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Liu X, Cui D, Xu D, Bok R, Wang ZJ, Vigneron DB, Larson PEZ, Gordon JW. Dynamic T 2 * relaxometry of hyperpolarized [1- 13 C]pyruvate MRI in the human brain and kidneys. Magn Reson Med 2024; 91:1030-1042. [PMID: 38013217 PMCID: PMC10872504 DOI: 10.1002/mrm.29942] [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: 08/14/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE This study aimed to quantifyT 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T. METHODS DynamicT 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamicT 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients.T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimatedT 2 * $$ {T}_2^{\ast } $$ correction. RESULTS TheT 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas theT 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. TheT 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and theT 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). TheT 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys. CONCLUSION Multi-echo dynamic imaging can quantifyT 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in theT 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.
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Affiliation(s)
- Xiaoxi Liu
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Di Cui
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Duan Xu
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Robert Bok
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Zhen J Wang
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Daniel B Vigneron
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, California, USA
| | - Peder E Z Larson
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, California, USA
| | - Jeremy W Gordon
- Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
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2
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Autry AW, Vaziri S, Gordon JW, Chen HY, Kim Y, Dang D, LaFontaine M, Noeske R, Bok R, Villanueva-Meyer JE, Clarke JL, Oberheim Bush NA, Chang SM, Xu D, Lupo JM, Larson PEZ, Vigneron DB, Li Y. Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach. Cancers (Basel) 2024; 16:354. [PMID: 38254844 PMCID: PMC10814348 DOI: 10.3390/cancers16020354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.
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Affiliation(s)
- Adam W. Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Duy Dang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Marisa LaFontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | | | - Robert Bok
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Javier E. Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jennifer L. Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Susan M. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Janine M. Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
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3
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Chung BT, Kim Y, Gordon JW, Chen HY, Autry AW, Lee PM, Hu JY, Tan CT, Suszczynski C, Chang SM, Villanueva-Meyer JE, Bok RA, Larson PEZ, Xu D, Li Y, Vigneron DB. Hyperpolarized [2- 13C]pyruvate MR molecular imaging with whole brain coverage. Neuroimage 2023; 280:120350. [PMID: 37634883 PMCID: PMC10530049 DOI: 10.1016/j.neuroimage.2023.120350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/20/2023] [Accepted: 08/24/2023] [Indexed: 08/29/2023] Open
Abstract
Hyperpolarized (HP) 13C Magnetic Resonance Imaging (MRI) was applied for the first time to image and quantify the uptake and metabolism of [2-13C]pyruvate in the human brain to provide new metabolic information on cerebral energy metabolism. HP [2-13C]pyruvate was injected intravenously and imaged in 5 healthy human volunteer exams with whole brain coverage in a 1-minute acquisition using a specialized spectral-spatial multi-slice echoplanar imaging (EPI) pulse sequence to acquire 13C-labeled volumetric and dynamic images of [2-13C]pyruvate and downstream metabolites [5-13C]glutamate and [2-13C]lactate. Metabolic ratios and apparent conversion rates of pyruvate-to-lactate (kPL) and pyruvate-to-glutamate (kPG) were quantified to investigate simultaneously glycolytic and oxidative metabolism in a single injection.
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Affiliation(s)
- Brian T Chung
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA.
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Philip M Lee
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Chou T Tan
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Chris Suszczynski
- ISOTEC Stable Isotope Division, MilliporeSigma, Merck KGaA, Miamisburg, OH 45342, USA
| | - Susan M Chang
- Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Robert A Bok
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, 1700 Fourth Street, Byers Hall Suite 102, San Francisco, CA 94158, USA; UCSF - UC Berkeley Graduate Program in Bioengineering, University of California, USA; Department of Neurological Surgery, University of California, San Francisco, CA 94158, USA
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Chaumeil M, Guglielmetti C, Qiao K, Tiret B, Ozen M, Krukowski K, Nolan A, Paladini MS, Lopez C, Rosi S. Hyperpolarized 13C metabolic imaging detects long-lasting metabolic alterations following mild repetitive traumatic brain injury. RESEARCH SQUARE 2023:rs.3.rs-3166656. [PMID: 37645937 PMCID: PMC10462249 DOI: 10.21203/rs.3.rs-3166656/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Career athletes, active military, and head trauma victims are at increased risk for mild repetitive traumatic brain injury (rTBI), a condition that contributes to the development of epilepsy and neurodegenerative diseases. Standard clinical imaging fails to identify rTBI-induced lesions, and novel non-invasive methods are needed. Here, we evaluated if hyperpolarized 13C magnetic resonance spectroscopic imaging (HP 13C MRSI) could detect long-lasting changes in brain metabolism 3.5 months post-injury in a rTBI mouse model. Our results show that this metabolic imaging approach can detect changes in cortical metabolism at that timepoint, whereas multimodal MR imaging did not detect any structural or contrast alterations. Using Machine Learning, we further show that HP 13C MRSI parameters can help classify rTBI vs. Sham and predict long-term rTBI-induced behavioral outcomes. Altogether, our study demonstrates the potential of metabolic imaging to improve detection, classification and outcome prediction of previously undetected rTBI.
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Affiliation(s)
| | | | - Kai Qiao
- University of California, San Francisco
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Liu X, Tang S, Cui D, Bok RA, Chen HY, Gordon JW, Wang ZJ, Larson PEZ. A metabolite specific 3D stack-of-spirals bSSFP sequence for improved bicarbonate imaging in hyperpolarized [1- 13C]Pyruvate MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 353:107518. [PMID: 37402333 PMCID: PMC10498937 DOI: 10.1016/j.jmr.2023.107518] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/23/2023] [Accepted: 06/25/2023] [Indexed: 07/06/2023]
Abstract
13C-bicarbonate is a crucial measure of pyruvate oxidation and TCA cycle flux, but is challenging to measure due to its relatively low concentration and thus will greatly benefit from improved signal-to-noise ratio (SNR). To address this, we developed and investigated the feasibility of a 3D stack-of-spirals metabolite-specific balanced steady-state free precession (MS-bSSFP) sequence for improving the SNR and spatial resolution of dynamic 13C-bicarbonate imaging in hyperpolarized [1-13C]pyruvate studies. The bicarbonate MS-bSSFP sequence was evaluated by simulations, phantoms studies, preclinical studies on five rats, brain studies on two healthy volunteers and renal study on one renal cell carcinoma patient. The simulations and phantom results showed that the bicarbonate-specific pulse had minimal perturbation of other metabolites (<1%). In the animal studies, the MS-bSSFP sequence provided an approximately 2.6-3 × improvement in 13C-bicarbonate SNR compared to a metabolite-specific gradient echo (MS-GRE) sequence without altering the bicarbonate or pyruvate kinetics, and the shorter spiral readout in the MS-bSSFP approach reduced blurring. Using the SNR ratio between MS-bSSFP and MS-GRE, the T2 values of bicarbonate and lactate in the rat kidneys were estimated as 0.5 s and 1.1 s, respectively. The in-vivo feasibility of bicarbonate MS-bSSFP sequence was demonstrated in two human brain studies and one renal study. These studies demonstrate the potential of the sequence for in-vivo applications, laying the foundation for future studies to observe this relatively low concentration metabolite with high-quality images and improve measurements of pyruvate oxidation.
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Affiliation(s)
- Xiaoxi Liu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | | | - Di Cui
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Robert A Bok
- 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
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Zhen J Wang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA; Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, San Francisco, CA, USA.
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6
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Hong D, Kim Y, Mushti C, Minami N, Wu J, Cherukuri MK, Swenson RE, Vigneron DB, Ronen SM. Monitoring response to a clinically relevant IDH inhibitor in glioma-Hyperpolarized 13C magnetic resonance spectroscopy approaches. Neurooncol Adv 2023; 5:vdad143. [PMID: 38024238 PMCID: PMC10681661 DOI: 10.1093/noajnl/vdad143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
Background Mutant isocitrate dehydrogenase (IDHmut) catalyzes 2-hydroxyglutarate (2HG) production and is considered a therapeutic target for IDHmut tumors. However, response is mostly associated with inhibition of tumor growth. Response assessment via anatomic imaging is therefore challenging. Our goal was to directly detect IDHmut inhibition using a new hyperpolarized (HP) 13C magnetic resonance spectroscopy-based approach to noninvasively assess α-ketoglutarate (αKG) metabolism to 2HG and glutamate. Methods We studied IDHmut-expressing normal human astrocyte (NHAIDH1mut) cells and rats with BT257 tumors, and assessed response to the IDHmut inhibitor BAY-1436032 (n ≥ 4). We developed a new 13C Echo Planar Spectroscopic Imaging sequence with an optimized RF pulse to monitor the fate of HP [1-13C]αKG and [5-12C,1-13C]αKG with a 2.5 × 2.5 × 8 mm3 spatial resolution. Results Cell studies confirmed that BAY-1436032-treatment leads to a drop in HP 2HG and an increase in HP glutamate detectable with both HP substrates. Data using HP [5-12C,1-13C]αKG also demonstrated that its conversion to 2HG is detectable without the proximal 1.1% natural abundance [5-13C]αKG signal. In vivo studies showed that glutamate is produced in normal brains but no 2HG is detectable. In tumor-bearing rats, we detected the production of both 2HG and glutamate, and BAY-1436032-treatment led to a drop in 2HG and an increase in glutamate. Using HP [5-12C,1-13C]αKG we detected metabolism with an signal-to-noise ratio of 23 for 2HG and 17 for glutamate. Conclusions Our findings point to the clinical potential of HP αKG, which recently received FDA investigational new drug approval for research, for noninvasive localized imaging of IDHmut status.
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Affiliation(s)
- Donghyun Hong
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | | | - Noriaki Minami
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Jing Wu
- National Cancer Institute, NIH, Bethesda, Maryland, USA
| | | | - Rolf E Swenson
- National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Brain Tumor Research Center, UCSF, San Francisco, California, USA
| | - Sabrina M Ronen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Brain Tumor Research Center, UCSF, San Francisco, California, USA
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7
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Vaziri S, Autry AW, Lafontaine M, Kim Y, Gordon JW, Chen HY, Hu JY, Lupo JM, Chang SM, Clarke JL, Villanueva-Meyer JE, Bush NAO, Xu D, Larson PEZ, Vigneron DB, Li Y. Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1- 13C]pyruvate MRI data from patients with glioma. Neuroimage Clin 2022; 36:103155. [PMID: 36007439 PMCID: PMC9421383 DOI: 10.1016/j.nicl.2022.103155] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma. METHODS Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared. RESULTS Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD). CONCLUSION Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.
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Affiliation(s)
- Sana Vaziri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Adam W Autry
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Marisa Lafontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yaewon Kim
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Jasmine Y Hu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.
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8
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Juengling FD, Wuest F, Kalra S, Agosta F, Schirrmacher R, Thiel A, Thaiss W, Müller HP, Kassubek J. Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective. Front Neurol 2022; 13:890425. [PMID: 36061999 PMCID: PMC9428135 DOI: 10.3389/fneur.2022.890425] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 07/20/2022] [Indexed: 01/18/2023] Open
Abstract
Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.
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Affiliation(s)
- Freimut D. Juengling
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Faculty of Medicine, University Bern, Bern, Switzerland
| | - Frank Wuest
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Neurology, University of Alberta, Edmonton, AB, Canada
| | - Federica Agosta
- Division of Neuroscience, San Raffaele Scientific Institute, University Vita Salute San Raffaele, Milan, Italy
| | - Ralf Schirrmacher
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Medical Isotope and Cyclotron Facility, University of Alberta, Edmonton, AB, Canada
| | - Alexander Thiel
- Lady Davis Institute for Medical Research, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Wolfgang Thaiss
- Department of Nuclear Medicine, University of Ulm Medical Center, Ulm, Germany
- Department of Diagnostic and Interventional Radiology, University of Ulm Medical Center, Ulm, Germany
| | - Hans-Peter Müller
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
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Kaggie JD, Khan AS, Matys T, Schulte RF, Locke MJ, Grimmer A, Frary A, Menih IH, Latimer E, Graves MJ, McLean MA, Gallagher FA. Deuterium metabolic imaging and hyperpolarized 13C-MRI of the normal human brain at clinical field strength reveals differential cerebral metabolism. Neuroimage 2022; 257:119284. [PMID: 35533826 DOI: 10.1016/j.neuroimage.2022.119284] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 12/01/2022] Open
Abstract
Deuterium metabolic imaging (DMI) and hyperpolarized 13C-pyruvate MRI (13C-HPMRI) are two emerging methods for non-invasive and non-ionizing imaging of tissue metabolism. Imaging cerebral metabolism has potential applications in cancer, neurodegeneration, multiple sclerosis, traumatic brain injury, stroke, and inborn errors of metabolism. Here we directly compare these two non-invasive methods at 3 T for the first time in humans and show how they simultaneously probe both oxidative and non-oxidative metabolism. DMI was undertaken 1-2 h after oral administration of [6,6'-2H2]glucose, and 13C-MRI was performed immediately following intravenous injection of hyperpolarized [1-13C]pyruvate in ten and nine normal volunteers within each arm respectively. DMI was used to generate maps of deuterium-labelled water, glucose, lactate, and glutamate/glutamine (Glx) and the spectral separation demonstrated that DMI is feasible at 3 T. 13C-HPMRI generated maps of hyperpolarized carbon-13 labelled pyruvate, lactate, and bicarbonate. The ratio of 13C-lactate/13C-bicarbonate (mean 3.7 ± 1.2) acquired with 13C-HPMRI was higher than the equivalent 2H-lactate/2H-Glx ratio (mean 0.18 ± 0.09) acquired using DMI. These differences can be explained by the route of administering each probe, the timing of imaging after ingestion or injection, as well as the biological differences in cerebral uptake and cellular physiology between the two molecules. The results demonstrate these two metabolic imaging methods provide different yet complementary readouts of oxidative and reductive metabolism within a clinically feasible timescale. Furthermore, as DMI was undertaken at a clinical field strength within a ten-minute scan time, it demonstrates its potential as a routine clinical tool in the future.
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Affiliation(s)
- Joshua D Kaggie
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK.
| | - Alixander S Khan
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK
| | | | - Matthew J Locke
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Ashley Grimmer
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Amy Frary
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Ines Horvat Menih
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Elizabeth Latimer
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Martin J Graves
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK
| | - Mary A McLean
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge UK
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK; Cambridge University Hospitals, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
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Pini C, Chiti A. New technologies-the best is yet to come. Eur J Nucl Med Mol Imaging 2021; 48:4136-4137. [PMID: 34652495 DOI: 10.1007/s00259-021-05589-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Cristiano Pini
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4Pieve Emanuele, 20090, Milan, Italy.,Department of Nuclear Medicine, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy
| | - Arturo Chiti
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4Pieve Emanuele, 20090, Milan, Italy. .,Department of Nuclear Medicine, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.
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