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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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Nickles TM, Kim Y, Lee PM, Chen HY, Ohliger M, Bok RA, Wang ZJ, Larson PEZ, Vigneron DB, Gordon JW. Hyperpolarized 13 C metabolic imaging of the human abdomen with spatiotemporal denoising. Magn Reson Med 2024; 91:2153-2161. [PMID: 38193310 PMCID: PMC10950515 DOI: 10.1002/mrm.29985] [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: 07/14/2023] [Revised: 10/27/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach. METHODS Denoising performance was first evaluated using the simulated [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients). RESULTS The parameterization of kglobal = 0.2 and klocal = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (conversion rate of pyruvate-to-metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground-truth metabolic conversion rates when there is adequate SNR (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5-fold increase in the number of voxels reliably fit across abdominal FOVs for kPL and kPA quantification maps. CONCLUSION Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen.
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Affiliation(s)
- Tanner M Nickles
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Yaewon Kim
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Philip M Lee
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Michael Ohliger
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Robert A Bok
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
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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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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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Christensen NV, Vaeggemose M, Bøgh N, Hansen ESS, Olesen JL, Kim Y, Vigneron DB, Gordon JW, Jespersen SN, Laustsen C. A user independent denoising method for x-nuclei MRI and MRS. Magn Reson Med 2023; 90:2539-2556. [PMID: 37526128 DOI: 10.1002/mrm.29817] [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: 06/02/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 08/02/2023]
Abstract
PURPOSE X-nuclei (also called non-proton MRI) MRI and spectroscopy are limited by the intrinsic low SNR as compared to conventional proton imaging. Clinical translation of x-nuclei examination warrants the need of a robust and versatile tool improving image quality for diagnostic use. In this work, we compare a novel denoising method with fewer inputs to the current state-of-the-art denoising method. METHODS Denoising approaches were compared on human acquisitions of sodium (23 Na) brain, deuterium (2 H) brain, carbon (13 C) heart and brain, and simulated dynamic hyperpolarized 13 C brain scans, with and without additional noise. The current state-of-the-art denoising method Global-local higher order singular value decomposition (GL-HOSVD) was compared to the few-input method tensor Marchenko-Pastur principal component analysis (tMPPCA). Noise-removal was quantified by residual distributions, and statistical analyses evaluated the differences in mean-square-error and Bland-Altman analysis to quantify agreement between original and denoised results of noise-added data. RESULTS GL-HOSVD and tMPPCA showed similar performance for the variety of x-nuclei data analyzed in this work, with tMPPCA removing ˜5% more noise on average over GL-HOSVD. The mean ratio between noise-added and denoising reproducibility coefficients of the Bland-Altman analysis when compared to the original are also similar for the two methods with 3.09 ± 1.03 and 2.83 ± 0.79 for GL-HOSVD and tMPPCA, respectively. CONCLUSION The strength of tMPPCA lies in the few-input approach, which generalizes well to different data sources. This makes the use of tMPPCA denoising a robust and versatile tool in x-nuclei imaging improvements and the preferred denoising method.
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Affiliation(s)
| | - Michael Vaeggemose
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- GE Healthcare, Brøndby, Denmark
| | - Nikolaj Bøgh
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- A&E, Gødstrup Hospital, Herning, Denmark
| | - Esben S S Hansen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jonas L Olesen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco (UCSF), San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco (UCSF), San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco (UCSF), San Francisco, California, USA
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Christoffer Laustsen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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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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7
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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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Brender JR, Assmann JC, Farthing DE, Saito K, Kishimoto S, Warrick KA, Maglakelidze N, Larus TL, Merkle H, Gress RE, Krishna MC, Buxbaum NP. In vivo deuterium magnetic resonance imaging of xenografted tumors following systemic administration of deuterated water. Sci Rep 2023; 13:14699. [PMID: 37679461 PMCID: PMC10485001 DOI: 10.1038/s41598-023-41163-9] [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: 04/20/2023] [Accepted: 08/23/2023] [Indexed: 09/09/2023] Open
Abstract
In vivo deuterated water (2H2O) labeling leads to deuterium (2H) incorporation into biomolecules of proliferating cells and provides the basis for its use in cell kinetics research. We hypothesized that rapidly proliferating cancer cells would become preferentially labeled with 2H and, therefore, could be visualized by deuterium magnetic resonance imaging (dMRI) following a brief period of in vivo systemic 2H2O administration. We initiated systemic 2H2O administration in two xenograft mouse models harboring either human colorectal, HT-29, or pancreatic, MiaPaCa-2, tumors and 2H2O level of ~ 8% in total body water (TBW). Three schemas of 2H2O administration were tested: (1) starting at tumor seeding and continuing for 7 days of in vivo growth with imaging on day 7, (2) starting at tumor seeding and continuing for 14 days of in vivo growth with imaging on day 14, and (3) initiation of labeling following a week of in vivo tumor growth and continuing until imaging was performed on day 14. Deuterium chemical shift imaging of the tumor bearing limb and contralateral control was performed on either day 7 of 14 after tumor seeding, as described. After 14 days of in vivo tumor growth and 7 days of systemic labeling with 2H2O, a clear deuterium contrast was demonstrated between the xenografts and normal tissue. Labeling in the second week after tumor implantation afforded the highest contrast between neoplastic and healthy tissue in both models. Systemic labeling with 2H2O can be used to create imaging contrast between tumor and healthy issue, providing a non-radioactive method for in vivo cancer imaging.
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Affiliation(s)
- Jeffrey R Brender
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Julian C Assmann
- Experimental Transplantation and Immunotherapy Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Don E Farthing
- Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Keita Saito
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shun Kishimoto
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kathrynne A Warrick
- Experimental Transplantation and Immunotherapy Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Natella Maglakelidze
- Experimental Transplantation and Immunotherapy Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Terri L Larus
- Center for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hellmut Merkle
- Laboratory for Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ronald E Gress
- Experimental Transplantation and Immunotherapy Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Murali C Krishna
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nataliya P Buxbaum
- Experimental Transplantation and Immunotherapy Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
- Pediatric Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
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9
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Minami N, Hong D, Taglang C, Batsios G, Gillespie AM, Viswanath P, Stevers N, Barger CJ, Costello JF, Ronen SM. Hyperpolarized δ-[1- 13C]gluconolactone imaging visualizes response to TERT or GABPB1 targeting therapy for glioblastoma. Sci Rep 2023; 13:5190. [PMID: 36997627 PMCID: PMC10063634 DOI: 10.1038/s41598-023-32463-1] [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: 01/19/2023] [Accepted: 03/28/2023] [Indexed: 04/01/2023] Open
Abstract
TERT promoter mutations are a hallmark of glioblastoma (GBM). Accordingly, TERT and GABPB1, a subunit of the upstream mutant TERT promoter transcription factor GABP, are being considered as promising therapeutic targets in GBM. We recently reported that the expression of TERT or GABP1 modulates flux via the pentose phosphate pathway (PPP). Here, we investigated whether 13C magnetic resonance spectroscopy (MRS) of hyperpolarized (HP) δ- [1-13C]gluconolactone can serve to image the reduction in PPP flux following TERT or GABPB1 silencing. We investigated two different human GBM cell lines stably expressing shRNAs targeting TERT or GABPB1, as well as doxycycline-inducible shTERT or shGABPB1cells. MRS studies were performed on live cells and in vivo tumors, and dynamic sets of 13C MR spectra were acquired following injection of HP δ-[1-13C]gluconolactone. HP 6-phosphogluconolactone (6PG), the product of δ-[1-13C]gluconolactone via the PPP, was significantly reduced in TERT or GABPB1-silenced cells or tumors compared to controls in all our models. Furthermore, a positive correlation between TERT expression and 6PG levels was observed. Our data indicate that HP δ-[1-13C]gluconolactone, an imaging tool with translational potential, could serve to monitor TERT expression and its silencing with therapies that target either TERT or GABPB1 in mutant TERT promoter GBM patients.
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Affiliation(s)
- Noriaki Minami
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Donghyun Hong
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Celine Taglang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Georgios Batsios
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Anne Marie Gillespie
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Pavithra Viswanath
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA
| | - Nicholas Stevers
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - Carter J Barger
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - Joseph F Costello
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, San Francisco, CA, 94158, USA.
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10
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Olesen JL, Ianus A, Østergaard L, Shemesh N, Jespersen SN. Tensor denoising of multidimensional MRI data. Magn Reson Med 2023; 89:1160-1172. [PMID: 36219475 PMCID: PMC10092037 DOI: 10.1002/mrm.29478] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 08/17/2022] [Accepted: 09/15/2022] [Indexed: 02/02/2023]
Abstract
PURPOSE To develop a denoising strategy leveraging redundancy in high-dimensional data. THEORY AND METHODS The SNR fundamentally limits the information accessible by MRI. This limitation has been addressed by a host of denoising techniques, recently including the so-called MPPCA: principal component analysis of the signal followed by automated rank estimation, exploiting the Marchenko-Pastur distribution of noise singular values. Operating on matrices comprised of data patches, this popular approach objectively identifies noise components and, ideally, allows noise to be removed without introducing artifacts such as image blurring, or nonlocal averaging. The MPPCA rank estimation, however, relies on a large number of noise singular values relative to the number of signal components to avoid such ill effects. This condition is unlikely to be met when data patches and therefore matrices are small, for example due to spatially varying noise. Here, we introduce tensor MPPCA (tMPPCA) for the purpose of denoising multidimensional data, such as from multicontrast acquisitions. Rather than combining dimensions in matrices, tMPPCA uses each dimension of the multidimensional data's inherent tensor-structure to better characterize noise, and to recursively estimate signal components. RESULTS Relative to matrix-based MPPCA, tMPPCA requires no additional assumptions, and comparing the two in a numerical phantom and a multi-TE diffusion MRI data set, tMPPCA dramatically improves denoising performance. This is particularly true for small data patches, suggesting that tMPPCA can be especially beneficial in such cases. CONCLUSIONS The MPPCA denoising technique can be extended to high-dimensional data with improved performance for smaller patch sizes.
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Affiliation(s)
- Jonas L Olesen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Andrada Ianus
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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11
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Hong D, Kim Y, Mushti C, Minami N, Wu J, Cherukuri MK, Swenson RE, Vigneron DB, Ronen SM. Monitoring response to a clinically relevant IDH inhibitor in glioma-Hyperpolarized 13C magnetic resonance spectroscopy approaches. Neurooncol Adv 2023; 5:vdad143. [PMID: 38024238 PMCID: PMC10681661 DOI: 10.1093/noajnl/vdad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
Background Mutant isocitrate dehydrogenase (IDHmut) catalyzes 2-hydroxyglutarate (2HG) production and is considered a therapeutic target for IDHmut tumors. However, response is mostly associated with inhibition of tumor growth. Response assessment via anatomic imaging is therefore challenging. Our goal was to directly detect IDHmut inhibition using a new hyperpolarized (HP) 13C magnetic resonance spectroscopy-based approach to noninvasively assess α-ketoglutarate (αKG) metabolism to 2HG and glutamate. Methods We studied IDHmut-expressing normal human astrocyte (NHAIDH1mut) cells and rats with BT257 tumors, and assessed response to the IDHmut inhibitor BAY-1436032 (n ≥ 4). We developed a new 13C Echo Planar Spectroscopic Imaging sequence with an optimized RF pulse to monitor the fate of HP [1-13C]αKG and [5-12C,1-13C]αKG with a 2.5 × 2.5 × 8 mm3 spatial resolution. Results Cell studies confirmed that BAY-1436032-treatment leads to a drop in HP 2HG and an increase in HP glutamate detectable with both HP substrates. Data using HP [5-12C,1-13C]αKG also demonstrated that its conversion to 2HG is detectable without the proximal 1.1% natural abundance [5-13C]αKG signal. In vivo studies showed that glutamate is produced in normal brains but no 2HG is detectable. In tumor-bearing rats, we detected the production of both 2HG and glutamate, and BAY-1436032-treatment led to a drop in 2HG and an increase in glutamate. Using HP [5-12C,1-13C]αKG we detected metabolism with an signal-to-noise ratio of 23 for 2HG and 17 for glutamate. Conclusions Our findings point to the clinical potential of HP αKG, which recently received FDA investigational new drug approval for research, for noninvasive localized imaging of IDHmut status.
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Affiliation(s)
- Donghyun Hong
- 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
| | | | - Noriaki Minami
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Jing Wu
- National Cancer Institute, NIH, Bethesda, Maryland, USA
| | | | - Rolf E Swenson
- National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Brain Tumor Research Center, UCSF, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Brain Tumor Research Center, UCSF, San Francisco, California, USA
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12
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Chen HY, Bok RA, Cooperberg MR, Nguyen HG, Shinohara K, Westphalen AC, Wang ZJ, Ohliger MA, Gebrezgiabhier D, Carvajal L, Gordon JW, Larson PEZ, Aggarwal R, Kurhanewicz J, Vigneron DB. Improving multiparametric MR-transrectal ultrasound guided fusion prostate biopsies with hyperpolarized 13 C pyruvate metabolic imaging: A technical development study. Magn Reson Med 2022; 88:2609-2620. [PMID: 35975978 PMCID: PMC9794017 DOI: 10.1002/mrm.29399] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE To develop techniques and establish a workflow using hyperpolarized carbon-13 (13 C) MRI and the pyruvate-to-lactate conversion rate (kPL ) biomarker to guide MR-transrectal ultrasound fusion prostate biopsies. METHODS The integrated multiparametric MRI (mpMRI) exam consisted of a 1-min hyperpolarized 13 C-pyruvate EPI acquisition added to a conventional prostate mpMRI exam. Maps of kPL values were calculated, uploaded to a picture archiving and communication system and targeting platform, and displayed as color overlays on T2 -weighted anatomic images. Abdominal radiologists identified 13 C research biopsy targets based on the general recommendation of focal lesions with kPL >0.02(s-1 ), and created a targeting report for each study. Urologists conducted transrectal ultrasound-guided MR fusion biopsies, including the standard 1 H-mpMRI targets as well as 12-14 core systematic biopsies informed by the research 13 C-kPL targets. All biopsy results were included in the final pathology report and calculated toward clinical risk. RESULTS This study demonstrated the safety and technical feasibility of integrating hyperpolarized 13 C metabolic targeting into routine 1 H-mpMRI and transrectal ultrasound fusion biopsy workflows, evaluated via 5 men (median age 71 years, prostate-specific antigen 8.4 ng/mL, Cancer of the Prostate Risk Assessment score 2) on active surveillance undergoing integrated scan and subsequent biopsies. No adverse event was reported. Median turnaround time was less than 3 days from scan to 13 C-kPL targeting, and scan-to-biopsy time was 2 weeks. Median number of 13 C targets was 1 (range: 1-2) per patient, measuring 1.0 cm (range: 0.6-1.9) in diameter, with a median kPL of 0.0319 s-1 (range: 0.0198-0.0410). CONCLUSIONS This proof-of-concept work demonstrated the safety and feasibility of integrating hyperpolarized 13 C MR biomarkers to the standard mpMRI workflow to guide MR-transrectal ultrasound fusion biopsies.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Matthew R. Cooperberg
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California United States
| | - Hao G. Nguyen
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California United States
| | - Katsuto Shinohara
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California United States
| | - Antonio C. Westphalen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Zhen J. Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Michael A. Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Daniel Gebrezgiabhier
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Rahul Aggarwal
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California United States
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California United States
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13
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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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14
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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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15
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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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16
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McCowan CV, Salmon D, Hu J, Pudakalakatti S, Whiting N, Davis JS, Carson DD, Zacharias NM, Bhattacharya PK, Farach-Carson MC. Post-Acquisition Hyperpolarized 29Silicon Magnetic Resonance Image Processing for Visualization of Colorectal Lesions Using a User-Friendly Graphical Interface. Diagnostics (Basel) 2022; 12:diagnostics12030610. [PMID: 35328163 PMCID: PMC8947341 DOI: 10.3390/diagnostics12030610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 02/04/2023] Open
Abstract
Medical imaging devices often use automated processing that creates and displays a self-normalized image. When improperly executed, normalization can misrepresent information or result in an inaccurate analysis. In the case of diagnostic imaging, a false positive in the absence of disease, or a negative finding when disease is present, can produce a detrimental experience for the patient and diminish their health prospects and prognosis. In many clinical settings, a medical technical specialist is trained to operate an imaging device without sufficient background information or understanding of the fundamental theory and processes involved in image creation and signal processing. Here, we describe a user-friendly image processing algorithm that mitigates user bias and allows for true signal to be distinguished from background. For proof-of-principle, we used antibody-targeted molecular imaging of colorectal cancer (CRC) in a mouse model, expressing human MUC1 at tumor sites. Lesion detection was performed using targeted magnetic resonance imaging (MRI) of hyperpolarized silicon particles. Resulting images containing high background and artifacts were then subjected to individualized image post-processing and comparative analysis. Post-acquisition image processing allowed for co-registration of the targeted silicon signal with the anatomical proton magnetic resonance (MR) image. This new methodology allows users to calibrate a set of images, acquired with MRI, and reliably locate CRC tumors in the lower gastrointestinal tract of living mice. The method is expected to be generally useful for distinguishing true signal from background for other cancer types, improving the reliability of diagnostic MRI.
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Affiliation(s)
- Caitlin V. McCowan
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA; (C.V.M.); (D.S.)
- Department of Diagnostic and Biomedical Sciences, School of Dentistry, The University of Texas Health Science Center, Houston, TX 77054, USA
| | - Duncan Salmon
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA; (C.V.M.); (D.S.)
| | - Jingzhe Hu
- Department of Bioengineering, Rice University, Houston, TX 77005, USA;
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.P.); (N.W.); (P.K.B.)
| | - Shivanand Pudakalakatti
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.P.); (N.W.); (P.K.B.)
| | - Nicholas Whiting
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.P.); (N.W.); (P.K.B.)
| | - Jennifer S. Davis
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Daniel D. Carson
- Department of BioSciences, Rice University, Houston, TX 77005, USA;
| | - Niki M. Zacharias
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Pratip K. Bhattacharya
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (S.P.); (N.W.); (P.K.B.)
| | - Mary C. Farach-Carson
- Department of Diagnostic and Biomedical Sciences, School of Dentistry, The University of Texas Health Science Center, Houston, TX 77054, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA;
- Department of BioSciences, Rice University, Houston, TX 77005, USA;
- Correspondence: ; Tel.: +1-713-486-4438
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Ursprung S, Woitek R, McLean MA, Priest AN, Crispin-Ortuzar M, Brodie CR, Gill AB, Gehrung M, Beer L, Riddick ACP, Field-Rayner J, Grist JT, Deen SS, Riemer F, Kaggie JD, Zaccagna F, Duarte JAG, Locke MJ, Frary A, Aho TF, Armitage JN, Casey R, Mendichovszky IA, Welsh SJ, Barrett T, Graves MJ, Eisen T, Mitchell TJ, Warren AY, Brindle KM, Sala E, Stewart GD, Gallagher FA. Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma-A Proof of Principle Study. Cancers (Basel) 2022; 14:335. [PMID: 35053497 PMCID: PMC8773685 DOI: 10.3390/cancers14020335] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 02/01/2023] Open
Abstract
Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.
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Affiliation(s)
- Stephan Ursprung
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Ramona Woitek
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Mary A. McLean
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Andrew N. Priest
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
- Department of Radiology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK;
| | - Mireia Crispin-Ortuzar
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
| | - Cara R. Brodie
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
| | - Andrew B. Gill
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Marcel Gehrung
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
| | - Lucian Beer
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Antony C. P. Riddick
- Department of Urology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK; (A.C.P.R.); (T.F.A.); (J.N.A.)
| | - Johanna Field-Rayner
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - James T. Grist
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Surrin S. Deen
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
- Department of Radiology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK;
| | - Frank Riemer
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Joshua D. Kaggie
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Fulvio Zaccagna
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Joao A. G. Duarte
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Matthew J. Locke
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Amy Frary
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Tevita F. Aho
- Department of Urology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK; (A.C.P.R.); (T.F.A.); (J.N.A.)
| | - James N. Armitage
- Department of Urology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK; (A.C.P.R.); (T.F.A.); (J.N.A.)
| | - Ruth Casey
- Department of Endocrinology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK;
| | - Iosif A. Mendichovszky
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
- Department of Radiology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK;
| | - Sarah J. Welsh
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Oncology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
- Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Tristan Barrett
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Martin J. Graves
- Department of Radiology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK;
| | - Tim Eisen
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Oncology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Thomas J. Mitchell
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Urology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK; (A.C.P.R.); (T.F.A.); (J.N.A.)
- Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK
- Wellcome Sanger Institute, Hinxton CB10 1RQ, UK
| | - Anne Y. Warren
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Pathology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Kevin M. Brindle
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
| | - Evis Sala
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
| | - Grant D. Stewart
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Urology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK; (A.C.P.R.); (T.F.A.); (J.N.A.)
- Department of Surgery, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Ferdia A. Gallagher
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge CB2 0QQ, UK; (S.U.); (R.W.); (M.A.M.); (M.C.-O.); (C.R.B.); (A.B.G.); (M.G.); (L.B.); (J.F.-R.); (S.S.D.); (F.R.); (J.D.K.); (F.Z.); (J.A.G.D.); (M.J.L.); (A.F.); (I.A.M.); (S.J.W.); (T.B.); (T.E.); (T.J.M.); (A.Y.W.); (K.M.B.); (E.S.); (G.D.S.)
- Department of Radiology, University of Cambridge, Cambridge CB2 0QQ, UK; (A.N.P.); (J.T.G.)
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Brender JR, Saida Y, Devasahayam N, Krishna MC, Kishimoto S. Hypoxia Imaging As a Guide for Hypoxia-Modulated and Hypoxia-Activated Therapy. Antioxid Redox Signal 2022; 36:144-159. [PMID: 34428981 PMCID: PMC8856011 DOI: 10.1089/ars.2021.0176] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Significance: Oxygen imaging techniques, which can probe the spatiotemporal heterogeneity of tumor oxygenation, could be of significant clinical utility in radiation treatment planning and in evaluating the effectiveness of hypoxia-activated prodrugs. To fulfill these goals, oxygen imaging techniques should be noninvasive, quantitative, and capable of serial imaging, as well as having sufficient temporal resolution to detect the dynamics of tumor oxygenation to distinguish regions of chronic and acute hypoxia. Recent Advances: No current technique meets all these requirements, although all have strengths in certain areas. The current status of positron emission tomography (PET)-based hypoxia imaging, oxygen-enhanced magnetic resonance imaging (MRI), 19F MRI, and electron paramagnetic resonance (EPR) oximetry are reviewed along with their strengths and weaknesses for planning hypoxia-guided, intensity-modulated radiation therapy and detecting treatment response for hypoxia-targeted prodrugs. Critical Issues: Spatial and temporal resolution emerges as a major concern for these areas along with specificity and quantitative response. Although multiple oxygen imaging techniques have reached the investigative stage, clinical trials to test the therapeutic effectiveness of hypoxia imaging have been limited. Future Directions: Imaging elements of the redox environment besides oxygen by EPR and hyperpolarized MRI may have a significant impact on our understanding of the basic biology of the reactive oxygen species response and may extend treatment possibilities.
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Affiliation(s)
- Jeffrey R Brender
- Radiation Biology Branch, Center for Cancer Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Yu Saida
- Radiation Biology Branch, Center for Cancer Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Nallathamby Devasahayam
- Radiation Biology Branch, Center for Cancer Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Murali C Krishna
- Radiation Biology Branch, Center for Cancer Research, National Institutes of Health, Bethesda, Maryland, USA
| | - Shun Kishimoto
- Radiation Biology Branch, Center for Cancer Research, National Institutes of Health, Bethesda, Maryland, USA
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Hong D, Batsios G, Viswanath P, Gillespie AM, Vaidya M, Larson PEZ, Ronen SM. Acquisition and quantification pipeline for in vivo hyperpolarized 13 C MR spectroscopy. Magn Reson Med 2021; 87:1673-1687. [PMID: 34775639 DOI: 10.1002/mrm.29081] [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: 02/17/2021] [Revised: 10/16/2021] [Accepted: 10/22/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE The goal of this study was to combine a specialized acquisition method with a new quantification pipeline to accurately and efficiently probe the metabolism of hyperpolarized 13 C-labeled compounds in vivo. In this study, we tested our approach on [2-13 C]pyruvate and [1-13 C]α-ketoglutarate data in rat orthotopic brain tumor models at 3T. METHODS We used a multiband metabolite-specific radiofrequency (RF) excitation in combination with a variable flip angle scheme to minimize substrate polarization loss and measure fast metabolic processes. We then applied spectral-temporal denoising using singular value decomposition to enhance spectral quality. This was combined with LCModel-based automatic 13 C spectral fitting and flip angle correction to separate overlapping signals and rapidly quantify the different metabolites. RESULTS Denoising improved the metabolite signal-to-noise ratio (SNR) by approximately 5. It also improved the accuracy of metabolite quantification as evidenced by a significant reduction of the Cramer Rao lower bounds. Furthermore, the use of the automated and user-independent LCModel-based quantification approach could be performed rapidly, with the kinetic quantification of eight metabolite peaks in a 12-spectrum array achieved in less than 1 minute. CONCLUSION The specialized acquisition method combined with denoising and a new quantification pipeline using LCModel for the first time for hyperpolarized 13 C data enhanced our ability to monitor the metabolism of [2-13 C]pyruvate and [1-13 C]α-ketoglutarate in rat orthotopic brain tumor models in vivo. This approach could be broadly applicable to other hyperpolarized agents both preclinically and in the clinical setting.
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Affiliation(s)
- Donghyun Hong
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Georgios Batsios
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Pavithra Viswanath
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Anne Marie Gillespie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Manushka Vaidya
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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20
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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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21
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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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22
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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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23
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Vaeggemose M, F. Schulte R, Laustsen C. Comprehensive Literature Review of Hyperpolarized Carbon-13 MRI: The Road to Clinical Application. Metabolites 2021; 11:metabo11040219. [PMID: 33916803 PMCID: PMC8067176 DOI: 10.3390/metabo11040219] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/31/2021] [Accepted: 04/01/2021] [Indexed: 01/02/2023] Open
Abstract
This review provides a comprehensive assessment of the development of hyperpolarized (HP) carbon-13 metabolic MRI from the early days to the present with a focus on clinical applications. The status and upcoming challenges of translating HP carbon-13 into clinical application are reviewed, along with the complexity, technical advancements, and future directions. The road to clinical application is discussed regarding clinical needs and technological advancements, highlighting the most recent successes of metabolic imaging with hyperpolarized carbon-13 MRI. Given the current state of hyperpolarized carbon-13 MRI, the conclusion of this review is that the workflow for hyperpolarized carbon-13 MRI is the limiting factor.
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Affiliation(s)
- Michael Vaeggemose
- GE Healthcare, 2605 Brondby, Denmark;
- MR Research Centre, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
| | | | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
- Correspondence:
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24
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Froeling M, Prompers JJ, Klomp DWJ, van der Velden TA. PCA denoising and Wiener deconvolution of 31 P 3D CSI data to enhance effective SNR and improve point spread function. Magn Reson Med 2021; 85:2992-3009. [PMID: 33522635 PMCID: PMC7986807 DOI: 10.1002/mrm.28654] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 11/10/2020] [Accepted: 12/01/2020] [Indexed: 12/19/2022]
Abstract
Purpose This study evaluates the performance of 2 processing methods, that is, principal component analysis‐based denoising and Wiener deconvolution, to enhance the quality of phosphorus 3D chemical shift imaging data. Methods Principal component analysis‐based denoising increases the SNR while maintaining spectral information. Wiener deconvolution reduces the FWHM of the voxel point spread function, which is increased by Hamming filtering or Hamming‐weighted acquisition. The proposed methods are evaluated using simulated and in vivo 3D phosphorus chemical shift imaging data by 1) visual inspection of the spatial signal distribution; 2) SNR calculation of the PCr peak; and 3) fitting of metabolite basis functions. Results With the optimal order of processing steps, we show that the effective SNR of in vivo phosphorus 3D chemical shift imaging data can be increased. In simulations, we show we can preserve phosphorus‐containing metabolite peaks that had an SNR < 1 before denoising. Furthermore, using Wiener deconvolution, we were able to reduce the FWHM of the voxel point spread function with only partially reintroducing Gibb‐ringing artifacts while maintaining the SNR. After data processing, fitting of the phosphorus‐containing metabolite signals improved. Conclusion In this study, we have shown that principal component analysis‐based denoising in combination with regularized Wiener deconvolution allows increasing the effective spectral SNR of in vivo phosphorus 3D chemical shift imaging data, with reduction of the FWHM of the voxel point spread function. Processing increased the effective SNR by at least threefold compared to Hamming weighted acquired data and minimized voxel bleeding. With these methods, fitting of metabolite amplitudes became more robust with decreased fitting residuals.
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Affiliation(s)
- Martijn Froeling
- Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeanine J Prompers
- Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dennis W J Klomp
- Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tijl A van der Velden
- Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
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25
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Autry AW, Park I, Kline C, Chen HY, Gordon JW, Raber S, Hoffman C, Kim Y, Okamoto K, Vigneron DB, Lupo JM, Prados M, Li Y, Xu D, Mueller S. Pilot Study of Hyperpolarized 13C Metabolic Imaging in Pediatric Patients with Diffuse Intrinsic Pontine Glioma and Other CNS Cancers. AJNR Am J Neuroradiol 2020; 42:178-184. [PMID: 33272950 DOI: 10.3174/ajnr.a6937] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/19/2020] [Indexed: 01/21/2023]
Abstract
BACKGROUND AND PURPOSE Pediatric CNS tumors commonly present challenges for radiographic interpretation on conventional MR imaging. This study sought to investigate the safety and tolerability of hyperpolarized carbon-13 (HP-13C) metabolic imaging in pediatric patients with brain tumors. MATERIALS AND METHODS Pediatric patients 3 to 18 years of age who were previously diagnosed with a brain tumor and could undergo MR imaging without sedation were eligible to enroll in this safety study of HP [1-13C]pyruvate. Participants received a one-time injection of HP [1-13C]pyruvate and were imaged using dynamic HP-13C MR imaging. We assessed 2 dose levels: 0.34 mL/kg and the highest tolerated adult dose of 0.43 mL/kg. Participants were monitored throughout imaging and for 60 minutes postinjection, including pre- and postinjection electrocardiograms and vital sign measurements. RESULTS Between February 2017 and July 2019, ten participants (9 males; median age, 14 years; range, 10-17 years) were enrolled, of whom 6 completed injection of HP [1-13C]pyruvate and dynamic HP-13C MR imaging. Four participants failed to undergo HP-13C MR imaging due to technical failures related to generating HP [1-13C]pyruvate or MR imaging operability. HP [1-13C]pyruvate was well-tolerated in all participants who completed the study, with no dose-limiting toxicities or adverse events observed at either 0.34 (n = 3) or 0.43 (n = 3) mL/kg. HP [1-13C]pyruvate demonstrated characteristic conversion to [1-13C]lactate and [13C]bicarbonate in the brain. Due to poor accrual, the study was closed after only 3 participants were enrolled at the highest dose level. CONCLUSIONS Dynamic HP-13C MR imaging was safely performed in 6 pediatric patients with CNS tumors and demonstrated HP [1-13C]pyruvate brain metabolism.
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Affiliation(s)
- A W Autry
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - I Park
- Department of Radiology (I.P.), Chonnam National University College of Medicine and Hospital, Gwangju, Korea
| | - C Kline
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Department of Neurology (C.K., S.M.)
| | - H-Y Chen
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - J W Gordon
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - S Raber
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics
| | - C Hoffman
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics
| | - Y Kim
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - K Okamoto
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - D B Vigneron
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.).,Bioengineering and Therapeutic Sciences (D.B.V.).,Neurological Surgery (D.B.V., M.P., S.M.).,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - J M Lupo
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.).,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - M Prados
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Neurological Surgery (D.B.V., M.P., S.M.)
| | - Y Li
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - D Xu
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.) .,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - S Mueller
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Department of Neurology (C.K., S.M.).,Neurological Surgery (D.B.V., M.P., S.M.)
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26
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von Morze C, Engelbach JA, Blazey T, Quirk JD, Reed GD, Ippolito JE, Garbow JR. Comparison of hyperpolarized 13 C and non-hyperpolarized deuterium MRI approaches for imaging cerebral glucose metabolism at 4.7 T. Magn Reson Med 2020; 85:1795-1804. [PMID: 33247884 DOI: 10.1002/mrm.28612] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 10/12/2020] [Accepted: 11/03/2020] [Indexed: 12/23/2022]
Abstract
PURPOSE The purpose of this study was to directly compare two isotopic metabolic imaging approaches, hyperpolarized (HP) 13 C MRI and deuterium metabolic imaging (DMI), for imaging specific closely related segments of cerebral glucose metabolism at 4.7 T. METHODS Comparative HP-13 C and DMI neuroimaging experiments were conducted consecutively in normal rats during the same scanning session. Localized conversions of [1-13 C]pyruvate and [6,6-2 H2 ]glucose to their respective downstream metabolic products were measured by spectroscopic imaging, using an identical 2D-CSI sequence with parameters optimized for the respective experiments. To facilitate direct comparison, a pair of substantially equivalent 2.5-cm double-tuned X/1 H RF surface coils was developed. For improved results, multidimensional low-rank reconstruction was applied to denoise the raw DMI data. RESULTS Localized conversion of HP [1-13 C]pyruvate to [1-13 C]lactate, and [6,6-2 H2 ]glucose to [3,3-2 H2 ]lactate and Glx-d (glutamate and glutamine), was detected in rat brain by spectroscopic imaging at 4.7 T. The SNR and spatial resolution of HP-13 C MRI was superior to DMI but limited to a short time window, whereas the lengthy DMI acquisition yielded maps of not only lactate, but also Glx production, albeit with relatively poor spectral discrimination between metabolites at this field strength. Across the individual rats, there was an apparent inverse correlation between cerebral production of HP [1-13 C]lactate and Glx-d, along with a trend toward increased [3,3-2 H2 ]lactate. CONCLUSION The HP-13 C MRI and DMI methods are both feasible at 4.7 T and have significant potential for metabolic imaging of specific segments of glucose metabolism.
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Affiliation(s)
- Cornelius von Morze
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - John A Engelbach
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - Tyler Blazey
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - James D Quirk
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | | | - Joseph E Ippolito
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - Joel R Garbow
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
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