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Wang K, Ju L, Song Y, Blair L, Xie K, Liu C, Li A, Zhu D, Xu F, Liu G, Heo HY, Yadav N, Oeltzschner G, Edden RAE, Qin Q, Kamson DO, Xu J. Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition. Magn Reson Med 2024; 92:1456-1470. [PMID: 38748853 PMCID: PMC11262991 DOI: 10.1002/mrm.30134] [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: 01/26/2024] [Revised: 04/01/2024] [Accepted: 04/09/2024] [Indexed: 05/22/2024]
Abstract
PURPOSE To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method. METHODS Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient. RESULTS The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well. CONCLUSION The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.
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Affiliation(s)
- Kexin Wang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Licheng Ju
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lindsay Blair
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kevin Xie
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Claire Liu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Anna Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Dan Zhu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Feng Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanshu Liu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hye-Young Heo
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nirbhay Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Georg Oeltzschner
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Richard A. E. Edden
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David Olayinka Kamson
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Huemer M, Stilianu C, Maier O, Fabian MS, Schmidt M, Doerfler A, Bredies K, Zaiss M, Stollberger R. Improved quantification in CEST-MRI by joint spatial total generalized variation. Magn Reson Med 2024; 92:1683-1697. [PMID: 38703028 DOI: 10.1002/mrm.30129] [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: 10/17/2023] [Revised: 03/19/2024] [Accepted: 04/07/2024] [Indexed: 05/06/2024]
Abstract
PURPOSE In this work, the use of joint Total Generalized Variation (TGV) regularization to improve Multipool-Lorentzian fitting of chemical exchange saturation transfer (CEST) Spectra in terms of stability and parameter signal-to-noise ratio (SNR) was investigated. THEORY AND METHODS The joint TGV term was integrated into the nonlinear parameter fitting problem. To increase convergence and weight the gradients, preconditioning using a voxel-wise singular value decomposition was applied to the problem, which was then solved using the iteratively regularized Gauss-Newton method combined with a Primal-Dual splitting algorithm. The TGV method was evaluated on simulated numerical phantoms, 3T phantom data and 7T in vivo data with respect to systematic errors and robustness. Three reference methods were also implemented: The standard nonlinear fitting, a method using a nonlocal-means filter for denoising and the pyramid scheme, which uses downsampled images to acquire accurate start values. RESULTS The proposed regularized fitting method showed significantly improved robustness (compared to the reference methods). In testing, over a range of SNR values the TGV fit outperformed the other methods and showed accurate results even for large amounts of added noise. Parameter values found were closer or comparable to the ground truth. For in vivo datasets, the added regularization increased the parameter map SNR and prevented instabilities. CONCLUSION The proposed fitting method using TGV regularization leads to improved results over a range of different data-sets and noise levels. Furthermore, it can be applied to all Z-spectrum data, with different amounts of pools, where the improved SNR and stability can increase diagnostic confidence.
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Affiliation(s)
- Markus Huemer
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Clemens Stilianu
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Oliver Maier
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Moritz Simon Fabian
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - Manuel Schmidt
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - Arnd Doerfler
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - Kristian Bredies
- Department of Mathematics and Scientific Computing, University of Graz, Graz, Austria
- BioTechMed Graz, Graz, Austria
| | - Moritz Zaiss
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
- High-Field Magnetic Resonance Center, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Rudolf Stollberger
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- BioTechMed Graz, Graz, Austria
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3
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Xiao G, Zhang XL, Wang SQ, Lai SX, Nie TT, Chen YW, Zhuang CY, Yan G, Wu RH. Quantitative separation of CEST effect by R ex-line-fit analysis of Z-spectra. Sci Rep 2024; 14:21471. [PMID: 39277679 PMCID: PMC11401877 DOI: 10.1038/s41598-024-72141-4] [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: 01/15/2024] [Accepted: 09/04/2024] [Indexed: 09/17/2024] Open
Abstract
The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.
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Affiliation(s)
- Gang Xiao
- School of Mathematics and Statistics, Hanshan Normal University, Chaozhou, 521041, China
| | - Xiao-Lei Zhang
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
| | - Si-Qi Wang
- College of Engineering, Shantou University, Shantou, 515063, China
| | - Shi-Xin Lai
- College of Engineering, Shantou University, Shantou, 515063, China
| | - Ting-Ting Nie
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430079, China
| | - Yao-Wen Chen
- College of Engineering, Shantou University, Shantou, 515063, China
| | - Cai-Yu Zhuang
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
| | - Gen Yan
- Department of Radiology, Second Affiliated Hospital of Xiamen Medical College, Xiamen, 361021, China.
| | - Ren-Hua Wu
- Department of Radiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
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Chung JJ, Kim H, Ji Y, Lu D, Zhou IY, Sun PZ. Improving standardization and accuracy of in vivo omega plot exchange parameter determination using rotating-frame model-based fitting of quasi-steady-state Z-spectra. Magn Reson Med 2024. [PMID: 39221563 DOI: 10.1002/mrm.30259] [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: 05/02/2024] [Revised: 07/31/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024]
Abstract
PURPOSE Although Ω-plot-driven quantification of in vivo amide exchange properties has been demonstrated, differences in scan parameters may complicate the fidelity of determination. This work systematically evaluated the use of quasi-steady-state (QUASS) Z-spectra reconstruction to standardize in vivo amide exchange quantification across acquisition conditions and further determined it in vivo. METHODS Simulation and in vivo rodent brain chemical exchange saturation transfer (CEST) data at 4.7 T were fit with and without QUASS reconstruction using both multi-Lorentzian and model-based fitting approaches. pH modulation was accomplished both in simulation and in vivo by inducing global ischemia via cardiac arrest. Amide parameters were determined via Ω-plots and compared across methods. RESULTS Simulation showed that Ω-plots using multi-Lorentzian fitting could underestimate the exchange rate, with error increasing as conditions diverged from the steady state. In comparison, model-based fitting using QUASS estimated the same exchange rate within 2%. These results aligned with in vivo findings where multi-Lorentzian fitting of native Z-spectra resulted in an exchange rate of 64 ± 13 s-1 (38 ± 16 s-1 after cardiac arrest), whereas model-based fitting of QUASS Z-spectra yielded an exchange rate of 126 ± 25 s-1 (49 ± 13 s-1). CONCLUSION The model-based fitting of QUASS CEST Z-spectra enables consistent and accurate quantification of exchange parameters through Ω-plot construction by reducing error due to signal overlap and nonequilibrium CEST effects.
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Affiliation(s)
- Julius Juhyun Chung
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA
| | - Hahnsung Kim
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Yang Ji
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Dongshuang Lu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Iris Y Zhou
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Phillip Zhe Sun
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA
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5
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Zhu H, Li Y, Ding Y, Liu Y, Shen N, Xie Y, Yan S, Liu D, Zhang X, Li L, Zhu W. Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation. J Neurooncol 2024; 169:287-297. [PMID: 38874844 DOI: 10.1007/s11060-024-04729-9] [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: 04/19/2024] [Accepted: 05/27/2024] [Indexed: 06/15/2024]
Abstract
PURPOSE To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5). METHODS 95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation. RESULTS The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001). CONCLUSION Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.
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Affiliation(s)
- Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Yuejie Ding
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Yufei Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Dong Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China
| | - Xiaoxiao Zhang
- Department of Clinical, Philips Healthcare, Wuhan, China
| | - Li Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China.
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, PR China.
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Chakraborty K, Burman R, Nisar S, Miller S, Loschinskey Z, Wu S, Li Y, Bag AK, Khan A, Goodenough C, Wilson N, Haris M, McCormack SE, Reddy R, Ness K, Finkel R, Bagga P. Reliability of In Vivo Creatine-Weighted Chemical Exchange Saturation Transfer (CrCEST) MRI in Calf Skeletal Muscle of Healthy Volunteers at 3 T. J Magn Reson Imaging 2024. [PMID: 39212126 DOI: 10.1002/jmri.29566] [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: 05/01/2024] [Revised: 07/29/2024] [Accepted: 07/29/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Skeletal muscle mitochondrial oxidative phosphorylation (mtOXPHOS) is important for ATP generation and its dysfunction leads to exercise intolerance. Phosphorus magnetic resonance spectroscopy (31P-MRS) is a useful, noninvasive technique for mtOXPHOS assessment but has limitations. Creatine-weighted chemical exchange saturation transfer (CrCEST) MRI is a potential alternative to assess muscle bioenergetics. PURPOSE To evaluate the interscan repeatability, intra- and interobserver reproducibility of CrCEST during mild plantar flexion exercise. STUDY TYPE Retrospective. SUBJECTS Twenty healthy volunteers (age 37.6 ± 12.4 years, 11 females). FIELD STRENGTH/SEQUENCE 3 T/CEST imaging using gradient echo readout. ASSESSMENT τCrCEST (postexercise Cr recovery time) was assessed in two scans for each participant, following mild plantar flexion exercises targeting the medial gastrocnemius (MG), lateral gastrocnemius (LG), and soleus (Sol) muscles. Three observers measured τCrCEST for interobserver reproducibility. Three readings by one observer were used to measure intraobserver reproducibility. Two scans were used for within-participant interscan repeatability. STATISTICAL TESTS Paired t tests, intraclass correlation coefficient (ICC), and Pearson correlation were conducted. Bland-Altman plots were used to analyze the interobserver variability. A P-value of 0.05 was considered statistically significant. RESULTS There was excellent intra- (ICC∈ 0.94 - 0.98 $$ \in \left[0.94-0.98\right] $$ ) and interobserver (ICC∈ 0.9 - 0.98 $$ \in \left[0.9-0.98\right] $$ ) reproducibility, with moderate interscan repeatability for τCrCEST in LG and MG (ICC∈ 0.54 - 0.74 $$ \in \left[0.54-0.74\right] $$ ) and poor-to-moderate interscan repeatability in Sol (ICC∈ 0.24 - 0.53 $$ \in \left[0.24-0.53\right] $$ ). Excellent interobserver reproducibility was confirmed by Bland-Altman plots (fixed bias P-value∈ 0.08 - 0.87 $$ \in \left[0.08-0.87\right] $$ ). DATA CONCLUSION CrCEST MRI shows promise in assessing muscle bioenergetics by evaluating τCrCEST during mild plantar flexion exercise with reasonable reliability, particularly in LG and MG. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Kasturee Chakraborty
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Ritambhar Burman
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Sabah Nisar
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Saorla Miller
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Zachary Loschinskey
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Shengjie Wu
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Yimei Li
- Department of Biostatistics, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Asim K Bag
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Ayaz Khan
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Chelsea Goodenough
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Neil Wilson
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mohammad Haris
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Shana E McCormack
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kirsten Ness
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Richard Finkel
- Department of Pediatric Medicine, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Puneet Bagga
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, Tennessee, USA
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7
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Peng Y, Dai Y, Zhang S, Deng J, Jia X. Joint k- ω Space Image Reconstruction and Data Fitting for Chemical Exchange Saturation Transfer Magnetic Resonance Imaging. Tomography 2024; 10:1123-1138. [PMID: 39058057 PMCID: PMC11280605 DOI: 10.3390/tomography10070085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/05/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k-ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω, while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively.
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Affiliation(s)
- Yuting Peng
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Yan Dai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Shu Zhang
- Department of Radiology, Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Jie Deng
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Xun Jia
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
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8
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Cai Z, Zhong Q, Feng Y, Wang Q, Zhang Z, Wei C, Yin Z, Liang C, Liew CW, Kazak L, Cypess AM, Liu Z, Cai K. Non-invasive mapping of brown adipose tissue activity with magnetic resonance imaging. Nat Metab 2024; 6:1367-1379. [PMID: 39054361 PMCID: PMC11272596 DOI: 10.1038/s42255-024-01082-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 06/14/2024] [Indexed: 07/27/2024]
Abstract
Thermogenic brown adipose tissue (BAT) has a positive impact on whole-body metabolism. However, in vivo mapping of BAT activity typically relies on techniques involving ionizing radiation, such as [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) and computed tomography (CT). Here we report a noninvasive metabolic magnetic resonance imaging (MRI) approach based on creatine chemical exchange saturation transfer (Cr-CEST) contrast to assess in vivo BAT activity in rodents and humans. In male rats, a single dose of the β3-adrenoceptor agonist (CL 316,243) or norepinephrine, as well as cold exposure, triggered a robust elevation of the Cr-CEST MRI signal, which was consistent with the [18F]FDG PET and CT data and 1H nuclear magnetic resonance measurements of creatine concentration in BAT. We further show that Cr-CEST MRI detects cold-stimulated BAT activation in humans (both males and females) using a 3T clinical scanner, with data-matching results from [18F]FDG PET and CT measurements. This study establishes Cr-CEST MRI as a promising noninvasive and radiation-free approach for in vivo mapping of BAT activity.
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Affiliation(s)
- Zimeng Cai
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- School of Medicine, South China University of Technology, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Qiaoling Zhong
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
| | - Qian Wang
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, China
| | - Zuoman Zhang
- Department of Neonatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Cailv Wei
- School of Medicine, Shenzhen Campus, Sun Yat-sen University, Shenzhen, China
| | - Zhinan Yin
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Tumor Interventional Diagnosis and Treatment, Zhuhai Institute of Translational Medicine, Zhuhai People's Hospital Affiliated with Jinan University, Jinan University, Zhuhai, China
| | - Changhong Liang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Chong Wee Liew
- Physiology and Biophysics Department, University of Illinois at Chicago, Chicago, IL, USA
| | - Lawrence Kazak
- Rosalind & Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada
- Department of Biochemistry, McGill University, Montreal, Quebec, Canada
| | - Aaron M Cypess
- Diabetes, Endocrinology, and Obesity Branch, Intramural Research Program, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, MD, USA
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, USA
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9
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Sun PZ. Quasi-steady-state (QUASS) reconstruction enhances T 1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T 1 correction in quantitative CEST MRI of rodent brain tumor models. Magn Reson Med 2024; 92:236-245. [PMID: 38380727 PMCID: PMC11055669 DOI: 10.1002/mrm.30056] [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: 10/30/2023] [Revised: 01/26/2024] [Accepted: 02/04/2024] [Indexed: 02/22/2024]
Abstract
PURPOSE The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions. THEORY AND METHODS Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction. RESULTS Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other. CONCLUSIONS AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.
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Affiliation(s)
- Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
- Winship Cancer Institute, Emory University, Atlanta, GA
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA
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10
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Tao Q, Zhang Q, An Z, Chen Z, Feng Y. Multi-Parametric MRI for Evaluating Variations in Renal Structure, Function, and Endogenous Metabolites in an Animal Model With Acute Kidney Injury Induced by Ischemia Reperfusion. J Magn Reson Imaging 2024; 60:245-255. [PMID: 37881827 DOI: 10.1002/jmri.29094] [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: 07/16/2023] [Revised: 10/12/2023] [Accepted: 10/12/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Ischemia reperfusion injury (IRI)-induced acute kidney injury (AKI) may occur after renal ischemic injury. There is a lack of an accurate and comprehensive detection technique for IRI-AKI. PURPOSE To longitudinally evaluate IRI-AKI in rats by renal structure, function, and metabolites using multi-parametric MRI (mpMRI). STUDY TYPE Prospective. ANIMAL MODEL Forty-eight rats undergoing IRI-AKI. FIELD STRENGTH/SEQUENCE 7-T, T1 mapping, and arterial spin labeling (ASL): echo planar imaging (EPI) sequence; blood oxygen level-dependent (BOLD): gradient recalled echo (GRE) sequence; T2 mapping, quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST): rapid acquisition with relaxation enhancement (RARE) sequence. ASSESSMENT The mpMRI for IRI-AKI was conducted at 0 (control), 1, 3, 7, 14, and 28 days, all included eight rats. The longitudinal mpMRI signal of manually outlined cortex, outer stripe of the outer medulla (OSOM), inner stripe of the outer medulla, and medulla plus pelvis were calculated and compared, their diagnosis performance for IRI-AKI also been evaluated. STATISTICAL TESTS Pearson correlations analysis for correlation between mpMRI signal and renal injury, unpaired t-tests for comparing the signal changes, and receiver operating characteristics (ROC) analysis was used to identify most sensitive indicator of mpMRI. A P-value <0.05 was considered statistically significant. RESULTS Compared with control kidneys, the T1 and T2 values of the cortex and medulla in IRI kidneys increased and reached their highest values on day 14, and the kidneys also showed the most severe edema and segments blurred. The RBF in the cortex and OSOM showed a significant decline after day 3. The BOLD signal in the OSOM largest increased on day 28. The cortical PSR and the amine-CEST both decreased with IRI-AKI progression, and amine-CEST achieved the highest AUC for the diagnosis (0.899). DATA CONCLUSION Multi-parametric MRI may show comprehensive variations in IRI-AKI, and amine-CEST may exhibit the highest accuracy for diagnosis of IRI-AKI. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Quan Tao
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Qianqian Zhang
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Ziqi An
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Zelong Chen
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Provincial Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
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11
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Shaghaghi M, Damen FC, Li W, Tai LM, Cai K. Induced saturation transfer recovery steady states (iSTRESS) for proton exchange rate mapping with CEST MRI, a preliminary study. Magn Reson Imaging 2024; 109:264-270. [PMID: 38522624 DOI: 10.1016/j.mri.2024.03.034] [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: 10/20/2023] [Revised: 03/21/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024]
Abstract
Proton exchange underpins essential mechanisms in diverse MR imaging contrasts. Omega plots have proven effective in mapping proton exchange rates (kex) in live human brains, enabling the differentiation of MS lesion activities and characterization of ischemic stroke. However, Omega plots require extended saturation durations (typically 5 to 10 s), resulting in high specific absorption rates (SAR) that can hinder clinical feasibility. In this study, we introduce a novel kex mapping approach, named induced Saturation Transfer Recovery Steady-States (iSTRESS). iSTRESS integrates an excitation flip angle pulse prior to chemical exchange saturation transfer (CEST) saturation, effectively aligning the magnetization with its steady-state value. This innovation reduces saturation times and mitigates SAR concerns. The formula for iSTRESS-based kex quantification was derived theoretically, involving two measurements with distinct excitation flip angles and saturation B1 values. Bloch-McConnell simulations confirmed that iSTRESS-based kex values closely matched input values (R2 > 0.99). An iSTRESS MRI sequence was implemented on a 9.4 T preclinical MRI, imaging protein phantoms with pH values ranging from 6.2 to 7.4 (n = 4). Z-spectra were acquired using excitation flip angles of 30° and 60°, followed by CEST saturation at powers of 30 and 120 Hz respectively, with a total saturation time of <1 s, resulting in two iSTRESS states for kex mapping. kex maps derived from the phantom study exhibited a linear correlation (R2 > 0.99) with Omega plot results. The developed iSTRESS method allows for kex quantification with significantly reduced saturation times, effectively minimizing SAR concerns.
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Affiliation(s)
- Mehran Shaghaghi
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Frederick C Damen
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Weiguo Li
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Leon M Tai
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA; Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA.
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12
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Shaghaghi M, Cai K. Analytical solution of the Bloch-McConnell equations for steady-state CEST Z-spectra. Magn Reson Imaging 2024; 109:74-82. [PMID: 38430977 DOI: 10.1016/j.mri.2024.02.015] [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: 01/29/2024] [Revised: 02/22/2024] [Accepted: 02/23/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE To derive an analytic expression for the steady-state Chemical Exchange Saturation Transfer (CEST) Z-spectra of a two-pool proton-exchanging system, facilitating simulations and expedited fitting of steady-state Z-spectra. METHOD The analytical expression is derived by directly solving the set of Bloch-McConnell differential equations in matrix form for a two-pool exchanging system, determining water magnetization under steady-state saturation across the entire Z-spectrum. The analytic solution is compared and validated against the numerical solution of Bloch-McConnell equations under prolonged saturation. The study also explores the line shape of a CEST peak, interpolating under-sampled Z-spectra, and Z-spectral fitting in the presence of noise. RESULTS The derived analytic solution accurately reproduces spectra obtained through numerical solutions. Direct fitting of simulated CEST spectra with the analytical solution yields the physical parameters of the exchanging system. The study shows that the analytical solution enables the reproduction of fully sampled spectra from sparsely sampled Z-spectra. Additionally, it confirms the approximation of the CEST spectrum of a single exchanging proton species with a Lorentzian function. Monte Carlo simulations reveal that the accuracy and precision of Z-spectral fittings for physical parameters are significantly influenced by data noise. The study also derives and discusses the analytical solution for three-pool Z-spectra. CONCLUSION The derived analytic solution for steady state Z-spectra can be utilized for simulations and Z-spectrum fitting, significantly reducing fitting times compared to numerical methods employed for fitting CEST Z-spectra.
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Affiliation(s)
- Mehran Shaghaghi
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA; Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA.
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13
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Schmitz-Abecassis B, Najac C, Plugge J, van Osch MJP, Ercan E. Investigation of metabolite correlates of CEST in the human brain at 7 T. NMR IN BIOMEDICINE 2024; 37:e5104. [PMID: 38258649 DOI: 10.1002/nbm.5104] [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: 08/25/2023] [Revised: 12/05/2023] [Accepted: 12/23/2023] [Indexed: 01/24/2024]
Abstract
Metabolite-weighted chemical exchange saturation transfer MRI can be used to indirectly image metabolites such as creatine and glutamate. This study aims to further explore the contrast of CEST at 2 ppm in the human brain at 7T and investigate the metabolite correlates of CEST at 2 ppm via correlations with magnetic resonance spectroscopy (MRS). Simulations were performed to establish the optimal acquisition parameters, such as total saturation time (tsat) and B1 root mean squared (B1rms) for CEST at 2 ppm in the human brain. Parameters were validated via in vitro phantom studies at 7T using concentrations, pH and temperature comparable to what is found in the human brain. Finally, 10 healthy volunteers were scanned at 7T for comparison with MRS. Our results show that the optimal parameters to acquire CEST at 2 ppm images are: B1rms = 2.14 μT & tsat = 1500 ms, respectively. Comparison with MRS showed no significant correlation between CEST at 2 ppm and total Creatine measured by MRS (R = 0.19; p-value = 0.273). However, a significant correlation was found between CEST at 2 ppm and Glu (R = 0.39; p-value = 0.033), indicating the broad Glutamate-weighted CEST as the main measurable contributor to CEST at 2 ppm. We identified and confirmed optimal CEST at 2 ppm sequence parameters and validated CEST at 2 ppm measurements in a controlled in vitro environment. Our findings suggest that glutamate is a substantial contributor to the CEST at 2 ppm contrast observed in the human brain, whereas the creatine contribution to CEST at 2 ppm in the brain did not show a measurable contribution.
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Affiliation(s)
- Bárbara Schmitz-Abecassis
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Chloé Najac
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jaimy Plugge
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute of Physics, Leiden University, Leiden, The Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Ece Ercan
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- MR R&D, Clinical Science, Philips, Best, The Netherlands
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14
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Viswanathan M, Yin L, Kurmi Y, Zu Z. Machine learning-based amide proton transfer imaging using partially synthetic training data. Magn Reson Med 2024; 91:1908-1922. [PMID: 38098340 PMCID: PMC10955622 DOI: 10.1002/mrm.29970] [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: 08/12/2023] [Revised: 10/30/2023] [Accepted: 11/26/2023] [Indexed: 12/20/2023]
Abstract
PURPOSE Machine learning (ML) has been increasingly used to quantify CEST effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, whereas training with fully simulated data may introduce bias because of limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect. METHODS Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9 L tumors. RESULTS Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data. CONCLUSION Partially synthetic CEST data can address the challenges in conventional ML methods.
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Affiliation(s)
- Malvika Viswanathan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Biomedical Engineering, Vanderbilt University, Nashville, US
| | - Leqi Yin
- School of Engineering, Vanderbilt University, Nashville, US
| | - Yashwant Kurmi
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Biomedical Engineering, Vanderbilt University, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
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15
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Fabian MS, Rajput JR, Schüre JR, Weinmüller S, Mennecke A, Möhle TA, Rampp S, Schmidt M, Dörfler A, Zaiss M. Comprehensive 7 T CEST: A clinical MRI protocol covering multiple exchange rate regimes. NMR IN BIOMEDICINE 2024; 37:e5096. [PMID: 38343093 DOI: 10.1002/nbm.5096] [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: 07/26/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 04/04/2024]
Abstract
Chemical exchange saturation transfer (CEST) is a magnetic resonance (MR) imaging method providing molecular image contrasts based on indirect detection of low concentrated solutes. Previous CEST studies focused predominantly on the imaging of single CEST exchange regimes (e.g., slow, intermediate or fast exchanging groups). In this work, we aim to establish a so-called comprehensive CEST protocol for 7 T, covering the different exchange regimes by three saturation B1 amplitude regimes: low, intermediate and high. We used the results of previous publications and our own simulations in pulseq-CEST to produce a 7 T CEST protocol that has sensitivity to these three B1 regimes. With postprocessing optimization (simultaneous mapping of water shift and B1, B0-fitting, multiple interleaved mode saturation B1 correction, neural network employment (deepCEST) and analytical input feature reduction), we are able to shorten our initially 40 min protocol to 15 min and generate six CEST contrast maps simultaneously. With this protocol, we measured four healthy subjects and one patient with a brain tumor. We established a comprehensive CEST protocol for clinical 7 T MRI, covering three different B1 amplitude regimes. We were able to reduce the acquisition time significantly by more than 50%, while still maintaining decent image quality and contrast in healthy subjects and one patient with a tumor. Our protocol paves the way to perform comprehensive CEST studies in clinical scan times for hypothesis generation regarding molecular properties of certain pathologies, for example, ischemic stroke or high-grade brain tumours.
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Affiliation(s)
- Moritz Simon Fabian
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Junaid Rasool Rajput
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Jan-Rüdiger Schüre
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Simon Weinmüller
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Angelika Mennecke
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Tim Alexius Möhle
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Stefan Rampp
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
- Department of Neurosurgery, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Schmidt
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Moritz Zaiss
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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16
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Ju L, Wang K, Schär M, Xu S, Rogers J, Zhu D, Qin Q, Weiss RG, Xu J. Simultaneous creatine and phosphocreatine mapping of skeletal muscle by CEST MRI at 3T. Magn Reson Med 2024; 91:942-954. [PMID: 37899691 PMCID: PMC10842434 DOI: 10.1002/mrm.29907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/20/2023] [Accepted: 10/11/2023] [Indexed: 10/31/2023]
Abstract
PURPOSE To confirm that CrCEST in muscle exhibits a slow-exchanging process, and to obtain high-resolution amide, creatine (Cr), and phosphocreatine (PCr) maps of skeletal muscle using a POlynomial and Lorentzian Line-shape Fitting (PLOF) CEST at 3T. METHODS We used dynamic changes in PCr/CrCEST of mouse hindlimb before and after euthanasia to assign the Cr and PCr CEST peaks in the Z-spectrum at 3T and to obtain the optimum saturation parameters. Segmented 3D EPI was employed to obtain multi-slice amide, PCr, and Cr CEST maps of human skeletal muscle. Subsequently, the PCrCEST maps were calibrated using the PCr concentrations determined by 31 P MRS. RESULTS A comparison of the Z-spectra in mouse hindlimb before and after euthanasia indicated that CrCEST is a slow-exchanging process in muscle (<150.7 s-1 ). This allowed us to simultaneously extract PCr/CrCEST signals at 3T using the PLOF method. We determined optimal B1 values ranging from 0.3 to 0.6 μT for CrCEST in muscle and 0.3-1.2 μT for PCrCEST. For the study on human calf muscle, we determined an optimum saturation time of 2 s for both PCr/CrCEST (B1 = 0.6 μT). The PCr/CrCEST using 3D EPI were found to be comparable to those obtained using turbo spin echo (TSE). (3D EPI/TSE PCr: (2.6 ± 0.3) %/(2.3 ± 0.1) %; Cr: (1.3 ± 0.1) %/(1.4 ± 0.07) %). CONCLUSIONS Our study showed that in vivo CrCEST is a slow-exchanging process. Hence, amide, Cr, and PCr CEST in the skeletal muscle can be mapped simultaneously at 3T by PLOF CEST.
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Affiliation(s)
- Licheng Ju
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kexin Wang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Schär
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Su Xu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Rogers
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dan Zhu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert G. Weiss
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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17
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Di Gregorio E, Papi C, Conti L, Di Lorenzo A, Cavallari E, Salvatore M, Cavaliere C, Ferrauto G, Aime S. A Magnetic Resonance Imaging-Chemical Exchange Saturation Transfer (MRI-CEST) Method for the Detection of Water Cycling across Cellular Membranes. Angew Chem Int Ed Engl 2024; 63:e202313485. [PMID: 37905585 DOI: 10.1002/anie.202313485] [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: 09/11/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 11/02/2023]
Abstract
Water cycling across the membrane transporters is considered a hallmark of cellular metabolism and it could be of high diagnostic relevance in the characterization of tumors and other diseases. The method relies on the response of intracellular proton exchanging molecules to the presence of extracellular Gd-based contrast agents (GBCAs). Paramagnetic GBCAs enhances the relaxation rate of water molecules in the extracellular compartment and, through membrane exchange, the relaxation enhancement is transferred to intracellular molecules. The effect is detected at the MRI-CEST (Magnetic Resonance Imaging - Chemical Exchange Saturation Transfer) signal of intracellular proton exchanging molecules. The magnitude of the change in the CEST response reports on water cycling across the membrane. The method has been tested on Red Blood Cells and on orthotopic murine models of breast cancer with different degree of malignancy (4T1, TS/A and 168FARN). The distribution of voxels reporting on membrane permeability fits well with the cells' aggressiveness and acts as an early reporter to monitor therapeutic treatments.
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Affiliation(s)
- Enza Di Gregorio
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Chiara Papi
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Laura Conti
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Antonino Di Lorenzo
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Eleonora Cavallari
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Marco Salvatore
- IRCCS SDN SynLab, Via E. Gianturco 113, 80143, Napoli, Italy
| | - Carlo Cavaliere
- IRCCS SDN SynLab, Via E. Gianturco 113, 80143, Napoli, Italy
| | - Giuseppe Ferrauto
- Department of Molecular Biotechnologies and Health Sciences, University of Torino, Via Nizza 52, 10126, Torino, Italy
| | - Silvio Aime
- IRCCS SDN SynLab, Via E. Gianturco 113, 80143, Napoli, Italy
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Viswanathan M, Kurmi Y, Zu Z. Nuclear Overhauser enhancement imaging at -1.6 ppm in rat brain at 4.7T. Magn Reson Med 2024; 91:615-629. [PMID: 37867419 DOI: 10.1002/mrm.29896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/21/2023] [Accepted: 10/04/2023] [Indexed: 10/24/2023]
Abstract
PURPOSE A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer signal at around -1.6 ppm, termed NOE(-1.6), has been reported at high fields of 7T and 9.4T previously. This study aims to validate the presence of this signal at a relatively low field of 4.7T and evaluate its variations in different brain regions and tumors. METHODS Rats were injected with monocrystalline iron oxide nanoparticles to reduce the NOE(-1.6) signal. CEST signals were measured using different saturation powers before and after injection to assess the presence of this signal. Multiple-pool Lorentzian fits, with/without inclusion of the NOE(-1.6) pool, were performed on CEST Z-spectra obtained from healthy rat brains and rats with 9L tumors. These fits aimed to further validate the presence of the NOE(-1.6) signal and quantify its amplitude. RESULTS The NOE(-1.6) signal exhibited a dramatic change following the injection of monocrystalline iron oxide nanoparticles, confirming its presence at 4.7T. The NOE(-1.6) signal reached its peak at a saturation power of ∼0.75 μT, indicating an optimized power level. The multiple-pool Lorentzian fit without the NOE(-1.6) pool showed higher residuals around -1.6 ppm compared to the fit with this pool, further supporting the presence of this signal. The NOE(-1.6) signal did not exhibit significant variation in the corpus callosum and caudate putamen regions, but it showed a significant decrease in tumors, which aligns with previous findings at 9.4T. CONCLUSION This study successfully demonstrated the presence of the NOE(-1.6) signal at 4.7T, which provides valuable insights into its potential applications at lower field strengths.
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Affiliation(s)
- Malvika Viswanathan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Yashwant Kurmi
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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19
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Wang K, Huang J, Ju L, Xu S, Gullapalli RP, Liang Y, Rogers J, Li Y, van Zijl PCM, Weiss RG, Chan KWY, Xu J. Creatine mapping of the brain at 3T by CEST MRI. Magn Reson Med 2024; 91:51-60. [PMID: 37814487 PMCID: PMC10843037 DOI: 10.1002/mrm.29876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 10/11/2023]
Abstract
PURPOSE To assess the feasibility of CEST-based creatine (Cr) mapping in brain at 3T using the guanidino (Guan) proton resonance. METHODS Wild type and knockout mice with guanidinoacetate N-methyltransferase deficiency and low Cr and phosphocreatine (PCr) concentrations in the brain were used to assign the Cr and protein-based arginine contributions to the GuanCEST signal at 2.0 ppm. To quantify the Cr proton exchange rate, two-step Bloch-McConnell fitting was used to fit the extracted CrCEST line-shape and multi-B1 Z-spectral data. The pH response of GuanCEST was simulated to demonstrate its potential for pH mapping. RESULTS Brain Z-spectra of wild type and guanidinoacetate N-methyltransferase deficiency mice show a clear Guan proton peak at 2.0 ppm at 3T. The CrCEST signal contributes ∼23% to the GuanCEST signal at B1 = 0.8 μT, where a maximum CrCEST effect of 0.007 was detected. An exchange rate range of 200-300 s-1 was estimated for the Cr Guan protons. As revealed by the simulation, an elevated GuanCEST in the brain is observed when B1 is less than 0.4 μT at 3T, when intracellular pH reduces by 0.2. Conversely, the GuanCEST decreases when B1 is greater than 0.4 μT with the same pH drop. CONCLUSIONS CrCEST mapping is possible at 3T, which has potential for detecting intracellular pH and Cr concentration in brain.
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Affiliation(s)
- Kexin Wang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jianpan Huang
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Licheng Ju
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Su Xu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rao P Gullapalli
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yajie Liang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Rogers
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C. M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert G. Weiss
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kannie W. Y. Chan
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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20
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Viswanathan M, Yin L, Kurmi Y, Zu Z. Amide Proton Transfer (APT) imaging in tumor with a machine learning approach using partially synthetic data. ARXIV 2023:arXiv:2311.01683v2. [PMID: 37961738 PMCID: PMC10635304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Purpose Machine learning (ML) has been increasingly used to quantify chemical exchange saturation transfer (CEST) effect. ML models are typically trained using either measured data or fully simulated data. However, training with measured data often lacks sufficient training data, while training with fully simulated data may introduce bias due to limited simulations pools. This study introduces a new platform that combines simulated and measured components to generate partially synthetic CEST data, and to evaluate its feasibility for training ML models to predict amide proton transfer (APT) effect. Methods Partially synthetic CEST signals were created using an inverse summation of APT effects from simulations and the other components from measurements. Training data were generated by varying APT simulation parameters and applying scaling factors to adjust the measured components, achieving a balance between simulation flexibility and fidelity. First, tissue-mimicking CEST signals along with ground truth information were created using multiple-pool model simulations to validate this method. Second, an ML model was trained individually on partially synthetic data, in vivo data, and fully simulated data, to predict APT effect in rat brains bearing 9L tumors. Results Experiments on tissue-mimicking data suggest that the ML method using the partially synthetic data is accurate in predicting APT. In vivo experiments suggest that our method provides more accurate and robust prediction than the training using in vivo data and fully synthetic data. Conclusion Partially synthetic CEST data can address the challenges in conventional ML methods.
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Affiliation(s)
- Malvika Viswanathan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Biomedical Engineering, Vanderbilt University, Nashville, US
| | - Leqi Yin
- School of Engineering, Vanderbilt University, Nashville, US
| | - Yashwant Kurmi
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Biomedical Engineering, Vanderbilt University, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
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21
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Rivlin M, Perlman O, Navon G. Metabolic brain imaging with glucosamine CEST MRI: in vivo characterization and first insights. Sci Rep 2023; 13:22030. [PMID: 38086821 PMCID: PMC10716494 DOI: 10.1038/s41598-023-48515-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
The utility of chemical exchange saturation transfer (CEST) MRI for monitoring the uptake of glucosamine (GlcN), a safe dietary supplement, has been previously demonstrated in detecting breast cancer in both murine and human subjects. Here, we studied and characterized the detectability of GlcN uptake and metabolism in the brain. Following intravenous GlcN administration in mice, CEST brain signals calculated by magnetization transfer ratio asymmetry (MTRasym) analysis, were significantly elevated, mainly in the cortex, hippocampus, and thalamus. The in vivo contrast remained stable during 40 min of examination, which can be attributed to GlcN uptake and its metabolic products accumulation as confirmed using 13C NMR spectroscopic studies of brain extracts. A Lorentzian multi-pool fitting analysis revealed an increase in the hydroxyl, amide, and relayed nuclear Overhauser effect (rNOE) signal components after GlcN treatment. With its ability to cross the blood-brain barrier (BBB), the GlcN CEST technique has the potential to serve as a metabolic biomarker for the diagnosis and monitoring various brain disorders.
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Affiliation(s)
- Michal Rivlin
- School of Chemistry, Tel-Aviv University, Tel-Aviv, Israel
| | - Or Perlman
- Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel
- Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel
| | - Gil Navon
- School of Chemistry, Tel-Aviv University, Tel-Aviv, Israel.
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22
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Wu L, Lu D, Sun PZ. Comparison of model-free Lorentzian and spinlock model-based fittings in quantitative CEST imaging of acute stroke. Magn Reson Med 2023; 90:1958-1968. [PMID: 37335834 PMCID: PMC10538953 DOI: 10.1002/mrm.29772] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 05/14/2023] [Accepted: 06/01/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE CEST MRI detects complex tissue changes following acute stroke. Our study aimed to test if spinlock model-based fitting of the quasi-steady-state (QUASS)-reconstructed equilibrium CEST MRI improves the determination of multi-pool signal changes over the commonly-used model-free Lorentzian fitting in acute stroke. THEORY AND METHODS Multiple three-pool CEST Z-spectra were simulated using Bloch-McConnell equations for a range of T1 , relaxation delay, and saturation times. The multi-pool CEST signals were solved from the simulated Z-spectra to test the accuracy of routine Lorentzian (model-free) and spinlock (model-based) fittings without and with QUASS reconstruction. In addition, multiparametric MRI scans were obtained in rat models of acute stroke, including relaxation, diffusion, and CEST Z-spectrum. Finally, we compared model-free and model-based per-pixel CEST quantification in vivo. RESULTS The spinlock model-based fitting of QUASS CEST MRI provided a nearly T1 -independent determination of multi-pool CEST signals, advantageous over the fittings of apparent CEST MRI (model-free and model-based). In vivo data also demonstrated that the spinlock model-based QUASS fitting captured significantly different changes in semisolid magnetization transfer (-0.9 ± 0.8 vs. 0.3 ± 0.8%), amide (-1.1 ± 0.4 vs. -0.5 ± 0.2%), and guanidyl (1.0 ± 0.4 vs. 0.7 ± 0.3%) signals over the model-free Lorentzian analysis. CONCLUSION Our study demonstrated that spinlock model-based fitting of QUASS CEST MRI improved the determination of the underlying tissue changes following acute stroke, promising further clinical translation of quantitative CEST imaging.
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Affiliation(s)
- Limin Wu
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Dongshuang Lu
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Phillip Zhe Sun
- Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Emory National Primate Research Center, Emory University, Atlanta GA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA
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23
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Sun PZ. Numerical simulation-based assessment of pH-sensitive chemical exchange saturation transfer MRI quantification accuracy across field strengths. NMR IN BIOMEDICINE 2023; 36:e5000. [PMID: 37401645 DOI: 10.1002/nbm.5000] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 04/27/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI detects dilute labile protons via their exchange with bulk water, conferring pH sensitivity. Based on published exchange and relaxation properties, a 19-pool simulation was used to model the brain pH-dependent CEST effect and assess the accuracy of quantitative CEST (qCEST) analysis across magnetic field strengths under typical scan conditions. First, the optimal B1 amplitude was determined by maximizing pH-sensitive amide proton transfer (APT) contrast under the equilibrium condition. Apparent and quasi-steady-state (QUASS) CEST effects were then derived under the optimal B1 amplitude as functions of pH, RF saturation duration, relaxation delay, Ernst flip angle, and field strength. Finally, CEST effects, particularly the APT signal, were isolated with spinlock model-based Z-spectral fitting to evaluate the accuracy and consistency of CEST quantification. Our data showed that QUASS reconstruction significantly improved the consistency between simulated and equilibrium Z-spectra. The residual difference between QUASS and equilibrium CEST Z-spectra was, on average, 30 times less than that of the apparent CEST Z-spectra across field strengths, saturation, and repetition times. Also, the spinlock fitting of the QUASS CEST effect significantly reduced the residual errors 9-fold. Furthermore, the isolated APT amplitude from QUASS reconstruction was consistent and higher than the apparent CEST analysis under nonequilibrium conditions. To summarize, this study confirmed that QUASS reconstruction facilitates accurate determination of the CEST system under different scan protocols across field strengths, with the potential to help standardize CEST quantification.
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Affiliation(s)
- Phillip Zhe Sun
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
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24
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Wang ZX, Wei XH, Cai KJ, Zhu WZ, Su CL. Noninvasive Characterization of Metabolic Changes in Ischemic Stroke Using Z-spectrum-fitted Multiparametric Chemical Exchange Saturation Transfer-weighted Magnetic Resonance Imaging. Curr Med Sci 2023; 43:970-978. [PMID: 37697160 DOI: 10.1007/s11596-023-2785-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/07/2023] [Indexed: 09/13/2023]
Abstract
OBJECTIVE This study aimed to noninvasively characterize the metabolic alterations in ischemic brain tissues using Z-spectrum-fitted multiparametric chemical exchange saturation transfer-weighted magnetic resonance imaging (CEST-MRI). METHODS Three sets of Z-spectrum data with saturation power (B1) values of 1.5, 2.5, and 3.5 µT, respectively, were acquired from 17 patients with ischemic stroke. Multiple contrasts contributing to the Z-spectrum, including fitted amide proton transfer (APTfitted), +2 ppm peak (CEST@2ppm), concomitantly fitted APTfitted and CEST@2ppm (APT&CEST@2ppm), semisolid magnetization transfer contrast (MT), aliphatic nuclear Overhauser effect (NOE), and direct saturation of water (DSW), were fitted with 4 and 5 Lorentzian functions, respectively. The CEST metrics were compared between ischemic lesions and contralateral normal white matter (CNWM), and the correlation between the CEST metrics and the apparent diffusion coefficient (ADC) was assessed. The differences in the Z-spectrum metrics under varied B1 values were also investigated. RESULTS Ischemic lesions showed increased APTfitted, CEST@2ppm, APT&CEST@2ppm, NOE, and DSW as well as decreased MT. APT&CEST@2ppm, MT, and DSW showed a significant correlation with ADC [APT&CEST@2ppm at the 3 B1 values: R=0.584/0.467/0.551; MT at the 3 B1 values: R=-0.717/-0.695/-0.762 (4-parameter fitting), R=-0.734/-0.711/-0.785 (5-parameter fitting); DSW of 4-/5-parameter fitting: R=0.794/0.811 (2.5 µT), R=0.800/0.790 (3.5 µT)]. However, the asymmetric analysis of amide proton transfer (APTasym) could not differentiate the lesions from CNWM and showed no correlation with ADC. Furthermore, the Z-spectrum contrasts varied with B1. CONCLUSION The Z-spectrum-fitted multiparametric CEST-MRI can comprehensively detect metabolic alterations in ischemic brain tissues.
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Affiliation(s)
- Zhen-Xiong Wang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Xin-Hua Wei
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Ke-Jia Cai
- Department of Radiology, Department of Bioengineering, and The Center for MR Research, University of Illinois at Chicago, Chicago, 60612, USA
| | - Wen-Zhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Chang-Liang Su
- Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China.
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25
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Dan Q, Jiang X, Wang R, Dai Z, Sun D. Biogenic Imaging Contrast Agents. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207090. [PMID: 37401173 PMCID: PMC10477908 DOI: 10.1002/advs.202207090] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/08/2023] [Indexed: 07/05/2023]
Abstract
Imaging contrast agents are widely investigated in preclinical and clinical studies, among which biogenic imaging contrast agents (BICAs) are developing rapidly and playing an increasingly important role in biomedical research ranging from subcellular level to individual level. The unique properties of BICAs, including expression by cells as reporters and specific genetic modification, facilitate various in vitro and in vivo studies, such as quantification of gene expression, observation of protein interactions, visualization of cellular proliferation, monitoring of metabolism, and detection of dysfunctions. Furthermore, in human body, BICAs are remarkably helpful for disease diagnosis when the dysregulation of these agents occurs and can be detected through imaging techniques. There are various BICAs matched with a set of imaging techniques, including fluorescent proteins for fluorescence imaging, gas vesicles for ultrasound imaging, and ferritin for magnetic resonance imaging. In addition, bimodal and multimodal imaging can be realized through combining the functions of different BICAs, which helps overcome the limitations of monomodal imaging. In this review, the focus is on the properties, mechanisms, applications, and future directions of BICAs.
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Affiliation(s)
- Qing Dan
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
| | - Xinpeng Jiang
- Department of Biomedical EngineeringCollege of Future TechnologyPeking UniversityBeijing100871P. R. China
| | - Run Wang
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
| | - Zhifei Dai
- Department of Biomedical EngineeringCollege of Future TechnologyPeking UniversityBeijing100871P. R. China
| | - Desheng Sun
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
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26
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Hoffmann E, Schache D, Höltke C, Soltwisch J, Niland S, Krähling T, Bergander K, Grewer M, Geyer C, Groeneweg L, Eble JA, Vogl T, Roth J, Heindel W, Maus B, Helfen A, Faber C, Wildgruber M, Gerwing M, Hoerr V. Multiparametric chemical exchange saturation transfer MRI detects metabolic changes in breast cancer following immunotherapy. J Transl Med 2023; 21:577. [PMID: 37641066 PMCID: PMC10463706 DOI: 10.1186/s12967-023-04451-6] [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: 03/08/2023] [Accepted: 08/19/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND With metabolic alterations of the tumor microenvironment (TME) contributing to cancer progression, metastatic spread and response to targeted therapies, non-invasive and repetitive imaging of tumor metabolism is of major importance. The purpose of this study was to investigate whether multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI) allows to detect differences in the metabolic profiles of the TME in murine breast cancer models with divergent degrees of malignancy and to assess their response to immunotherapy. METHODS Tumor characteristics of highly malignant 4T1 and low malignant 67NR murine breast cancer models were investigated, and their changes during tumor progression and immune checkpoint inhibitor (ICI) treatment were evaluated. For simultaneous analysis of different metabolites, multiparametric CEST-MRI with calculation of asymmetric magnetization transfer ratio (MTRasym) at 1.2 to 2.0 ppm for glucose-weighted, 2.0 ppm for creatine-weighted and 3.2 to 3.6 ppm for amide proton transfer- (APT-) weighted CEST contrast was conducted. Ex vivo validation of MRI results was achieved by 1H nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization mass spectrometry imaging with laser postionization and immunohistochemistry. RESULTS During tumor progression, the two tumor models showed divergent trends for all examined CEST contrasts: While glucose- and APT-weighted CEST contrast decreased and creatine-weighted CEST contrast increased over time in the 4T1 model, 67NR tumors exhibited increased glucose- and APT-weighted CEST contrast during disease progression, accompanied by decreased creatine-weighted CEST contrast. Already three days after treatment initiation, CEST contrasts captured response to ICI therapy in both tumor models. CONCLUSION Multiparametric CEST-MRI enables non-invasive assessment of metabolic signatures of the TME, allowing both for estimation of the degree of tumor malignancy and for assessment of early response to immune checkpoint inhibition.
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Affiliation(s)
- Emily Hoffmann
- Clinic of Radiology, University of Münster, Münster, Germany.
| | - Daniel Schache
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Carsten Höltke
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Jens Soltwisch
- Institute of Hygiene, University of Münster, Münster, Germany
| | - Stephan Niland
- Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany
| | - Tobias Krähling
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Klaus Bergander
- Institute of Organic Chemistry, University of Münster, Münster, Germany
| | - Martin Grewer
- Clinic of Radiology, University of Münster, Münster, Germany
| | | | - Linda Groeneweg
- Institute of Immunology, University of Münster, Münster, Germany
| | - Johannes A Eble
- Institute of Physiological Chemistry and Pathobiochemistry, University of Münster, Münster, Germany
| | - Thomas Vogl
- Institute of Immunology, University of Münster, Münster, Germany
| | - Johannes Roth
- Institute of Immunology, University of Münster, Münster, Germany
| | - Walter Heindel
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Bastian Maus
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Anne Helfen
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Cornelius Faber
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Moritz Wildgruber
- Clinic of Radiology, University of Münster, Münster, Germany
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Mirjam Gerwing
- Clinic of Radiology, University of Münster, Münster, Germany
| | - Verena Hoerr
- Clinic of Radiology, University of Münster, Münster, Germany
- Heart Center Bonn, Department of Internal Medicine II, University Hospital Bonn, Bonn, Germany
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27
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Chen Y, Dang X, Zhao B, Chen Z, Zhao Y, Zhao F, Zheng Z, He X, Peng J, Song X. Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest. NMR IN BIOMEDICINE 2023; 36:e4744. [PMID: 35434864 DOI: 10.1002/nbm.4744] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/07/2022] [Accepted: 04/14/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B1 . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B0 , B1 conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.
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Affiliation(s)
- Yibing Chen
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xujian Dang
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Benqi Zhao
- Department of Radiology, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Zhensen Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yingcheng Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Fengjun Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Zhuozhao Zheng
- Department of Radiology, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Xiaowei He
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Jinye Peng
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
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28
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Xu J, Chung JJ, Jin T. Chemical exchange saturation transfer imaging of creatine, phosphocreatine, and protein arginine residue in tissues. NMR IN BIOMEDICINE 2023; 36:e4671. [PMID: 34978371 PMCID: PMC9250548 DOI: 10.1002/nbm.4671] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/06/2021] [Accepted: 12/02/2021] [Indexed: 05/05/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has become a promising technique to assay target proteins and metabolites through their exchangeable protons, noninvasively. The ubiquity of creatine (Cr) and phosphocreatine (PCr) due to their pivotal roles in energy homeostasis through the creatine phosphate pathway has made them prime targets for CEST in the diagnosis and monitoring of disease pathologies, particularly in tissues heavily dependent on the maintenance of rich energy reserves. Guanidinium CEST from protein arginine residues (i.e. arginine CEST) can also provide information about the protein profile in tissue. However, numerous obfuscating factors stand as obstacles to the specificity of arginine, Cr, and PCr imaging through CEST, such as semisolid magnetization transfer, fast chemical exchanges such as primary amines, and the effects of nuclear Overhauser enhancement from aromatic and amide protons. In this review, the specific exchange properties of protein arginine residues, Cr, and PCr, along with their validation, are discussed, including the considerations necessary to target and tune their signal effects through CEST imaging. Additionally, strategies that have been employed to enhance the specificity of these exchanges in CEST imaging are described, along with how they have opened up possible applications of protein arginine residues, Cr and PCr CEST imaging in the study and diagnosis of pathology. A clear understanding of the capabilities and caveats of using CEST to image these vital metabolites and mitigation strategies is crucial to expanding the possibilities of this promising technology.
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Affiliation(s)
- Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Julius Juhyun Chung
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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29
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Glang F, Fabian MS, German A, Khakzar KM, Mennecke A, Liebert A, Herz K, Liebig P, Kasper BS, Schmidt M, Zuazua E, Nagel AM, Laun FB, Dörfler A, Scheffler K, Zaiss M. Linear projection-based chemical exchange saturation transfer parameter estimation. NMR IN BIOMEDICINE 2023; 36:e4697. [PMID: 35067998 DOI: 10.1002/nbm.4697] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 12/14/2021] [Accepted: 01/15/2022] [Indexed: 05/23/2023]
Abstract
Isolated evaluation of multiparametric in vivo chemical exchange saturation transfer (CEST) MRI often requires complex computational processing for both correction of B0 and B1 inhomogeneity and contrast generation. For that, sufficiently densely sampled Z-spectra need to be acquired. The list of acquired frequency offsets largely determines the total CEST acquisition time, while potentially representing redundant information. In this work, a linear projection-based multiparametric CEST evaluation method is introduced that offers fast B0 and B1 inhomogeneity correction, contrast generation and feature selection for CEST data, enabling reduction of the overall measurement time. To that end, CEST data acquired at 7 T in six healthy subjects and in one brain tumor patient were conventionally evaluated by interpolation-based inhomogeneity correction and Lorentzian curve fitting. Linear regression was used to obtain coefficient vectors that directly map uncorrected data to corrected Lorentzian target parameters. L1-regularization was applied to find subsets of the originally acquired CEST measurements that still allow for such a linear projection mapping. The linear projection method allows fast and interpretable mapping from acquired raw data to contrast parameters of interest, generalizing from healthy subject training data to unseen healthy test data and to the tumor patient dataset. The L1-regularization method shows that a fraction of the acquired CEST measurements is sufficient to preserve tissue contrasts, offering up to a 2.8-fold reduction of scan time. Similar observations as for the 7-T data can be made for data from a clinical 3-T scanner. Being a fast and interpretable computation step, the proposed method is complementary to neural networks that have recently been employed for similar purposes. The scan time acceleration offered by the L1-regularization ("CEST-LASSO") constitutes a step towards better applicability of multiparametric CEST protocols in a clinical context.
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Affiliation(s)
- Felix Glang
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Moritz S Fabian
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Alexander German
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Katrin M Khakzar
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Angelika Mennecke
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andrzej Liebert
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Kai Herz
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karls University Tübingen, Tübingen, Germany
| | | | - Burkhard S Kasper
- Department of Neurology, University Clinic of Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Schmidt
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Enrique Zuazua
- Department of Data Science, Friedrich-Alexander-Universität Erlangen, Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Arnd Dörfler
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Klaus Scheffler
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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30
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Hangel G, Schmitz‐Abecassis B, Sollmann N, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda KM, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Hirschler L, Smits M, Petr J, Emblem KE. Advanced MR Techniques for Preoperative Glioma Characterization: Part 2. J Magn Reson Imaging 2023; 57:1676-1695. [PMID: 36912262 PMCID: PMC10947037 DOI: 10.1002/jmri.28663] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/14/2023] Open
Abstract
Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Medical Delta FoundationDelftthe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - N. Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Cancer Center AmsterdamAmsterdamNetherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyHaaglanden Medical CenterNetherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental HealthBabes‐Bolyai UniversityRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | | | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftthe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University HospitalBrnoCzechia
- Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Marion Smits
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamthe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
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31
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Zhou Y, Bie C, van Zijl PC, Yadav NN. The relayed nuclear Overhauser effect in magnetization transfer and chemical exchange saturation transfer MRI. NMR IN BIOMEDICINE 2023; 36:e4778. [PMID: 35642102 PMCID: PMC9708952 DOI: 10.1002/nbm.4778] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/19/2022] [Accepted: 05/29/2022] [Indexed: 05/23/2023]
Abstract
Magnetic resonance (MR) is a powerful technique for noninvasively probing molecular species in vivo but suffers from low signal sensitivity. Saturation transfer (ST) MRI approaches, including chemical exchange saturation transfer (CEST) and conventional magnetization transfer contrast (MTC), allow imaging of low-concentration molecular components with enhanced sensitivity using indirect detection via the abundant water proton pool. Several recent studies have shown the utility of chemical exchange relayed nuclear Overhauser effect (rNOE) contrast originating from nonexchangeable carbon-bound protons in mobile macromolecules in solution. In this review, we describe the mechanisms leading to the occurrence of rNOE-based signals in the water saturation spectrum (Z-spectrum), including those from mobile and immobile molecular sources and from molecular binding. While it is becoming clear that MTC is mainly an rNOE-based signal, we continue to use the classical MTC nomenclature to separate it from the rNOE signals of mobile macromolecules, which we will refer to as rNOEs. Some emerging applications of the use of rNOEs for probing macromolecular solution components such as proteins and carbohydrates in vivo or studying the binding of small substrates are discussed.
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Affiliation(s)
- Yang Zhou
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, Guangdong 518055 (China)
| | - Chongxue Bie
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
- Department of Information Science and Technology, Northwest University, No.1 Xuefu Avenue, Xi’an, Shanxi 710127 (China)
| | - Peter C.M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Nirbhay N. Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
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32
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Bie C, van Zijl P, Xu J, Song X, Yadav NN. Radiofrequency labeling strategies in chemical exchange saturation transfer MRI. NMR IN BIOMEDICINE 2023; 36:e4944. [PMID: 37002814 PMCID: PMC10312378 DOI: 10.1002/nbm.4944] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/19/2023] [Accepted: 03/27/2023] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has generated great interest for molecular imaging applications because it can image low-concentration solute molecules in vivo with enhanced sensitivity. CEST effects are detected indirectly through a reduction in the bulk water signal after repeated perturbation of the solute proton magnetization using one or more radiofrequency (RF) irradiation pulses. The parameters used for these RF pulses-frequency offset, duration, shape, strength, phase, and interpulse spacing-determine molecular specificity and detection sensitivity, thus their judicious selection is critical for successful CEST MRI scans. This review article describes the effects of applying RF pulses on spin systems and compares conventional saturation-based RF labeling with more recent excitation-based approaches that provide spectral editing capabilities for selectively detecting molecules of interest and obtaining maximal contrast.
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Affiliation(s)
- Chongxue Bie
- Department of Information Science and Technology, Northwest University, No.1 Xuefu Avenue, Xi’an, Shaanxi 710127 (China)
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Peter van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Haidian District, Beijing 100084 (China)
| | - Nirbhay N. Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
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Liu Y, Gauthier GC, Gendelman HE, Bade AN. Dual-Peak Lorentzian CEST MRI for antiretroviral drug brain distribution. NEUROIMMUNE PHARMACOLOGY AND THERAPEUTICS 2023; 2:63-69. [PMID: 37027345 PMCID: PMC10070014 DOI: 10.1515/nipt-2022-0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 08/24/2022] [Indexed: 11/15/2022]
Abstract
Objectives Spatial-temporal biodistribution of antiretroviral drugs (ARVs) can now be achieved using MRI by utilizing chemical exchange saturation transfer (CEST) contrasts. However, the presence of biomolecules in tissue limits the specificity of current CEST methods. To overcome this limitation, a Lorentzian line-shape fitting algorithm was developed that simultaneously fits CEST peaks of ARV protons on its Z-spectrum. Case presentation This algorithm was tested on the common first line ARV, lamivudine (3TC), that has two peaks resulting from amino (-NH2) and hydroxyl (-OH) protons in 3TC. The developed dual-peak Lorentzian function fitted these two peaks simultaneously, and used the ratio of -NH2 and -OH CEST contrasts as a constraint parameter to measure 3TC presence in brains of drug-treated mice. 3TC biodistribution calculated using the new algorithm was compared against actual drug levels measured using UPLC-MS/MS. In comparison to the method that employs the -NH2 CEST peak only, the dual-peak Lorentzian fitting algorithm showed stronger correlation with brain tissue 3TC levels, signifying estimation of actual drug levels. Conclusions We concluded that 3TC levels can be extracted from confounding CEST effects of tissue biomolecules resulting in improved specificity for drug mapping. This algorithm can be expanded to measure a variety of ARVs using CEST MRI.
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Affiliation(s)
- Yutong Liu
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE, USA
- Department of Radiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Gabriel C. Gauthier
- Department of Radiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Howard E. Gendelman
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE, USA
| | - Aditya N. Bade
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE, USA
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Wittsack HJ, Radke KL, Stabinska J, Ljimani A, Müller-Lutz A. calf - Software for CEST Analysis with Lorentzian Fitting. J Med Syst 2023; 47:39. [PMID: 36961580 PMCID: PMC10038975 DOI: 10.1007/s10916-023-01931-6] [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: 09/14/2022] [Accepted: 02/27/2023] [Indexed: 03/25/2023]
Abstract
Analysis of chemical exchange saturation transfer (CEST) MRI data requires sophisticated methods to obtain reliable results about metabolites in the tissue under study. CEST generates z-spectra with multiple components, each originating from individual molecular groups. The individual lines with Lorentzian line shape are mostly overlapping and disturbed by various effects. We present an elaborate method based on an adaptive nonlinear least squares algorithm that provides robust quantification of z-spectra and incorporates prior knowledge in the fitting process. To disseminate CEST to the research community, we developed software as part of this study that runs on the Microsoft Windows operating system and will be made freely available to the community. Special attention has been paid to establish a low entrance threshold and high usability, so that even less experienced users can successfully analyze CEST data.
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Affiliation(s)
- Hans-Jörg Wittsack
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, D-40225, Dusseldorf, Germany.
| | - Karl Ludger Radke
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, D-40225, Dusseldorf, Germany
| | - Julia Stabinska
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, 21205, USA
- Division of MR Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Alexandra Ljimani
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, D-40225, Dusseldorf, Germany
| | - Anja Müller-Lutz
- Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, D-40225, Dusseldorf, Germany
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35
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Zhang L, Xu C, Li Z, Sun J, Wang X, Hou B, Zhao Y. Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis. Quant Imaging Med Surg 2023; 13:1860-1873. [PMID: 36915363 PMCID: PMC10006163 DOI: 10.21037/qims-22-420] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 10/30/2022] [Indexed: 12/12/2022]
Abstract
Background Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement. Methods To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting. Specifically, a 5-pool Lorentzian simulation was conducted with the following brain tissue parameters: water, amide (3.5 ppm), amine (2.2 ppm), magnetization transfer (MT), and nuclear Overhauser enhancement (NOE; -3.5 ppm). The parameters were first calculated offline and stored as the initial value of the Z-spectrum fitting. Then, the measured Z-spectrum with the peak value set to 0 was fitted via the stored initial value, which yielded the reference Z-spectrum. Finally, the difference between the inverse of the Z-spectrum and the inverse of the reference Z-spectrum was used as the CEST definite spectrum. Results The simulation results demonstrated that the Z-spectra of the rat brain were well simulated by a 5-pool Lorentzian fitting. Further, the proposed method detected a larger difference than did either the saturation transfer difference or the 5-pool Lorentzian fitting, as demonstrated by simulations. According to the results of the cerebral ischemia rat model, the proposed method provided the highest contrast-to-noise ratio (CNR) between the contralateral and the ipsilateral striatum under various acquisition conditions. The results indicated that the difference of fitted amplitudes generated with a 5-pool Lorentzian fitting in amide at 3.5 ppm (6.04%±0.39%; 6.86%±0.39%) was decreased in a stroke lesion compared to the contralateral normal tissue. Moreover, the difference of the residual of inversed Z-spectra in which 5-pool Lorentzian fitting was used to calculate the reference Z-spectra ( M T R R e x 5 L ) amplitudes in amide at 3.5 ppm (13.83%±2.20%, 15.69%±1.99%) was reduced in a stroke lesion compared to the contralateral normal tissue. Conclusions M T R R e x 5 L is predominantly pH-sensitive and is suitable for detecting tissue acidosis following an acute stroke.
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Affiliation(s)
- Lihong Zhang
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Chongxin Xu
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Zhen Li
- Department of Medical Imaging, Weifang Medical University, Weifang, China
| | - Junding Sun
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Xiaoli Wang
- Department of Medical Imaging, Weifang Medical University, Weifang, China
| | - Beibei Hou
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Yingcheng Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
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36
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Sun PZ. Demonstration of accurate multi-pool chemical exchange saturation transfer MRI quantification - Quasi-steady-state reconstruction empowered quantitative CEST analysis. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 348:107379. [PMID: 36689786 PMCID: PMC10023465 DOI: 10.1016/j.jmr.2023.107379] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/05/2023] [Accepted: 01/15/2023] [Indexed: 05/18/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute labile protons and microenvironment properties, yet CEST quantification has been challenging. This difficulty is because the CEST measurement depends not only on the underlying CEST system but also on the scan protocols, including RF saturation amplitude, duration, and repetition time. In addition, T1 normalization is not straightforward under non-equilibrium conditions. Recently, a quasi-steady-state (QUASS) algorithm was established to reconstruct the desired equilibrium state from experimental measurements. Our study aimed to determine the accuracy of spinlock-model-based multi-pool CEST quantification using numerical simulations and phantom experiments. In short, CEST Z-spectra were simulated for a representative 3-pool model, and CEST amplitudes were solved with spinlock model-based multi-pool fitting and assessed as a function of RF saturation time (Ts), repetition time (TR), and T1. Although the apparent CEST signals showed significant T1 dependence, such relationships were not observed following QUASS reconstruction. To test the accuracy of T1 correction, a multi-vial phantom of nicotinamide and creatine was doped with manganese chloride, resulting in T1 ranging from 1 s to beyond 2 s. The multi-labile signals determined from the routine measurements showed significant dependence on Ts, TR, and T1. In contrast, CEST signals from the QUASS reconstruction showed consistent quantification independent of such variables. To summarize, our study demonstrated that accurate CEST quantification is feasible in multi-pool CEST systems with the spinlock-model-based fitting of QUASS CEST MRI.
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Affiliation(s)
- Phillip Zhe Sun
- Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, GA, United States; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States.
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37
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Wu Y, Sun PZ. Demonstration of pH imaging in acute stroke with endogenous ratiometric chemical exchange saturation transfer magnetic resonance imaging at 2 ppm. NMR IN BIOMEDICINE 2023; 36:e4850. [PMID: 36259279 DOI: 10.1002/nbm.4850] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 10/11/2022] [Accepted: 10/11/2022] [Indexed: 06/16/2023]
Abstract
pH change is often considered a hallmark of metabolic disruption in diseases such as ischemic stroke and cancer. Chemical exchange saturation transfer (CEST) MRI, particularly amide proton transfer (APT), has emerged as a noninvasive pH imaging approach. However, there are changes in multipool CEST effects besides APT MRI. Our study investigated radiofrequency (RF) amplitude-based ratiometric CEST pH imaging in acute stroke. Briefly, adult male Wistar rats underwent CEST MRI under two RF saturation (B1 ) levels of 0.75 and 1.5 μT following middle cerebral artery occlusion. Magnetization transfer (MT), direct water saturation, CEST at 2 ppm (CEST@2 ppm), amine (2.75 ppm), and APT (3.5 ppm) effects were resolved with the multipool Lorentzian fitting approach. The ratiometric analysis was measured in the ischemic lesion and the contralateral normal area, which was also correlated with pH-specific MT and the relaxation normalized APT (MRAPT) index. MT, amine CEST effect, and their respective ratiometric indices did not show significant changes in ischemic regions (p > 0.05), as expected. Whereas APT decreased in the ischemic lesion for B1 of 1.5 μT (p < 0.01), the correlation between the amide ratio with MRAPT index was moderate (r = 0.52, p = 0.02). By comparison, the ischemic tissue showed a significantly increased CEST@2 ppm for both saturation levels from the contralateral normal area (p ≤ 0.01). Importantly, the CEST@2 ppm ratio decreased in the ischemic lesion (p < 0.01), which highly correlated with the MRAPT index (r = 0.93, p < 0.001). To summarize, our study demonstrated the feasibility of endogenous CEST@2 ppm ratiometric imaging of pH upon acute stroke, promising to detect pH changes in metabolic diseases.
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Affiliation(s)
- Yin Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Phillip Zhe Sun
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
- Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA
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38
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Cui J, Sun C, Zu Z. NOE-weighted imaging in tumors using low-duty-cycle 2π-CEST. Magn Reson Med 2023; 89:636-651. [PMID: 36198015 PMCID: PMC9792266 DOI: 10.1002/mrm.29475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/19/2022] [Accepted: 09/12/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE Nuclear Overhauser enhancement (NOE)-mediated CEST imaging at -3.5 ppm has shown clinical interest in diagnosing tumors. Multiple-pool Lorentzian fit has been used to quantify NOE, which, however, requires a long scan time. Asymmetric analysis of CEST signals could be a simple and fast method to quantify this NOE, but it has contamination from the amide proton transfer (APT) at 3.5 ppm. This work proposes a new method using an asymmetric analysis of a low-duty-cycle pulsed-CEST sequence with a flip angle of 360°, termed 2π-CEST, to reduce the contribution from APT. METHODS Simulations were used to evaluate the capability of the 2π-CEST to reduce APT. Experiments on animal tumor models were performed to show its advantages compared with the conventional asymmetric analysis. Samples of reconstituted phospholipids and proteins were used to evaluate the molecular origin of this NOE. RESULTS The 2π-CEST has reduced contribution from APT. In tumors where we show that the NOE is comparable to the APT effect, reducing the contamination from APT is crucial. The results show that the NOE signal obtained with 2π-CEST in tumor regions appears more homogeneous than that obtained with the conventional method. The phantom study showed that both phospholipids and proteins contribute to the NOE at -3.5 ppm. CONCLUSION The NOE at -3.5 ppm has a different contrast mechanism from APT and other CEST/NOE effects. The proposed 2π-CEST is more accurate than the conventional asymmetric analysis in detecting NOE, and requires much less scan time than the multiple-pool Lorentzian fit.
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Affiliation(s)
- Jing Cui
- Vanderbilt University Institute of Imaging Science, Nashville, US,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Casey Sun
- Vanderbilt University Institute of Imaging Science, Nashville, US,Department of Chemistry, University of Florida, Gainesville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Nashville, US,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
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39
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Shaghaghi M, Cai K. Toward In Vivo MRI of the Tissue Proton Exchange Rate in Humans. BIOSENSORS 2022; 12:bios12100815. [PMID: 36290953 PMCID: PMC9599426 DOI: 10.3390/bios12100815] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/19/2022] [Accepted: 09/29/2022] [Indexed: 05/28/2023]
Abstract
Quantification of proton exchange rate (kex) is a challenge in MR studies. Current techniques either have low resolutions or are dependent on the estimation of parameters that are not measurable. The Omega plot method, on the other hand, provides a direct way for determining kex independent of the agent concentration. However, it cannot be used for in vivo studies without some modification due to the contributions from the water signal. In vivo tissue proton exchange rate (kex) MRI, based on the direct saturation (DS) removed Omega plot, quantifies the weighted average of kex of the endogenous tissue metabolites. This technique has been successfully employed for imaging the variation in the kex of ex vivo phantoms, as well as in vivo human brains in healthy subjects, and stroke or multiple sclerosis (MS) patients. In this paper, we present a brief review of the methods used for kex imaging with a focus on the development of in vivo kex MRI technique based on the DS-removed Omega plot. We then review the recent clinical studies utilizing this technique for better characterizing brain lesions. We also outline technical challenges for the presented technique and discuss its prospects for detecting tissue microenvironmental changes under oxidative stress.
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Affiliation(s)
- Mehran Shaghaghi
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL 60612, USA
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA
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40
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Tao Q, Yi P, Cai Z, Chen Z, Deng Z, Liu R, Feng Y. Ratiometric chemical exchange saturation transfer pH mapping using two iodinated agents with nonequivalent amide protons and a single low saturation power. Quant Imaging Med Surg 2022; 12:3889-3902. [PMID: 35782235 PMCID: PMC9246745 DOI: 10.21037/qims-21-1229] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 04/29/2022] [Indexed: 07/26/2023]
Abstract
BACKGROUND As an essential physiological parameter, pH plays a critical role in maintaining cellular and tissue homeostasis. The ratiometric chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) method using clinically approved iodinated agents has emerged as one of the most promising noninvasive techniques for pH assessment. METHODS In this study, we investigated the ability to use the combination of two different nonequivalent amide protons, chosen from five iodinated agents, namely iodixanol, iohexol, iobitridol, iopamidol, and iopromide, for pH measurement. The ratio of two nonequivalent amide CEST signals was calculated and compared for pH measurements in the range of 5.6 to 7.6. To quantify the CEST signals at 4.3 and 5.5 parts per million (ppm), we employed two analytic methods: magnetization transfer ratio asymmetry and Lorentzian fitting analysis. Lastly, the established protocol was used to measure the pH values in healthy rat kidneys (n=5). RESULTS The combination of iodixanol and iobitridol at a ratio of 1:1 was found to be suitable for pH mapping. The saturation power level (B1) was also investigated, and a low B1 of 1.5 µT was adopted for subsequent pH measurements. Improved precision and an extended pH detection range were achieved using iodixanol and iobitridol (1:1 ratio) and a single low B1 of 1.5 µT in vitro. In vivo renal pH values were measured as 7.23±0.09, 6.55±0.15, and 6.29±0.23 for the cortex, medulla, and calyx, respectively. CONCLUSIONS These results show that the ratiometric CEST method using two iodinated agents with nonequivalent amide protons could be used for in vivo pH mapping of the kidney under a single low B1 saturation power.
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Affiliation(s)
- Quan Tao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Peiwei Yi
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Zimeng Cai
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Zelong Chen
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zongwu Deng
- CAS Key Laboratory of Nano-Bio Interface and Division of Nanobionics, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, China
| | - Ruiyuan Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
- Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Key Laboratory of Mental Health of the Ministry of Education & Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, China
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41
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Jin T, Chung JJ. Average saturation efficiency filter (ASEF) for CEST imaging. Magn Reson Med 2022; 88:254-265. [PMID: 35344594 PMCID: PMC9172934 DOI: 10.1002/mrm.29211] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 01/06/2022] [Accepted: 02/08/2022] [Indexed: 12/21/2022]
Abstract
PURPOSE Endogenous CEST signal usually has low specificity due to contamination from the magnetization transfer effect and from fast exchanging labile protons with close Larmor frequencies. We propose to improve CEST signal specificity with an average saturation efficiency filter (ASEF). METHODS ASEF measures the difference between CEST signals acquired with similar average irradiation power but largely different duty cycles (DC), for example, a continuous wave or a high DC pulse train versus a low DC one. Simulation and Cr phantom studies were performed to evaluate the characteristics of ASEF for CEST. RESULTS Theoretical and simulation studies show that ASEF can suppress fast exchanging processes, with only a small loss of chemical exchange contrast for slow-to-intermediate exchange rates if the difference in DC is large. In the RF offset range of 2 to 5 ppm with an averaged saturation power of 0.8 and 1.6 microteslas, there is a mismatch of ∼0.1% to 2% in the magnetization transfer signal between saturation by continuous wave and a pulse train with DC = 15% and pulse duration of 24 ms, respectively. This mismatch can be minimized by careful selection of saturation power, pulse duration, and DC differences or by applying a small fudge factor between the 2 irradiation powers. Phantom studies of Cr confirmed that ASEF can minimize the magnetization transfer effect and reduce sensitivity to fast exchange processes. CONCLUSION ASEF can improve the specificity of slow-to-intermediate exchanging CEST signal with a relatively small loss of sensitivity.
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Affiliation(s)
- Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Julius Juhyun Chung
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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42
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Breitling J, Korzowski A, Kempa N, Boyd PS, Paech D, Schlemmer HP, Ladd ME, Bachert P, Goerke S. Motion correction for three-dimensional chemical exchange saturation transfer imaging without direct water saturation artifacts. NMR IN BIOMEDICINE 2022; 35:e4720. [PMID: 35233847 DOI: 10.1002/nbm.4720] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/25/2021] [Accepted: 02/22/2022] [Indexed: 06/14/2023]
Abstract
In chemical exchange saturation transfer (CEST) MRI, motion correction is compromised by the drastically changing image contrast at different frequency offsets, particularly at the direct water saturation. In this study, a simple extension for conventional image registration algorithms is proposed, enabling robust and accurate motion correction of CEST-MRI data. The proposed method uses weighted averaging of motion parameters from a conventional rigid image registration to identify and mitigate erroneously misaligned images. Functionality of the proposed method was verified by ground truth datasets generated from 10 three-dimensional in vivo measurements at 3 T with simulated realistic random rigid motion patterns and noise. Performance was assessed using two different criteria: the maximum image misalignment as a measure for the robustness against direct water saturation artifacts, and the spectral error as a measure of the overall accuracy. For both criteria, the proposed method achieved the best scores compared with two motion-correction algorithms specifically developed to handle the varying contrasts in CEST-MRI. Compared with a straightforward linear interpolation of the motion parameters at frequency offsets close to the direct water saturation, the proposed method offers better performance in the absence of artifacts. The proposed method for motion correction in CEST-MRI allows identification and mitigation of direct water saturation artifacts that occur with conventional image registration algorithms. The resulting improved robustness and accuracy enable reliable motion correction, which is particularly crucial for an automated and carefree evaluation of spectral CEST-MRI data, e.g., for large patient cohorts or in clinical routines.
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Affiliation(s)
- Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Neele Kempa
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Philip S Boyd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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43
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Bardin S, Lecis M, Boido D, Boutin C, Baron G, Aldini G, Berthault P, Boumezbeur F, Ciobanu L. In vivo detection of carnosine and its derivatives using chemical exchange saturation transfer. Magn Reson Med 2022; 88:1314-1323. [PMID: 35526234 PMCID: PMC9320878 DOI: 10.1002/mrm.29282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/29/2022] [Accepted: 04/11/2022] [Indexed: 11/09/2022]
Abstract
Purpose To detect carnosine, anserine and homocarnosine in vivo with chemical exchange saturation transfer (CEST) at 17.2 T. Methods CEST MR acquisitions were performed using a CEST‐linescan sequence developed in‐house and optimized for carnosine detection. In vivo CEST data were collected from three different regions of interest (the lower leg muscle, the olfactory bulb and the neocortex) of eight rats. Results The CEST effect for carnosine, anserine and homocarnosine was characterized in phantoms, demonstrating the possibility to separate individual contributions by employing high spectral resolution (0.005 ppm) and low CEST saturation power (0.15 μT). The CEST signature of these peptides was evidenced, in vivo, in the rat brain and skeletal muscle. The presence of carnosine and anserine in the muscle was corroborated by in vivo localized spectroscopy (MRS). However, the sensitivity of MRS was insufficient for carnosine and homocarnosine detection in the brain. The absolute amounts of carnosine and derivatives in the investigated tissues were determined by liquid chromatography–electrospray ionization‐tandem mass spectrometry using isotopic dilution standard methods and were in agreement with the CEST results. Conclusion The robustness of the CEST‐linescan approach and the favorable conditions for CEST at ultra‐high magnetic field allowed the in vivo CEST MR detection of carnosine and related peptides. This approach could be useful to investigate noninvasively the (patho)‐physiological roles of these molecules.
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Affiliation(s)
- Solène Bardin
- NeuroSpin, UMR CEA/CNRS 9027 Paris‐Saclay University Gif‐sur‐Yvette France
| | - Michele Lecis
- NeuroSpin, UMR CEA/CNRS 9027 Paris‐Saclay University Gif‐sur‐Yvette France
| | - Davide Boido
- NeuroSpin, UMR CEA/CNRS 9027 Paris‐Saclay University Gif‐sur‐Yvette France
| | - Céline Boutin
- IRAMIS, NIMBE, UMR CEA/CNRS 3685 Laboratoire Structure et Dynamique par Résonance Magnétique Gif‐sur‐Yvette France
| | - Giovanna Baron
- Department of Pharmaceutical Sciences, Medicinal Chemistry Section "Pietro Pratesi” University of Milan Milan Italy
| | - Giancarlo Aldini
- Department of Pharmaceutical Sciences, Medicinal Chemistry Section "Pietro Pratesi” University of Milan Milan Italy
| | - Patrick Berthault
- IRAMIS, NIMBE, UMR CEA/CNRS 3685 Laboratoire Structure et Dynamique par Résonance Magnétique Gif‐sur‐Yvette France
| | - Fawzi Boumezbeur
- NeuroSpin, UMR CEA/CNRS 9027 Paris‐Saclay University Gif‐sur‐Yvette France
| | - Luisa Ciobanu
- NeuroSpin, UMR CEA/CNRS 9027 Paris‐Saclay University Gif‐sur‐Yvette France
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44
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Zhou J, Zaiss M, Knutsson L, Sun PZ, Ahn SS, Aime S, Bachert P, Blakeley JO, Cai K, Chappell MA, Chen M, Gochberg DF, Goerke S, Heo HY, Jiang S, Jin T, Kim SG, Laterra J, Paech D, Pagel MD, Park JE, Reddy R, Sakata A, Sartoretti-Schefer S, Sherry AD, Smith SA, Stanisz GJ, Sundgren PC, Togao O, Vandsburger M, Wen Z, Wu Y, Zhang Y, Zhu W, Zu Z, van Zijl PCM. Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors. Magn Reson Med 2022; 88:546-574. [PMID: 35452155 PMCID: PMC9321891 DOI: 10.1002/mrm.29241] [Citation(s) in RCA: 81] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/26/2022] [Accepted: 03/02/2022] [Indexed: 12/16/2022]
Abstract
Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
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Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Linda Knutsson
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Medical Radiation Physics, Lund University, Lund, Sweden.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Silvio Aime
- Molecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Peter Bachert
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jaishri O Blakeley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Michael A Chappell
- Mental Health and Clinical Neurosciences and Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Daniel F Gochberg
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Physics, Vanderbilt University, Nashville, Tennessee, USA
| | - Steffen Goerke
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - John Laterra
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Mark D Pagel
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Ravinder Reddy
- Center for Advance Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - A Dean Sherry
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Chemistry and Biochemistry, University of Texas at Dallas, Richardson, Texas, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Pia C Sundgren
- Department of Diagnostic Radiology/Clinical Sciences Lund, Lund University, Lund, Sweden.,Lund University Bioimaging Center, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter C M van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
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45
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Liu Z, Yang Q, Luo H, Luo D, Qian L, Liu X, Zheng H, Sun PZ, Wu Y. Demonstration of fast and equilibrium human muscle creatine CEST imaging at 3 T. Magn Reson Med 2022; 88:322-331. [PMID: 35324024 DOI: 10.1002/mrm.29223] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/23/2022] [Accepted: 02/20/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE Creatine chemical exchange saturation transfer (CrCEST) MRI is used increasingly in muscle imaging. However, the CrCEST measurement depends on the RF saturation duration (Ts) and relaxation delay (Td), and it is challenging to compare the results of different scan parameters. Therefore, this study aims to evaluate the quasi-steady-state (QUASS) CrCEST MRI on clinical 3T scanners. METHODS T1 and CEST MRI scans of Ts/Td of 1 s/1 s and 2 s/2 s were obtained from a multi-compartment creatine phantom and 5 healthy volunteers. The CrCEST effect was quantified with asymmetry analysis in the phantom, whereas 5-pool Lorentzian fitting was applied to isolate creatine from phosphocreatine, amide proton transfer, combined magnetization transfer and nuclear Overhauser enhancement effects, and direct water saturation in four major muscle groups of the lower leg. The routine and QUASS CrCEST measurements were compared under two different imaging conditions. Paired Student's t-test was performed with p-values less than 0.05 considered statistically significant. RESULTS The phantom study showed a substantial influence of Ts/Td on the routine CrCEST quantification (p = 0.02), and such impact was mitigated with the QUASS algorithm (p = 0.20). The volunteer experiment showed that the routine CrCEST, amide proton transfer, and combined magnetization transfer and nuclear Overhauser enhancement effects increased significantly with Ts and Td (p < 0.05) and were significantly smaller than the corresponding QUASS indices (p < 0.01). In comparison, the QUASS CrCEST MRI showed little dependence on Ts and Td, indicating its robustness and accuracy. CONCLUSION The QUASS CrCEST MRI is feasible to provide fast and accurate muscle creatine imaging.
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Affiliation(s)
- Zhou Liu
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Qian Yang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Honghong Luo
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Dehong Luo
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Long Qian
- MR Research, GE Healthcare, Beijing, China
| | - Xin Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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Brain pH Measurement Using AACID CEST MRI Incorporating the 2 ppm Amine Resonance. Tomography 2022; 8:730-739. [PMID: 35314637 PMCID: PMC8938777 DOI: 10.3390/tomography8020060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 01/23/2022] [Accepted: 03/01/2022] [Indexed: 11/17/2022] Open
Abstract
Many pathological conditions lead to altered intracellular pH (pHi) disrupting normal cellular functions. The chemical exchange saturation transfer (CEST) method, known as Amine and Amide Concentration Independent Detection (AACID), can produce image contrast that is predominantly dependent on tissue intracellular pHi. The AACID value is linearly related to the ratio of the 3.5 ppm amide CEST effect and the 2.75 ppm amine CEST effect in the physiological range. However, the amine CEST effect at 2 ppm is often more clearly defined in vivo, and may provide greater sensitivity to pH changes. The purpose of the current study was to compare AACID measurement precision utilizing the 2.0 and 2.75 ppm amine CEST effects. We hypothesized that the 2.0 ppm amine CEST resonance would produce measurements with greater sensitivity to pH changes. In the current study, we compare the range of the AACID values obtained in 24 mice with brain tumors and in normal tissue using the 2 ppm and 2.75 ppm amine resonances. All CEST data were acquired on a 9.4T MRI scanner. The AACID measurement range increased by 39% when using the 2 ppm amine resonance compared to the 2.75 ppm resonance, with decreased measurement variability across the brain. These data indicate that in vivo pH measurements made using AACID CEST can be enhanced by incorporating the 2 ppm amine resonance. This approach should be considered for pH measurements made over short intervals when no changes are expected in the concentration of metabolites that contribute to the 2 ppm amine resonance.
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Huang J, Chen Z, Park SW, Lai JHC, Chan KWY. Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges. Pharmaceutics 2022; 14:451. [PMID: 35214183 PMCID: PMC8880023 DOI: 10.3390/pharmaceutics14020451] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/10/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Zilin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Se-Weon Park
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Joseph H. C. Lai
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Kannie W. Y. Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- Tung Biomedical Science Centre, City University of Hong Kong, Hong Kong, China
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Perlman O, Farrar CT, Heo HY. MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification. NMR IN BIOMEDICINE 2022; 36:e4710. [PMID: 35141967 PMCID: PMC9808671 DOI: 10.1002/nbm.4710] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 01/18/2022] [Accepted: 02/04/2022] [Indexed: 05/11/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms have been developed to further boost the performance and speed of CEST and semi-solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.
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Affiliation(s)
- Or Perlman
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Christian T. Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Cui J, Zhao Y, Wang F, Gochberg DF, Zu Z. Contribution of blood to nuclear Overhauser effect at -1.6 ppm. Magn Reson Med 2022; 87:409-416. [PMID: 34480767 PMCID: PMC8616842 DOI: 10.1002/mrm.28973] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 07/19/2021] [Accepted: 07/26/2021] [Indexed: 01/04/2023]
Abstract
PURPOSE A relayed nuclear Overhauser enhancement (rNOE) saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was previously reported in rat and human brain, and some publications suggest that it may be related to blood. Here, we studied whether the NOE(-1.6) arises from blood through in vivo and ex vivo experiments. METHODS To evaluate the contribution from in vivo blood to NOE(-1.6), intravascular signals in rat brain were suppressed by two approaches: (1) signal acquisition with a diffusion-weighting of b = 400 s/mm2 ; (2) intravascular injection of 5 mg/kg monocrystalline iron oxide nanoparticle (MION). Ex vivo blood sample was also prepared. The signals were acquired using a chemical exchange saturation transfer (CEST) pulse sequence. Multiple-pool Lorentzian fitting of CEST Z-spectra was performed to quantify the NOE(-1.6) signal. RESULTS There are no significant variations in the fitted in vivo NOE(-1.6) signals when measured with or without diffusion-weighting, but significant signal decease does occur after injection of MION. The NOE(-1.6) signal from ex vivo blood is weaker than that from in vivo tissues. CONCLUSION Considering the relatively small volume of blood in brain, the in vivo experiments with diffusion weighting and the ex vivo experiments both suggest that the NOE(-1.6) is not mainly from blood. The mechanism for the in vivo experiments with MION are less clear. MION not only suppresses MR signals from intravascular space, but changes the susceptibility in the perivascular space. This result suggests that although the NOE(-1.6) is not mainly from blood, it may be vasculature dependent.
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Affiliation(s)
- Jing Cui
- Vanderbilt University Institute of Imaging Science,
Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Yu Zhao
- Vanderbilt University Institute of Imaging Science,
Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Feng Wang
- Vanderbilt University Institute of Imaging Science,
Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Daniel F. Gochberg
- Vanderbilt University Institute of Imaging Science,
Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
- Deparment of Physics and Astronomy, Vanderbilt University,
Nashville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science,
Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
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50
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Orzyłowska A, Oakden W. Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease. Brain Sci 2021; 12:53. [PMID: 35053797 PMCID: PMC8773856 DOI: 10.3390/brainsci12010053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/21/2021] [Accepted: 12/25/2021] [Indexed: 01/08/2023] Open
Abstract
Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.
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Affiliation(s)
- Anna Orzyłowska
- Department of Neurosurgery and Paediatric Neurosurgery, Medical University of Lublin, Jaczewskiego 8 (SPSK 4), 20-090 Lublin, Poland
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada;
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