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Chaumeil MM, Bankson JA, Brindle KM, Epstein S, Gallagher FA, Grashei M, Guglielmetti C, Kaggie JD, Keshari KR, Knecht S, Laustsen C, Schmidt AB, Vigneron D, Yen YF, Schilling F. New Horizons in Hyperpolarized 13C MRI. Mol Imaging Biol 2024; 26:222-232. [PMID: 38147265 PMCID: PMC10972948 DOI: 10.1007/s11307-023-01888-5] [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: 09/20/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 12/27/2023]
Abstract
Hyperpolarization techniques significantly enhance the sensitivity of magnetic resonance (MR) and thus present fascinating new directions for research and applications with in vivo MR imaging and spectroscopy (MRI/S). Hyperpolarized 13C MRI/S, in particular, enables real-time non-invasive assessment of metabolic processes and holds great promise for a diverse range of clinical applications spanning fields like oncology, neurology, and cardiology, with a potential for improving early diagnosis of disease, patient stratification, and therapy response assessment. Despite its potential, technical challenges remain for achieving clinical translation. This paper provides an overview of the discussions that took place at the international workshop "New Horizons in Hyperpolarized 13C MRI," in March 2023 at the Bavarian Academy of Sciences and Humanities, Munich, Germany. The workshop covered new developments, as well as future directions, in topics including polarization techniques (particularly focusing on parahydrogen-based methods), novel probes, considerations related to data acquisition and analysis, and emerging clinical applications in oncology and other fields.
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Affiliation(s)
- Myriam M Chaumeil
- Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, CA, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
| | - James A Bankson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kevin M Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | - Ferdia A Gallagher
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Centre, Cambridge, UK
| | - Martin Grashei
- Department of Nuclear Medicine, TUM School of Medicine, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany
| | - Caroline Guglielmetti
- Department of Physical Therapy and Rehabilitation Science, University of California, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Joshua D Kaggie
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Kayvan R Keshari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Weill Cornell Graduate School, New York City, NY, USA
| | | | - Christoffer Laustsen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, Aarhus, Denmark
| | - Andreas B Schmidt
- Partner Site Freiburg and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany
- Department of Chemistry, Integrative Biosciences (Ibio), Karmanos Cancer Institute (KCI), Wayne State University, Detroit, MI, 48202, USA
| | - Daniel Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Yi-Fen Yen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Franz Schilling
- Department of Nuclear Medicine, TUM School of Medicine, Klinikum Rechts Der Isar, Technical University of Munich, Munich, Germany
- Partner Site Freiburg and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
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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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Chung BT, Kim Y, Gordon JW, Chen HY, Autry AW, Lee PM, Hu JY, Tan CT, Suszczynski C, Chang SM, Villanueva-Meyer JE, Bok RA, Larson PEZ, Xu D, Li Y, Vigneron DB. Hyperpolarized [2- 13C]pyruvate MR molecular imaging with whole brain coverage. Neuroimage 2023; 280:120350. [PMID: 37634883 PMCID: PMC10530049 DOI: 10.1016/j.neuroimage.2023.120350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/20/2023] [Accepted: 08/24/2023] [Indexed: 08/29/2023] Open
Abstract
Hyperpolarized (HP) 13C Magnetic Resonance Imaging (MRI) was applied for the first time to image and quantify the uptake and metabolism of [2-13C]pyruvate in the human brain to provide new metabolic information on cerebral energy metabolism. HP [2-13C]pyruvate was injected intravenously and imaged in 5 healthy human volunteer exams with whole brain coverage in a 1-minute acquisition using a specialized spectral-spatial multi-slice echoplanar imaging (EPI) pulse sequence to acquire 13C-labeled volumetric and dynamic images of [2-13C]pyruvate and downstream metabolites [5-13C]glutamate and [2-13C]lactate. Metabolic ratios and apparent conversion rates of pyruvate-to-lactate (kPL) and pyruvate-to-glutamate (kPG) were quantified to investigate simultaneously glycolytic and oxidative metabolism in a single injection.
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Affiliation(s)
- Brian T Chung
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA.
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Philip M Lee
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Chou T Tan
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Chris Suszczynski
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA; Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
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Xu Z, Michel KA, Walker CM, Harlan CJ, Martinez GV, Gordon JW, Chen HY, Vigneron DB, Bankson JA. Model-constrained reconstruction accelerated with Fourier-based undersampling for hyperpolarized [1- 13 C] pyruvate imaging. Magn Reson Med 2023; 89:1481-1495. [PMID: 36468638 PMCID: PMC9892212 DOI: 10.1002/mrm.29551] [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: 04/15/2022] [Revised: 11/14/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE Model-constrained reconstruction with Fourier-based undersampling (MoReFUn) is introduced to accelerate the acquisition of dynamic MRI using hyperpolarized [1-13 C]-pyruvate. METHODS The MoReFUn method resolves spatial aliasing using constraints introduced by a pharmacokinetic model that describes the signal evolution of both pyruvate and lactate. Acceleration was evaluated on three single-channel data sets: a numerical digital phantom that is used to validate the accuracy of reconstruction and model parameter restoration under various SNR and undersampling ratios, prospectively and retrospectively sampled data of an in vitro dynamic multispectral phantom, and retrospectively undersampled imaging data from a prostate cancer patient to test the fidelity of reconstructed metabolite time series. RESULTS All three data sets showed successful reconstruction using MoReFUn. In simulation and retrospective phantom data, the restored time series of pyruvate and lactate maintained the image details, and the mean square residual error of the accelerated reconstruction increased only slightly (< 10%) at a reduction factor up to 8. In prostate data, the quantitative estimation of the conversion-rate constant of pyruvate to lactate was achieved with high accuracy of less than 10% error at a reduction factor of 2 compared with the conversion rate derived from unaccelerated data. CONCLUSION The MoReFUn technique can be used as an effective and reliable imaging acceleration method for metabolic imaging using hyperpolarized [1-13 C]-pyruvate.
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Affiliation(s)
- Zhan Xu
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
| | - Keith A. Michel
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
| | - Christopher M. Walker
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
| | - Collin J. Harlan
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
- The University of Texas MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston, TX
| | - Gary V. Martinez
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
| | - Jeremy W. Gordon
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Hsin-Yu Chen
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - Daniel B. Vigneron
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA
| | - James A. Bankson
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX
- The University of Texas MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston, TX
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Harlan CJ, Xu Z, Walker CM, Michel KA, Reed GD, Bankson JA. The effect of transmit B 1 inhomogeneity on hyperpolarized [1- 13 C]-pyruvate metabolic MR imaging biomarkers. Med Phys 2021; 48:4900-4908. [PMID: 34287945 DOI: 10.1002/mp.15107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 07/13/2021] [Accepted: 07/13/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE A specialized Helmholtz-style 13 C volume transmit "clamshell" coil is currently being utilized for 13 C excitation in pre-clinical and clinical hyperpolarized 13 C MRI studies aimed at probing the metabolic activity of tumors in various target anatomy. Due to the widespread use of this 13 C clamshell coil design, it is important that the effects of the 13 C clamshell coil B1 + profile on HP signal evolution and quantification are well understood. The goal of this study was to characterize the B1 + field of the 13 C clamshell coil and assess the impact of inhomogeneities on semi-quantitative and quantitative hyperpolarized MR imaging biomarkers of metabolism. METHODS The B1 + field of the 13 C clamshell coil was mapped by hand using a network analyzer equipped with an S-parameter test set. Pharmacokinetic models were used to simulate signal evolution as a function of position-dependent local excitation angles, for various nominal excitation angles, which were assumed to be accurately calibrated at the isocenter. These signals were then quantified according to the normalized lactate ratio (nLac) and the apparent rate constant for the conversion of pyruvate to lactate (kPL ). The percent difference between these metabolic imaging biomarker maps and the reference value observed at the isocenter of the clamshell coil was calculated to estimate the potential for error due to position within the clamshell coil. Finally, regions were identified within the clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the value at the isocenter. RESULTS The B1 + field maps show that a limited volume encompassed by a region measuring approximately 12.9 × 11.5 × 13.4 cm (X-direction, Y-direction, Z-direction) centered in the 13 C clamshell coil will produce deviations in the B1 + field within ±10% of that at the isocenter. For the metabolic imaging biomarkers that we evaluated, the case when the pyruvate excitation angle (θP ) and lactate excitation angle (θL ) were equal to 10° produced the largest volumetric region with deviations within ±10% of the value at the isocenter. Higher excitation angles yielded higher signal and SNR, but the size of the region in which uniform measurements could be collected near the isocenter of the coil was reduced at higher excitation angles. The tradeoff between the size of the homogenous region at the isocenter and signal intensity must be weighed carefully depending on the particular imaging application. CONCLUSION This work identifies regions and optimal excitation angles (θP and θL ) within the 13 C clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the respective value at the isocenter, and thus where excitation angles are reproducible and well-calibrated. Semi-quantitative and quantitative metabolic imaging biomarkers can vary with position in the clamshell coil as a result of B1 + field inhomogeneity, necessitating care in patient positioning and the selection of an excitation angle set that balances reproducibility and SNR performance over the target imaging volume.
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Affiliation(s)
- Collin J Harlan
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Christopher M Walker
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Keith A Michel
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | | | - James A Bankson
- Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.,The University of Texas M.D. Anderson Cancer Center, UT Health Graduate School of Biomedical Sciences, Houston, TX, USA
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Larson PEZ, Gordon JW. Hyperpolarized Metabolic MRI-Acquisition, Reconstruction, and Analysis Methods. Metabolites 2021; 11:386. [PMID: 34198574 PMCID: PMC8231874 DOI: 10.3390/metabo11060386] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/05/2021] [Accepted: 06/08/2021] [Indexed: 01/05/2023] Open
Abstract
Hyperpolarized metabolic MRI with 13C-labeled agents has emerged as a powerful technique for in vivo assessments of real-time metabolism that can be used across scales of cells, tissue slices, animal models, and human subjects. Hyperpolarized contrast agents have unique properties compared to conventional MRI scanning and MRI contrast agents that require specialized imaging methods. Hyperpolarized contrast agents have a limited amount of available signal, irreversible decay back to thermal equilibrium, bolus injection and perfusion kinetics, cellular uptake and metabolic conversion kinetics, and frequency shifts between metabolites. This article describes state-of-the-art methods for hyperpolarized metabolic MRI, summarizing data acquisition, reconstruction, and analysis methods in order to guide the design and execution of studies.
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Affiliation(s)
- Peder Eric Zufall Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA;
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA 94143, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley, CA 94143, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA;
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Perkons NR, Johnson O, Pilla G, Gade TPF. Pharmacodynamics and pharmacokinetics of hyperpolarized [1- 13 C]-pyruvate in a translational oncologic model. NMR IN BIOMEDICINE 2021; 34:e4502. [PMID: 33772910 DOI: 10.1002/nbm.4502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 02/18/2021] [Indexed: 06/12/2023]
Abstract
This study investigates the in vivo pharmacokinetics and pharmacodynamics of hyperpolarized [1-13 C]-pyruvate in a translational cancer model in order to inform the application of dynamic nuclear polarization (DNP)-enhanced magnetic resonance spectroscopic imaging (MRSI) as a tool for imaging liver cancer. Intratumoral metabolism within autochthonous hepatocellular carcinomas in male Wistar rats was analyzed by MRSI following hyperpolarized [1-13 C]-pyruvate injections with 80 mM (low dose [LD]) or 160 mM (high dose [HD]) pyruvate. Rats received (i) LD followed by HD injection, (ii) sequential LD injections with or without an interposed lactate dehydrogenase inhibitor (LDHi) injection, or (iii) a single LD injection. A subset of rats in (ii) were sacrificed immediately after imaging, permitting measurement of active LDH concentrations in tumor extracts. Urine and serum were collected before and after injections for rats in (iii). Comparison of LD and HD injections confirmed concentration-dependent variation of intratumoral metabolite fractions and intermetabolite ratios. In addition, quantification of the lactate-to-pyruvate ratio was sensitive to pharmacologic inhibition with intermetabolite ratios correlating with active LDH concentrations in tumor extracts. Finally, comparison of pre- and post-DNP urine collections revealed that pyruvate and the radical source are renally excreted after injection. These data demonstrate that DNP-MRSI facilitates real-time quantification of intratumoral metabolism that is repeatable and reflective of intracellular processes. A translational model system confirmed that interpretation requires consideration of probe dose, administration frequency and excretion.
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Affiliation(s)
- Nicholas R Perkons
- Penn Image Guided Interventions Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Omar Johnson
- Penn Image Guided Interventions Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gabrielle Pilla
- Penn Image Guided Interventions Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Terence P F Gade
- Penn Image Guided Interventions Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Cancer Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Xu Z, Niedzielski JS, Sun C, Walker CM, Michel KA, Einstein SA, Martinez GV, Bankson JA. Correction and optimization of symmetric echo-planar spectroscopic imaging for hyperpolarized [1- 13C]-pyruvate. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 321:106859. [PMID: 33160268 PMCID: PMC7722237 DOI: 10.1016/j.jmr.2020.106859] [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: 05/21/2020] [Revised: 10/21/2020] [Accepted: 10/23/2020] [Indexed: 06/11/2023]
Abstract
Symmetric echo-planar spectroscopic imaging (EPSI) supports higher spectral bandwidth and improves signal-to-noise efficiency compared to flyback EPSI with the same readout bandwidth, but suffers from artifacts that are associated with non-uniform temporal sampling in k-t space. Our goal is to eliminate these artifacts and enhance observation of hyperpolarized [1-13C] pyruvate and its metabolites using symmetric EPSI. We used symmetric EPSI to efficiently acquire radially encoded spectroscopic imaging projections with a spectral under-sampling scheme that was optimized for HP pyruvate and its metabolites. A simple approach called selective correction of off-resonance effects (SCORE) was developed and applied to eliminate spectral artifacts. Simulations were used to assess the relative SNR performance of this technique, and a phantom study was carried out at 3 T to evaluate this method and compare it with alternative strategies. SCORE correction eliminated spectral artifacts due to chemical shift and non-uniform sampling in time. It is also compatible with established methods to eliminate artifacts caused by eddy currents. SCORE corrected symmetric EPSI supported maximal EPSI spectral bandwidth and improved SNR efficiency. Symmetric EPSI with SCORE correction offers a straightforward, efficient, and effective framework for assessment of hyperpolarized [1-13C] pyruvate and its metabolites.
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Affiliation(s)
- Zhan Xu
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - Joshua S Niedzielski
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - Changyu Sun
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - Christopher M Walker
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - Keith A Michel
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Samuel A Einstein
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - Gary V Martinez
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA
| | - James A Bankson
- Department of Imaging Physics, The University of Texas-MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston, TX, USA.
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9
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Gordon JW, Autry AW, Tang S, Graham JY, Bok RA, Zhu X, Villanueva-Meyer JE, Li Y, Ohilger MA, Abraham MR, Xu D, Vigneron DB, Larson PEZ. A variable resolution approach for improved acquisition of hyperpolarized 13 C metabolic MRI. Magn Reson Med 2020; 84:2943-2952. [PMID: 32697867 PMCID: PMC7719570 DOI: 10.1002/mrm.28421] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 05/27/2020] [Accepted: 06/19/2020] [Indexed: 01/06/2023]
Abstract
PURPOSE To ameliorate tradeoffs between a fixed spatial resolution and signal-to-noise ratio (SNR) for hyperpolarized 13 C MRI. METHODS In MRI, SNR is proportional to voxel volume but retrospective downsampling or voxel averaging only improves SNR by the square root of voxel size. This can be exploited with a metabolite-selective imaging approach that independently encodes each compound, yielding high-resolution images for the injected substrate and coarser resolution images for downstream metabolites, while maintaining adequate SNR for each. To assess the efficacy of this approach, hyperpolarized [1-13 C]pyruvate data were acquired in healthy Sprague-Dawley rats (n = 4) and in two healthy human subjects. RESULTS Compared with a constant resolution acquisition, variable-resolution data sets showed improved detectability of metabolites in pre-clinical renal studies with a 3.5-fold, 8.7-fold, and 6.0-fold increase in SNR for lactate, alanine, and bicarbonate data, respectively. Variable-resolution data sets from healthy human subjects showed cardiac structure and neuro-vasculature in the higher resolution pyruvate images (6.0 × 6.0 mm2 for cardiac and 7.5 × 7.5 mm2 for brain) that would otherwise be missed due to partial-volume effects and illustrates the level of detail that can be achieved with hyperpolarized substrates in a clinical setting. CONCLUSION We developed a variable-resolution strategy for hyperpolarized 13 C MRI using metabolite-selective imaging and demonstrated that it mitigates tradeoffs between a fixed spatial resolution and SNR for hyperpolarized substrates, providing both high resolution pyruvate and coarse resolution metabolite data sets in a single exam. This technique shows promise to improve future studies by maximizing metabolite SNR while minimizing partial-volume effects from the injected substrate.
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Affiliation(s)
- Jeremy W. Gordon
- 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
| | - Shuyu Tang
- 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
| | - Jasmine Y. Graham
- 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
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Xucheng Zhu
- 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
| | - Javier E. Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Michael A. Ohilger
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Maria Roselle Abraham
- Division of Cardiology, Department of Medicine, 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
| | - 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
| | - 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
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10
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Walker CM, Gordon JW, Xu Z, Michel KA, Li L, Larson PEZ, Vigneron DB, Bankson JA. Slice profile effects on quantitative analysis of hyperpolarized pyruvate. NMR IN BIOMEDICINE 2020; 33:e4373. [PMID: 32743881 PMCID: PMC7484340 DOI: 10.1002/nbm.4373] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 06/25/2020] [Accepted: 06/26/2020] [Indexed: 06/01/2023]
Abstract
Magnetic resonance imaging of hyperpolarized pyruvate provides a new imaging biomarker for cancer metabolism, based on the dynamic in vivo conversion of hyperpolarized pyruvate to lactate. Methods for quantification of signal evolution need to be robust and reproducible across a range of experimental conditions. Pharmacokinetic analysis of dynamic spectroscopic imaging data from hyperpolarized pyruvate and its metabolites generally assumes that signal arises from ideal rectangular slice excitation profiles. In this study, we examined whether this assumption could lead to bias in kinetic analysis of hyperpolarized pyruvate and, if so, whether such a bias can be corrected. A Bloch-McConnell simulator was used to generate synthetic data using a known set of "ground truth" pharmacokinetic parameter values. Signal evolution was then analyzed using analysis software that either assumed a uniform slice profile, or incorporated information about the slice profile into the analysis. To correct for slice profile effects, the expected slice profile was subdivided into multiple sub-slices to account for variable excitation angles along the slice dimension. An ensemble of sub-slices was then used to fit the measured signal evolution. A mismatch between slice profiles used for data acquisition and those assumed during kinetic analysis was identified as a source of quantification bias. Results indicate that imperfect slice profiles preferentially increase detected lactate signal, leading to an overestimation of the apparent metabolic exchange rate. The slice profile-correction algorithm was tested in simulation, in phantom measurements, and applied to data acquired from a patient with prostate cancer. The results demonstrated that slice profile-induced biases can be minimized by accounting for the slice profile during pharmacokinetic analysis. This algorithm can be used to correct data from either single or multislice acquisitions.
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Affiliation(s)
- Christopher M. Walker
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Zhan Xu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Keith A. Michel
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX
| | - Liang Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - James A. Bankson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX
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11
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Grist JT, Hansen ES, Sánchez‐Heredia JD, McLean MA, Tougaard R, Riemer F, Schulte RF, Kaggie JD, Ardenkjaer‐Larsen JH, Laustsen C, Gallagher FA. Creating a clinical platform for carbon-13 studies using the sodium-23 and proton resonances. Magn Reson Med 2020; 84:1817-1827. [PMID: 32167199 PMCID: PMC8638662 DOI: 10.1002/mrm.28238] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 02/06/2020] [Accepted: 02/08/2020] [Indexed: 01/01/2023]
Abstract
PURPOSE Calibration of hyperpolarized 13 C-MRI is limited by the low signal from endogenous carbon-containing molecules and consequently requires 13 C-enriched external phantoms. This study investigated the feasibility of using either 23 Na-MRI or 1 H-MRI to calibrate the 13 C excitation. METHODS Commercial 13 C-coils were used to estimate the transmit gain and center frequency for 13 C and 23 Na resonances. Simulations of the transmit B1 profile of a Helmholtz loop were performed. Noise correlation was measured for both nuclei. A retrospective analysis of human data assessing the use of the 1 H resonance to predict [1-13 C]pyruvate center frequency was also performed. In vivo experiments were undertaken in the lower limbs of 6 pigs following injection of hyperpolarized 13 C-pyruvate. RESULTS The difference in center frequencies and transmit gain between tissue 23 Na and [1-13 C]pyruvate was reproducible, with a mean scale factor of 1.05179 ± 0.00001 and 10.4 ± 0.2 dB, respectively. Utilizing the 1 H water peak, it was possible to retrospectively predict the 13 C-pyruvate center frequency with a standard deviation of only 11 Hz sufficient for spectral-spatial excitation-based studies. CONCLUSION We demonstrate the feasibility of using the 23 Na and 1 H resonances to calibrate the 13 C transmit B1 using commercially available 13 C-coils. The method provides a simple approach for in vivo calibration and could improve clinical workflow.
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Affiliation(s)
- James T. Grist
- Department of RadiologyUniversity of CambridgeCambridgeUnited Kingdom
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUnited Kingdom
| | | | | | - Mary A. McLean
- Department of RadiologyUniversity of CambridgeCambridgeUnited Kingdom
- CRUKCambridge InstituteCambridgeUnited Kingdom
| | | | - Frank Riemer
- Department of RadiologyUniversity of CambridgeCambridgeUnited Kingdom
| | | | - Joshua D. Kaggie
- Department of RadiologyUniversity of CambridgeCambridgeUnited Kingdom
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12
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Mammoli D, Gordon J, Autry A, Larson PEZ, Li Y, Chen HY, Chung B, Shin P, Van Criekinge M, Carvajal L, Slater JB, Bok R, Crane J, Xu D, Chang S, Vigneron DB. Kinetic Modeling of Hyperpolarized Carbon-13 Pyruvate Metabolism in the Human Brain. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:320-327. [PMID: 31283497 PMCID: PMC6939147 DOI: 10.1109/tmi.2019.2926437] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Kinetic modeling of the in vivo pyruvate-to-lactate conversion is crucial to investigating aberrant cancer metabolism that demonstrates Warburg effect modifications. Non-invasive detection of alterations to metabolic flux might offer prognostic value and improve the monitoring of response to treatment. In this clinical research project, hyperpolarized [1-13C] pyruvate was intravenously injected in a total of 10 brain tumor patients to measure its rate of conversion to lactate ( kPL ) and bicarbonate ( kPB ) via echo-planar imaging. Our aim was to investigate new methods to provide kPL and kPB maps with whole-brain coverage. The approach was data-driven and addressed two main issues: selecting the optimal model for fitting our data and determining an appropriate goodness-of-fit metric. The statistical analysis suggested that an input-less model had the best agreement with the data. It was also found that selecting voxels based on post-fitting error criteria provided improved precision and wider spatial coverage compared to using signal-to-noise cutoffs alone.
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13
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Olin RB, Sánchez‐Heredia JD, Schulte RF, Bøgh N, Hansen ESS, Laustsen C, Hanson LG, Ardenkjær‐Larsen JH. Three‐dimensional accelerated acquisition for hyperpolarized
13
C MR with blipped stack‐of‐spirals and conjugate‐gradient SENSE. Magn Reson Med 2020; 84:519-534. [DOI: 10.1002/mrm.28171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 12/16/2019] [Accepted: 12/19/2019] [Indexed: 01/12/2023]
Affiliation(s)
- Rie B. Olin
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
| | | | | | - Nikolaj Bøgh
- MR Research CentreAarhus University Aarhus Denmark
| | | | | | - Lars G. Hanson
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
- Danish Research Centre for Magnetic ResonanceCentre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital Hvidovre Hvidovre Denmark
| | - Jan H. Ardenkjær‐Larsen
- Department of Health Technology Technical University of Denmark Kongens Lyngby Denmark
- GE Healthcare Brøndby Denmark
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14
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Michel KA, Zieliński R, Walker CM, Le Roux L, Priebe W, Bankson JA, Schellingerhout D. Hyperpolarized Pyruvate MR Spectroscopy Depicts Glycolytic Inhibition in a Mouse Model of Glioma. Radiology 2019; 293:168-173. [PMID: 31385757 DOI: 10.1148/radiol.2019182919] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BackgroundA generation of therapies targeting tumor metabolism is becoming available for treating glioma. Hyperpolarized MRI is uniquely suited to directly measure the metabolic effects of these emerging treatments.PurposeTo explore the feasibility of the use of hyperpolarized [1-carbon 13 {13C}]-pyruvate for real-time measurement of metabolism and response to treatment with a glycolytic inhibitor in an orthotopic mouse model of glioma.Materials and MethodsIn this animal study, anatomic MRI and dynamic 13C MR spectroscopy were performed at 7 T during intravenous injection of hyperpolarized [1-13C]-pyruvate on mice with orthotopic U87MG glioma and healthy control mice. Anatomic MRI and dynamic 13C MR spectroscopy were repeated after administration of the glycolytic inhibitor WP1122, a prodrug of 2-deoxy-d-glucose. All experiments were conducted in athymic nude mice between October 2016 and March 2017. Hyperpolarized lactate production was quantified as an apparent reaction rate, or kPL, and normalized lactate ratio (nLac). The Wilcoxon signed-rank test was used to assess changes in paired measures of lactate production before and after treatment.ResultsThirteen 12-16-week-old female mice and five healthy female mice underwent anatomic MRI and hyperpolarized [1-13C]-pyruvate spectroscopy. Large contrast agent-enhanced tumors were shown in mice with glioma at T2-weighted and T1-weighted postcontrast MRI by postimplantation day 40. After treatment with WP1122, a decrease in lactate was observed in mice with glioma (baseline and treatment mean kPL, 0.027 and 0.018 sec-1, respectively, P = .01; baseline and posttreatment mean nLac, 0.28 and 0.22, respectively, P = .01) whereas no significant decrease was observed in healthy control mice (baseline and posttreatment mean kPL, 0.011 and 0.017 sec-1, respectively, P = .91; baseline and posttreatment mean nLac, 0.16 and 0.21, respectively, P = .84).ConclusionHyperpolarized carbon 13 measurements of pyruvate metabolism can provide rapid feedback for monitoring treatment response in glioma.© RSNA, 2019.
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Affiliation(s)
- Keith A Michel
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - Rafal Zieliński
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - Christopher M Walker
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - Lucia Le Roux
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - Waldemar Priebe
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - James A Bankson
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
| | - Dawid Schellingerhout
- From the Departments of Imaging Physics (K.A.M., C.M.W., J.A.B.), Experimental Therapeutics (R.Z., W.P.), Cancer Systems Imaging (L.L.R., D.S.), and Diagnostic Radiology (D.S.), The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030-4009
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15
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Dutta P, Salzillo TC, Pudakalakatti S, Gammon ST, Kaipparettu BA, McAllister F, Wagner S, Frigo DE, Logothetis CJ, Zacharias NM, Bhattacharya PK. Assessing Therapeutic Efficacy in Real-time by Hyperpolarized Magnetic Resonance Metabolic Imaging. Cells 2019; 8:E340. [PMID: 30978984 PMCID: PMC6523855 DOI: 10.3390/cells8040340] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 03/30/2019] [Accepted: 04/06/2019] [Indexed: 01/22/2023] Open
Abstract
Precisely measuring tumor-associated alterations in metabolism clinically will enable the efficient assessment of therapeutic responses. Advances in imaging technologies can exploit the differences in cancer-associated cell metabolism as compared to normal tissue metabolism, linking changes in target metabolism to therapeutic efficacy. Metabolic imaging by Positron Emission Tomography (PET) employing 2-fluoro-deoxy-glucose ([18F]FDG) has been used as a routine diagnostic tool in the clinic. Recently developed hyperpolarized Magnetic Resonance (HP-MR), which radically increases the sensitivity of conventional MRI, has created a renewed interest in functional and metabolic imaging. The successful translation of this technique to the clinic was achieved recently with measurements of 13C-pyruvate metabolism. Here, we review the potential clinical roles for metabolic imaging with hyperpolarized MRI as applied in assessing therapeutic intervention in different cancer systems.
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Affiliation(s)
- Prasanta Dutta
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Travis C Salzillo
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- The University of Texas MD Anderson Cancer Center UT Health Graduate School of Biomedical Sciences, Houston, TX 77030, USA.
| | - Shivanand Pudakalakatti
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Seth T Gammon
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Benny A Kaipparettu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Florencia McAllister
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Shawn Wagner
- Biomedical Imaging Research Institute Cedars Sinai Medical Center, Los Angeles, CA 90048, USA.
| | - Daniel E Frigo
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
| | - Christopher J Logothetis
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Department of Clinical Therapeutics, University of Athens, 11527 Athens, Greece.
| | - Niki M Zacharias
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- 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.
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16
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Grist JT, McLean MA, Riemer F, Schulte RF, Deen SS, Zaccagna F, Woitek R, Daniels CJ, Kaggie JD, Matys T, Patterson I, Slough R, Gill AB, Chhabra A, Eichenberger R, Laurent MC, Comment A, Gillard JH, Coles AJ, Tyler DJ, Wilkinson I, Basu B, Lomas DJ, Graves MJ, Brindle KM, Gallagher FA. Quantifying normal human brain metabolism using hyperpolarized [1- 13C]pyruvate and magnetic resonance imaging. Neuroimage 2019; 189:171-179. [PMID: 30639333 PMCID: PMC6435102 DOI: 10.1016/j.neuroimage.2019.01.027] [Citation(s) in RCA: 124] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 01/08/2019] [Accepted: 01/10/2019] [Indexed: 01/14/2023] Open
Abstract
Hyperpolarized 13C Magnetic Resonance Imaging (13C-MRI) provides a highly sensitive tool to probe tissue metabolism in vivo and has recently been translated into clinical studies. We report the cerebral metabolism of intravenously injected hyperpolarized [1-13C]pyruvate in the brain of healthy human volunteers for the first time. Dynamic acquisition of 13C images demonstrated 13C-labeling of both lactate and bicarbonate, catalyzed by cytosolic lactate dehydrogenase and mitochondrial pyruvate dehydrogenase respectively. This demonstrates that both enzymes can be probed in vivo in the presence of an intact blood-brain barrier: the measured apparent exchange rate constant (kPL) for exchange of the hyperpolarized 13C label between [1-13C]pyruvate and the endogenous lactate pool was 0.012 ± 0.006 s-1 and the apparent rate constant (kPB) for the irreversible flux of [1-13C]pyruvate to [13C]bicarbonate was 0.002 ± 0.002 s-1. Imaging also revealed that [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate were significantly higher in gray matter compared to white matter. Imaging normal brain metabolism with hyperpolarized [1-13C]pyruvate and subsequent quantification, have important implications for interpreting pathological cerebral metabolism in future studies.
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Affiliation(s)
- James T Grist
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Mary A McLean
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Frank Riemer
- Department of Radiology, University of Cambridge, Cambridge, UK
| | | | - Surrin S Deen
- Department of Radiology, University of Cambridge, Cambridge, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Fulvio Zaccagna
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Ramona Woitek
- Department of Radiology, University of Cambridge, Cambridge, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | | | - Joshua D Kaggie
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Ilse Patterson
- Radiology, Cambridge University Hospitals, Cambridge, UK
| | - Rhys Slough
- Radiology, Cambridge University Hospitals, Cambridge, UK
| | - Andrew B Gill
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Anita Chhabra
- Pharmacy, Cambridge University Hospitals, Cambridge, UK
| | | | | | - Arnaud Comment
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK; GE Healthcare, Chalfont St Giles, UK
| | | | - Alasdair J Coles
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Damian J Tyler
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK
| | - Ian Wilkinson
- Department of Medicine, University of Cambridge and Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Bristi Basu
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - David J Lomas
- Department of Radiology, University of Cambridge, Cambridge, UK
| | | | - Kevin M Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
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17
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Chen HY, Gordon JW, Bok RA, Cao P, von Morze C, van Criekinge M, Milshteyn E, Carvajal L, Hurd RE, Kurhanewicz J, Vigneron DB, Larson PE. Pulse sequence considerations for quantification of pyruvate-to-lactate conversion k PL in hyperpolarized 13 C imaging. NMR IN BIOMEDICINE 2019; 32:e4052. [PMID: 30664305 PMCID: PMC6380928 DOI: 10.1002/nbm.4052] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 10/16/2018] [Accepted: 11/09/2018] [Indexed: 05/26/2023]
Abstract
Hyperpolarized 13 C MRI takes advantage of the unprecedented 50 000-fold signal-to-noise ratio enhancement to interrogate cancer metabolism in patients and animals. It can measure the pyruvate-to-lactate conversion rate, kPL , a metabolic biomarker of cancer aggressiveness and progression. Therefore, it is crucial to evaluate kPL reliably. In this study, three sequence components and parameters that modulate kPL estimation were identified and investigated in model simulations and through in vivo animal studies using several specifically designed pulse sequences. These factors included a magnetization spoiling effect due to RF pulses, a crusher gradient-induced flow suppression, and intrinsic image weightings due to relaxation. Simulation showed that the RF-induced magnetization spoiling can be substantially improved using an inputless kPL fitting. In vivo studies found a significantly higher apparent kPL with an additional gradient that leads to flow suppression (kPL,FID-Delay,Crush /kPL,FID-Delay = 1.37 ± 0.33, P < 0.01, N = 6), which agrees with simulation outcomes (12.5% kPL error with Δv = 40 cm/s), indicating that the gradients predominantly suppressed flowing pyruvate spins. Significantly lower kPL was found using a delayed free induction decay (FID) acquisition versus a minimum-TE version (kPL,FID-Delay /kPL,FID = 0.67 ± 0.09, P < 0.01, N = 5), and the lactate peak had broader linewidth than pyruvate (Δωlactate /Δωpyruvate = 1.32 ± 0.07, P < 0.000 01, N = 13). This illustrated that lactate's T2 *, shorter than that of pyruvate, can affect calculated kPL values. We also found that an FID sequence yielded significantly lower kPL versus a double spin-echo sequence that includes spin-echo spoiling, flow suppression from crusher gradients, and more T2 weighting (kPL,DSE /kPL,FID = 2.40 ± 0.98, P < 0.0001, N = 7). In summary, the pulse sequence, as well as its interaction with pharmacokinetics and the tissue microenvironment, can impact and be optimized for the measurement of kPL . The data acquisition and analysis pipelines can work synergistically to provide more robust and reproducible kPL measures for future preclinical and clinical studies.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Peng Cao
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Cornelius von Morze
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Mark van Criekinge
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Eugene Milshteyn
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Ralph E. Hurd
- Department of Radiology, Stanford University, California, United States
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Peder E.Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
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18
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Walker CM, Fuentes D, Larson PEZ, Kundra V, Vigneron DB, Bankson JA. Effects of excitation angle strategy on quantitative analysis of hyperpolarized pyruvate. Magn Reson Med 2019; 81:3754-3762. [PMID: 30793791 DOI: 10.1002/mrm.27687] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 12/21/2018] [Accepted: 01/18/2019] [Indexed: 12/21/2022]
Abstract
PURPOSE Various excitation strategies have been proposed for dynamic imaging of hyperpolarized agents such as [1-13 C]-pyruvate, but the impact of these strategies on quantitative evaluation of signal evolution remains unclear. To better understand their relative performance, we compared the accuracy and repeatability of measurements made using variable excitation angle strategies and conventional constant excitation angle strategies. METHODS Signal evolution for constant and variable excitation angle schedules was simulated using a pharmacokinetic model of hyperpolarized pyruvate with 2 chemical pools and 2 physical compartments. Noisy synthetic data were then fit using the same pharmacokinetic model with the apparent chemical exchange term as an unknown, and fit results were compared with simulation parameters to determine accuracy and reproducibility. RESULTS Constant excitations and a variable excitation strategy that maximizes the HP lactate signal yielded data that supported quantitative analyses with similar accuracy and repeatability. Variable excitation angle strategies that were designed to produce a constant signal level resulted in lower signal and worse quantitative accuracy and repeatability, particularly for longer acquisition times. CONCLUSIONS These results suggest that either constant excitation angle or variable excitation angles that attempt to maximize total signal, as opposed to maintaining a constant signal level, are preferred for metabolic quantification using hyperpolarized pyruvate.
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Affiliation(s)
- Christopher M Walker
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - David Fuentes
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California
| | - Vikas Kundra
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas.,Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, California
| | - James A Bankson
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
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19
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Tang S, Milshteyn E, Reed G, Gordon J, Bok R, Zhu X, Zhu Z, Vigneron DB, Larson PE. A regional bolus tracking and real-time B 1 calibration method for hyperpolarized 13 C MRI. Magn Reson Med 2019; 81:839-851. [PMID: 30277268 PMCID: PMC6289616 DOI: 10.1002/mrm.27391] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 05/14/2018] [Accepted: 05/15/2018] [Indexed: 01/13/2023]
Abstract
PURPOSE Acquisition timing and B1 calibration are two key factors that affect the quality and accuracy of hyperpolarized 13 C MRI. The goal of this project was to develop a new approach using regional bolus tracking to trigger Bloch-Siegert B1 mapping and real-time B1 calibration based on regional B1 measurements, followed by dynamic imaging of hyperpolarized 13 C metabolites in vivo. METHODS The proposed approach was implemented on a system which allows real-time data processing and real-time control on the sequence. Real-time center frequency calibration upon the bolus arrival was also added. The feasibility of applying the proposed framework for in vivo hyperpolarized 13 C imaging was tested on healthy rats, tumor-bearing mice and a healthy volunteer on a clinical 3T scanner following hyperpolarized [1-13 C]pyruvate injection. Multichannel receive coils were used in the human study. RESULTS Automatic acquisition timing based on either regional bolus peak or bolus arrival was achieved with the proposed framework. Reduced blurring artifacts in real-time reconstructed images were observed with real-time center frequency calibration. Real-time computed B1 scaling factors agreed with real-time acquired B1 maps. Flip angle correction using B1 maps results in a more consistent quantification of metabolic activity (i.e, pyruvate-to-lactate conversion, kPL ). Experiment recordings are provided to demonstrate the real-time actions during the experiment. CONCLUSIONS The proposed method was successfully demonstrated on animals and a human volunteer, and is anticipated to improve the efficient use of the hyperpolarized signal as well as the accuracy and robustness of hyperpolarized 13 C imaging.
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Affiliation(s)
- Shuyu Tang
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Eugene Milshteyn
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | | | - Jeremy Gordon
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Xucheng Zhu
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Zihan Zhu
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Daniel B. Vigneron
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Peder E.Z. Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
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20
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Larson PEZ, Chen HY, Gordon JW, Korn N, Maidens J, Arcak M, Tang S, Criekinge M, Carvajal L, Mammoli D, Bok R, Aggarwal R, Ferrone M, Slater JB, Nelson SJ, Kurhanewicz J, Vigneron DB. Investigation of analysis methods for hyperpolarized 13C-pyruvate metabolic MRI in prostate cancer patients. NMR IN BIOMEDICINE 2018. [PMID: 30230646 DOI: 10.1002/nbm.3997e3997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
MRI using hyperpolarized (HP) carbon-13 pyruvate is being investigated in clinical trials to provide non-invasive measurements of metabolism for cancer and cardiac imaging. In this project, we applied HP [1-13 C]pyruvate dynamic MRI in prostate cancer to measure the conversion from pyruvate to lactate, which is expected to increase in aggressive cancers. The goal of this work was to develop and test analysis methods for improved quantification of this metabolic conversion. In this work, we compared specialized kinetic modeling methods to estimate the pyruvate-to-lactate conversion rate, kPL , as well as the lactate-to-pyruvate area-under-curve (AUC) ratio. The kinetic modeling included an "inputless" method requiring no assumptions regarding the input function, as well as a method incorporating bolus characteristics in the fitting. These were first evaluated with simulated data designed to match human prostate data, where we examined the expected sensitivity of metabolism quantification to variations in kPL , signal-to-noise ratio (SNR), bolus characteristics, relaxation rates, and B1 variability. They were then applied to 17 prostate cancer patient datasets. The simulations indicated that the inputless method with fixed relaxation rates provided high expected accuracy with no sensitivity to bolus characteristics. The AUC ratio showed an undesired strong sensitivity to bolus variations. Fitting the input function as well did not improve accuracy over the inputless method. In vivo results showed qualitatively accurate kPL maps with inputless fitting. The AUC ratio was sensitive to bolus delivery variations. Fitting with the input function showed high variability in parameter maps. Overall, we found the inputless kPL fitting method to be a simple, robust approach for quantification of metabolic conversion following HP [1-13 C]pyruvate injection in human prostate cancer studies. This study also provided initial ranges of HP [1-13 C]pyruvate parameters (SNR, kPL , bolus characteristics) in the human prostate.
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Affiliation(s)
- Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Natalie Korn
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - John Maidens
- Department of Electrical Engineering and Computer Sciences, University of California - Berkeley, Berkeley, California
| | - Murat Arcak
- Department of Electrical Engineering and Computer Sciences, University of California - Berkeley, Berkeley, California
| | - Shuyu Tang
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Mark Criekinge
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Daniele Mammoli
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Rahul Aggarwal
- Department of Medicine, University of California - San Francisco, San Francisco, California
| | - Marcus Ferrone
- Department of Clinical Pharmacy, University of California - San Francisco, San Francisco, California
| | - James B Slater
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
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21
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Larson PEZ, Chen HY, Gordon JW, Korn N, Maidens J, Arcak M, Tang S, Criekinge M, Carvajal L, Mammoli D, Bok R, Aggarwal R, Ferrone M, Slater JB, Nelson SJ, Kurhanewicz J, Vigneron DB. Investigation of analysis methods for hyperpolarized 13C-pyruvate metabolic MRI in prostate cancer patients. NMR IN BIOMEDICINE 2018; 31:e3997. [PMID: 30230646 PMCID: PMC6392436 DOI: 10.1002/nbm.3997] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 06/14/2018] [Accepted: 06/28/2018] [Indexed: 05/08/2023]
Abstract
MRI using hyperpolarized (HP) carbon-13 pyruvate is being investigated in clinical trials to provide non-invasive measurements of metabolism for cancer and cardiac imaging. In this project, we applied HP [1-13 C]pyruvate dynamic MRI in prostate cancer to measure the conversion from pyruvate to lactate, which is expected to increase in aggressive cancers. The goal of this work was to develop and test analysis methods for improved quantification of this metabolic conversion. In this work, we compared specialized kinetic modeling methods to estimate the pyruvate-to-lactate conversion rate, kPL , as well as the lactate-to-pyruvate area-under-curve (AUC) ratio. The kinetic modeling included an "inputless" method requiring no assumptions regarding the input function, as well as a method incorporating bolus characteristics in the fitting. These were first evaluated with simulated data designed to match human prostate data, where we examined the expected sensitivity of metabolism quantification to variations in kPL , signal-to-noise ratio (SNR), bolus characteristics, relaxation rates, and B1 variability. They were then applied to 17 prostate cancer patient datasets. The simulations indicated that the inputless method with fixed relaxation rates provided high expected accuracy with no sensitivity to bolus characteristics. The AUC ratio showed an undesired strong sensitivity to bolus variations. Fitting the input function as well did not improve accuracy over the inputless method. In vivo results showed qualitatively accurate kPL maps with inputless fitting. The AUC ratio was sensitive to bolus delivery variations. Fitting with the input function showed high variability in parameter maps. Overall, we found the inputless kPL fitting method to be a simple, robust approach for quantification of metabolic conversion following HP [1-13 C]pyruvate injection in human prostate cancer studies. This study also provided initial ranges of HP [1-13 C]pyruvate parameters (SNR, kPL , bolus characteristics) in the human prostate.
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Affiliation(s)
- Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Natalie Korn
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - John Maidens
- Department of Electrical Engineering and Computer Sciences, University of California – Berkeley, Berkeley, California
| | - Murat Arcak
- Department of Electrical Engineering and Computer Sciences, University of California – Berkeley, Berkeley, California
| | - Shuyu Tang
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Mark Criekinge
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Daniele Mammoli
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Rahul Aggarwal
- Department of Medicine, University of California – San Francisco, San Francisco, California
| | - Marcus Ferrone
- Department of Clinical Pharmacy, University of California – San Francisco, San Francisco, California
| | - James B. Slater
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
| | - Sarah J. Nelson
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California – San Francisco, San Francisco, California
- UC Berkeley–UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California
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