed effects model. To enable cross-nucleus parameter association, normalized perfusion, diffusion, and dynamic/steady-state (HP-13C/spectroscopic) metabolic data were collectively examined at the 13C resolution. Prog/TN GBM were similarly compared against progressive G4AIDH+ and treatment effects. RESULTS Regional analysis of Prog/TN GBM metabolism revealed statistically significant heterogeneity in 1H choline-to-N-acetylaspartate index (CNI)max, [1-13C]lactate, modified [1-13C]lactate-to-[1-13C]pyruvate ratio (CELval > NELval > NAWMval); [1-13C]lactate-to-[13C]bicarbonate ratio (CELval > NELval/NAWMval); and 1H-lactate (CELval/NELval > NAWMundetected). Significant associations were found between normalized perfusion (cerebral blood volume, nCBV; peak height, nPH) and levels of [1-13C]pyruvate and [1-13C]lactate, as well as between CNImax and levels of [1-13C]pyruvate, [1-13C]lactate and modified ratio. GBM, by comparison to G4AIDH+, displayed lower perfusion %-recovery and modeled rate constants for [1-13C]pyruvate-to-[1-13C]lactate conversion (kPL), and higher 1H-lactate and [1-13C]pyruvate levels, while having higher nCBV, %-recovery, kPL, [1-13C]pyruvate-to-[1-13C]lactate and modified ratios relative to treatment effects. CONCLUSIONS GBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.
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Affiliation(s)
- Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Marisa LaFontaine
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA; Department of Neurological Surgery, University of California, San Francisco, USA
| | - Annette Molinaro
- Department of Neurological Surgery, University of California, San Francisco, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, USA
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California, San Francisco, USA; Department of Neurology, University of California, San Francisco, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California, San Francisco, USA; Department of Neurology, University of California, San Francisco, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA; Department of Bioengineering and Therapeutic Science, University of California, San Francisco, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
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13
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Guglielmetti C, Cordano C, Najac C, Green AJ, Chaumeil MM. Imaging immunomodulatory treatment responses in a multiple sclerosis mouse model using hyperpolarized 13C metabolic MRI. COMMUNICATIONS MEDICINE 2023; 3:71. [PMID: 37217574 DOI: 10.1038/s43856-023-00300-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 05/03/2023] [Indexed: 05/24/2023] Open
Abstract
BACKGROUND In recent years, the ability of conventional magnetic resonance imaging (MRI), including T1 contrast-enhanced (CE) MRI, to monitor high-efficacy therapies and predict long-term disability in multiple sclerosis (MS) has been challenged. Therefore, non-invasive methods to improve MS lesions detection and monitor therapy response are needed. METHODS We studied the combined cuprizone and experimental autoimmune encephalomyelitis (CPZ-EAE) mouse model of MS, which presents inflammatory-mediated demyelinated lesions in the central nervous system as commonly seen in MS patients. Using hyperpolarized 13C MR spectroscopy (MRS) metabolic imaging, we measured cerebral metabolic fluxes in control, CPZ-EAE and CPZ-EAE mice treated with two clinically-relevant therapies, namely fingolimod and dimethyl fumarate. We also acquired conventional T1 CE MRI to detect active lesions, and performed ex vivo measurements of enzyme activities and immunofluorescence analyses of brain tissue. Last, we evaluated associations between imaging and ex vivo parameters. RESULTS We show that hyperpolarized [1-13C]pyruvate conversion to lactate is increased in the brain of untreated CPZ-EAE mice when compared to the control, reflecting immune cell activation. We further demonstrate that this metabolic conversion is significantly decreased in response to the two treatments. This reduction can be explained by increased pyruvate dehydrogenase activity and a decrease in immune cells. Importantly, we show that hyperpolarized 13C MRS detects dimethyl fumarate therapy, whereas conventional T1 CE MRI cannot. CONCLUSIONS In conclusion, hyperpolarized MRS metabolic imaging of [1-13C]pyruvate detects immunological responses to disease-modifying therapies in MS. This technique is complementary to conventional MRI and provides unique information on neuroinflammation and its modulation.
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Affiliation(s)
- Caroline Guglielmetti
- Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, USA.
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
| | - Christian Cordano
- Department of Neurology, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
| | - Chloé Najac
- Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden, The Netherlands
| | - Ari J Green
- Department of Neurology, Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
- Department of Ophthalmology, University of California at San Francisco, CA, San Francisco, USA
| | - Myriam M Chaumeil
- Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, USA.
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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14
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Lovibond S, Gewirtz AN, Pasquini L, Krebs S, Graham MS. The promise of metabolic imaging in diffuse midline glioma. Neoplasia 2023; 39:100896. [PMID: 36944297 PMCID: PMC10036941 DOI: 10.1016/j.neo.2023.100896] [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] [Revised: 02/10/2023] [Accepted: 03/13/2023] [Indexed: 03/23/2023]
Abstract
Recent insights into histopathological and molecular subgroups of glioma have revolutionized the field of neuro-oncology by refining diagnostic categories. An emblematic example in pediatric neuro-oncology is the newly defined diffuse midline glioma (DMG), H3 K27-altered. DMG represents a rare tumor with a dismal prognosis. The diagnosis of DMG is largely based on clinical presentation and characteristic features on conventional magnetic resonance imaging (MRI), with biopsy limited by its delicate neuroanatomic location. Standard MRI remains limited in its ability to characterize tumor biology. Advanced MRI and positron emission tomography (PET) imaging offer additional value as they enable non-invasive evaluation of molecular and metabolic features of brain tumors. These techniques have been widely used for tumor detection, metabolic characterization and treatment response monitoring of brain tumors. However, their role in the realm of pediatric DMG is nascent. By summarizing DMG metabolic pathways in conjunction with their imaging surrogates, we aim to elucidate the untapped potential of such imaging techniques in this devastating disease.
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Affiliation(s)
- Samantha Lovibond
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexandra N Gewirtz
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Luca Pasquini
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Krebs
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Radiochemistry and Imaging Sciences Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Radiology, Weill Cornell Medical College, New York, NY 10065, USA
| | - Maya S Graham
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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15
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Sharma G, Enriquez JS, Armijo R, Wang M, Bhattacharya P, Pudakalakatti S. Enhancing Cancer Diagnosis with Real-Time Feedback: Tumor Metabolism through Hyperpolarized 1- 13C Pyruvate MRSI. Metabolites 2023; 13:metabo13050606. [PMID: 37233647 DOI: 10.3390/metabo13050606] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/19/2023] [Accepted: 04/23/2023] [Indexed: 05/27/2023] Open
Abstract
This review article discusses the potential of hyperpolarized (HP) 13C magnetic resonance spectroscopic imaging (MRSI) as a noninvasive technique for identifying altered metabolism in various cancer types. Hyperpolarization significantly improves the signal-to-noise ratio for the identification of 13C-labeled metabolites, enabling dynamic and real-time imaging of the conversion of [1-13C] pyruvate to [1-13C] lactate and/or [1-13C] alanine. The technique has shown promise in identifying upregulated glycolysis in most cancers, as compared to normal cells, and detecting successful treatment responses at an earlier stage than multiparametric MRI in breast and prostate cancer patients. The review provides a concise overview of the applications of HP [1-13C] pyruvate MRSI in various cancer systems, highlighting its potential for use in preclinical and clinical investigations, precision medicine, and long-term studies of therapeutic response. The article also discusses emerging frontiers in the field, such as combining multiple metabolic imaging techniques with HP MRSI for a more comprehensive view of cancer metabolism, and leveraging artificial intelligence to develop real-time, actionable biomarkers for early detection, assessing aggressiveness, and interrogating the early efficacy of therapies.
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Affiliation(s)
- Gaurav Sharma
- Department of Cardiovascular & Thoracic Surgery, UT Southwestern Medical Center, Dallas, TX 75390, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - José S Enriquez
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
| | - Ryan Armijo
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
| | - Muxin Wang
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
| | - Pratip Bhattacharya
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
- Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
| | - Shivanand Pudakalakatti
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 75390, USA
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16
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Li H, Guglielmetti C, Sei YJ, Zilberter M, Le Page LM, Shields L, Yang J, Nguyen K, Tiret B, Gao X, Bennett N, Lo I, Dayton TL, Kampmann M, Huang Y, Rathmell JC, Vander Heiden M, Chaumeil MM, Nakamura K. Neurons require glucose uptake and glycolysis in vivo. Cell Rep 2023; 42:112335. [PMID: 37027294 PMCID: PMC10556202 DOI: 10.1016/j.celrep.2023.112335] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/22/2023] [Accepted: 03/20/2023] [Indexed: 04/08/2023] Open
Abstract
Neurons require large amounts of energy, but whether they can perform glycolysis or require glycolysis to maintain energy remains unclear. Using metabolomics, we show that human neurons do metabolize glucose through glycolysis and can rely on glycolysis to supply tricarboxylic acid (TCA) cycle metabolites. To investigate the requirement for glycolysis, we generated mice with postnatal deletion of either the dominant neuronal glucose transporter (GLUT3cKO) or the neuronal-enriched pyruvate kinase isoform (PKM1cKO) in CA1 and other hippocampal neurons. GLUT3cKO and PKM1cKO mice show age-dependent learning and memory deficits. Hyperpolarized magnetic resonance spectroscopic (MRS) imaging shows that female PKM1cKO mice have increased pyruvate-to-lactate conversion, whereas female GLUT3cKO mice have decreased conversion, body weight, and brain volume. GLUT3KO neurons also have decreased cytosolic glucose and ATP at nerve terminals, with spatial genomics and metabolomics revealing compensatory changes in mitochondrial bioenergetics and galactose metabolism. Therefore, neurons metabolize glucose through glycolysis in vivo and require glycolysis for normal function.
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Affiliation(s)
- Huihui Li
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Caroline Guglielmetti
- Department of Physical Therapy and Rehabilitation Science, San Francisco, CA 94158, USA; Department of Radiology and Biomedical Imaging, San Francisco, CA 94158, USA
| | - Yoshitaka J Sei
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Misha Zilberter
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Lydia M Le Page
- Department of Physical Therapy and Rehabilitation Science, San Francisco, CA 94158, USA; Department of Radiology and Biomedical Imaging, San Francisco, CA 94158, USA
| | - Lauren Shields
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA; Graduate Program in Biomedical Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Joyce Yang
- Graduate Program in Neuroscience, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kevin Nguyen
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Brice Tiret
- Department of Physical Therapy and Rehabilitation Science, San Francisco, CA 94158, USA; Department of Radiology and Biomedical Imaging, San Francisco, CA 94158, USA
| | - Xiao Gao
- Department of Physical Therapy and Rehabilitation Science, San Francisco, CA 94158, USA; Department of Radiology and Biomedical Imaging, San Francisco, CA 94158, USA; UCSF/UCB Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA 94158, USA
| | - Neal Bennett
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Iris Lo
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA
| | - Talya L Dayton
- Koch Institute for Integrative Cancer Research and the Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Martin Kampmann
- Graduate Program in Biomedical Sciences, University of California San Francisco, San Francisco, CA 94143, USA; Graduate Program in Neuroscience, University of California San Francisco, San Francisco, CA 94158, USA; UCSF/UCB Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA 94158, USA; Institute for Neurodegenerative Diseases, University of California San Francisco, San Francisco, CA, USA; Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA; Graduate Program in Biomedical Sciences, University of California San Francisco, San Francisco, CA 94143, USA; Graduate Program in Neuroscience, University of California San Francisco, San Francisco, CA 94158, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jeffrey C Rathmell
- Vanderbilt Center for Immunobiology, Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Matthew Vander Heiden
- Koch Institute for Integrative Cancer Research and the Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Myriam M Chaumeil
- Department of Physical Therapy and Rehabilitation Science, San Francisco, CA 94158, USA; Department of Radiology and Biomedical Imaging, San Francisco, CA 94158, USA; Graduate Program in Biomedical Sciences, University of California San Francisco, San Francisco, CA 94143, USA; UCSF/UCB Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA 94158, USA.
| | - Ken Nakamura
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA 94158, USA; Graduate Program in Biomedical Sciences, University of California San Francisco, San Francisco, CA 94143, USA; Graduate Program in Neuroscience, University of California San Francisco, San Francisco, CA 94158, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA.
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17
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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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18
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Penet MF, Sharma RK, Bharti S, Mori N, Artemov D, Bhujwalla ZM. Cancer insights from magnetic resonance spectroscopy of cells and excised tumors. NMR IN BIOMEDICINE 2023; 36:e4724. [PMID: 35262263 PMCID: PMC9458776 DOI: 10.1002/nbm.4724] [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: 12/14/2021] [Revised: 03/03/2022] [Accepted: 03/04/2022] [Indexed: 06/14/2023]
Abstract
Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to evolve as a stand-alone technology or as a complement to in vivo MRS to characterize the metabolome of cancer cells, cancer-associated stromal cells, immune cells, tumors, biofluids and, more recently, changes in the metabolome of organs induced by cancers. Here, we review some of the insights into cancer obtained with ex vivo MRS and provide a perspective of future directions. Ex vivo MRS of cells and tumors provides opportunities to understand the role of metabolism in cancer immune surveillance and immunotherapy. With advances in computational capabilities, the integration of artificial intelligence to identify differences in multinuclear spectral patterns, especially in easily accessible biofluids, is providing exciting advances in detection and monitoring response to treatment. Metabolotheranostics to target cancers and to normalize metabolic changes in organs induced by cancers to prevent cancer-induced morbidity are other areas of future development.
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Affiliation(s)
- Marie-France Penet
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
- Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, USA
| | - Raj Kumar Sharma
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
| | - Santosh Bharti
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
| | - Noriko Mori
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
| | - Dmitri Artemov
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
- Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, USA
| | - Zaver M. Bhujwalla
- Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, Maryland, USA
- Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, USA
- Department of Radiation Oncology and Molecular Radiation Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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19
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Grist JT, Bøgh N, Hansen ES, Schneider AM, Healicon R, Ball V, Miller JJJJ, Smart S, Couch Y, Buchan AM, Tyler DJ, Laustsen C. Developing a metabolic clearance rate framework as a translational analysis approach for hyperpolarized 13C magnetic resonance imaging. Sci Rep 2023; 13:1613. [PMID: 36709217 PMCID: PMC9884306 DOI: 10.1038/s41598-023-28643-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/23/2023] [Indexed: 01/29/2023] Open
Abstract
Hyperpolarized carbon-13 magnetic resonance imaging is a promising technique for in vivo metabolic interrogation of alterations between health and disease. This study introduces a formalism for quantifying the metabolic information in hyperpolarized imaging. This study investigated a novel perfusion formalism and metabolic clearance rate (MCR) model in pre-clinical stroke and in the healthy human brain. Simulations showed that the proposed model was robust to perturbations in T1, transmit B1, and kPL. A significant difference in ipsilateral vs contralateral pyruvate derived cerebral blood flow (CBF) was detected in rats (140 ± 2 vs 89 ± 6 mL/100 g/min, p < 0.01, respectively) and pigs (139 ± 12 vs 95 ± 5 mL/100 g/min, p = 0.04, respectively), along with an increase in fractional metabolism (26 ± 5 vs 4 ± 2%, p < 0.01, respectively) in the rodent brain. In addition, a significant increase in ipsilateral vs contralateral MCR (0.034 ± 0.007 vs 0.017 ± 0.02/s, p = 0.03, respectively) and a decrease in mean transit time (31 ± 8 vs 60 ± 2 s, p = 0.04, respectively) was observed in the porcine brain. In conclusion, MCR mapping is a simple and robust approach to the post-processing of hyperpolarized magnetic resonance imaging.
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Affiliation(s)
- James T Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Division of Cardiovascular Medicine, Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK
- Department of Radiology, Oxford University Hospitals Trust, Oxford, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Nikolaj Bøgh
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark
| | - Esben Søvsø Hansen
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark
| | - Anna M Schneider
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Richard Healicon
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Vicky Ball
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Jack J J J Miller
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Division of Cardiovascular Medicine, Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark
| | - Sean Smart
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Yvonne Couch
- Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | | | - Damian J Tyler
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
- Division of Cardiovascular Medicine, Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK
| | - Christoffer Laustsen
- Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark.
- Aarhus University Hospital, MR Center, Palle Juul Jensens Boulevard 99, 8200, Aarhus N, Denmark.
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20
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Heid I, Münch C, Karakaya S, Lueong SS, Winkelkotte AM, Liffers ST, Godfrey L, Cheung PFY, Savvatakis K, Topping GJ, Englert F, Kritzner L, Grashei M, Tannapfel A, Viebahn R, Wolters H, Uhl W, Vangala D, Smeets EMM, Aarntzen EHJG, Rauh D, Weichert W, Hoheisel JD, Hahn SA, Schilling F, Braren R, Trajkovic-Arsic M, Siveke JT. Functional noninvasive detection of glycolytic pancreatic ductal adenocarcinoma. Cancer Metab 2022; 10:24. [PMID: 36494842 PMCID: PMC9737747 DOI: 10.1186/s40170-022-00298-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) lacks effective treatment options beyond chemotherapy. Although molecular subtypes such as classical and QM (quasi-mesenchymal)/basal-like with transcriptome-based distinct signatures have been identified, deduced therapeutic strategies and targets remain elusive. Gene expression data show enrichment of glycolytic genes in the more aggressive and therapy-resistant QM subtype. However, whether the glycolytic transcripts are translated into functional glycolysis that could further be explored for metabolic targeting in QM subtype is still not known. METHODS We used different patient-derived PDAC model systems (conventional and primary patient-derived cells, patient-derived xenografts (PDX), and patient samples) and performed transcriptional and functional metabolic analysis. These included RNAseq and Illumina HT12 bead array, in vitro Seahorse metabolic flux assays and metabolic drug targeting, and in vivo hyperpolarized [1-13C]pyruvate and [1-13C]lactate magnetic resonance spectroscopy (HP-MRS) in PDAC xenografts. RESULTS We found that glycolytic metabolic dependencies are not unambiguously functionally exposed in all QM PDACs. Metabolic analysis demonstrated functional metabolic heterogeneity in patient-derived primary cells and less so in conventional cell lines independent of molecular subtype. Importantly, we observed that the glycolytic product lactate is actively imported into the PDAC cells and used in mitochondrial oxidation in both classical and QM PDAC cells, although more actively in the QM cell lines. By using HP-MRS, we were able to noninvasively identify highly glycolytic PDAC xenografts by detecting the last glycolytic enzymatic step and prominent intra-tumoral [1-13C]pyruvate and [1-13C]lactate interconversion in vivo. CONCLUSION Our study adds functional metabolic phenotyping to transcriptome-based analysis and proposes a functional approach to identify highly glycolytic PDACs as candidates for antimetabolic therapeutic avenues.
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Affiliation(s)
- Irina Heid
- grid.6936.a0000000123222966Institute of Diagnostic and Interventional Radiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Corinna Münch
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Sinan Karakaya
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Smiths S. Lueong
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Alina M. Winkelkotte
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany
| | - Sven T. Liffers
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Laura Godfrey
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Phyllis F. Y. Cheung
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Konstantinos Savvatakis
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Geoffrey J. Topping
- grid.6936.a0000000123222966Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Florian Englert
- grid.6936.a0000000123222966Institute of Diagnostic and Interventional Radiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Lukas Kritzner
- grid.6936.a0000000123222966Institute of Diagnostic and Interventional Radiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Martin Grashei
- grid.6936.a0000000123222966Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Andrea Tannapfel
- grid.5570.70000 0004 0490 981XInstitute of Pathology, Ruhr University of Bochum, Bochum, Germany
| | - Richard Viebahn
- grid.5570.70000 0004 0490 981XDepartment of Surgery, Knappschaftskrankenhaus, Ruhr University Bochum, Bochum, Germany
| | - Heiner Wolters
- grid.416438.cDepartment of Visceral and General Surgery, St. Josef-Hospital, Dortmund, Germany
| | - Waldemar Uhl
- grid.416438.cClinic for General and Visceral Surgery, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Deepak Vangala
- grid.5570.70000 0004 0490 981XDepartment of Medicine, Ruhr University Bochum, University Hospital Knappschaftskrankenhaus Bochum GmbH, Bochum, Germany
| | - Esther M. M. Smeets
- grid.10417.330000 0004 0444 9382Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Erik H. J. G. Aarntzen
- grid.10417.330000 0004 0444 9382Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Daniel Rauh
- grid.5675.10000 0001 0416 9637Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany ,Drug Discovery Hub Dortmund (DDHD) Am Zentrum Für Integrierte Wirkstoffforschung (ZIW), Dortmund, Germany
| | - Wilko Weichert
- grid.6936.a0000000123222966Institute of Pathology, TUM School of Medicine, Technical University of Munich, Munich, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany ,Comprehensive Cancer Center Munich (CCCM), Munich, Germany
| | - Jörg D. Hoheisel
- grid.7497.d0000 0004 0492 0584Division of Functional Genome Analysis, German Cancer Research Center, DKFZ, Heidelberg, Germany
| | - Stephan A. Hahn
- grid.5570.70000 0004 0490 981XDepartment of Molecular GI Oncology, Faculty of Medicine, Ruhr University Bochum, 44780 Bochum, Germany
| | - Franz Schilling
- grid.6936.a0000000123222966Department of Nuclear Medicine, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rickmer Braren
- grid.6936.a0000000123222966Institute of Diagnostic and Interventional Radiology, School of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Marija Trajkovic-Arsic
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
| | - Jens T. Siveke
- grid.5718.b0000 0001 2187 5445West German Cancer Center, Bridge Institute of Experimental Tumor Therapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany ,grid.7497.d0000 0004 0492 0584Division of Solid Tumor Translational Oncology, German Cancer Consortium (DKTK, Partner Site Essen) and German Cancer Research Center, DKFZ, Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany
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21
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Liu Z, Zhu Y, Zhang L, Jiang W, Liu Y, Tang Q, Cai X, Li J, Wang L, Tao C, Yin X, Li X, Hou S, Jiang D, Liu K, Zhou X, Zhang H, Liu M, Fan C, Tian Y. Structural and functional imaging of brains. Sci China Chem 2022; 66:324-366. [PMID: 36536633 PMCID: PMC9753096 DOI: 10.1007/s11426-022-1408-5] [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: 07/27/2022] [Accepted: 09/28/2022] [Indexed: 12/23/2022]
Abstract
Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.
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Affiliation(s)
- Zhichao Liu
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
| | - Ying Zhu
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Liming Zhang
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
| | - Weiping Jiang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Yawei Liu
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022 China
| | - Qiaowei Tang
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Xiaoqing Cai
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Jiang Li
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Lihua Wang
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Changlu Tao
- Interdisciplinary Center for Brain Information, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China
| | | | - Xiaowei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Shangguo Hou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055 China
| | - Dawei Jiang
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022 China
| | - Kai Liu
- Department of Chemistry, Tsinghua University, Beijing, 100084 China
| | - Xin Zhou
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Hongjie Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022 China
- Department of Chemistry, Tsinghua University, Beijing, 100084 China
| | - Maili Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Chunhai Fan
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Yang Tian
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
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22
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Lee PM, Chen HY, Gordon JW, Wang ZJ, Bok R, Hashoian R, Kim Y, Liu X, Nickles T, Cheung K, De Las Alas F, Daniel H, Larson PEZ, von Morze C, Vigneron DB, Ohliger MA. Whole-Abdomen Metabolic Imaging of Healthy Volunteers Using Hyperpolarized [1- 13 C]pyruvate MRI. J Magn Reson Imaging 2022; 56:1792-1806. [PMID: 35420227 PMCID: PMC9562149 DOI: 10.1002/jmri.28196] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/31/2022] [Accepted: 04/01/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Hyperpolarized 13 C MRI quantitatively measures enzyme-catalyzed metabolism in cancer and metabolic diseases. Whole-abdomen imaging will permit dynamic metabolic imaging of several abdominal organs simultaneously in healthy and diseased subjects. PURPOSE Image hyperpolarized [1-13 C]pyruvate and products in the abdomens of healthy volunteers, overcoming challenges of motion, magnetic field variations, and spatial coverage. Compare hyperpolarized [1-13 C]pyruvate metabolism across abdominal organs of healthy volunteers. STUDY TYPE Prospective technical development. SUBJECTS A total of 13 healthy volunteers (8 male), 21-64 years (median 36). FIELD STRENGTH/SEQUENCE A 3 T. Proton: T1 -weighted spoiled gradient echo, T2 -weighted single-shot fast spin echo, multiecho fat/water imaging. Carbon-13: echo-planar spectroscopic imaging, metabolite-specific echo-planar imaging. ASSESSMENT Transmit magnetic field was measured. Variations in main magnetic field (ΔB0 ) determined using multiecho proton acquisitions were compared to carbon-13 acquisitions. Changes in ΔB0 were measured after localized shimming. Improvements in metabolite signal-to-noise ratio were calculated. Whole-organ regions of interests were drawn over the liver, spleen, pancreas, and kidneys by a single investigator. Metabolite signals, time-to-peak, decay times, and mean first-order rate constants for pyruvate-to-lactate (kPL ) and alanine (kPA ) conversion were measured in each organ. STATISTICAL TESTS Linear regression, one-sample Kolmogorov-Smirnov tests, paired t-tests, one-way ANOVA, Tukey's multiple comparisons tests. P ≤ 0.05 considered statistically significant. RESULTS Proton ΔB0 maps correlated with carbon-13 ΔB0 maps (slope = 0.93, y-intercept = -2.88, R2 = 0.73). Localized shimming resulted in mean frequency offset within ±25 Hz for all organs. Metabolite SNR significantly increased after denoising. Mean kPL and kPA were highest in liver, followed by pancreas, spleen, and kidneys (all comparisons with liver were significant). DATA CONCLUSION Whole-abdomen coverage with hyperpolarized carbon-13 MRI was feasible despite technical challenges. Multiecho gradient echo 1 H acquisitions accurately predicted chemical shifts observed using carbon-13 spectroscopy. Carbon-13 acquisitions benefited from local shimming. Metabolite energetics in the abdomen compiled for healthy volunteers can be used to design larger clinical trials in patients with metabolic diseases. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Philip M Lee
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | | | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Tanner Nickles
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Kiersten Cheung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Francesca De Las Alas
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Heather Daniel
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Peder EZ Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Cornelius von Morze
- Mallinckrodt Institute of Radiology, Washington University in St. Louis; St. Louis, Missouri, USA
| | - Daniel B Vigneron
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Michael A Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology, Zuckerberg San Francisco General Hospital and Trauma Center; San Francisco, California, USA
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23
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Minami N, Hong D, Stevers N, Barger CJ, Radoul M, Hong C, Chen L, Kim Y, Batsios G, Gillespie AM, Pieper RO, Costello JF, Viswanath P, Ronen SM. Imaging biomarkers of TERT or GABPB1 silencing in TERT-positive glioblastoma. Neuro Oncol 2022; 24:1898-1910. [PMID: 35460557 PMCID: PMC9629440 DOI: 10.1093/neuonc/noac112] [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] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND TERT promoter mutations are observed in 80% of wild-type IDH glioblastoma (GBM). Moreover, the upstream TERT transcription factor GABPB1 was recently identified as a cancer-specific therapeutic target for tumors harboring a TERT promoter mutation. In that context, noninvasive imaging biomarkers are needed for the detection of TERT modulation. METHODS Multiple GBM models were investigated as cells and in vivo tumors and the impact of TERT silencing, either directly or by targeting GABPB1, was determined using 1H and hyperpolarized 13C magnetic resonance spectroscopy (MRS). Changes in associated metabolic enzymes were also investigated. RESULTS 1H-MRS revealed that lactate and glutathione (GSH) were the most significantly altered metabolites when either TERT or GABPB1 was silenced, and lactate and GSH levels were correlated with cellular TERT expression. Consistent with the drop in lactate, 13C-MRS showed that hyperpolarized [1-13C]lactate production from [1-13C]pyruvate was also reduced when TERT was silenced. Mechanistically, the reduction in GSH was associated with a reduction in pentose phosphate pathway flux, reduced activity of glucose-6-phosphate dehydrogenase, and reduced NADPH. The drop in lactate and hyperpolarized lactate were associated with reductions in glycolytic flux, NADH, and expression/activity of GLUT1, monocarboxylate transporters, and lactate dehydrogenase A. CONCLUSIONS Our study indicates that MRS-detectable GSH, lactate, and lactate production could serve as metabolic biomarkers of response to emerging TERT-targeted therapies for GBM with activating TERT promoter mutations. Importantly these biomarkers are readily translatable to the clinic, and thus could ultimately improve GBM patient management.
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Affiliation(s)
- Noriaki Minami
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Donghyun Hong
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Nicholas Stevers
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Carter J Barger
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Marina Radoul
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Chibo Hong
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Lee Chen
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Georgios Batsios
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Anne Marie Gillespie
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Russel O Pieper
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Joseph F Costello
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Pavithra Viswanath
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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24
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Hu JY, Kim Y, Autry AW, Frost MM, Bok RA, Villanueva-Meyer JE, Xu D, Li Y, Larson PEZ, Vigneron DB, Gordon JW. Kinetic analysis of multi-resolution hyperpolarized 13 C human brain MRI to study cerebral metabolism. Magn Reson Med 2022; 88:2190-2197. [PMID: 35754148 PMCID: PMC9420752 DOI: 10.1002/mrm.29354] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 04/15/2022] [Accepted: 05/23/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To investigate multi-resolution hyperpolarized (HP) 13 C pyruvate MRI for measuring kinetic conversion rates in the human brain. METHODS HP [1-13 C]pyruvate MRI was acquired in 6 subjects with a multi-resolution EPI sequence at 7.5 × 7.5 mm2 resolution for pyruvate and 15 × 15 mm2 resolution for lactate and bicarbonate. With the same lactate data, 2 quantitative maps of pyruvate-to-lactate conversion (kPL ) maps were generated: 1 using 7.5 × 7.5 mm2 resolution pyruvate data and the other using synthetic 15 × 15 mm2 resolution pyruvate data to simulate a standard constant resolution acquisition. To examine local kPL values, 4 voxels were manually selected in each study representing brain tissue near arteries, brain tissue near veins, white matter, and gray matter. RESULTS High resolution 7.5 × 7.5 mm2 pyruvate images increased the spatial delineation of brain structures and decreased partial volume effects compared to coarser resolution 15 × 15 mm2 pyruvate images. Voxels near arteries, veins and in white matter exhibited higher calculated kPL for multi-resolution images. CONCLUSION Acquiring HP 13 C pyruvate metabolic data with a multi-resolution approach minimized partial volume effects from vascular pyruvate signals while maintaining the SNR of downstream metabolites. Higher resolution pyruvate images for kinetic fitting resulted in increased kinetic rate values, particularly around the superior sagittal sinus and cerebral arteries, by reducing extracellular pyruvate signal contributions from adjacent blood vessels. This HP 13 C study showed that acquiring pyruvate with finer resolution improved the quantification of kinetic rates throughout the human brain.
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Affiliation(s)
- Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Mary M Frost
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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25
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Healicon R, Rooney CHE, Ball V, Shinozaki A, Miller JJ, Smart S, Radford‐Smith D, Anthony D, Tyler DJ, Grist JT. Assessing the effect of anesthetic gas mixtures on hyperpolarized 13 C pyruvate metabolism in the rat brain. Magn Reson Med 2022; 88:1324-1332. [PMID: 35468245 PMCID: PMC9325476 DOI: 10.1002/mrm.29274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 03/11/2022] [Accepted: 03/31/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To determine the effect of altering anesthetic oxygen protocols on measurements of cerebral perfusion and metabolism in the rodent brain. METHODS Seven rats were anesthetized and underwent serial MRI scans with hyperpolarized [1-13 C]pyruvate and perfusion weighted imaging. The anesthetic carrier gas protocol used varied from 100:0% to 90:10% to 60:40% O2 :N2 O. Spectra were quantified with AMARES and perfusion imaging was processed using model-free deconvolution. A 1-way ANOVA was used to compare results across groups, with pairwise t tests performed with correction for multiple comparisons. Spearman's correlation analysis was performed between O2 % and MR measurements. RESULTS There was a significant increase in bicarbonate:total 13 C carbon and bicarbonate:13 C pyruvate when moving between 100:0 to 90:10 and 100:0 to 60:40 O2 :N2 O % (0.02 ± 0.01 vs. 0.019 ± 0.005 and 0.02 ± 0.01 vs. 0.05 ± 0.02, respectively) and (0.04 ± 0.01 vs. 0.03 ± 0.01 and 0.04 ± 0.01 vs. 0.08 ± 0.02, respectively). There was a significant difference in 13 C pyruvate time to peak when moving between 100:0 to 90:10 and 100:0 to 60:40 O2 :N2 O % (13 ± 2 vs. 10 ± 1 and 13 ± 2 vs. 7.5 ± 0.5 s, respectively) as well as significant differences in cerebral blood flow (CBF) between gas protocols. Significant correlations between bicarbonate:13 C pyruvate and gas protocol (ρ = -0.47), mean transit time and gas protocol (ρ = 0.41) and 13 C pyruvate time-to-peak and cerebral blood flow (ρ = -0.54) were also observed. CONCLUSIONS These results demonstrate that the detection and quantification of cerebral metabolism and perfusion is dependent on the oxygen protocol used in the anesthetized rodent brain.
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Affiliation(s)
- Richard Healicon
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Catriona H. E. Rooney
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Vicky Ball
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Ayaka Shinozaki
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUnited Kingdom
| | - Jack J. Miller
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
- Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUnited Kingdom
- Clarendon Laboratory, Department of PhysicsUniversity of OxfordOxfordUnited Kingdom
- The PET Centre and The MR Centre, Clinical MedicineAarhus University and Aarhus University HospitalAarhusDenmark
| | - Sean Smart
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | | | - Daniel Anthony
- Department of PharmacologyUniversity of OxfordOxfordUnited Kingdom
| | - Damian J. Tyler
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
- The PET Centre and The MR Centre, Clinical MedicineAarhus University and Aarhus University HospitalAarhusDenmark
| | - James T. Grist
- Department of Physiology, Anatomy, and GeneticsUniversity of OxfordOxfordUnited Kingdom
- The PET Centre and The MR Centre, Clinical MedicineAarhus University and Aarhus University HospitalAarhusDenmark
- Department of RadiologyOxford University HospitalsOxfordUnited Kingdom
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUnited Kingdom
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26
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Wei Y, Yang C, Jiang H, Li Q, Che F, Wan S, Yao S, Gao F, Zhang T, Wang J, Song B. Multi-nuclear magnetic resonance spectroscopy: state of the art and future directions. Insights Imaging 2022; 13:135. [PMID: 35976510 PMCID: PMC9382599 DOI: 10.1186/s13244-022-01262-z] [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] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/04/2022] [Indexed: 12/16/2022] Open
Abstract
With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.
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Affiliation(s)
- Yi Wei
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Caiwei Yang
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Hanyu Jiang
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Qian Li
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Feng Che
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Shang Wan
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Shan Yao
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Feifei Gao
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Tong Zhang
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China
| | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People's Republic of China. .,Department of Radiology, Sanya People's Hospital, Sanya, China.
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Vaziri S, Autry AW, Lafontaine M, Kim Y, Gordon JW, Chen HY, Hu JY, Lupo JM, Chang SM, Clarke JL, Villanueva-Meyer JE, Bush NAO, Xu D, Larson PEZ, Vigneron DB, Li Y. Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1- 13C]pyruvate MRI data from patients with glioma. Neuroimage Clin 2022; 36:103155. [PMID: 36007439 PMCID: PMC9421383 DOI: 10.1016/j.nicl.2022.103155] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma. METHODS Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared. RESULTS Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD). CONCLUSION Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.
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Affiliation(s)
- Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Marisa Lafontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.
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28
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Zaccagna F, McLean MA, Grist JT, Kaggie J, Mair R, Riemer F, Woitek R, Gill AB, Deen S, Daniels CJ, Ursprung S, Schulte RF, Allinson K, Chhabra A, Laurent MC, Locke M, Frary A, Hilborne S, Patterson I, Carmo BD, Slough R, Wilkinson I, Basu B, Wason J, Gillard JH, Matys T, Watts C, Price SJ, Santarius T, Graves MJ, Jefferies S, Brindle KM, Gallagher FA. Imaging Glioblastoma Metabolism by Using Hyperpolarized [1- 13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study. Radiol Imaging Cancer 2022; 4:e210076. [PMID: 35838532 PMCID: PMC9360994 DOI: 10.1148/rycan.210076] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 04/27/2022] [Accepted: 05/19/2022] [Indexed: 01/20/2023]
Abstract
Purpose To evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (13C) MRI to monitor the exchange of the hyperpolarized 13C label between injected [1-13C]pyruvate and tumor lactate and bicarbonate. Materials and Methods In this prospective study, seven treatment-naive patients (age [mean ± SD], 60 years ± 11; five men) with GBM were imaged at 3 T by using a dual-tuned 13C-hydrogen 1 head coil. Hyperpolarized [1-13C]pyruvate was injected, and signal was acquired by using a dynamic MRI spiral sequence. Metabolism was assessed within the tumor, in the normal-appearing brain parenchyma (NABP), and in healthy volunteers by using paired or unpaired t tests and a Wilcoxon signed rank test. The Spearman ρ correlation coefficient was used to correlate metabolite labeling with lactate dehydrogenase A (LDH-A) expression and some immunohistochemical markers. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. Results The bicarbonate-to-pyruvate (BP) ratio was lower in the tumor than in the contralateral NABP (P < .01). The tumor lactate-to-pyruvate (LP) ratio was not different from that in the NABP (P = .38). The LP and BP ratios in the NABP were higher than those observed previously in healthy volunteers (P < .05). Tumor lactate and bicarbonate signal intensities were strongly correlated with the pyruvate signal intensity (ρ = 0.92, P < .001, and ρ = 0.66, P < .001, respectively), and the LP ratio was weakly correlated with LDH-A expression in biopsy samples (ρ = 0.43, P = .04). Conclusion Hyperpolarized 13C MRI demonstrated variation in lactate labeling in GBM, both within and between tumors. In contrast, bicarbonate labeling was consistently lower in tumors than in the surrounding NABP. Keywords: Hyperpolarized 13C MRI, Glioblastoma, Metabolism, Cancer, MRI, Neuro-oncology Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Affiliation(s)
- Fulvio Zaccagna
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Mary A. McLean
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - James T. Grist
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Joshua Kaggie
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Richard Mair
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Frank Riemer
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ramona Woitek
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Andrew B. Gill
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Surrin Deen
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Charlie J. Daniels
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Stephan Ursprung
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Rolf F. Schulte
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Kieren Allinson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Anita Chhabra
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Marie-Christine Laurent
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Matthew Locke
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Amy Frary
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Sarah Hilborne
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ilse Patterson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Bruno D. Carmo
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Rhys Slough
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ian Wilkinson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Bristi Basu
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - James Wason
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Jonathan H. Gillard
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Tomasz Matys
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Colin Watts
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Stephen J. Price
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Thomas Santarius
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Martin J. Graves
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Sarah Jefferies
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Kevin M. Brindle
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ferdia A. Gallagher
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
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29
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Reynolds S, Kazan SM, Anton A, Alizadeh T, Gunn RN, Paley MN, Tozer GM, Cunningham VJ. Kinetic modelling of dissolution dynamic nuclear polarisation 13 C magnetic resonance spectroscopy data for analysis of pyruvate delivery and fate in tumours. NMR IN BIOMEDICINE 2022; 35:e4650. [PMID: 34841602 DOI: 10.1002/nbm.4650] [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: 02/02/2021] [Revised: 09/19/2021] [Accepted: 10/24/2021] [Indexed: 06/13/2023]
Abstract
Dissolution dynamic nuclear polarisation (dDNP) of 13 C-labelled pyruvate in magnetic resonance spectroscopy/imaging (MRS/MRSI) has the potential for monitoring tumour progression and treatment response. Pyruvate delivery, its metabolism to lactate and efflux were investigated in rat P22 sarcomas following simultaneous intravenous administration of hyperpolarised 13 C-labelled pyruvate (13 C1 -pyruvate) and urea (13 C-urea), a nonmetabolised marker. A general mathematical model of pyruvate-lactate exchange, incorporating an arterial input function (AIF), enabled the losses of pyruvate and lactate from tumour to be estimated, in addition to the clearance rate of pyruvate signal from blood into tumour, Kip , and the forward and reverse fractional rate constants for pyruvate-lactate signal exchange, kpl and klp . An analogous model was developed for urea, enabling estimation of urea tumour losses and the blood clearance parameter, Kiu . A spectral fitting procedure to blood time-course data proved superior to assuming a gamma-variate form for the AIFs. Mean arterial blood pressure marginally correlated with clearance rates. Kiu equalled Kip , indicating equivalent permeability of the tumour vasculature to urea and pyruvate. Fractional loss rate constants due to effluxes of pyruvate, lactate and urea from tumour tissue into blood (kpo , klo and kuo , respectively) indicated that T1 s and the average flip angle, θ, obtained from arterial blood were poor surrogates for these parameters in tumour tissue. A precursor-product model, using the tumour pyruvate signal time-course as the input for the corresponding lactate signal time-course, was modified to account for the observed delay between them. The corresponding fractional rate constant, kavail , most likely reflected heterogeneous tumour microcirculation. Loss parameters, estimated from this model with different TRs, provided a lower limit on the estimates of tumour T1 for lactate and urea. The results do not support use of hyperpolarised urea for providing information on the tumour microcirculation over and above what can be obtained from pyruvate alone. The results also highlight the need for rigorous processes controlling signal quantitation, if absolute estimations of biological parameters are required.
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Affiliation(s)
- Steven Reynolds
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK
| | - Samira M Kazan
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK
| | - Adriana Anton
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK
| | - Tooba Alizadeh
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK
| | - Roger N Gunn
- Department of Brain Sciences, Imperial College London, London, UK
| | - Martyn N Paley
- Academic Unit of Radiology, Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, UK
| | - Gillian M Tozer
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK
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30
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Initial Experience on Hyperpolarized [1-13C]Pyruvate MRI Multicenter Reproducibility—Are Multicenter Trials Feasible? Tomography 2022; 8:585-595. [PMID: 35314625 PMCID: PMC8938827 DOI: 10.3390/tomography8020048] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 12/31/2022] Open
Abstract
Background: Magnetic resonance imaging (MRI) with hyperpolarized [1-13C]pyruvate allows real-time and pathway specific clinical detection of otherwise unimageable in vivo metabolism. However, the comparability between sites and protocols is unknown. Here, we provide initial experiences on the agreement of hyperpolarized MRI between sites and protocols by repeated imaging of same healthy volunteers in Europe and the US. Methods: Three healthy volunteers traveled for repeated multicenter brain MRI exams with hyperpolarized [1-13C]pyruvate within one year. First, multisite agreement was assessed with the same echo-planar imaging protocol at both sites. Then, this was compared to a variable resolution echo-planar imaging protocol. In total, 12 examinations were performed. Common metrics of 13C-pyruvate to 13C-lactate conversion were calculated, including the kPL, a model-based kinetic rate constant, and its model-free equivalents. Repeatability was evaluated with intraclass correlation coefficients (ICC) for absolute agreement computed using two-way random effects models. Results: The mean kPL across all examinations in the multisite comparison was 0.024 ± 0.0016 s−1. The ICC of the kPL was 0.83 (p = 0.14) between sites and 0.7 (p = 0.09) between examinations of the same volunteer at any of the two sites. For the model-free metrics, the lactate Z-score had similar site-to-site ICC, while it was considerably lower for the lactate-to-pyruvate ratio. Conclusions: Estimation of metabolic conversion from hyperpolarized [1-13C]pyruvate to lactate using model-based metrics such as kPL suggests close agreement between sites and examinations in volunteers. Our initial results support harmonization of protocols, support multicenter studies, and inform their design.
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31
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Ma J, Pinho MC, Harrison CE, Chen J, Sun C, Hackett EP, Liticker J, Ratnakar J, Reed GD, Chen AP, Sherry AD, Malloy CR, Wright SM, Madden CJ, Park JM. Dynamic 13 C MR spectroscopy as an alternative to imaging for assessing cerebral metabolism using hyperpolarized pyruvate in humans. Magn Reson Med 2022; 87:1136-1149. [PMID: 34687086 PMCID: PMC8776582 DOI: 10.1002/mrm.29049] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/01/2021] [Accepted: 09/29/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE This study is to investigate time-resolved 13 C MR spectroscopy (MRS) as an alternative to imaging for assessing pyruvate metabolism using hyperpolarized (HP) [1-13 C]pyruvate in the human brain. METHODS Time-resolved 13 C spectra were acquired from four axial brain slices of healthy human participants (n = 4) after a bolus injection of HP [1-13 C]pyruvate. 13 C MRS with low flip-angle excitations and a multichannel 13 C/1 H dual-frequency radiofrequency (RF) coil were exploited for reliable and unperturbed assessment of HP pyruvate metabolism. Slice-wise areas under the curve (AUCs) of 13 C-metabolites were measured and kinetic analysis was performed to estimate the production rates of lactate and HCO3- . Linear regression analysis between brain volumes and HP signals was performed. Region-focused pyruvate metabolism was estimated using coil-wise 13 C reconstruction. Reproducibility of HP pyruvate exams was presented by performing two consecutive injections with a 45-minutes interval. RESULTS [1-13 C]Lactate relative to the total 13 C signal (tC) was 0.21-0.24 in all slices. [13 C] HCO3- /tC was 0.065-0.091. Apparent conversion rate constants from pyruvate to lactate and HCO3- were calculated as 0.014-0.018 s-1 and 0.0043-0.0056 s-1 , respectively. Pyruvate/tC and lactate/tC were in moderate linear relationships with fractional gray matter volume within each slice. White matter presented poor linear regression fit with HP signals, and moderate correlations of the fractional cerebrospinal fluid volume with pyruvate/tC and lactate/tC were measured. Measured HP signals were comparable between two consecutive exams with HP [1-13 C]pyruvate. CONCLUSIONS Dynamic MRS in combination with multichannel RF coils is an affordable and reliable alternative to imaging methods in investigating cerebral metabolism using HP [1-13 C]pyruvate.
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Affiliation(s)
- Junjie Ma
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marco C. Pinho
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Crystal E. Harrison
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jun Chen
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Chenhao Sun
- Department of Electrical and Computer Engineering, Texas A & M, College Station, TX, USA
| | - Edward P. Hackett
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jeff Liticker
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Ratnakar
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | | | - A. Dean Sherry
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Biochemistry and Chemical Biology, University of Texas Dallas, Richardson, TX, USA
| | - Craig R. Malloy
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Steven M. Wright
- Department of Electrical and Computer Engineering, Texas A & M, College Station, TX, USA
| | - Christopher J. Madden
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jae Mo Park
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Electrical and Computer Engineering, University of Texas Dallas, Richardson, TX, USA,Correspondence to: Jae Mo Park, Ph.D., 5323 Harry Hines Blvd. Dallas, Texas 75390-8568, , Tel: +1-214-645-7206, Fax: +1-214-645-2744
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32
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Tomiyasu M, Harada M. In vivo Human MR Spectroscopy Using a Clinical Scanner: Development, Applications, and Future Prospects. Magn Reson Med Sci 2022; 21:235-252. [PMID: 35173095 PMCID: PMC9199975 DOI: 10.2463/mrms.rev.2021-0085] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
MR spectroscopy (MRS) is a unique and useful method for noninvasively evaluating biochemical metabolism in human organs and tissues, but its clinical dissemination has been slow and often limited to specialized institutions or hospitals with experts in MRS technology. The number of 3-T clinical MR scanners is now increasing, representing a major opportunity to promote the use of clinical MRS. In this review, we summarize the theoretical background and basic knowledge required to understand the results obtained with MRS and introduce the general consensus on the clinical utility of proton MRS in routine clinical practice. In addition, we present updates to the consensus guidelines on proton MRS published by the members of a working committee of the Japan Society of Magnetic Resonance in Medicine in 2013. Recent research into multinuclear MRS equipped in clinical MR scanners is explained with an eye toward future development. This article seeks to provide an overview of the current status of clinical MRS and to promote the understanding of when it can be useful. In the coming years, MRS-mediated biochemical evaluation is expected to become available for even routine clinical practice.
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Affiliation(s)
- Moyoko Tomiyasu
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology.,Department of Radiology, Kanagawa Children's Medical Center
| | - Masafumi Harada
- Department of Radiology and Radiation Oncology, Graduate School of Biomedical Sciences, Tokushima University
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33
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Hyppönen V, Stenroos P, Nivajärvi R, Ardenkjaer-Larsen JH, Gröhn O, Paasonen J, Kettunen MI. Metabolism of hyperpolarised [1- 13 C]pyruvate in awake and anaesthetised rat brains. NMR IN BIOMEDICINE 2022; 35:e4635. [PMID: 34672399 DOI: 10.1002/nbm.4635] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 09/16/2021] [Accepted: 09/26/2021] [Indexed: 06/13/2023]
Abstract
The use of hyperpolarised 13 C pyruvate for nononcological neurological applications has not been widespread so far, possibly due to delivery issues limiting the visibility of metabolites. First proof-of-concept results have indicated that metabolism can be detected in human brain, and this may supersede the results obtained in preclinical settings. One major difference between the experimental setups is that preclinical MRI/MRS routinely uses anaesthesia, which alters both haemodynamics and metabolism. Here, we used hyperpolarised [1-13 C]pyruvate to compare brain metabolism in awake rats and under isoflurane, urethane or medetomidine anaesthesia. Spectroscopic [1-13 C]pyruvate time courses measured sequentially showed that pyruvate-to-bicarbonate and pyruvate-to-lactate labelling rates were lower in isoflurane animals than awake animals. An increased bicarbonate-to-lactate ratio was observed in the medetomidine group compared with other groups. The study shows that hyperpolarised [1-13 C]pyruvate experiments can be performed in awake rats, thus avoiding anaesthesia-related issues. The results suggest that haemodynamics probably dominate the observed pyruvate-to-metabolite labelling rates and area-under-time course ratios of referenced to pyruvate. On the other hand, the results obtained with medetomidine suggest that the ratios are also modulated by the underlying cerebral metabolism. However, the ratios between intracellular metabolites were unchanged in awake compared with isoflurane-anaesthetised rats.
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Affiliation(s)
- Viivi Hyppönen
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Petteri Stenroos
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Riikka Nivajärvi
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jan Henrik Ardenkjaer-Larsen
- Center for Hyperpolarization in Magnetic Resonance, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Olli Gröhn
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Paasonen
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mikko I Kettunen
- Kuopio Biomedical Imaging Unit, A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
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34
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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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Lee SJ, Park I, Talbott JF, Gordon J. Investigating the Feasibility of In Vivo Perfusion Imaging Methods for Spinal Cord Using Hyperpolarized [ 13C]t-Butanol and [ 13C, 15N 2]Urea. Mol Imaging Biol 2021; 24:371-376. [PMID: 34779970 DOI: 10.1007/s11307-021-01682-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/30/2021] [Accepted: 11/02/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE This study examined the feasibility of using two novel agents, hyperpolarized [13C]t-butanol and [13C,15N2]urea, for assessing in vivo perfusion of the intact spinal cord in rodents. Due to their distinct permeabilities to blood brain barrier (BBB), we hypothesized that [13C]t-butanol and [13C,15N2]urea exhibit unique 13C signal characteristics in the spinal cord. PROCEDURES Dynamic 13C t-butanol MRI data were acquired from healthy Long-Evans rats using a symmetric, ramp-sampled, partial-Fourier 13C echo-planar imaging sequence after the injection of hyperpolarized [13C]t-butanol solution. In subsequent scans, dynamic 13C urea MRI data were acquired after the injection of hyperpolarized [13C,15N2]urea. The SNRs of t-butanol and urea were calculated for regions corresponding to spine, supratentorial brain, and blood vessels and plotted over time. Mean peak SNR and AUC were calculated from the dynamic plots for each region and compared between t-butanol and urea. RESULTS In spine and supratentorial brain, the mean peak SNR and AUC of t-butanol were significantly higher than those of urea (p < 0.05). In contrast, urea was predominantly contained within vasculature and exhibited significantly higher levels of mean peak SNR and AUC compared to t-butanol in blood vessels (p < 0.05). CONCLUSION This study has demonstrated the feasibility of using hyperpolarized [13C]t-butanol and [13C,15N2]urea for assessing in vivo perfusion in cervical spinal cord. Due to differences in blood-brain barrier permeability, t-butanol rapidly crossed the blood-brain barrier and diffused into spine and brain tissue, while urea predominantly remained in vasculature. The results from this study suggest that this technique may provide unique non-invasive imaging tracers that are able to directly monitor hemodynamic processes in the normal and injured spinal cord.
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Affiliation(s)
- Seung Jin Lee
- Department of Radiology, Chonnam National University Hospital, 42 Jaebongro, Donggu, Gwangju, 61469, South Korea
| | - Ilwoo Park
- Department of Radiology, Chonnam National University Hospital, 42 Jaebongro, Donggu, Gwangju, 61469, South Korea. .,Department of Radiology, Chonnam National University, 42 Jaebongro, Donggu, Gwangju, 61469, South Korea. .,Department of Artificial Intelligence Convergence, Chonnam National University, 77 Yongbongro, Bukgu, Gwangju, 61186, South Korea.
| | - Jason F Talbott
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143, USA.,Brain and Spine Injury Center (BASIC), San Francisco General Hospital, University of California, San Francisco, CA, 94110, USA
| | - Jeremy Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143, USA
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Fiedorowicz M, Wieteska M, Rylewicz K, Kossowski B, Piątkowska-Janko E, Czarnecka AM, Toczylowska B, Bogorodzki P. Hyperpolarized 13C tracers: Technical advancements and perspectives for clinical applications. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2021.03.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Salzillo TC, Mawoneke V, Weygand J, Shetty A, Gumin J, Zacharias NM, Gammon ST, Piwnica-Worms D, Fuller GN, Logothetis CJ, Lang FF, Bhattacharya PK. Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance. Cells 2021; 10:cells10102621. [PMID: 34685601 PMCID: PMC8534002 DOI: 10.3390/cells10102621] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/20/2021] [Accepted: 09/23/2021] [Indexed: 12/23/2022] Open
Abstract
Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research.
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Affiliation(s)
- Travis C. Salzillo
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Vimbai Mawoneke
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Joseph Weygand
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Akaanksh Shetty
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Joy Gumin
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (J.G.); (F.F.L.)
| | - Niki M. Zacharias
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Seth T. Gammon
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - David Piwnica-Worms
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Gregory N. Fuller
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Christopher J. Logothetis
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Frederick F. Lang
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (J.G.); (F.F.L.)
| | - Pratip K. Bhattacharya
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
- Correspondence: ; Tel.: +1-713-454-9887
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Editorial commentary for the special issue: technological developments in hyperpolarized 13C imaging-toward a deeper understanding of tumor metabolism in vivo. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:1-3. [PMID: 33580833 PMCID: PMC7910238 DOI: 10.1007/s10334-021-00908-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Zaccagna F, Grist JT, Quartuccio N, Riemer F, Fraioli F, Caracò C, Halsey R, Aldalilah Y, Cunningham CH, Massoud TF, Aloj L, Gallagher FA. Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances. Eur J Radiol 2021; 142:109842. [PMID: 34274843 DOI: 10.1016/j.ejrad.2021.109842] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.
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Affiliation(s)
- Fulvio Zaccagna
- Division of Neuroimaging, Department of Medical Imaging, University of Toronto, Toronto, Canada.
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom; Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, United Kingdom; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Palermo, Italy
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, University of Bergen, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Corradina Caracò
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Richard Halsey
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Yazeed Aldalilah
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom; Department of Radiology, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Tarik F Massoud
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, USA
| | - Luigi Aloj
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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Li Y, Vigneron DB, Xu D. Current human brain applications and challenges of dynamic hyperpolarized carbon-13 labeled pyruvate MR metabolic imaging. Eur J Nucl Med Mol Imaging 2021; 48:4225-4235. [PMID: 34432118 PMCID: PMC8566394 DOI: 10.1007/s00259-021-05508-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 07/27/2021] [Indexed: 12/17/2022]
Abstract
The ability of hyperpolarized carbon-13 MR metabolic imaging to acquire dynamic metabolic information in real time is crucial to gain mechanistic insights into metabolic pathways, which are complementary to anatomic and other functional imaging methods. This review presents the advantages of this emerging functional imaging technology, describes considerations in clinical translations, and summarizes current human brain applications. Despite rapid development in methodologies, significant technological and physiological related challenges continue to impede broader clinical translation.
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Affiliation(s)
- Yan Li
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA.
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA
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Hackett EP, Shah BR, Cheng B, LaGue E, Vemireddy V, Mendoza M, Bing C, Bachoo RM, Billingsley KL, Chopra R, Park JM. Probing Cerebral Metabolism with Hyperpolarized 13C Imaging after Opening the Blood-Brain Barrier with Focused Ultrasound. ACS Chem Neurosci 2021; 12:2820-2828. [PMID: 34291630 DOI: 10.1021/acschemneuro.1c00197] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Transient disruption of the blood-brain barrier (BBB) with focused ultrasound (FUS) is an emerging clinical method to facilitate targeted drug delivery to the brain. The focal noninvasive disruption of the BBB can be applied to promote the local delivery of hyperpolarized substrates. In this study, we investigated the effects of FUS on imaging brain metabolism using two hyperpolarized 13C-labeled substrates in rodents: [1-13C]pyruvate and [1-13C]glycerate. The BBB is a rate-limiting factor for pyruvate delivery to the brain, and glycerate minimally passes through the BBB. First, cerebral imaging with hyperpolarized [1-13C]pyruvate resulted in an increase in total 13C signals (p = 0.05) after disrupting the BBB with FUS. Significantly higher levels of both [1-13C]lactate (lactate/total 13C signals, p = 0.01) and [13C]bicarbonate (p = 0.008) were detected in the FUS-applied brain region as compared to the contralateral FUS-unaffected normal-appearing brain region. The application of FUS without opening the BBB in a separate group of rodents resulted in comparable lactate and bicarbonate productions between the FUS-applied and the contralateral brain regions. Second, 13C imaging with hyperpolarized [1-13C]glycerate after opening the BBB showed increased [1-13C]glycerate delivery to the FUS-applied region (p = 0.04) relative to the contralateral side, and [1-13C]lactate production was consistently detected from the FUS-applied region. Our findings suggest that FUS accelerates the delivery of hyperpolarized molecules across the BBB and provides enhanced sensitivity to detect metabolic products in the brain; therefore, hyperpolarized 13C imaging with FUS may provide new opportunities to study cerebral metabolic pathways as well as various neurological pathologies.
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Affiliation(s)
- Edward P. Hackett
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Bhavya R. Shah
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Bingbing Cheng
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Department of Radiology, The University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Evan LaGue
- Department of Chemistry and Biochemistry, California State University, Fullerton, Fullerton, California 92834, United States
| | - Vamsidihara Vemireddy
- Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Manuel Mendoza
- Department of Chemistry and Biochemistry, California State University, Fullerton, Fullerton, California 92834, United States
| | - Chenchen Bing
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Department of Radiology, The University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Robert M. Bachoo
- Department of Neurology and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Harold C. Simmons Comprehensive Cancer Center, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Kelvin L. Billingsley
- Department of Chemistry and Biochemistry, California State University, Fullerton, Fullerton, California 92834, United States
| | - Rajiv Chopra
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Jae Mo Park
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390, United States
- Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, Texas 75080, United States
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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: 4] [Impact Index Per Article: 1.3] [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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Characterization of Distinctive In Vivo Metabolism between Enhancing and Non-Enhancing Gliomas Using Hyperpolarized Carbon-13 MRI. Metabolites 2021; 11:metabo11080504. [PMID: 34436445 PMCID: PMC8398100 DOI: 10.3390/metabo11080504] [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: 06/29/2021] [Revised: 07/26/2021] [Accepted: 07/28/2021] [Indexed: 11/17/2022] Open
Abstract
The development of hyperpolarized carbon-13 (13C) metabolic MRI has enabled the sensitive and noninvasive assessment of real-time in vivo metabolism in tumors. Although several studies have explored the feasibility of using hyperpolarized 13C metabolic imaging for neuro-oncology applications, most of these studies utilized high-grade enhancing tumors, and little is known about hyperpolarized 13C metabolic features of a non-enhancing tumor. In this study, 13C MR spectroscopic imaging with hyperpolarized [1-13C]pyruvate was applied for the differential characterization of metabolic profiles between enhancing and non-enhancing gliomas using rodent models of glioblastoma and a diffuse midline glioma. Distinct metabolic profiles were found between the enhancing and non-enhancing tumors, as well as their contralateral normal-appearing brain tissues. The preliminary results from this study suggest that the characterization of metabolic patterns from hyperpolarized 13C imaging between non-enhancing and enhancing tumors may be beneficial not only for understanding distinct metabolic features between the two lesions, but also for providing a basis for understanding 13C metabolic processes in ongoing clinical trials with neuro-oncology patients using this technology.
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Harlan CJ, Xu Z, Walker CM, Michel KA, Reed GD, Bankson JA. The effect of transmit B 1 inhomogeneity on hyperpolarized [1- 13 C]-pyruvate metabolic MR imaging biomarkers. Med Phys 2021; 48:4900-4908. [PMID: 34287945 DOI: 10.1002/mp.15107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 07/13/2021] [Accepted: 07/13/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE A specialized Helmholtz-style 13 C volume transmit "clamshell" coil is currently being utilized for 13 C excitation in pre-clinical and clinical hyperpolarized 13 C MRI studies aimed at probing the metabolic activity of tumors in various target anatomy. Due to the widespread use of this 13 C clamshell coil design, it is important that the effects of the 13 C clamshell coil B1 + profile on HP signal evolution and quantification are well understood. The goal of this study was to characterize the B1 + field of the 13 C clamshell coil and assess the impact of inhomogeneities on semi-quantitative and quantitative hyperpolarized MR imaging biomarkers of metabolism. METHODS The B1 + field of the 13 C clamshell coil was mapped by hand using a network analyzer equipped with an S-parameter test set. Pharmacokinetic models were used to simulate signal evolution as a function of position-dependent local excitation angles, for various nominal excitation angles, which were assumed to be accurately calibrated at the isocenter. These signals were then quantified according to the normalized lactate ratio (nLac) and the apparent rate constant for the conversion of pyruvate to lactate (kPL ). The percent difference between these metabolic imaging biomarker maps and the reference value observed at the isocenter of the clamshell coil was calculated to estimate the potential for error due to position within the clamshell coil. Finally, regions were identified within the clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the value at the isocenter. RESULTS The B1 + field maps show that a limited volume encompassed by a region measuring approximately 12.9 × 11.5 × 13.4 cm (X-direction, Y-direction, Z-direction) centered in the 13 C clamshell coil will produce deviations in the B1 + field within ±10% of that at the isocenter. For the metabolic imaging biomarkers that we evaluated, the case when the pyruvate excitation angle (θP ) and lactate excitation angle (θL ) were equal to 10° produced the largest volumetric region with deviations within ±10% of the value at the isocenter. Higher excitation angles yielded higher signal and SNR, but the size of the region in which uniform measurements could be collected near the isocenter of the coil was reduced at higher excitation angles. The tradeoff between the size of the homogenous region at the isocenter and signal intensity must be weighed carefully depending on the particular imaging application. CONCLUSION This work identifies regions and optimal excitation angles (θP and θL ) within the 13 C clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the respective value at the isocenter, and thus where excitation angles are reproducible and well-calibrated. Semi-quantitative and quantitative metabolic imaging biomarkers can vary with position in the clamshell coil as a result of B1 + field inhomogeneity, necessitating care in patient positioning and the selection of an excitation angle set that balances reproducibility and SNR performance over the target imaging volume.
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Affiliation(s)
- Collin J Harlan
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Christopher M Walker
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Keith A Michel
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | | | - James A Bankson
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.,The University of Texas M.D. Anderson Cancer Center, UT Health Graduate School of Biomedical Sciences, Houston, TX, USA
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Lee PM, Chen HY, Gordon JW, Zhu Z, Larson PEZ, Dwork N, Van Criekinge M, Carvajal L, Ohliger MA, Wang ZJ, Xu D, Kurhanewicz J, Bok RA, Aggarwal R, Munster PN, Vigneron DB. Specialized computational methods for denoising, B 1 correction, and kinetic modeling in hyperpolarized 13 C MR EPSI studies of liver tumors. Magn Reson Med 2021; 86:2402-2411. [PMID: 34216051 DOI: 10.1002/mrm.28901] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 05/14/2021] [Accepted: 06/03/2021] [Indexed: 01/10/2023]
Abstract
PURPOSE To develop a novel post-processing pipeline for hyperpolarized (HP) 13 C MRSI that integrates tensor denoising and B 1 + correction to measure pyruvate-to-lactate conversion rates (kPL ) in patients with liver tumors. METHODS Seven HP 13 C MR scans of progressing liver tumors were acquired using a custom 13 C surface transmit/receive coil and the echo-planar spectroscopic imaging (EPSI) data analysis included B0 correction, tensor rank truncation, and zero- and first-order phase corrections to recover metabolite signals that would otherwise be obscured by spectral noise as well as a correction for inhomogeneous transmit ( B 1 + ) using a B 1 + map aligned to the coil position for each patient scan. Processed HP data and corrected flip angles were analyzed with an inputless two-site exchange model to calculate kPL . RESULTS Denoising averages SNR increases of pyruvate, lactate, and alanine were 37.4-, 34.0-, and 20.1-fold, respectively, with lactate and alanine dynamics most noticeably recovered and better defined. In agreement with Monte Carlo simulations, over-flipped regions underestimated kPL and under-flipped regions overestimated kPL . B 1 + correction addressed this issue. CONCLUSION The new HP 13 C EPSI post-processing pipeline integrated tensor denoising and B 1 + correction to measure kPL in patients with liver tumors. These technical developments not only recovered metabolite signals in voxels that did not receive the prescribed flip angle, but also increased the extent and accuracy of kPL estimations throughout the tumor and adjacent regions including normal-appearing tissue and additional lesions.
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Affiliation(s)
- Philip M Lee
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Zihan Zhu
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Peder E Z Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas Dwork
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Mark Van Criekinge
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Michael A Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Duan Xu
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - John Kurhanewicz
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Rahul Aggarwal
- Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Pamela N Munster
- Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Daniel B Vigneron
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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46
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Shaul D, Grieb B, Sapir G, Uppala S, Sosna J, Gomori JM, Katz-Brull R. The metabolic representation of ischemia in rat brain slices: A hyperpolarized 13 C magnetic resonance study. NMR IN BIOMEDICINE 2021; 34:e4509. [PMID: 33774865 DOI: 10.1002/nbm.4509] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 02/15/2021] [Accepted: 02/26/2021] [Indexed: 06/12/2023]
Abstract
The ischemic penumbra in stroke is not clearly defined by today's available imaging tools. This study aimed to develop a model system and noninvasive biomarkers of ischemic brain tissue for an examination that might potentially be performed in humans, very quickly, in the course of stroke triage. Perfused rat brain slices were used as a model system and 31 P spectroscopy verified that the slices were able to recover from an ischemic insult of about 3.5 min of perfusion arrest. This was indicated as a return to physiological pH and adenosine triphosphate levels. Instantaneous changes in lactate dehydrogenase (LDH) and pyruvate dehydrogenase (PDH) activities were monitored and quantified by the metabolic conversions of hyperpolarized [1-13 C]pyruvate to [1-13 C]lactate and [13 C]bicarbonate, respectively, using 13 C spectroscopy. In a control group (n = 8), hyperpolarized [1-13 C]pyruvate was administered during continuous perfusion of the slices. In the ischemia group (n = 5), the perfusion was arrested 30 s prior to administration of hyperpolarized [1-13 C]pyruvate and perfusion was not resumed throughout the measurement time (approximately 3.5 min). Following about 110 s of the ischemic insult, LDH activity increased by 80.4 ± 13.5% and PDH activity decreased by 47.8 ± 25.3%. In the control group, the mean LDH/PDH ratio was 16.6 ± 3.3, and in the ischemia group, the LDH/PDH ratio reached an average value of 38.7 ± 16.9. The results suggest that monitoring the activity of LDH and PDH, and their relative activities, using hyperpolarized [1-13 C]pyruvate, could serve as an imaging biomarker to characterize the changes in the ischemic penumbra.
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Affiliation(s)
- David Shaul
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Benjamin Grieb
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
- Department of Psychiatry and Psychotherapy I (Weissenau), Ulm University, Ravensburg, Germany
| | - Gal Sapir
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Sivaranjan Uppala
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Jacob Sosna
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - J Moshe Gomori
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
| | - Rachel Katz-Brull
- Department of Radiology, Hadassah Medical Center, Hebrew University of Jerusalem, The Faculty of Medicine, Jerusalem, Israel
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47
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Rao Y, Gammon ST, Sutton MN, Zacharias NM, Bhattacharya P, Piwnica-Worms D. Excess exogenous pyruvate inhibits lactate dehydrogenase activity in live cells in an MCT1-dependent manner. J Biol Chem 2021; 297:100775. [PMID: 34022218 PMCID: PMC8233206 DOI: 10.1016/j.jbc.2021.100775] [Citation(s) in RCA: 18] [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: 10/28/2020] [Revised: 04/27/2021] [Accepted: 05/11/2021] [Indexed: 12/21/2022] Open
Abstract
Cellular pyruvate is an essential metabolite at the crossroads of glycolysis and oxidative phosphorylation, capable of supporting fermentative glycolysis by reduction to lactate mediated by lactate dehydrogenase (LDH) among other functions. Several inherited diseases of mitochondrial metabolism impact extracellular (plasma) pyruvate concentrations, and [1-13C]pyruvate infusion is used in isotope-labeled metabolic tracing studies, including hyperpolarized magnetic resonance spectroscopic imaging. However, how these extracellular pyruvate sources impact intracellular metabolism is not clear. Herein, we examined the effects of excess exogenous pyruvate on intracellular LDH activity, extracellular acidification rates (ECARs) as a measure of lactate production, and hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates across a panel of tumor and normal cells. Combined LDH activity and LDHB/LDHA expression analysis intimated various heterotetrameric isoforms comprising LDHA and LDHB in tumor cells, not only canonical LDHA. Millimolar concentrations of exogenous pyruvate induced substrate inhibition of LDH activity in both enzymatic assays ex vivo and in live cells, abrogated glycolytic ECAR, and inhibited hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in cellulo. Of importance, the extent of exogenous pyruvate-induced inhibition of LDH and glycolytic ECAR in live cells was highly dependent on pyruvate influx, functionally mediated by monocarboxylate transporter-1 localized to the plasma membrane. These data provided evidence that highly concentrated bolus injections of pyruvate in vivo may transiently inhibit LDH activity in a tissue type- and monocarboxylate transporter-1-dependent manner. Maintaining plasma pyruvate at submillimolar concentrations could potentially minimize transient metabolic perturbations, improve pyruvate therapy, and enhance quantification of metabolic studies, including hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging and stable isotope tracer experiments.
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Affiliation(s)
- Yi Rao
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Seth T Gammon
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Margie N Sutton
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Niki M Zacharias
- Department of Urology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Pratip Bhattacharya
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - David Piwnica-Worms
- Department of Cancer System Imaging, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA.
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48
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Kim Y, Chen HY, Autry AW, Villanueva-Meyer J, Chang SM, Li Y, Larson PEZ, Brender JR, Krishna MC, Xu D, Vigneron DB, Gordon JW. Denoising of hyperpolarized 13 C MR images of the human brain using patch-based higher-order singular value decomposition. Magn Reson Med 2021; 86:2497-2511. [PMID: 34173268 DOI: 10.1002/mrm.28887] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/23/2021] [Accepted: 05/20/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE To improve hyperpolarized 13 C (HP-13 C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD). METHODS The benefit of using a patch-based HOSVD method to denoise dynamic HP-13 C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1-13 C]pyruvate and its metabolic product, [1-13 C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1-13 C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error. RESULTS Simulation results demonstrated an 8-fold increase in the calculated SNR of [1-13 C]pyruvate and [1-13 C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of kPL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted kPL after denoising. The patch-based denoising performed superior to the global denoising in recovering kPL information. In volunteer data sets, [1-13 C]lactate and [13 C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping kPB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping kPL . CONCLUSIONS Sensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research.
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Affiliation(s)
- Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Javier Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeffrey R Brender
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Murali C Krishna
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.,Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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49
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Non-Invasive Differentiation of M1 and M2 Activation in Macrophages Using Hyperpolarized 13C MRS of Pyruvate and DHA at 1.47 Tesla. Metabolites 2021; 11:metabo11070410. [PMID: 34206326 PMCID: PMC8305442 DOI: 10.3390/metabo11070410] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 01/09/2023] Open
Abstract
Macrophage activation, first generalized to the M1/M2 dichotomy, is a complex and central process of the innate immune response. Simply, M1 describes the classical proinflammatory activation, leading to tissue damage, and M2 the alternative activation promoting tissue repair. Given the central role of macrophages in multiple diseases, the ability to noninvasively differentiate between M1 and M2 activation states would be highly valuable for monitoring disease progression and therapeutic responses. Since M1/M2 activation patterns are associated with differential metabolic reprogramming, we hypothesized that hyperpolarized 13C magnetic resonance spectroscopy (HP 13C MRS), an innovative metabolic imaging approach, could distinguish between macrophage activation states noninvasively. The metabolic conversions of HP [1-13C]pyruvate to HP [1-13C]lactate, and HP [1-13C]dehydroascorbic acid to HP [1-13C]ascorbic acid were monitored in live M1 and M2 activated J774a.1 macrophages noninvasively by HP 13C MRS on a 1.47 Tesla NMR system. Our results show that both metabolic conversions were significantly increased in M1 macrophages compared to M2 and nonactivated cells. Biochemical assays and high resolution 1H MRS were also performed to investigate the underlying changes in enzymatic activities and metabolite levels linked to M1/M2 activation. Altogether, our results demonstrate the potential of HP 13C MRS for monitoring macrophage activation states noninvasively.
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50
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Larson PEZ, Gordon JW. Hyperpolarized Metabolic MRI-Acquisition, Reconstruction, and Analysis Methods. Metabolites 2021; 11:386. [PMID: 34198574 PMCID: PMC8231874 DOI: 10.3390/metabo11060386] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/05/2021] [Accepted: 06/08/2021] [Indexed: 01/05/2023] Open
Abstract
Hyperpolarized metabolic MRI with 13C-labeled agents has emerged as a powerful technique for in vivo assessments of real-time metabolism that can be used across scales of cells, tissue slices, animal models, and human subjects. Hyperpolarized contrast agents have unique properties compared to conventional MRI scanning and MRI contrast agents that require specialized imaging methods. Hyperpolarized contrast agents have a limited amount of available signal, irreversible decay back to thermal equilibrium, bolus injection and perfusion kinetics, cellular uptake and metabolic conversion kinetics, and frequency shifts between metabolites. This article describes state-of-the-art methods for hyperpolarized metabolic MRI, summarizing data acquisition, reconstruction, and analysis methods in order to guide the design and execution of studies.
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Affiliation(s)
- Peder Eric Zufall Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA;
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA 94143, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, CA 94143, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA;
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