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Wodtke P, Grashei M, Schilling F. Quo Vadis Hyperpolarized 13C MRI? Z Med Phys 2025; 35:8-32. [PMID: 38160135 PMCID: PMC11910262 DOI: 10.1016/j.zemedi.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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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2
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Sahin S, Haller AB, Gordon J, Kim Y, Hu J, Nickles T, Dai Q, Leynes AP, Vigneron DB, Wang ZJ, Larson PEZ. Spatially constrained hyperpolarized 13C MRI pharmacokinetic rate constant map estimation using a digital brain phantom and a U-Net. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2025; 371:107832. [PMID: 39818019 PMCID: PMC11807744 DOI: 10.1016/j.jmr.2025.107832] [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: 11/15/2024] [Accepted: 01/05/2025] [Indexed: 01/18/2025]
Abstract
Fitting rate constants to Hyperpolarized [1-13C]Pyruvate (HP C13) MRI data is a promising approach for quantifying metabolism in vivo. Current methods typically fit each voxel of the dataset using a least-squares objective. With these methods, each voxel is considered independently, and the spatial relationships are not considered during fitting. In this work, we use a convolutional neural network, a U-Net, with convolutions across the 2D spatial dimensions to estimate pyruvate-to-lactate conversion rate, kPL, maps from dynamic HP C13 datasets. We designed a framework for creating simulated anatomically accurate brain data that matches typical HP C13 characteristics to provide large amounts of data for training with ground truth results. The U-Net is initially trained with the digital phantom data and then further trained with in vivo datasets for regularization. In simulation where ground-truth kPL maps are available, the U-Net outperforms voxel-wise fitting with and without spatiotemporal denoising, particularly for low SNR data. In vivo data was evaluated qualitatively, as no ground truth is available, and before regularization the U-Net predicted kPL maps appear oversmoothed. After further training with in vivo data, the resulting kPL maps appear more realistic. This study demonstrates how to use a U-Net to estimate rate constant maps for HP C13 data, including a comprehensive framework for generating a large amount of anatomically realistic simulated data and an approach for regularization. This simulation and architecture provide a foundation that can be built upon in the future for improved performance.
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Affiliation(s)
- Sule Sahin
- UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA.
| | - Anna Bennett Haller
- UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Jeremy Gordon
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Yaewon Kim
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Jasmine Hu
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Tanner Nickles
- UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Qing Dai
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA; Radiological Sciences, University of California, Los Angeles, 300 UCLA Medical Plaza, Los Angeles, CA 90095, USA
| | - Andrew P Leynes
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Daniel B Vigneron
- UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Zhen Jane Wang
- Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
| | - Peder E Z Larson
- UC Berkeley - UCSF Graduate Program in Bioengineering, 1700 4th St, San Francisco, CA 94158, USA; Radiology and Biomedical Imaging, University of California, San Francisco, 1700 4th St, San Francisco, CA 94158, USA
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3
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Dingwell DA, Cunningham CH. Particle-based MR modeling with diffusion, microstructure, and enzymatic reactions. Magn Reson Med 2025; 93:369-383. [PMID: 39250417 DOI: 10.1002/mrm.30279] [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: 03/08/2024] [Revised: 07/21/2024] [Accepted: 08/14/2024] [Indexed: 09/11/2024]
Abstract
PURPOSE To develop a novel particle-based in silico MR model and demonstrate applications of this model to signal mechanisms which are affected by the spatial organization of particles, including metabolic reaction kinetics, microstructural effects on diffusion, and radiofrequency (RF) refocusing effects in gradient-echo sequences. METHODS The model was developed by integrating a forward solution of the Bloch equations with a Brownian dynamics simulator. Simulation configurations were then designed to model MR signal dynamics of interest, with a primary focus on hyperpolarized 13C MRI methods. Phantom scans and spectrophotometric assays were conducted to validate model results in vitro. RESULTS The model accurately reproduced the reaction kinetics of enzyme-mediated conversion of pyruvate to lactate. When varying proportions of restrictive structure were added to the reaction volume, nonlinear changes in the reaction rate measured in vitro were replicated in silico. Modeling of RF refocusing effects characterized the degree of diffusion-weighted contribution from preserved residual magnetization in nonspoiled gradient-echo sequences. CONCLUSIONS These results show accurate reproduction of a range of MR signal mechanisms, establishing the model's capability to investigate the multifactorial signal dynamics such as those underlying hyperpolarized 13C MRI data.
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Affiliation(s)
- Dylan Archer Dingwell
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
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何 长, 何 华, 杨 小, 幸 浩, 吕 粟, 吴 敏. [Research Progress in Applying Hyperpolarized 13C Labeling Technology in Neurological Metabolic Diagnostics]. SICHUAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF SICHUAN UNIVERSITY. MEDICAL SCIENCE EDITION 2024; 55:1343-1349. [PMID: 39990827 PMCID: PMC11839364 DOI: 10.12182/20241160101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/01/2024] [Indexed: 02/25/2025]
Abstract
By using hyperpolarized 13C labeling technology, the magnetic resonance signals of 13C-labeled metabolic substrates are enhanced, which enables the in vivo monitoring of their metabolic states through magnetic resonance spectroscopy. Compared with traditional non-invasive metabolic diagnostic technologies, hyperpolarized 13C technology exhibits a number of strengths, including real-time monitoring, high precision, non-invasiveness, the absence of radiation, and the ability to assess a broader range of metabolic pathways, showing great potential for application in the treatment of glioma, stroke, Alzheimer disease, and cerebral injury. Following the approval of [1-13C]-pyruvate for clinical trials by U.S. Food and Drug Administration (FDA), there has been growing academic interest in this technology. Currently, the primary challenge lies in creating more probes and promoting their clinical applications. Herein, we outlined the principles of hyperpolarized 13C labeling technology, examined its current role in neurological metabolic diagnostics, and explored the future directions, including conducting hyperpolarized 13C magnetic resonance spectroscopy (MRS) technology at higher magnetic field strengths (such as 7T), designing additional magnetic resonance sequences specific to hyperpolarized 13C MRS, and its integration with other neuro-metabolic diagnostic methods.
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Affiliation(s)
- 长蔚 何
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
| | - 华龙 何
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
| | - 小方 杨
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
| | - 浩洋 幸
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
- 四川大学华西医院 放射科 磁共振研究中心 功能与分子影像四川省重点实验室 (成都 610041)Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology and Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu 610041, China
| | - 粟 吕
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
| | - 敏 吴
- 四川大学物理学院 (成都 610064)College of Physics, Sichuan University, Chengdu 610064, China
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5
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Diaz E, Sriram R, Gordon JW, Sinha A, Liu X, Sahin SI, Crane JC, Olson MP, Chen HY, Bernard JML, Vigneron DB, Wang ZJ, Xu D, Larson PEZ. Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:2627-2634. [PMID: 38710970 PMCID: PMC11522264 DOI: 10.1007/s10278-024-01100-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 05/08/2024]
Abstract
Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique.
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Affiliation(s)
- Ernesto Diaz
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Renuka Sriram
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Avantika Sinha
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Sule I Sahin
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
- UC Berkeley/UCSF Graduate Program in Bioengineering, Berkeley and San Francisco, CA, USA
| | - Jason C Crane
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Marram P Olson
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Jenna M L Bernard
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
- UC Berkeley/UCSF Graduate Program in Bioengineering, Berkeley and San Francisco, CA, USA
| | - Zhen Jane Wang
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
- UC Berkeley/UCSF Graduate Program in Bioengineering, Berkeley and San Francisco, CA, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA.
- UC Berkeley/UCSF Graduate Program in Bioengineering, Berkeley and San Francisco, CA, USA.
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6
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Blazey T, Shaw A, von Morze C. A vendor-neutral EPI sequence for hyperpolarized 13C MRI. Magn Reson Med 2024; 92:772-781. [PMID: 38525658 DOI: 10.1002/mrm.30090] [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: 09/29/2023] [Revised: 02/02/2024] [Accepted: 03/06/2024] [Indexed: 03/26/2024]
Abstract
PURPOSE To develop a flexible, vendor-neutral EPI sequence for hyperpolarized 13C metabolic imaging. METHODS An open-source EPI sequence consisting of a metabolite-specific spectral-spatial RF excitation pulse and a customizable EPI readout was created using the Pulseq framework. To explore the flexibility of our sequence, we tested several versions of the sequence including a symmetric 3D readout with different spatial resolutions for each metabolite (1.0 cm3 and 1.5 cm3). A multichamber phantom constructed with a Shepp-Logan geometry, containing two chambers filled with either natural abundance 13C compounds or hyperpolarized (HP) [1-13C]pyruvate, was used to test each sequence. For experiments involving HP [1-13C]pyruvate, a single chamber was prefilled with nicotinamide adenine dinucleotide hydride and lactate dehydrogenase to facilitate the conversion of [1-13C]pyruvate to [1-13C]lactate. All experiments were performed on a Siemens Prisma 3T scanner. RESULTS All the sequence variations localized natural-abundance 13C ethylene glycol and methanol to the appropriate compartment of the multichamber phantom. [1-13C]pyruvate was detectable in both chambers following the injection of HP [1-13C]pyruvate, whereas [1-13C]lactate was only found in the chamber containing nicotinamide adenine dinucleotide hydride and lactate dehydrogenase. The conversion rate from [1-13C]pyruvate to [1-13C]lactate (kPL) was 0.01 s-1 (95% confidence interval [0.00, 0.02]). CONCLUSION We have developed and tested a vendor-neutral EPI sequence for imaging HP 13C agents. We have made all of our sequence creation and image reconstruction code freely available online for other investigators to use.
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Affiliation(s)
- Tyler Blazey
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - Ashley Shaw
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
| | - Cornelius von Morze
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA
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7
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Gordon JW, Chen HY, Nickles T, Lee PM, Bok R, Ohliger MA, Okamoto K, Ko AH, Larson PEZ, Wang ZJ. Hyperpolarized 13C Metabolic MRI of Patients with Pancreatic Ductal Adenocarcinoma. J Magn Reson Imaging 2024; 60:741-749. [PMID: 38041836 PMCID: PMC11144260 DOI: 10.1002/jmri.29162] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/09/2023] [Accepted: 11/13/2023] [Indexed: 12/04/2023] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related death in the United States. However, early response assessment using the current approach of measuring changes in tumor size on computed tomography (CT) or MRI is challenging. PURPOSE To investigate the feasibility of hyperpolarized (HP) [1-13C]pyruvate MRI to quantify metabolism in the normal appearing pancreas and PDA, and to assess changes in PDA metabolism following systemic chemotherapy. STUDY TYPE Prospective. SUBJECTS Six patients (65.0 ± 7.6 years, 2 females) with locally advanced or metastatic PDA enrolled prior to starting a new line of systemic chemotherapy. FIELD STRENGTH/SEQUENCE 3-T, T1-weighted gradient echo, metabolite-selective 13C echoplanar imaging. ASSESSMENT Time-resolved HP [1-13C]pyruvate data were acquired before (N = 6) and 4-weeks after (N = 3) treatment initiation. Pyruvate metabolism, as quantified by pharmacokinetic modeling and metabolite area-under-the-curve ratios, was assessed in manually segmented PDA and normal appearing pancreas ROIs (N = 5). The change in tumor metabolism before and 4-weeks after treatment initiation was assessed in primary PDA (N = 2) and liver metastases (N = 1), and was compared to objective tumor response defined by response evaluation criteria in solid tumors (RECIST) on subsequent CTs. STATISTICAL TESTS Descriptive tests (mean ± standard deviation), model fit error for pharmacokinetic rate constants. RESULTS Primary PDA showed reduced alanine-to-lactate ratios when compared to normal pancreas, due to increased lactate-to-pyruvate or reduced alanine-to-pyruvate ratios. Of the three patients who received HP [1-13C]pyruvate MRI before and 4-weeks after treatment initiation, one patient had a primary tumor with early metabolic response (increase in alanine-to-lactate) and subsequent partial response according to RECIST, one patient had a primary tumor with relatively stable metabolism and subsequent stable disease by RECIST, and one patient had metastatic PDA with increase in lactate-to-pyruvate of the liver metastases and corresponding progressive disease according to RECIST. DATA CONCLUSION Altered pyruvate metabolism with increased lactate or reduced alanine was observed in the primary tumor. Early metabolic response assessed at 4-weeks after treatment initiation correlated with subsequent objective tumor response assessed using RECIST. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Tanner Nickles
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Philip M Lee
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Michael A Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Kimberly Okamoto
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Andrew H Ko
- Department of Medicine, University of California, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
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Deh K, Zhang G, Park AH, Cunningham CH, Bragagnolo ND, Lyashchenko S, Ahmmed S, Leftin A, Coffee E, Hricak H, Miloushev V, Mayerhoefer M, Keshari KR. First in-human evaluation of [1- 13C]pyruvate in D 2O for hyperpolarized MRI of the brain: A safety and feasibility study. Magn Reson Med 2024; 91:2559-2567. [PMID: 38205934 PMCID: PMC11009889 DOI: 10.1002/mrm.30002] [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: 10/23/2023] [Revised: 12/15/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024]
Abstract
PURPOSE To investigate the safety and value of hyperpolarized (HP) MRI of [1-13C]pyruvate in healthy volunteers using deuterium oxide (D2O) as a solvent. METHODS Healthy volunteers (n = 5), were injected with HP [1-13C]pyruvate dissolved in D2O and imaged with a metabolite-specific 3D dual-echo dynamic EPI sequence at 3T at one site (Site 1). Volunteers were monitored following the procedure to assess safety. Image characteristics, including SNR, were compared to data acquired in a separate cohort using water as a solvent (n = 5) at another site (Site 2). The apparent spin-lattice relaxation time (T1) of [1-13C]pyruvate was determined both in vitro and in vivo from a mono-exponential fit to the image intensity at each time point of our dynamic data. RESULTS All volunteers completed the study safely and reported no adverse effects. The use of D2O increased the T1 of [1-13C]pyruvate from 66.5 ± 1.6 s to 92.1 ± 5.1 s in vitro, which resulted in an increase in signal by a factor of 1.46 ± 0.03 at the time of injection (90 s after dissolution). The use of D2O also increased the apparent relaxation time of [1-13C]pyruvate by a factor of 1.4 ± 0.2 in vivo. After adjusting for inter-site SNR differences, the use of D2O was shown to increase image SNR by a factor of 2.6 ± 0.2 in humans. CONCLUSIONS HP [1-13C]pyruvate in D2O is safe for human imaging and provides an increase in T1 and SNR that may improve image quality.
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Affiliation(s)
- Kofi Deh
- Radiology, Memorial Sloan Kettering Cancer Center
| | | | - Angela Hijin Park
- Radiochemistry & Imaging Probes Core (RMIP), Memorial Sloan Kettering Cancer Center
| | - Charles H. Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario
| | | | - Serge Lyashchenko
- Radiochemistry & Imaging Probes Core (RMIP), Memorial Sloan Kettering Cancer Center
| | - Shake Ahmmed
- Radiochemistry & Imaging Probes Core (RMIP), Memorial Sloan Kettering Cancer Center
| | | | | | - Hedvig Hricak
- Radiology, Memorial Sloan Kettering Cancer Center
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center
| | | | | | - Kayvan R. Keshari
- Radiology, Memorial Sloan Kettering Cancer Center
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center
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9
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Diaz E, Sriram R, Gordon JW, Sinha A, Liu X, Sahin S, Crane J, Olson MP, Chen HY, Bernard J, Vigneron DB, Wang ZJ, Xu D, Larson PEZ. Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI. ARXIV 2024:arXiv:2405.03147v1. [PMID: 38764595 PMCID: PMC11100919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/21/2024]
Abstract
Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM Attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies and technical developments of this imaging technique.
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Affiliation(s)
- Ernesto Diaz
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Renuka Sriram
- 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
| | - Avantika Sinha
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Sule Sahin
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Jason Crane
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Marram P Olson
- 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
| | - Jenna Bernard
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, California, USA
| | - Zhen Jane Wang
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and University of California, San Francisco, 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, Berkeley and University of California, San Francisco, California, USA
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Nickles TM, Kim Y, Lee PM, Chen HY, Ohliger M, Bok RA, Wang ZJ, Larson PEZ, Vigneron DB, Gordon JW. Hyperpolarized 13 C metabolic imaging of the human abdomen with spatiotemporal denoising. Magn Reson Med 2024; 91:2153-2161. [PMID: 38193310 PMCID: PMC10950515 DOI: 10.1002/mrm.29985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/27/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach. METHODS Denoising performance was first evaluated using the simulated [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients). RESULTS The parameterization of kglobal = 0.2 and klocal = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (conversion rate of pyruvate-to-metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground-truth metabolic conversion rates when there is adequate SNR (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5-fold increase in the number of voxels reliably fit across abdominal FOVs for kPL and kPA quantification maps. CONCLUSION Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen.
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Affiliation(s)
- Tanner M Nickles
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Yaewon Kim
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Philip M Lee
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Michael Ohliger
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Robert A Bok
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, USA
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Christensen NV, Holm R, Sanchez JD, Hansen ESS, Lerche MH, Ardenkjær-Larsen JH, Laustsen C, Bertelsen LB. A continuous flow bioreactor system for high-throughput hyperpolarized metabolic flux analysis. NMR IN BIOMEDICINE 2024; 37:e5107. [PMID: 38279190 DOI: 10.1002/nbm.5107] [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: 04/21/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/28/2024]
Abstract
Hyperpolarized carbon-13 labeled compounds are increasingly being used in medical MR imaging (MRI) and MR imaging (MRI) and spectroscopy (MRS) research, due to its ability to monitor tissue and cell metabolism in real-time. Although radiological biomarkers are increasingly being considered as clinical indicators, biopsies are still considered the gold standard for a large variety of indications. Bioreactor systems can play an important role in biopsy examinations because of their ability to provide a physiochemical environment that is conducive for therapeutic response monitoring ex vivo. We demonstrate here a proof-of-concept bioreactor and microcoil receive array setup that allows for ex vivo preservation and metabolic NMR spectroscopy on up to three biopsy samples simultaneously, creating an easy-to-use and robust way to simultaneously run multisample carbon-13 hyperpolarization experiments. Experiments using hyperpolarized [1-13C]pyruvate on ML-1 leukemic cells in the bioreactor setup were performed and the kinetic pyruvate-to-lactate rate constants ( k PL ) extracted. The coefficient of variation of the experimentally found k PL s for five repeated experiments was C V = 35 % . With this statistical power, treatment effects of 30%-40% change in lactate production could be easily differentiable with only a few hyperpolarization dissolutions on this setup. Furthermore, longitudinal experiments showed preservation of ML-1 cells in the bioreactor setup for at least 6 h. Rat brain tissue slices were also seen to be preserved within the bioreactor for at least 1 h. This validation serves as the basis for further optimization and upscaling of the setup, which undoubtedly has huge potential in high-throughput studies with various biomarkers and tissue types.
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Affiliation(s)
| | - Rikke Holm
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | | | - Esben S S Hansen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Mathilde H Lerche
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | | | - Christoffer Laustsen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Lotte Bonde Bertelsen
- The MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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12
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Chen HY, Gordon JW, Dwork N, Chung BT, Riselli A, Sivalokanathan S, Bok RA, Slater JB, Vigneron DB, Abraham MR, Larson PEZ. Probing human heart TCA cycle metabolism and response to glucose load using hyperpolarized [2- 13 C]pyruvate MRS. NMR IN BIOMEDICINE 2024; 37:e5074. [PMID: 38054254 DOI: 10.1002/nbm.5074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/22/2023] [Accepted: 10/24/2023] [Indexed: 12/07/2023]
Abstract
INTRODUCTION The healthy heart has remarkable metabolic flexibility that permits rapid switching between mitochondrial glucose oxidation and fatty acid oxidation to generate ATP. Loss of metabolic flexibility has been implicated in the genesis of contractile dysfunction seen in cardiomyopathy. Metabolic flexibility has been imaged in experimental models, using hyperpolarized (HP) [2-13 C]pyruvate MRI, which enables interrogation of metabolites that reflect tricarboxylic acid (TCA) cycle flux in cardiac myocytes. This study aimed to develop methods, demonstrate feasibility for [2-13 C]pyruvate MRI in the human heart for the first time, and assess cardiac metabolic flexibility. METHODS Good manufacturing practice [2-13 C]pyruvic acid was polarized in a 5 T polarizer for 2.5-3 h. Following dissolution, quality control parameters of HP pyruvate met all safety and sterility criteria for pharmacy release, prior to administration to study subjects. Three healthy subjects each received two HP injections and MR scans, first under fasting conditions, followed by oral glucose load. A 5 cm axial slab-selective spectroscopy approach was prescribed over the left ventricle and acquired at 3 s intervals on a 3 T clinical MRI scanner. RESULTS The study protocol, which included HP substrate injection, MR scanning, and oral glucose load, was performed safely without adverse events. Key downstream metabolites of [2-13 C]pyruvate metabolism in cardiac myocytes include the glycolytic derivative [2-13 C]lactate, TCA-associated metabolite [5-13 C]glutamate, and [1-13 C]acetylcarnitine, catalyzed by carnitine acetyltransferase (CAT). After glucose load, 13 C-labeling of lactate, glutamate, and acetylcarnitine from 13 C-pyruvate increased by an average of 39.3%, 29.5%, and 114% respectively in the three subjects, which could result from increases in lactate dehydrogenase, pyruvate dehydrogenase, and CAT enzyme activity as well as TCA cycle flux (glucose oxidation). CONCLUSIONS HP [2-13 C]pyruvate imaging is safe and permits noninvasive assessment of TCA cycle intermediates and the acetyl buffer, acetylcarnitine, which is not possible using HP [1-13 C]pyruvate. Cardiac metabolite measurement in the fasting/fed states provides information on cardiac metabolic flexibility and the acetylcarnitine pool.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Nicholas Dwork
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Brian T Chung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Andrew Riselli
- School of Pharmacy, University of California, San Francisco, California, USA
| | | | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - James B Slater
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - M Roselle Abraham
- Division of Cardiology, University of California, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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Mo Z, Zhang X, Liang H, Chen Q, Tie C, Xiao W, Cao Q, Liu C, Zou C, Wan L, Zhang X, Li Y. A Novel Three-Channel Endorectal Coil for Prostate Magnetic Resonance Imaging at 3T. IEEE Trans Biomed Eng 2023; 70:3381-3388. [PMID: 37318962 DOI: 10.1109/tbme.2023.3286488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
OBJECTIVE The purpose of this work is to develop a 3-channel endorectal coil (ERC-3C) structure to obtain higher signal-to-noise (SNR) and better parallel imaging performance for prostate magnetic resonance imaging (MRI) at 3T. METHODS The coil performance was validated by in vivo studies and the SNR, g-factor, and diffusion-weighted imaging (DWI) were compared. A 2-channel endorectal coil (ERC-2C) with two orthogonal loops and a 12-channel external surface coil were employed for comparison. RESULTS Compared with the ERC-2C with a quadrature configuration and the external 12-channel coil array, the proposed ERC-3C improved SNR performance by 23.9% and 428.9%, respectively. The improved SNR enables the ERC-3C to produce spatial high-resolution images of 0.24 mm × 0.24 mm × 2 mm (0.1152 μL) in the prostate area within 9 minutes. CONCLUSION We developed an ERC-3C and validated its performance through in vivo MR imaging experiments. SIGNIFICANCE The results demonstrated the feasibility of an ERC with more than two channels and that a higher SNR can be achieved using the ERC-3C compared with an orthogonal ERC-2C of the same coverage.
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14
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Chen HY, Gordon JW, Dwork N, Chung BT, Riselli A, Sivalokanathan S, Bok RA, Slater JB, Vigneron DB, Abraham MR, Larson PE. Probing Human Heart TCA Cycle Metabolism and Response to Glucose Load using Hyperpolarized [2- 13C]Pyruvate MR Spectroscopy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.16.23297053. [PMID: 37905131 PMCID: PMC10615004 DOI: 10.1101/2023.10.16.23297053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Introduction The normal heart has remarkable metabolic flexibility that permits rapid switching between mitochondrial glucose oxidation and fatty acid (FA) oxidation to generate ATP. Loss of metabolic flexibility has been implicated in the genesis of contractile dysfunction seen in cardiomyopathy. Metabolic flexibility has been imaged in experimental models, using hyperpolarized (HP) [2-13C]pyruvate MRI, which enables interrogation of metabolites that reflect tricarboxylic acid (TCA) cycle flux in cardiac myocytes. This study aimed to develop methods, demonstrate feasibility for [2-13C]pyruvate MRI in the human heart for the first time, and assess cardiac metabolic flexibility. Methods Good Manufacturing Practice [2-13C]pyruvic acid was polarized in a 5T polarizer for 2.5-3 hours. Following dissolution, QC parameters of HP pyruvate met all safety and sterility criteria for pharmacy release, prior to administration to study subjects. Three healthy subjects each received two HP injections and MR scans, first under fasting conditions, followed by oral glucose load. A 5cm axial slab-selective spectroscopy approach was prescribed over the left ventricle and acquired at 3s intervals on a 3T clinical MRI scanner. Results The study protocol which included HP substrate injection, MR scanning and oral glucose load, was performed safely without adverse events. Key downstream metabolites of [2-13C]pyruvate metabolism in cardiac myocytes include the glycolytic derivative [2-13C]lactate, TCA-associated metabolite [5-13C]glutamate, and [1-13C]acetylcarnitine, catalyzed by carnitine acetyltransferase (CAT). After glucose load, 13C-labeling of lactate, glutamate, and acetylcarnitine from 13C-pyruvate increased by 39.3%, 29.5%, and 114%, respectively in the three subjects, that could result from increases in lactate dehydrogenase (LDH), pyruvate dehydrogenase (PDH), and CAT enzyme activity as well as TCA cycle flux (glucose oxidation). Conclusions HP [2-13C]pyruvate imaging is safe and permits non-invasive assessment of TCA cycle intermediates and the acetyl buffer, acetylcarnitine, which is not possible using HP [1-13C]pyruvate. Cardiac metabolite measurement in the fasting/fed states provides information on cardiac metabolic flexibility and the acetylcarnitine pool.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Nicholas Dwork
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Brian T. Chung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Andrew Riselli
- School of Pharmacy, University of California, San Francisco, United States
| | | | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - James B. Slater
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
| | - M. Roselle Abraham
- Division of Cardiology, University of California, San Francisco, United States
| | - Peder E.Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, United States
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15
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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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16
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Sahin SI, Ji X, Agarwal S, Sinha A, Mali I, Gordon JW, Mattingly M, Subramaniam S, Kurhanewicz J, Larson PEZ, Sriram R. Metabolite-Specific Echo Planar Imaging for Preclinical Studies with Hyperpolarized 13C-Pyruvate MRI. Tomography 2023; 9:736-749. [PMID: 37104130 PMCID: PMC10143874 DOI: 10.3390/tomography9020059] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 03/29/2023] Open
Abstract
Metabolite-specific echo-planar imaging (EPI) sequences with spectral-spatial (spsp) excitation are commonly used in clinical hyperpolarized [1-13C]pyruvate studies because of their speed, efficiency, and flexibility. In contrast, preclinical systems typically rely on slower spectroscopic methods, such as chemical shift imaging (CSI). In this study, a 2D spspEPI sequence was developed for use on a preclinical 3T Bruker system and tested on in vivo mice experiments with patient-derived xenograft renal cell carcinoma (RCC) or prostate cancer tissues implanted in the kidney or liver. Compared to spspEPI sequences, CSI were found to have a broader point spread function via simulations and exhibited signal bleeding between vasculature and tumors in vivo. Parameters for the spspEPI sequence were optimized using simulations and verified with in vivo data. The expected lactate SNR and pharmacokinetic modeling accuracy increased with lower pyruvate flip angles (less than 15°), intermediate lactate flip angles (25° to 40°), and temporal resolution of 3 s. Overall SNR was also higher with coarser spatial resolution (4 mm isotropic vs. 2 mm isotropic). Pharmacokinetic modelling used to fit kPL maps showed results consistent with the previous literature and across different sequences and tumor xenografts. This work describes and justifies the pulse design and parameter choices for preclinical spspEPI hyperpolarized 13C-pyruvate studies and shows superior image quality to CSI.
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Affiliation(s)
- Sule I. Sahin
- UC Berkeley—UCSF Graduate Program in Bioengineering, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Xiao Ji
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Shubhangi Agarwal
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Avantika Sinha
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Ivina Mali
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | | | - Sukumar Subramaniam
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Peder E. Z. Larson
- UC Berkeley—UCSF Graduate Program in Bioengineering, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
| | - Renuka Sriram
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94016, USA
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Sun P, Wu Z, Lin L, Hu G, Zhang X, Wang J. MR-Nucleomics: The study of pathological cellular processes with multinuclear magnetic resonance spectroscopy and imaging in vivo. NMR IN BIOMEDICINE 2023; 36:e4845. [PMID: 36259659 DOI: 10.1002/nbm.4845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 09/28/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
Clinical medicine has experienced a rapid development in recent decades, during which therapies targeting specific cellular signaling pathways, or specific cell surface receptors, have been increasingly adopted. While these developments in clinical medicine call for improved precision in diagnosis and treatment monitoring, modern medical imaging methods are restricted mainly to anatomical imaging, lagging behind the requirements of precision medicine. Although positron emission tomography and single photon emission computed tomography have been used clinically for studies of metabolism, their applications have been limited by the exposure risk to ionizing radiation, the subsequent limitation in repeated and longitudinal studies, and the incapability in assessing downstream metabolism. Magnetic resonance spectroscopy (MRS) or spectroscopic imaging (MRSI) are, in theory, capable of assessing molecular activities in vivo, although they are often limited by sensitivity. Here, we review some recent developments in MRS and MRSI of multiple nuclei that have potential as molecular imaging tools in the clinic.
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Affiliation(s)
- Peng Sun
- Clinical & Technical Support, Philips Healthcare, China
| | - Zhigang Wu
- Clinical & Technical Support, Philips Healthcare, China
| | - Liangjie Lin
- Clinical & Technical Support, Philips Healthcare, China
| | - Geli Hu
- Clinical & Technical Support, Philips Healthcare, China
| | | | - Jiazheng Wang
- Clinical & Technical Support, Philips Healthcare, China
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18
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Lee PM, Chen HY, Gordon JW, Wang ZJ, Bok R, Hashoian R, Kim Y, Liu X, Nickles T, Cheung K, De Las Alas F, Daniel H, Larson PEZ, von Morze C, Vigneron DB, Ohliger MA. Whole-Abdomen Metabolic Imaging of Healthy Volunteers Using Hyperpolarized [1- 13 C]pyruvate MRI. J Magn Reson Imaging 2022; 56:1792-1806. [PMID: 35420227 PMCID: PMC9562149 DOI: 10.1002/jmri.28196] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/31/2022] [Accepted: 04/01/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Hyperpolarized 13 C MRI quantitatively measures enzyme-catalyzed metabolism in cancer and metabolic diseases. Whole-abdomen imaging will permit dynamic metabolic imaging of several abdominal organs simultaneously in healthy and diseased subjects. PURPOSE Image hyperpolarized [1-13 C]pyruvate and products in the abdomens of healthy volunteers, overcoming challenges of motion, magnetic field variations, and spatial coverage. Compare hyperpolarized [1-13 C]pyruvate metabolism across abdominal organs of healthy volunteers. STUDY TYPE Prospective technical development. SUBJECTS A total of 13 healthy volunteers (8 male), 21-64 years (median 36). FIELD STRENGTH/SEQUENCE A 3 T. Proton: T1 -weighted spoiled gradient echo, T2 -weighted single-shot fast spin echo, multiecho fat/water imaging. Carbon-13: echo-planar spectroscopic imaging, metabolite-specific echo-planar imaging. ASSESSMENT Transmit magnetic field was measured. Variations in main magnetic field (ΔB0 ) determined using multiecho proton acquisitions were compared to carbon-13 acquisitions. Changes in ΔB0 were measured after localized shimming. Improvements in metabolite signal-to-noise ratio were calculated. Whole-organ regions of interests were drawn over the liver, spleen, pancreas, and kidneys by a single investigator. Metabolite signals, time-to-peak, decay times, and mean first-order rate constants for pyruvate-to-lactate (kPL ) and alanine (kPA ) conversion were measured in each organ. STATISTICAL TESTS Linear regression, one-sample Kolmogorov-Smirnov tests, paired t-tests, one-way ANOVA, Tukey's multiple comparisons tests. P ≤ 0.05 considered statistically significant. RESULTS Proton ΔB0 maps correlated with carbon-13 ΔB0 maps (slope = 0.93, y-intercept = -2.88, R2 = 0.73). Localized shimming resulted in mean frequency offset within ±25 Hz for all organs. Metabolite SNR significantly increased after denoising. Mean kPL and kPA were highest in liver, followed by pancreas, spleen, and kidneys (all comparisons with liver were significant). DATA CONCLUSION Whole-abdomen coverage with hyperpolarized carbon-13 MRI was feasible despite technical challenges. Multiecho gradient echo 1 H acquisitions accurately predicted chemical shifts observed using carbon-13 spectroscopy. Carbon-13 acquisitions benefited from local shimming. Metabolite energetics in the abdomen compiled for healthy volunteers can be used to design larger clinical trials in patients with metabolic diseases. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Philip M Lee
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | | | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Tanner Nickles
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Kiersten Cheung
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Francesca De Las Alas
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Heather Daniel
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Peder EZ Larson
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Cornelius von Morze
- Mallinckrodt Institute of Radiology, Washington University in St. Louis; St. Louis, Missouri, USA
| | - Daniel B Vigneron
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
| | - Michael A Ohliger
- Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA
- Department of Radiology, Zuckerberg San Francisco General Hospital and Trauma Center; San Francisco, California, USA
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Agudelo JP, Upadhyay D, Zhang D, Zhao H, Nolley R, Sun J, Agarwal S, Bok RA, Vigneron DB, Brooks JD, Kurhanewicz J, Peehl DM, Sriram R. Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma. Metabolites 2022; 12:1117. [PMID: 36422257 PMCID: PMC9692472 DOI: 10.3390/metabo12111117] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 10/31/2022] [Accepted: 11/08/2022] [Indexed: 08/26/2023] Open
Abstract
Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies.
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Affiliation(s)
- Joao Piraquive Agudelo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Deepti Upadhyay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Dalin Zhang
- Department of Urology, Stanford University, Stanford, CA 94305, USA
| | - Hongjuan Zhao
- Department of Urology, Stanford University, Stanford, CA 94305, USA
| | - Rosalie Nolley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jinny Sun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Shubhangi Agarwal
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - James D. Brooks
- Department of Urology, Stanford University, Stanford, CA 94305, USA
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Donna M. Peehl
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
| | - Renuka Sriram
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
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20
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Hu JY, Kim Y, Autry AW, Frost MM, Bok RA, Villanueva-Meyer JE, Xu D, Li Y, Larson PEZ, Vigneron DB, Gordon JW. Kinetic analysis of multi-resolution hyperpolarized 13 C human brain MRI to study cerebral metabolism. Magn Reson Med 2022; 88:2190-2197. [PMID: 35754148 PMCID: PMC9420752 DOI: 10.1002/mrm.29354] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 04/15/2022] [Accepted: 05/23/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To investigate multi-resolution hyperpolarized (HP) 13 C pyruvate MRI for measuring kinetic conversion rates in the human brain. METHODS HP [1-13 C]pyruvate MRI was acquired in 6 subjects with a multi-resolution EPI sequence at 7.5 × 7.5 mm2 resolution for pyruvate and 15 × 15 mm2 resolution for lactate and bicarbonate. With the same lactate data, 2 quantitative maps of pyruvate-to-lactate conversion (kPL ) maps were generated: 1 using 7.5 × 7.5 mm2 resolution pyruvate data and the other using synthetic 15 × 15 mm2 resolution pyruvate data to simulate a standard constant resolution acquisition. To examine local kPL values, 4 voxels were manually selected in each study representing brain tissue near arteries, brain tissue near veins, white matter, and gray matter. RESULTS High resolution 7.5 × 7.5 mm2 pyruvate images increased the spatial delineation of brain structures and decreased partial volume effects compared to coarser resolution 15 × 15 mm2 pyruvate images. Voxels near arteries, veins and in white matter exhibited higher calculated kPL for multi-resolution images. CONCLUSION Acquiring HP 13 C pyruvate metabolic data with a multi-resolution approach minimized partial volume effects from vascular pyruvate signals while maintaining the SNR of downstream metabolites. Higher resolution pyruvate images for kinetic fitting resulted in increased kinetic rate values, particularly around the superior sagittal sinus and cerebral arteries, by reducing extracellular pyruvate signal contributions from adjacent blood vessels. This HP 13 C study showed that acquiring pyruvate with finer resolution improved the quantification of kinetic rates throughout the human brain.
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Affiliation(s)
- Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Mary M Frost
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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21
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Liu X, Tang S, Mu C, Qin H, Cu D, Lai YC, Riselli AM, Delos Santos R, Carvajal L, Gebrezgiabhier D, Bok RA, Chen HY, Flavell RR, Gordon JW, Vigneron DB, Kurhanewicz J, Larson PE. Development of specialized magnetic resonance acquisition techniques for human hyperpolarized [ 13 C, 15 N 2 ]urea + [1- 13 C]pyruvate simultaneous perfusion and metabolic imaging. Magn Reson Med 2022; 88:1039-1054. [PMID: 35526263 PMCID: PMC9810116 DOI: 10.1002/mrm.29266] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/22/2022] [Accepted: 03/23/2022] [Indexed: 01/05/2023]
Abstract
PURPOSE This study aimed to develop and demonstrate the in vivo feasibility of a 3D stack-of-spiral balanced steady-state free precession(3D-bSSFP) urea sequence, interleaved with a metabolite-specific gradient echo (GRE) sequence for pyruvate and metabolic products, for improving the SNR and spatial resolution of the first hyperpolarized 13 C-MRI human study with injection of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea. METHODS A metabolite-specific bSSFP urea imaging sequence was designed using a urea-specific excitation pulse, optimized TR, and 3D stack-of-spiral readouts. Simulations and phantom studies were performed to validate the spectral response of the sequence. The image quality of urea data acquired by the 3D-bSSFP sequence and the 2D-GRE sequence was evaluated with 2 identical injections of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea formula in a rat. Subsequently, the feasibility of the acquisition strategy was validated in a prostate cancer patient. RESULTS Simulations and phantom studies demonstrated that 3D-bSSFP sequence achieved urea-only excitation, while minimally perturbing other metabolites (<1%). An animal study demonstrated that compared to GRE, bSSFP sequence provided an ∼2.5-fold improvement in SNR without perturbing urea or pyruvate kinetics, and bSSFP approach with a shorter spiral readout reduced blurring artifacts caused by J-coupling of [13 C,15 N2 ]urea. The human study demonstrated the in vivo feasibility and data quality of the acquisition strategy. CONCLUSION The 3D-bSSFP urea sequence with a stack-of-spiral acquisition demonstrated significantly increased SNR and image quality for [13 C,15 N2 ]urea in co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea imaging studies. This work lays the foundation for future human studies to achieve high-quality and high-SNR metabolism and perfusion images.
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Affiliation(s)
- Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Shuyu Tang
- HeartVista Inc., Los Altos, California, USA
| | - Changhua Mu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Hecong Qin
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Di Cu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ying-Chieh Lai
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Andrew M. Riselli
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Romelyn Delos Santos
- 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
| | - Daniel Gebrezgiabhier
- 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
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Robert R. Flavell
- 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
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, San Francisco, California, USA
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, San Francisco, California, USA
| | - Peder E.Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, San Francisco, California, USA
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22
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Vaziri S, Autry AW, Lafontaine M, Kim Y, Gordon JW, Chen HY, Hu JY, Lupo JM, Chang SM, Clarke JL, Villanueva-Meyer JE, Bush NAO, Xu D, Larson PEZ, Vigneron DB, Li Y. Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1- 13C]pyruvate MRI data from patients with glioma. Neuroimage Clin 2022; 36:103155. [PMID: 36007439 PMCID: PMC9421383 DOI: 10.1016/j.nicl.2022.103155] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma. METHODS Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared. RESULTS Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD). CONCLUSION Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.
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Affiliation(s)
- Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Marisa Lafontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.
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23
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Zaccagna F, McLean MA, Grist JT, Kaggie J, Mair R, Riemer F, Woitek R, Gill AB, Deen S, Daniels CJ, Ursprung S, Schulte RF, Allinson K, Chhabra A, Laurent MC, Locke M, Frary A, Hilborne S, Patterson I, Carmo BD, Slough R, Wilkinson I, Basu B, Wason J, Gillard JH, Matys T, Watts C, Price SJ, Santarius T, Graves MJ, Jefferies S, Brindle KM, Gallagher FA. Imaging Glioblastoma Metabolism by Using Hyperpolarized [1- 13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study. Radiol Imaging Cancer 2022; 4:e210076. [PMID: 35838532 PMCID: PMC9360994 DOI: 10.1148/rycan.210076] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 04/27/2022] [Accepted: 05/19/2022] [Indexed: 01/20/2023]
Abstract
Purpose To evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (13C) MRI to monitor the exchange of the hyperpolarized 13C label between injected [1-13C]pyruvate and tumor lactate and bicarbonate. Materials and Methods In this prospective study, seven treatment-naive patients (age [mean ± SD], 60 years ± 11; five men) with GBM were imaged at 3 T by using a dual-tuned 13C-hydrogen 1 head coil. Hyperpolarized [1-13C]pyruvate was injected, and signal was acquired by using a dynamic MRI spiral sequence. Metabolism was assessed within the tumor, in the normal-appearing brain parenchyma (NABP), and in healthy volunteers by using paired or unpaired t tests and a Wilcoxon signed rank test. The Spearman ρ correlation coefficient was used to correlate metabolite labeling with lactate dehydrogenase A (LDH-A) expression and some immunohistochemical markers. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. Results The bicarbonate-to-pyruvate (BP) ratio was lower in the tumor than in the contralateral NABP (P < .01). The tumor lactate-to-pyruvate (LP) ratio was not different from that in the NABP (P = .38). The LP and BP ratios in the NABP were higher than those observed previously in healthy volunteers (P < .05). Tumor lactate and bicarbonate signal intensities were strongly correlated with the pyruvate signal intensity (ρ = 0.92, P < .001, and ρ = 0.66, P < .001, respectively), and the LP ratio was weakly correlated with LDH-A expression in biopsy samples (ρ = 0.43, P = .04). Conclusion Hyperpolarized 13C MRI demonstrated variation in lactate labeling in GBM, both within and between tumors. In contrast, bicarbonate labeling was consistently lower in tumors than in the surrounding NABP. Keywords: Hyperpolarized 13C MRI, Glioblastoma, Metabolism, Cancer, MRI, Neuro-oncology Supplemental material is available for this article. Published under a CC BY 4.0 license.
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Affiliation(s)
- Fulvio Zaccagna
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Mary A. McLean
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - James T. Grist
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Joshua Kaggie
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Richard Mair
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Frank Riemer
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ramona Woitek
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Andrew B. Gill
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Surrin Deen
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Charlie J. Daniels
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Stephan Ursprung
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Rolf F. Schulte
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Kieren Allinson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Anita Chhabra
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Marie-Christine Laurent
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Matthew Locke
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Amy Frary
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Sarah Hilborne
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ilse Patterson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Bruno D. Carmo
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Rhys Slough
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ian Wilkinson
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Bristi Basu
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - James Wason
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Jonathan H. Gillard
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Tomasz Matys
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Colin Watts
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Stephen J. Price
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Thomas Santarius
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Martin J. Graves
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Sarah Jefferies
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Kevin M. Brindle
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
| | - Ferdia A. Gallagher
- From the Departments of Radiology (F.Z., J.T.G., J.K., F.R., R.W.,
A.B.G., S.D., C.J.D., S.U., M.C.L., M.L., A.F., S.H., J.H.G., T.M., M.J.G.,
F.A.G.), Clinical Neurosciences (R.M., C.W., S.J.P., T.S.), and Medicine (I.W.),
University of Cambridge School of Clinical Medicine, Cambridge, England; Cancer
Research UK Cambridge Institute (M.A.M., S.U., K.M.B.), Medical Research Council
Biostatistics Unit (J.W.), and Department of Biochemistry (K.M.B.), University
of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, England;
Department of Biomedical Imaging and Image-guided Therapy, Medical University of
Vienna, Vienna, Austria (R.W.); GE Healthcare, Munich, Germany (R.F.S.);
Department of Pathology (K.A.), Cambridge Cancer Trials Centre (A.C.),
Department of Radiology (I.P., B.D.C., R.S.), and Department of Oncology (B.B.,
S.J.), Cambridge University Hospitals National Health Service Foundation Trust,
Cambridge, England; and Population Health Sciences Institute, Newcastle
University, Newcastle upon Tyne, England (J.W.)
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Li Y, Vigneron DB, Xu D. Current human brain applications and challenges of dynamic hyperpolarized carbon-13 labeled pyruvate MR metabolic imaging. Eur J Nucl Med Mol Imaging 2021; 48:4225-4235. [PMID: 34432118 PMCID: PMC8566394 DOI: 10.1007/s00259-021-05508-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 07/27/2021] [Indexed: 12/17/2022]
Abstract
The ability of hyperpolarized carbon-13 MR metabolic imaging to acquire dynamic metabolic information in real time is crucial to gain mechanistic insights into metabolic pathways, which are complementary to anatomic and other functional imaging methods. This review presents the advantages of this emerging functional imaging technology, describes considerations in clinical translations, and summarizes current human brain applications. Despite rapid development in methodologies, significant technological and physiological related challenges continue to impede broader clinical translation.
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Affiliation(s)
- Yan Li
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA.
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, UCSF Radiology, University of California, 185 Berry Street, Ste 350, Box 0946, San Francisco, CA, 94107, USA
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25
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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: 8] [Impact Index Per Article: 2.0] [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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26
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Salzillo TC, Mawoneke V, Weygand J, Shetty A, Gumin J, Zacharias NM, Gammon ST, Piwnica-Worms D, Fuller GN, Logothetis CJ, Lang FF, Bhattacharya PK. Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance. Cells 2021; 10:cells10102621. [PMID: 34685601 PMCID: PMC8534002 DOI: 10.3390/cells10102621] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/20/2021] [Accepted: 09/23/2021] [Indexed: 12/23/2022] Open
Abstract
Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research.
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Affiliation(s)
- Travis C. Salzillo
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Vimbai Mawoneke
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Joseph Weygand
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL 33612, USA;
| | - Akaanksh Shetty
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Joy Gumin
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (J.G.); (F.F.L.)
| | - Niki M. Zacharias
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Seth T. Gammon
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - David Piwnica-Worms
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
| | - Gregory N. Fuller
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Christopher J. Logothetis
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA;
| | - Frederick F. Lang
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (J.G.); (F.F.L.)
| | - Pratip K. Bhattacharya
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA; (T.C.S.); (V.M.); (A.S.); (S.T.G.); (D.P.-W.)
- Correspondence: ; Tel.: +1-713-454-9887
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27
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Kim Y, Chen HY, Autry AW, Villanueva-Meyer J, Chang SM, Li Y, Larson PEZ, Brender JR, Krishna MC, Xu D, Vigneron DB, Gordon JW. Denoising of hyperpolarized 13 C MR images of the human brain using patch-based higher-order singular value decomposition. Magn Reson Med 2021; 86:2497-2511. [PMID: 34173268 DOI: 10.1002/mrm.28887] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/23/2021] [Accepted: 05/20/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE To improve hyperpolarized 13 C (HP-13 C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD). METHODS The benefit of using a patch-based HOSVD method to denoise dynamic HP-13 C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1-13 C]pyruvate and its metabolic product, [1-13 C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1-13 C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error. RESULTS Simulation results demonstrated an 8-fold increase in the calculated SNR of [1-13 C]pyruvate and [1-13 C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of kPL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted kPL after denoising. The patch-based denoising performed superior to the global denoising in recovering kPL information. In volunteer data sets, [1-13 C]lactate and [13 C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping kPB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping kPL . CONCLUSIONS Sensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research.
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Affiliation(s)
- Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Javier Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeffrey R Brender
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Murali C Krishna
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.,Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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28
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Choi IY, Kreis R. Advanced methodology for in vivo magnetic resonance spectroscopy. NMR IN BIOMEDICINE 2021; 34:e4504. [PMID: 33709530 DOI: 10.1002/nbm.4504] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 02/21/2021] [Indexed: 06/12/2023]
Affiliation(s)
- In-Young Choi
- Department of Neurology, Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Roland Kreis
- Department of Radiology, Nuclear Medicine, and Neuroradiology and Department of Biomedical Research, University Bern, Bern, Switzerland
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Vaeggemose M, F. Schulte R, Laustsen C. Comprehensive Literature Review of Hyperpolarized Carbon-13 MRI: The Road to Clinical Application. Metabolites 2021; 11:metabo11040219. [PMID: 33916803 PMCID: PMC8067176 DOI: 10.3390/metabo11040219] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/31/2021] [Accepted: 04/01/2021] [Indexed: 01/02/2023] Open
Abstract
This review provides a comprehensive assessment of the development of hyperpolarized (HP) carbon-13 metabolic MRI from the early days to the present with a focus on clinical applications. The status and upcoming challenges of translating HP carbon-13 into clinical application are reviewed, along with the complexity, technical advancements, and future directions. The road to clinical application is discussed regarding clinical needs and technological advancements, highlighting the most recent successes of metabolic imaging with hyperpolarized carbon-13 MRI. Given the current state of hyperpolarized carbon-13 MRI, the conclusion of this review is that the workflow for hyperpolarized carbon-13 MRI is the limiting factor.
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Affiliation(s)
- Michael Vaeggemose
- GE Healthcare, 2605 Brondby, Denmark;
- MR Research Centre, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
| | | | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
- Correspondence:
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30
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Autry AW, Park I, Kline C, Chen HY, Gordon JW, Raber S, Hoffman C, Kim Y, Okamoto K, Vigneron DB, Lupo JM, Prados M, Li Y, Xu D, Mueller S. Pilot Study of Hyperpolarized 13C Metabolic Imaging in Pediatric Patients with Diffuse Intrinsic Pontine Glioma and Other CNS Cancers. AJNR Am J Neuroradiol 2020; 42:178-184. [PMID: 33272950 DOI: 10.3174/ajnr.a6937] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/19/2020] [Indexed: 01/21/2023]
Abstract
BACKGROUND AND PURPOSE Pediatric CNS tumors commonly present challenges for radiographic interpretation on conventional MR imaging. This study sought to investigate the safety and tolerability of hyperpolarized carbon-13 (HP-13C) metabolic imaging in pediatric patients with brain tumors. MATERIALS AND METHODS Pediatric patients 3 to 18 years of age who were previously diagnosed with a brain tumor and could undergo MR imaging without sedation were eligible to enroll in this safety study of HP [1-13C]pyruvate. Participants received a one-time injection of HP [1-13C]pyruvate and were imaged using dynamic HP-13C MR imaging. We assessed 2 dose levels: 0.34 mL/kg and the highest tolerated adult dose of 0.43 mL/kg. Participants were monitored throughout imaging and for 60 minutes postinjection, including pre- and postinjection electrocardiograms and vital sign measurements. RESULTS Between February 2017 and July 2019, ten participants (9 males; median age, 14 years; range, 10-17 years) were enrolled, of whom 6 completed injection of HP [1-13C]pyruvate and dynamic HP-13C MR imaging. Four participants failed to undergo HP-13C MR imaging due to technical failures related to generating HP [1-13C]pyruvate or MR imaging operability. HP [1-13C]pyruvate was well-tolerated in all participants who completed the study, with no dose-limiting toxicities or adverse events observed at either 0.34 (n = 3) or 0.43 (n = 3) mL/kg. HP [1-13C]pyruvate demonstrated characteristic conversion to [1-13C]lactate and [13C]bicarbonate in the brain. Due to poor accrual, the study was closed after only 3 participants were enrolled at the highest dose level. CONCLUSIONS Dynamic HP-13C MR imaging was safely performed in 6 pediatric patients with CNS tumors and demonstrated HP [1-13C]pyruvate brain metabolism.
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Affiliation(s)
- A W Autry
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - I Park
- Department of Radiology (I.P.), Chonnam National University College of Medicine and Hospital, Gwangju, Korea
| | - C Kline
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Department of Neurology (C.K., S.M.)
| | - H-Y Chen
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - J W Gordon
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - S Raber
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics
| | - C Hoffman
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics
| | - Y Kim
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - K Okamoto
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - D B Vigneron
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.).,Bioengineering and Therapeutic Sciences (D.B.V.).,Neurological Surgery (D.B.V., M.P., S.M.).,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - J M Lupo
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.).,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - M Prados
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Neurological Surgery (D.B.V., M.P., S.M.)
| | - Y Li
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.)
| | - D Xu
- From the Departments of Radiology and Biomedical Imaging (A.W.A., H.-Y.C., J.W.G., Y.K., K.O., D.B.V., J.M.L., Y.L., D.X.) .,UCSF/UC Berkeley Joint Graduate Group in Bioengineering (D.B.V., J.M.L., D.X.), University of California, San Francisco, San Francisco, California
| | - S Mueller
- Division of Hematology/Oncology (C.K., S.R., C.H., M.P., S.M.), Department of Pediatrics.,Department of Neurology (C.K., S.M.).,Neurological Surgery (D.B.V., M.P., S.M.)
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Ngo B, Kim E, Osorio-Vasquez V, Doll S, Bustraan S, Liang RJ, Luengo A, Davidson SM, Ali A, Ferraro GB, Fischer GM, Eskandari R, Kang DS, Ni J, Plasger A, Rajasekhar VK, Kastenhuber ER, Bacha S, Sriram RK, Stein BD, Bakhoum SF, Snuderl M, Cotzia P, Healey JH, Mainolfi N, Suri V, Friedman A, Manfredi M, Sabatini DM, Jones DR, Yu M, Zhao JJ, Jain RK, Keshari KR, Davies MA, Vander Heiden MG, Hernando E, Mann M, Cantley LC, Pacold ME. Limited Environmental Serine and Glycine Confer Brain Metastasis Sensitivity to PHGDH Inhibition. Cancer Discov 2020; 10:1352-1373. [PMID: 32571778 PMCID: PMC7483776 DOI: 10.1158/2159-8290.cd-19-1228] [Citation(s) in RCA: 173] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 04/15/2020] [Accepted: 06/17/2020] [Indexed: 12/19/2022]
Abstract
A hallmark of metastasis is the adaptation of tumor cells to new environments. Metabolic constraints imposed by the serine and glycine-limited brain environment restrict metastatic tumor growth. How brain metastases overcome these growth-prohibitive conditions is poorly understood. Here, we demonstrate that 3-phosphoglycerate dehydrogenase (PHGDH), which catalyzes the rate-limiting step of glucose-derived serine synthesis, is a major determinant of brain metastasis in multiple human cancer types and preclinical models. Enhanced serine synthesis proved important for nucleotide production and cell proliferation in highly aggressive brain metastatic cells. In vivo, genetic suppression and pharmacologic inhibition of PHGDH attenuated brain metastasis, but not extracranial tumor growth, and improved overall survival in mice. These results reveal that extracellular amino acid availability determines serine synthesis pathway dependence, and suggest that PHGDH inhibitors may be useful in the treatment of brain metastasis. SIGNIFICANCE: Using proteomics, metabolomics, and multiple brain metastasis models, we demonstrate that the nutrient-limited environment of the brain potentiates brain metastasis susceptibility to serine synthesis inhibition. These findings underscore the importance of studying cancer metabolism in physiologically relevant contexts, and provide a rationale for using PHGDH inhibitors to treat brain metastasis.This article is highlighted in the In This Issue feature, p. 1241.
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Affiliation(s)
- Bryan Ngo
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Eugenie Kim
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Victoria Osorio-Vasquez
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Sophia Doll
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Sophia Bustraan
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
| | - Roger J Liang
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Alba Luengo
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Shawn M Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey
| | - Ahmed Ali
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Gino B Ferraro
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Grant M Fischer
- Departments of Translational Molecular Pathology, Melanoma Medical Oncology, Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Roozbeh Eskandari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Diane S Kang
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California Norris Comprehensive Cancer Center, Keck School of Medicine, Los Angeles, California
| | - Jing Ni
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Ariana Plasger
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | | | - Edward R Kastenhuber
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Sarah Bacha
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Roshan K Sriram
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Benjamin D Stein
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York
| | - Samuel F Bakhoum
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matija Snuderl
- Department of Pathology, New York University Langone Health, New York, New York
| | - Paolo Cotzia
- Department of Pathology, New York University Langone Health, New York, New York
| | - John H Healey
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Vipin Suri
- Raze Therapeutics, Cambridge, Massachusetts
| | | | | | - David M Sabatini
- Whitehead Institute for Biomedical Research, Cambridge, Massachusetts
- Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Drew R Jones
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York
- Metabolomics Core Resource Laboratory, NYU Langone Health, New York, New York
| | - Min Yu
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jean J Zhao
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Rakesh K Jain
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Kayvan R Keshari
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael A Davies
- Departments of Translational Molecular Pathology, Melanoma Medical Oncology, Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Matthew G Vander Heiden
- Koch Institute for Integrative Cancer Research, Cambridge, Massachusetts
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Broad Institute, Cambridge, Massachusetts
| | - Eva Hernando
- Department of Pathology, New York University Langone Health, New York, New York
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
- Faculty of Health and Medical Sciences, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Lewis C Cantley
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, New York.
| | - Michael E Pacold
- Department of Radiation Oncology, Perlmutter Cancer Center and NYU Langone Health, New York, New York.
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Autry AW, Gordon JW, Chen HY, LaFontaine M, Bok R, Van Criekinge M, Slater JB, Carvajal L, Villanueva-Meyer JE, Chang SM, Clarke JL, Lupo JM, Xu D, Larson PEZ, Vigneron DB, Li Y. Characterization of serial hyperpolarized 13C metabolic imaging in patients with glioma. NEUROIMAGE-CLINICAL 2020; 27:102323. [PMID: 32623139 PMCID: PMC7334458 DOI: 10.1016/j.nicl.2020.102323] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 06/15/2020] [Accepted: 06/21/2020] [Indexed: 01/07/2023]
Abstract
Serial HP 13C MRI was evaluated for data consistency and abnormal metabolism. Metabolism of [1-13C]pyruvate to lactate and bicarbonate was kinetically modeled. Conversion rates within NAWM were consistent in healthy volunteer and patient scans Progressed tumor lesions showed higher relative conversion rates to [1-13C]lactate. Globally elevated rate constants were observed with anti-angiogenic treatment.
Background Hyperpolarized carbon-13 (HP-13C) MRI is a non-invasive imaging technique for probing brain metabolism, which may improve clinical cancer surveillance. This work aimed to characterize the consistency of serial HP-13C imaging in patients undergoing treatment for brain tumors and determine whether there is evidence of aberrant metabolism in the tumor lesion compared to normal-appearing tissue. Methods Serial dynamic HP [1-13C]pyruvate MRI was performed on 3 healthy volunteers (6 total examinations) and 5 patients (21 total examinations) with diffuse infiltrating glioma during their course of treatment, using a frequency-selective echo-planar imaging (EPI) sequence. HP-13C imaging at routine clinical timepoints overlapped treatment, including radiotherapy (RT), temozolomide (TMZ) chemotherapy, and anti-angiogenic/investigational agents. Apparent rate constants for [1-13C]pyruvate conversion to [1-13C]lactate (kPL) and [13C]bicarbonate (kPB) were simultaneously quantified based on an inputless kinetic model within normal-appearing white matter (NAWM) and anatomic lesions defined from 1H MRI. The inter/intra-subject consistency of kPL-NAWM and kPB-NAWM was measured in terms of the coefficient of variation (CV). Results When excluding scans following anti-angiogenic therapy, patient values of kPL-NAWM and kPB-NAWM were 0.020 s−1 ± 23.8% and 0.0058 s−1 ± 27.7% (mean ± CV) across 17 HP-13C MRIs, with intra-patient serial kPL-NAWM/kPB-NAWM CVs ranging 6.8–16.6%/10.6–40.7%. In 4/5 patients, these values (0.018 s−1 ± 13.4% and 0.0058 s−1 ± 24.4%; n = 13) were more similar to those from healthy volunteers (0.018 s−1 ± 5.0% and 0.0043 s−1 ± 12.6%; n = 6) (mean ± CV). The anti-angiogenic agent bevacizumab was associated with global elevations in apparent rate constants, with maximum kPL-NAWM in 2 patients reaching 0.047 ± 0.001 and 0.047 ± 0.003 s−1 (±model error). In 3 patients with progressive disease, anatomic lesions showed elevated kPL relative to kPL-NAWM of 0.024 ± 0.001 s−1 (±model error) in the absence of gadolinium enhancement, and 0.032 ± 0.008, 0.040 ± 0.003 and 0.041 ± 0.009 s−1 with gadolinium enhancement. The lesion kPB in patients was reduced to unquantifiable values compared to kPB-NAWM. Conclusion Serial measures of HP [1-13C]pyruvate metabolism displayed consistency in the NAWM of healthy volunteers and patients. Both kPL and kPB were globally elevated following bevacizumab treatment, while progressive disease demonstrated elevated kPL in gadolinium-enhancing and non-enhancing lesions. Larger prospective studies with homogeneous patient populations are planned to evaluate metabolic changes following treatment.
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Affiliation(s)
- Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Marisa LaFontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Mark Van Criekinge
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - James B Slater
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, USA
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA.
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