1
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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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2
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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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3
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Chowdhury R, Moorthy M, Smith L, Mueller CA, Gong F, Rogers HJ, Papoutsaki MV, Syer T, Brembilla G, Singh S, Retter A, Parry T, Clemente J, Caselton L, Jeraj H, Bullock M, Mathew M, Chung TT, Akker S, Chapple P, Salsbury GA, Bainbridge A, Atkinson D, Gadian DG, Srirangalingam U, Punwani S. First-in-human in-vivo depiction of paraganglioma metabolism by hyperpolarised 13C-magnetic resonance. BJR Case Rep 2023; 9:20220089. [PMID: 37928705 PMCID: PMC10621573 DOI: 10.1259/bjrcr.20220089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/31/2023] [Accepted: 08/10/2023] [Indexed: 11/07/2023] Open
Abstract
Phaeochromocytomas (PCC) and paragangliomas (PGL), cumulatively referred to as PPGLs, are neuroendocrine tumours arising from neural crest-derived cells in the sympathetic and parasympathetic nervous systems. Predicting future tumour behaviour and the likelihood of metastatic disease remains problematic as genotype-phenotype correlations are limited, the disease has variable penetrance and, to date, no reliable molecular, cellular or histological markers have emerged. Tumour metabolism quantification can be considered as a method to delineating tumour aggressiveness by utilising hyperpolarised 13 C-MR (HP-MR). The technique may provide an opportunity to non-invasively characterise disease behaviour. Here, we present the first instance of the analysis of PPGL metabolism via HP-MR in a single case.
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Affiliation(s)
- Rafat Chowdhury
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Myuri Moorthy
- Department of Endocrinology, University College London Hospital, London, UK
| | - Lorna Smith
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | | | - Fiona Gong
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Harriet J Rogers
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | | | - Tom Syer
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Giorgio Brembilla
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Saurabh Singh
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Adam Retter
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Thomas Parry
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Joey Clemente
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Lucy Caselton
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Hassan Jeraj
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Max Bullock
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Manju Mathew
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - Teng Teng Chung
- Department of Endocrinology, University College London Hospital, London, UK
| | - Scott Akker
- Department of Endocrinology, St Bartholomew’s Hospital, London, UK
| | - Paul Chapple
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Grace A Salsbury
- Department of Endocrinology, University College London Hospital, London, UK
| | - Alan Bainbridge
- Department of Medical Physics and Biomedical Engineering, University College London Hospitals NHS Foundation Trust, London, UK
| | - David Atkinson
- Centre for Medical Imaging, Division of Medicine, University College London, London, UK
| | - David G Gadian
- UCL Great Ormond Street Institute of Child Health, London, UK
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4
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Arponen O, Wodtke P, Gallagher FA, Woitek R. Hyperpolarised 13C-MRI using 13C-pyruvate in breast cancer: A review. Eur J Radiol 2023; 167:111058. [PMID: 37666071 DOI: 10.1016/j.ejrad.2023.111058] [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: 06/24/2023] [Revised: 08/14/2023] [Accepted: 08/21/2023] [Indexed: 09/06/2023]
Abstract
Tumour metabolism can be imaged with a novel imaging technique termed hyperpolarised carbon-13 (13C)-MRI using probes, i.e., endogenously found molecules that are labeled with 13C. Hyperpolarisation of the 13C label increases the sensitivity to a level that allows dynamic imaging of the distribution and metabolism of the probes. Dynamic imaging of [1-13C]pyruvate metabolism is of particular biological interest in cancer because of the Warburg effect resulting in the intratumoural accumulation of [1-13C]pyruvate and conversion to [1-13C]lactate. Numerous preclinical studies in breast cancer and other tumours have shown that hyperpolarised 13C-pyruvate has potential for metabolic phenotyping and response assessment at earlier timepoints than the current clinical imaging techniques allow. The clinical feasibility of hyperpolarised 13C-MRI after the injection of pyruvate in patients with breast cancer has now been demonstrated, with increased 13C-label exchange between pyruvate and lactate present in higher grade tumours with associated increased expression of the monocarboxylate transporter 1 (MCT1), the transmembrane transporter mediating intracellular pyruvate uptake, and lactate dehydrogenase (LDH) as the enzyme catalysing the conversion of pyruvate to lactate. Furthermore, a study in patients with breast cancer undergoing neoadjuvant chemotherapy suggested that early changes in 13C-label exchange can distinguish between patients who reach pathologic complete response (pCR) and those who do not. This review summarises the current literature on preclinical and clinical research on hyperpolarised 13C-MRI with [1-13C]-pyruvate in breast cancer imaging.
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Affiliation(s)
- Otso Arponen
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom.
| | - Pascal Wodtke
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Center, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Center, Cambridge, United Kingdom
| | - Ramona Woitek
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Center, Cambridge, United Kingdom; Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Danube Private University, Krems, Austria
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5
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Chowdhury R, Mueller CA, Smith L, Gong F, Papoutsaki M, Rogers H, Syer T, Singh S, Brembilla G, Retter A, Bullock M, Caselton L, Mathew M, Dineen E, Parry T, Hennig J, von Elverfeldt D, Schmidt AB, Hövener J, Emberton M, Atkinson D, Bainbridge A, Gadian DG, Punwani S. Quantification of Prostate Cancer Metabolism Using 3D Multiecho bSSFP and Hyperpolarized [1- 13 C] Pyruvate: Metabolism Differs Between Tumors of the Same Gleason Grade. J Magn Reson Imaging 2023; 57:1865-1875. [PMID: 36315000 PMCID: PMC10946772 DOI: 10.1002/jmri.28467] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/09/2022] [Accepted: 09/09/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Three-dimensional (3D) multiecho balanced steady-state free precession (ME-bSSFP) has previously been demonstrated in preclinical hyperpolarized (HP) 13 C-MRI in vivo experiments, and it may be suitable for clinical metabolic imaging of prostate cancer (PCa). PURPOSE To validate a signal simulation framework for the use of sequence parameter optimization. To demonstrate the feasibility of ME-bSSFP for HP 13 C-MRI in patients. To evaluate the metabolism in PCa measured by ME-bSSFP. STUDY TYPE Retrospective single-center cohort study. PHANTOMS/POPULATION Phantoms containing aqueous solutions of [1-13 C] lactate (2.3 M) and [13 C] urea (8 M). Eight patients (mean age 67 ± 6 years) with biopsy-confirmed Gleason 3 + 4 (n = 7) and 4 + 3 (n = 1) PCa. FIELD STRENGTH/SEQUENCES: 1 H MRI at 3 T with T2 -weighted turbo spin-echo sequence used for spatial localization and spoiled dual gradient-echo sequence used for B0 -field measurement. ME-bSSFP sequence for 13 C MR spectroscopic imaging with retrospective multipoint IDEAL metabolite separation. ASSESSMENT The primary endpoint was the analysis of pyruvate-to-lactate conversion in PCa and healthy prostate regions of interest (ROIs) using model-free area under the curve (AUC) ratios and a one-directional kinetic model (kP ). The secondary objectives were to investigate the correlation between simulated and experimental ME-bSSFP metabolite signals for HP 13 C-MRI parameter optimization. STATISTICAL TESTS Pearson correlation coefficients with 95% confidence intervals and paired t-tests. The level of statistical significance was set at P < 0.05. RESULTS Strong correlations between simulated and empirical ME-bSSFP signals were found (r > 0.96). Therefore, the simulation framework was used for sequence optimization. Whole prostate metabolic HP 13 C-MRI, observing the conversion of pyruvate into lactate, with a temporal resolution of 6 seconds was demonstrated using ME-bSSFP. Both assessed metrics resulted in significant differences between PCa (mean ± SD) (AUC = 0.33 ± 012, kP = 0.038 ± 0.014) and healthy (AUC = 0.15 ± 0.10, kP = 0.011 ± 0.007) ROIs. DATA CONCLUSION Metabolic HP 13 C-MRI in the prostate using ME-bSSFP allows for differentiation between aggressive PCa and healthy tissue. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rafat Chowdhury
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Christoph A. Mueller
- Department of Radiology, Medical Physics, Medical CenterUniversity of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Lorna Smith
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Fiona Gong
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | | | - Harriet Rogers
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Tom Syer
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Saurabh Singh
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Giorgio Brembilla
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Adam Retter
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Max Bullock
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Lucy Caselton
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Manju Mathew
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Eoin Dineen
- Division of Surgery and Interventional ScienceUniversity College LondonLondonUK
| | - Thomas Parry
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical CenterUniversity of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Dominik von Elverfeldt
- Department of Radiology, Medical Physics, Medical CenterUniversity of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Andreas B. Schmidt
- Department of Radiology, Medical Physics, Medical CenterUniversity of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
- German Cancer Consortium (DKTK)partner site Freiburg and German Cancer Research Center (DKFZ)HeidelbergGermany
- Department of Radiology, and Neuroradiology, Section Biomedical Imaging, MOIN CC, University Medical Center Schleswig‐HolsteinUniversity of KielKielGermany
| | - Jan‐Bernd Hövener
- Department of Radiology, and Neuroradiology, Section Biomedical Imaging, MOIN CC, University Medical Center Schleswig‐HolsteinUniversity of KielKielGermany
| | - Mark Emberton
- Division of Surgery and Interventional ScienceUniversity College LondonLondonUK
| | - David Atkinson
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
| | - Alan Bainbridge
- Department of Medical Physics and Biomedical EngineeringUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - David G. Gadian
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
- UCL Great Ormond Street Institute of Child HealthLondonUK
| | - Shonit Punwani
- Centre for Medical Imaging, Division of MedicineUniversity College LondonLondonUK
- Department of RadiologyUniversity College London Hospitals NHS Foundation TrustLondonUK
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6
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Chowdhury R, Papoutsaki MV, Müller CA, Smith L, Gong F, Bullock M, Rogers H, Mathew M, Syer T, Singh S, Retter A, Caselton L, Ryu J, Oliver-Taylor A, Golay X, Bainbridge A, Gadian DG, Punwani S. A reproducible dynamic phantom for sequence testing in hyperpolarised 13C-magnetic resonance. Br J Radiol 2022; 95:20210770. [PMID: 35230136 PMCID: PMC10996405 DOI: 10.1259/bjr.20210770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 02/10/2022] [Accepted: 02/28/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To develop a phantom system which can be integrated with an automated injection system, eliminating the experimental variability that arises with manual injection; for the purposes of pulse sequence testing and metric derivation in hyperpolarised 13C-MR. METHODS The custom dynamic phantom was machined from Ultem and filled with a nicotinamide adenine dinucleotide and lactate dehydrogenase mixture dissolved in phosphate buffered saline. Hyperpolarised [1-13C]-pyruvate was then injected into the phantom (n = 8) via an automated syringe pump and the conversion of pyruvate to lactate monitored through a 13C imaging sequence. RESULTS The phantom showed low coefficient of variation for the lactate to pyruvate peak signal heights (11.6%) and dynamic area-under curve ratios (11.0%). The variance for the lactate dehydrogenase enzyme rate constant (kP) was also seen to be low at 15.6%. CONCLUSION The dynamic phantom demonstrates high reproducibility for quantification of 13C-hyperpolarised MR-derived metrics. Establishing such a phantom is needed to facilitate development of hyperpolarsed 13C-MR pulse sequenced; and moreover, to enable multisite hyperpolarised 13C-MR clinical trials where assessment of metric variability across sites is critical. ADVANCES IN KNOWLEDGE The dynamic phantom developed during the course of this study will be a useful tool in testing new pulse sequences and standardisation in future hyperpolarised work.
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Affiliation(s)
- Rafat Chowdhury
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | | | - Christoph A Müller
- Department of Radiology, Medical Physics, Medical Center
– University of Freiburg, Faculty of Medicine, University of
Freiburg, Freiburg,
Germany
- German Cancer Consortium (DKTK), partner site Freiburg, German
Cancer Research Center (DKFZ),
Heidelberg, Germany
| | | | - Fiona Gong
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Max Bullock
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Harriet Rogers
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Manju Mathew
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Tom Syer
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Saurabh Singh
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Adam Retter
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Lucy Caselton
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | - Jung Ryu
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
| | | | - Xavier Golay
- Gold Standard Phantoms Limited,
London, UK
- Department of Brain Repair and Rehabilitation, Institute of
Neurology, Queen’s Square, University College
London, London,
UK
| | - Alan Bainbridge
- Department of Medical Physics and Biomedical Engineering,
University College London Hospitals,
London, UK
| | - David G Gadian
- UCL Great Ormond Street Institute of Child
Health, London, UK
| | - Shonit Punwani
- Centre for Medical Imaging, Division of Medicine, University
College London, London,
UK
- Department of Radiology, University College London Hospitals
NHS Foundation Trust, London,
UK
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7
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Lee PM, Chen HY, Gordon JW, Zhu Z, Larson PE, 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 PMCID: PMC8565779 DOI: 10.1002/mrm.28901] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [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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8
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Woitek R, Gallagher FA. The use of hyperpolarised 13C-MRI in clinical body imaging to probe cancer metabolism. Br J Cancer 2021; 124:1187-1198. [PMID: 33504974 PMCID: PMC8007617 DOI: 10.1038/s41416-020-01224-6] [Citation(s) in RCA: 16] [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: 09/21/2019] [Revised: 11/19/2020] [Accepted: 12/02/2020] [Indexed: 01/30/2023] Open
Abstract
Metabolic reprogramming is one of the hallmarks of cancer and includes the Warburg effect, which is exhibited by many tumours. This can be exploited by positron emission tomography (PET) as part of routine clinical cancer imaging. However, an emerging and alternative method to detect altered metabolism is carbon-13 magnetic resonance imaging (MRI) following injection of hyperpolarised [1-13C]pyruvate. The technique increases the signal-to-noise ratio for the detection of hyperpolarised 13C-labelled metabolites by several orders of magnitude and facilitates the dynamic, noninvasive imaging of the exchange of 13C-pyruvate to 13C-lactate over time. The method has produced promising preclinical results in the area of oncology and is currently being explored in human imaging studies. The first translational studies have demonstrated the safety and feasibility of the technique in patients with prostate, renal, breast and pancreatic cancer, as well as revealing a successful response to treatment in breast and prostate cancer patients at an earlier stage than multiparametric MRI. This review will focus on the strengths of the technique and its applications in the area of oncological body MRI including noninvasive characterisation of disease aggressiveness, mapping of tumour heterogeneity, and early response assessment. A comparison of hyperpolarised 13C-MRI with state-of-the-art multiparametric MRI is likely to reveal the unique additional information and applications offered by the technique.
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Affiliation(s)
- Ramona Woitek
- Department of Radiology, University of Cambridge, Cambridge, UK.
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
- Cancer Research UK Cambridge Centre, Cambridge, UK.
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, UK
- Cancer Research UK Cambridge Centre, Cambridge, UK
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