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Shin HG, Li X, Heo HY, Knutsson L, Szczepankiewicz F, Nilsson M, van Zijl PCM. Compartmental anisotropy of filtered exchange imaging (FEXI) in human white matter: What is happening in FEXI? Magn Reson Med 2024. [PMID: 38525601 DOI: 10.1002/mrm.30086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/30/2024] [Accepted: 02/28/2024] [Indexed: 03/26/2024]
Abstract
PURPOSE To investigate the effects of compartmental anisotropy on filtered exchange imaging (FEXI) in white matter (WM). THEORY AND METHODS FEXI signals were measured using multiple combinations of diffusion filter and detection directions in five healthy volunteers. Additional filters, including a trace-weighted diffusion filter with trapezoidal gradients, a spherical b-tensor encoded diffusion filter, and a T2 filter, were tested with trace-weighted diffusion detection. RESULTS A large range of apparent exchange rates (AXR) and both positive and negative filter efficiencies (σ) were found depending on the mutual orientation of the filter and detection gradients relative to WM fiber orientation. The data demonstrated that the fast-diffusion compartment suppressed by diffusional filtering is not exclusively extra-cellular, but also intra-cellular. While not comprehensive, a simple two-compartment diffusion tensor model with water exchange was able to account qualitatively for the trends in positive and negative filtering efficiencies, while standard model imaging (SMI) without exchange could not. This two-compartment diffusion tensor model also demonstrated smaller AXR variances across subjects. When employing trace-weighted diffusion detection, AXR values were on the order of the R1 (=1/T1) of water at 3T for crossing fibers, while being less than R1 for parallel fibers. CONCLUSION Orientation-dependent AXR and σ values were observed when using multi-orientation filter and detection gradients in FEXI, indicating that WM FEXI models need to account for compartmental anisotropy. When using trace-weighted detection, AXR values were on the order of or less than R1, complicating the interpretation of FEXI results in WM in terms of biological exchange properties. These findings may contribute toward better understanding of FEXI results in WM.
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Affiliation(s)
- Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hye-Young Heo
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Linda Knutsson
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Filip Szczepankiewicz
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Zeng Q, Machado M, Bie C, van Zijl PCM, Malvar S, Li Y, D’souza V, Poon KA, Grimm A, Yadav NN. In vivo characterization of glycogen storage disease type III in a mouse model using glycoNOE MRI. Magn Reson Med 2024; 91:1115-1121. [PMID: 38009988 PMCID: PMC10842402 DOI: 10.1002/mrm.29923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/28/2023] [Accepted: 10/24/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE Glycogen storage disease type III (GSD III) is a rare inherited metabolic disease characterized by excessive accumulation of glycogen in liver, skeletal muscle, and heart. Currently, there are no widely available noninvasive methods to assess tissue glycogen levels and disease load. Here, we use glycogen nuclear Overhauser effect (glycoNOE) MRI to quantify hepatic glycogen levels in a mouse model of GSD III. METHODS Agl knockout mice (n = 13) and wild-type controls (n = 10) were scanned for liver glycogen content using glycoNOE MRI. All mice were fasted for 12 to 16 h before MRI scans. GlycoNOE signal was quantified by fitting the Z-spectrum using a four-pool Voigt lineshape model. Next, the fitted direct water saturation pool was removed and glycoNOE signal was estimated from the integral of the residual Z spectrum within -0.6 to -1.4 ppm. Glycogen concentration was also measured ex vivo using a biochemical assay. RESULTS GlycoNOE MRI clearly distinguished Agl knockout mice from wild-type controls, showing a statistically significant difference in glycoNOE signals in the livers across genotypes. There was a linear correlation between glycoNOE signal and glycogen concentration determined by the biochemical assay. The obtained glycoNOE maps of mouse livers also showed higher glycogen levels in Agl knockout mice compared to wild-type mice. CONCLUSION GlycoNOE MRI was used successfully as a noninvasive method to detect liver glycogen levels in mice, suggesting the potential of this method to be applied to assess glycogen storage diseases.
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Affiliation(s)
- Qing Zeng
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Chongxue Bie
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Sofi Malvar
- Ultragenyx Pharmaceutical Inc., Novato, CA, United States
| | - Yuguo Li
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Valentina D’souza
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Andrew Grimm
- Ultragenyx Pharmaceutical Inc., Novato, CA, United States
| | - Nirbhay N. Yadav
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Seidemo A, Wirestam R, Helms G, Markenroth Bloch K, Xu X, Bengzon J, Sundgren PC, van Zijl PCM, Knutsson L. Tissue response curve-shape analysis of dynamic glucose-enhanced and dynamic contrast-enhanced magnetic resonance imaging in patients with brain tumor. NMR Biomed 2023; 36:e4863. [PMID: 36310022 DOI: 10.1002/nbm.4863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/10/2022] [Accepted: 10/28/2022] [Indexed: 05/23/2023]
Abstract
Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p < 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.
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Affiliation(s)
- Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Gunther Helms
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | | | - Xiang Xu
- Icahn School of Medicine at Mount Sinai, BioMedical Engineering and Imaging Institute, New York, New York, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Johan Bengzon
- Division of Neurosurgery, Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Lund Stem Cell Center, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Pia C Sundgren
- Lund University Bioimaging Center, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund and Malmö, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, 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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Yadav NN, Xu J, Heo HY, van Zijl PCM. Special issue on chemical exchange saturation transfer MRI. NMR Biomed 2023; 36:e4960. [PMID: 37182903 DOI: 10.1002/nbm.4960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Affiliation(s)
- Nirbhay N Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hye-Young Heo
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Lehmann PM, Seidemo A, Andersen M, Xu X, Li X, Yadav NN, Wirestam R, Liebig P, Testud F, Sundgren P, van Zijl PCM, Knutsson L. A numerical human brain phantom for dynamic glucose-enhanced (DGE) MRI: On the influence of head motion at 3T. Magn Reson Med 2023; 89:1871-1887. [PMID: 36579955 PMCID: PMC9992166 DOI: 10.1002/mrm.29563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 11/09/2022] [Accepted: 12/07/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE Dynamic glucose-enhanced (DGE) MRI relates to a group of exchange-based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction. METHODS MPRAGE data from a tumor patient were used to simulate dynamic Z-spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head-motion-induced B0 -changes in presence of first-order shimming. The effect of retrospective motion correction was evaluated. RESULTS Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo-DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location. CONCLUSION DGE MRI studies can be corrupted by motion artifacts. Designing post-processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques.
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Affiliation(s)
- Patrick M Lehmann
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Mads Andersen
- Philips Healthcare, Copenhagen, Denmark
- Lund University Bioimaging Centre, Lund University, Lund, Sweden
| | - Xiang Xu
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Nirbhay N Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Ronnie Wirestam
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | | | | | - Pia Sundgren
- Lund University Bioimaging Centre, Lund University, Lund, Sweden
- Department of Radiology, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins, University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, 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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Zhang K, Chen L, Li Y, Paez AG, Miao X, Cao D, Gu C, Pekar JJ, van Zijl PCM, Hua J, Bakker A. Differential Laminar Activation Dissociates Encoding and Retrieval in the Human Medial and Lateral Entorhinal Cortex. J Neurosci 2023; 43:2874-2884. [PMID: 36948584 PMCID: PMC10124959 DOI: 10.1523/jneurosci.1488-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 02/28/2023] [Accepted: 03/12/2023] [Indexed: 03/24/2023] Open
Abstract
The hierarchically organized structures of the medial temporal lobe are critically important for episodic memory function. Accumulating evidence suggests dissociable information processing pathways are maintained throughout these structures including in the medial and lateral entorhinal cortex. Cortical layers provide an additional dimension of dissociation as the primary input to the hippocampus derives from layer 2 neurons in the entorhinal cortex, whereas the deeper layers primarily receive output from the hippocampus. Here, novel high-resolution T2-prepared functional MRI methods were successfully used to mitigate susceptibility artifacts typically affecting MRI signals in this region providing uniform sensitivity across the medial and lateral entorhinal cortex. During the performance of a memory task, healthy human subjects (age 25-33 years, mean age 28.2 ± 3.3 years, 4 female) showed differential functional activation in the superficial and deep layers of the entorhinal cortex associated with task-related encoding and retrieval conditions, respectively. The methods provided here offer an approach to probe layer-specific activation in normal cognition and conditions contributing to memory impairment.SIGNIFICANCE STATEMENT This study provides new evidence for differential neuronal activation in the superficial versus deep layers of the entorhinal cortex associated with encoding and retrieval memory processes, respectively, in cognitively normal adults. The study further shows that this dissociation can be observed in both the medial and the lateral entorhinal cortex. The study was achieved by using a novel functional MRI method allowing us to measure robust functional MRI signals in both the medial and lateral entorhinal cortex that was not possible in previous studies. The methodology established here in healthy human subjects lays a solid foundation for subsequent studies investigating layer-specific and region-specific changes in the entorhinal cortex associated with memory impairment in various conditions such as Alzheimer's disease.
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Affiliation(s)
- Kaihua Zhang
- School of Psychology, Shandong Normal University, Jinan 250014, China
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Liuyi Chen
- Departments of Psychiatry and Behavioral Sciences
| | - Yinghao Li
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - Adrian G Paez
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Xinyuan Miao
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Di Cao
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - Chunming Gu
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - James J Pekar
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Peter C M van Zijl
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Jun Hua
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Arnold Bakker
- Departments of Psychiatry and Behavioral Sciences
- Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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9
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Liu H, Chen L, Zhang C, Liu C, Li Y, Cheng L, Wei Z, Zhang Z, Lu H, van Zijl PCM, Iliff JJ, Xu J, Duan W. Interrogation of dynamic glucose-enhanced MRI and fluorescence-based imaging reveals a perturbed glymphatic network in Huntington's disease. bioRxiv 2023:2023.04.03.535397. [PMID: 37066166 PMCID: PMC10103957 DOI: 10.1101/2023.04.03.535397] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Huntington's disease (HD) is a neurodegenerative disorder that presents with progressive motor, mental, and cognitive impairment leading to early disability and mortality. The accumulation of mutant huntingtin protein aggregates in neurons is a pathological hallmark of HD. The glymphatic system, a brain-wide perivascular network, facilitates the exchange of interstitial fluid (ISF) and cerebrospinal fluid (CSF), supporting interstitial solute clearance including abnormal proteins from mammalian brains. In this study, we employed dynamic glucose-enhanced (DGE) MRI to measure D-glucose clearance from CSF as a tool to assess CSF clearance capacity to predict glymphatic function in a mouse model of HD. Our results demonstrate significantly diminished CSF clearance efficiency in premanifest zQ175 HD mice. The impairment of CSF clearance of D-glucose, measured by DGE MRI, worsened with disease progression. These DGE MRI findings in compromised glymphatic function in HD mice were further confirmed with fluorescence-based imaging of glymphatic CSF tracer influx, suggesting an impaired glymphatic function in premanifest stage of HD. Moreover, expression of the astroglial water channel aquaporin-4 (AQP4) in the perivascular compartment, a key mediator of glymphatic function, was significantly diminished in both HD mouse brain as well as postmortem human HD brain. Our data, acquired using a clinically translatable MRI approach, indicate a perturbed glymphatic network in the HD brain as early as in the premanifest stage. Further validation of these findings in clinical studies should provide insights into potential of glymphatic clearance as a HD biomarker and for glymphatic functioning as a disease-modifying therapeutic target for HD.
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10
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Bie C, van Zijl PCM, Mao D, Yadav NN. Ultrafast Z-spectroscopic imaging in vivo at 3T using through-slice spectral encoding (TS-UFZ). Magn Reson Med 2023; 89:1429-1440. [PMID: 36373181 PMCID: PMC9892239 DOI: 10.1002/mrm.29532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 10/02/2022] [Accepted: 10/31/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE Acquisition of high-resolution Z-spectra for CEST or magnetization transfer contrast (MTC) MRI requires excessive scan times. Ultrafast Z-spectroscopy (UFZ) has been proposed to address this; however, the quality of in vivo UFZ spectra has been insufficient. Here, we present a simple approach to improve this. THEORY AND METHODS UFZ imaging acquires full Z-spectra by encoding the spectral dimension spatially via a gradient applied concurrently with the RF saturation pulse. Different from previous implementations, both this saturation gradient and its readout were applied in the slice direction, resulting in a relatively uniform voxel composition. Phase-encoding was applied in both in-plane directions, allowing additional under-sampling and acceleration. RESULTS In phantoms, UFZ imaging with through-slice Z-spectral encoding (TS-UFZ) provided Z-spectra of salicylic acid and egg white in excellent agreement with conventional acquisitions. In vivo brain Z-spectra were influenced by flow through the imaging slice which affected the Z-spectral baseline. Still, CEST signals could be quantified after baseline fitting and mapping the residual CEST signal. Amide proton transfer (APT) contrast intensities obtained by TS-UFZ were on the same order of magnitude as conventional CEST but with different contrast across slice which likely is a result of different tissue regions contributing. CONCLUSION TS-UFZ approach improves signal stability and spectral uniformity over previous implementations and allows high spectral-resolution imaging of saturation transfer effects in the human brain at 3T. This implementation allows for further acceleration by reducing phase encoding steps and thus opens up the possibility of mapping dynamic CEST signals in vivo with a practical temporal resolution.
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Affiliation(s)
- Chongxue Bie
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore MD (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- Department of Information Science and Technology, Northwest University, Xi’an, Shaanxi (China)
| | - Peter C. M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore MD (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Deng Mao
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore MD (USA)
- Philips Healthcare, Baltimore, MD (USA)
| | - Nirbhay N. Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore MD (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
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11
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Miao X, Li Y, Zhou X, Luo Y, Paez AG, Liu D, van Zijl PCM, Hua J. Evaluation of T2-prepared blood oxygenation level dependent functional magnetic resonance imaging with an event-related task: Hemodynamic response function and reproducibility. Front Neurosci 2023; 17:1114045. [PMID: 36937683 PMCID: PMC10017524 DOI: 10.3389/fnins.2023.1114045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/13/2023] [Indexed: 03/06/2023] Open
Abstract
T2-prepared (T2prep) blood oxygenation level dependent (BOLD) functional MRI (fMRI) is an alternative fMRI approach developed to mitigate the susceptibility artifacts that are typically observed in brain regions near air-filled cavities, bleeding and calcification, and metallic objects in echo-planar-imaging (EPI) based fMRI images. Here, T2prep BOLD fMRI was evaluated in an event-related paradigm for the first time. Functional experiments were performed using gradient-echo (GRE) EPI, spin-echo (SE) EPI, and T2prep BOLD fMRI during an event-related visual task in 10 healthy human subjects. Each fMRI method was performed with a low (3.4 × 3.4 × 4 mm3) and a high (1.5 mm isotropic) spatial resolution on 3T and a high resolution (1.5 mm isotropic) on 7T. Robust activation were detected in the visual cortex with all three fMRI methods. In each group of fMRI scans (3T low resolution, 3T high resolution, and 7T high resolution), GRE EPI showed the highest signal change (ΔS/S), largest full-width-at-half-maximum (FWHM) and longest time-to-peak (TTP) extracted from the hemodynamic response functions (HRF), indicating substantial signal contribution from large draining veins which have longer response times than microvessels. In contrast, T2prep BOLD showed the lowest ΔS/S, smallest FWHM, and shortest TTP, suggesting that T2prep BOLD may have a purer T2-weighted BOLD contrast that is more sensitive to microvessels compared to GRE/SE EPI BOLD. This trend was more obvious in fMRI scans performed with a lower spatial resolution on a lower field (3T with a 3.4 × 3.4 × 4 mm3 voxel). Scan-rescan reproducibility in the same subjects was comparable among the three fMRI methods. The results from the current study are expected to be useful to establish T2prep BOLD as a useful alternative fMRI approach for event-related fMRI in brain regions with large susceptibility artifacts.
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Affiliation(s)
- Xinyuan Miao
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yinghao Li
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Xinyi Zhou
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Yu Luo
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Adrian G. Paez
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Dapeng Liu
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Peter C. M. van Zijl
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jun Hua
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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12
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Liu J, Chu C, Zhang J, Bie C, Chen L, Aafreen S, Xu J, Kamson DO, van Zijl PCM, Walczak P, Janowski M, Liu G. Label-Free Assessment of Mannitol Accumulation Following Osmotic Blood-Brain Barrier Opening Using Chemical Exchange Saturation Transfer Magnetic Resonance Imaging. Pharmaceutics 2022; 14:pharmaceutics14112529. [PMID: 36432721 PMCID: PMC9695341 DOI: 10.3390/pharmaceutics14112529] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/02/2022] [Accepted: 11/16/2022] [Indexed: 11/22/2022] Open
Abstract
PURPOSE Mannitol is a hyperosmolar agent for reducing intracranial pressure and inducing osmotic blood-brain barrier opening (OBBBO). There is a great clinical need for a non-invasive method to optimize the safety of mannitol dosing. The aim of this study was to develop a label-free Chemical Exchange Saturation Transfer (CEST)-based MRI approach for detecting intracranial accumulation of mannitol following OBBBO. METHODS In vitro MRI was conducted to measure the CEST properties of D-mannitol of different concentrations and pH. In vivo MRI and MRS measurements were conducted on Sprague-Dawley rats using a Biospec 11.7T horizontal MRI scanner. Rats were catheterized at the internal carotid artery (ICA) and randomly grouped to receive either 1 mL or 3 mL D-mannitol. CEST MR images were acquired before and at 20 min after the infusion. RESULTS In vitro MRI showed that mannitol has a strong, broad CEST contrast at around 0.8 ppm with a mM CEST MRI detectability. In vivo studies showed that CEST MRI could effectively detect mannitol in the brain. The low dose mannitol treatment led to OBBBO but no significant mannitol accumulation, whereas the high dose regimen resulted in both OBBBO and mannitol accumulation. The CEST MRI findings were consistent with 1H-MRS and Gd-enhanced MRI assessments. CONCLUSION We demonstrated that CEST MRI can be used for non-invasive, label-free detection of mannitol accumulation in the brain following BBBO treatment. This method may be useful as a rapid imaging tool to optimize the dosing of mannitol-based OBBBO and improve its safety and efficacy.
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Affiliation(s)
- Jing Liu
- Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510230, China
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Chengyan Chu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Jia Zhang
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Chongxue Bie
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Safiya Aafreen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - David O. Kamson
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Neurology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Piotr Walczak
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Miroslaw Janowski
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD 21201, USA
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21218, USA
- Correspondence: ; Tel.: +1-443-923-9500; Fax: +1-410-614-3147
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13
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Zhou Y, Bie C, van Zijl PCM, Xu J, Zou C, Yadav NN. Detection of electrostatic molecular binding using the water proton signal. Magn Reson Med 2022; 88:901-915. [PMID: 35394084 PMCID: PMC9232913 DOI: 10.1002/mrm.29230] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/07/2022] [Accepted: 02/22/2022] [Indexed: 12/25/2022]
Abstract
PURPOSE Saturation transfer MRI has previously been used to probe molecular binding interactions with signal enhancement via the water signal. Here, we detail the relayed nuclear overhauser effect (rNOE) based mechanisms of this signal enhancement, develop a strategy of quantifying molecular binding affinity, i.e., the dissociation constant ( K D $$ {K}_D $$ ), and apply the method to detect electrostatic binding of several charged small biomolecules. Another goal was to estimate the detection limit for transient receptor-substrate binding. THEORY AND METHODS The signal enhancement mechanism was quantitatively described by a three-step magnetization transfer model, and numerical simulations were performed to verify this theory. The binding equilibria of arginine, choline, and acetyl-choline to anionic resin were studied as a function of ligand concentration, pH, and salt content. Equilibrium dissociation constants ( K D $$ {K}_D $$ ) were determined by fitting the multiple concentration data. RESULTS The numerical simulations indicate that the signal enhancement is sufficient to detect the molecular binding of sub-millimolar (∼100 μM) concentration ligands to low micromolar levels of molecular targets. The measured rNOE signals from arginine, choline, and acetyl-choline binding experiments show that several magnetization transfer pathways (intra-ligand rNOEs and intermolecular rNOEs) can contribute. The rNOEs that arise from molecular ionic binding were influenced by pH and salt concentration. The molecular binding strengths in terms of K D $$ {K}_{\mathrm{D}} $$ ranged from 70-160 mM for the three cations studied. CONCLUSION The capability to use MRI to detect the transient binding of small substrates paves a pathway towards the detection of micromolar level receptor-substrate binding in vivo.
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Affiliation(s)
- Yang Zhou
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMDUSA
- The Russell H. Morgan Department of RadiologyThe Johns Hopkins University School of MedicineBaltimoreMDUSA
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong ProvinceShenzhen Institute of Advanced Technology, Chinese Academy of SciencesShenzhenGuangdongChina
| | - Chongxue Bie
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMDUSA
- The Russell H. Morgan Department of RadiologyThe Johns Hopkins University School of MedicineBaltimoreMDUSA
- Department of Information Science and TechnologyNorthwest UniversityXi'anChina
| | - Peter C. M. van Zijl
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMDUSA
- The Russell H. Morgan Department of RadiologyThe Johns Hopkins University School of MedicineBaltimoreMDUSA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMDUSA
- The Russell H. Morgan Department of RadiologyThe Johns Hopkins University School of MedicineBaltimoreMDUSA
| | - Chao Zou
- Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong ProvinceShenzhen Institute of Advanced Technology, Chinese Academy of SciencesShenzhenGuangdongChina
| | - Nirbhay N. Yadav
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMDUSA
- The Russell H. Morgan Department of RadiologyThe Johns Hopkins University School of MedicineBaltimoreMDUSA
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14
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Thomas AM, Yang E, Smith MD, Chu C, Calabresi PA, Glunde K, van Zijl PCM, Bulte JWM. CEST MRI and MALDI imaging reveal metabolic alterations in the cervical lymph nodes of EAE mice. J Neuroinflammation 2022; 19:130. [PMID: 35659311 PMCID: PMC9164344 DOI: 10.1186/s12974-022-02493-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 05/15/2022] [Indexed: 11/10/2022] Open
Abstract
Background Multiple sclerosis (MS) is a neurodegenerative disease, wherein aberrant immune cells target myelin-ensheathed nerves. Conventional magnetic resonance imaging (MRI) can be performed to monitor damage to the central nervous system that results from previous inflammation; however, these imaging biomarkers are not necessarily indicative of active, progressive stages of the disease. The immune cells responsible for MS are first activated and sensitized to myelin in lymph nodes (LNs). Here, we present a new strategy for monitoring active disease activity in MS, chemical exchange saturation transfer (CEST) MRI of LNs. Methods and results We studied the potential utility of conventional (T2-weighted) and CEST MRI to monitor changes in these LNs during disease progression in an experimental autoimmune encephalomyelitis (EAE) model. We found CEST signal changes corresponded temporally with disease activity. CEST signals at the 3.2 ppm frequency during the active stage of EAE correlated significantly with the cellular (flow cytometry) and metabolic (mass spectrometry imaging) composition of the LNs, as well as immune cell infiltration into brain and spinal cord tissue. Correlating primary metabolites as identified by matrix-assisted laser desorption/ionization (MALDI) imaging included alanine, lactate, leucine, malate, and phenylalanine. Conclusions Taken together, we demonstrate the utility of CEST MRI signal changes in superficial cervical LNs as a complementary imaging biomarker for monitoring disease activity in MS. CEST MRI biomarkers corresponded to disease activity, correlated with immune activation (surface markers, antigen-stimulated proliferation), and correlated with LN metabolite levels. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02493-z.
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Affiliation(s)
- Aline M Thomas
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA.,Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ethan Yang
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA
| | - Matthew D Smith
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Solomon H Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chengyan Chu
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA.,Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Solomon H Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kristine Glunde
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA.,Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jeff W M Bulte
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, MD, 21205, Baltimore, USA. .,Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Chemical and Biomolecular Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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15
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Li W, Xu F, Zhu D, van Zijl PCM, Qin Q. T 2 -oximetry-based cerebral venous oxygenation mapping using Fourier-transform-based velocity-selective pulse trains. Magn Reson Med 2022; 88:1292-1302. [PMID: 35608208 PMCID: PMC9247032 DOI: 10.1002/mrm.29300] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 12/14/2022]
Abstract
Purpose To develop a T2‐oximetry method for quantitative mapping of cerebral venous oxygenation fraction (Yv) using Fourier‐transform–based velocity‐selective (FT‐VS) pulse trains. Methods The venous isolation preparation was achieved by using an FT‐VS inversion plus a nonselective inversion (NSI) pulse to null the arterial blood signal while minimally affected capillary blood flows out into the venular vasculature during the outflow time (TO), and then applying an Fourier transform based velocity selective saturation (FT‐VSS) pulse to suppress the tissue signal. A multi‐echo readout was employed to obtain venous T2 (T2,v) efficiently with the last echo used to detect the residual CSF signal and correct its contamination in the fitting. Here we compared the performance of this FT‐VS–based venous isolation preparations with a traditional velocity‐selective saturation (VSS)–based approach (quantitative imaging of extraction of oxygen and tissue consumption [QUIXOTIC]) with different cutoff velocities for Yv mapping on 6 healthy volunteers at 3 Tesla. Results The FT‐VS–based methods yielded higher venous blood signal and temporal SNR with less CSF contamination than the velocity‐selective saturation–based results. The averaged Yv values across the whole slice measured in different experiments were close to the global Yv measured from the individual internal jugular vein. Conclusion The feasibility of the FT‐VS–based Yv estimation was demonstrated on healthy volunteers. The obtained high venous signal as well as the mitigation of CSF contamination led to a good agreement between the T2,v and Yv measured in the proposed method with the values in the literature. Click here for author‐reader discussions
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Affiliation(s)
- Wenbo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dan Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, 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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16
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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: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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17
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Bie C, Li Y, Zhou Y, Bhujwalla ZM, Song X, Liu G, van Zijl PCM, Yadav NN. Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging. NMR Biomed 2022; 35:e4626. [PMID: 34668251 PMCID: PMC8876537 DOI: 10.1002/nbm.4626] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 08/31/2021] [Accepted: 09/11/2021] [Indexed: 05/08/2023]
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often required to extract the signal of interest. We investigated whether deep learning could help identify pertinent Z-spectral features for distinguishing tumor aggressiveness as well as the possibility of acquiring only the pertinent spectral regions for more efficient CEST acquisition. Human breast cancer cells, MDA-MB-231 and MCF-7, were used to establish bi-lateral tumor xenografts in mice to represent higher and lower aggressive tumors, respectively. A convolutional neural network (CNN)-based classification model, trained on simulated data, utilized Z-spectral features as input to predict labels of different tissue types, including MDA-MB-231, MCF-7, and muscle tissue. Saliency maps reported the influence of Z-spectral regions on classifying tissue types. The model was robust to noise with an accuracy of more than 91.5% for low and moderate noise levels in simulated testing data (SD of noise less than 2.0%). For in vivo CEST data acquired with a saturation pulse amplitude of 2.0 μT, the model had a superior ability to delineate tissue types compared with Lorentzian difference (LD) and magnetization transfer ratio asymmetry (MTRasym ) analysis, classifying tissues to the correct types with a mean accuracy of 85.7%, sensitivity of 81.1%, and specificity of 94.0%. The model's performance did not improve substantially when using data acquired at multiple saturation pulse amplitudes or when adding LD or MTRasym spectral features, and did not change when using saliency map-based partial or downsampled Z-spectra. This study demonstrates the potential of CNN-based classification to distinguish between different tumor types and muscle tissue, and speed up CEST acquisition protocols.
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Affiliation(s)
- Chongxue Bie
- Department of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yuguo Li
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yang Zhou
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Zaver M Bhujwalla
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xiaolei Song
- Department of Information Science and Technology, Northwest University, Xi'an, Shaanxi, China
| | - Guanshu Liu
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Nirbhay N Yadav
- The Russell H. Morgan Department of Radiology, The 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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18
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Liu H, Zhang C, Xu J, Jin J, Cheng L, Miao X, Wu Q, Wei Z, Liu P, Lu H, van Zijl PCM, Ross CA, Hua J, Duan W. Huntingtin silencing delays onset and slows progression of Huntington's disease: a biomarker study. Brain 2021; 144:3101-3113. [PMID: 34043007 PMCID: PMC8634120 DOI: 10.1093/brain/awab190] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/19/2021] [Accepted: 04/29/2021] [Indexed: 01/29/2023] Open
Abstract
Huntington's disease is a dominantly inherited, fatal neurodegenerative disorder caused by a CAG expansion in the huntingtin (HTT) gene, coding for pathological mutant HTT protein (mHTT). Because of its gain-of-function mechanism and monogenic aetiology, strategies to lower HTT are being actively investigated as disease-modifying therapies. Most approaches are currently targeted at the manifest stage, where clinical outcomes are used to evaluate the effectiveness of therapy. However, as almost 50% of striatal volume has been lost at the time of onset of clinical manifest, it would be preferable to begin therapy in the premanifest period. An unmet challenge is how to evaluate therapeutic efficacy before the presence of clinical symptoms as outcome measures. To address this, we aim to develop non-invasive sensitive biomarkers that provide insight into therapeutic efficacy in the premanifest stage of Huntington's disease. In this study, we mapped the temporal trajectories of arteriolar cerebral blood volumes (CBVa) using inflow-based vascular-space-occupancy (iVASO) MRI in the heterozygous zQ175 mice, a full-length mHTT expressing and slowly progressing model with a premanifest period as in human Huntington's disease. Significantly elevated CBVa was evident in premanifest zQ175 mice prior to motor deficits and striatal atrophy, recapitulating altered CBVa in human premanifest Huntington's disease. CRISPR/Cas9-mediated non-allele-specific HTT silencing in striatal neurons restored altered CBVa in premanifest zQ175 mice, delayed onset of striatal atrophy, and slowed the progression of motor phenotype and brain pathology. This study-for the first time-shows that a non-invasive functional MRI measure detects therapeutic efficacy in the premanifest stage and demonstrates long-term benefits of a non-allele-selective HTT silencing treatment introduced in the premanifest Huntington's disease.
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Affiliation(s)
- Hongshuai Liu
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chuangchuang Zhang
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jing Jin
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Liam Cheng
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Xinyuan Miao
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qian Wu
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peiying Liu
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christopher A Ross
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jun Hua
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wenzhen Duan
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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19
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Miao X, Paez AG, Rajan S, Cao D, Liu D, Pantelyat AY, Rosenthal LI, van Zijl PCM, Bassett SS, Yousem DM, Kamath V, Hua J. Functional Activities Detected in the Olfactory Bulb and Associated Olfactory Regions in the Human Brain Using T2-Prepared BOLD Functional MRI at 7T. Front Neurosci 2021; 15:723441. [PMID: 34588949 PMCID: PMC8476065 DOI: 10.3389/fnins.2021.723441] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 08/16/2021] [Indexed: 11/17/2022] Open
Abstract
Olfaction is a fundamental sense that plays a vital role in daily life in humans, and can be altered in neuropsychiatric and neurodegenerative diseases. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) using conventional echo-planar-imaging (EPI) based sequences can be challenging in brain regions important for olfactory processing, such as the olfactory bulb (OB) and orbitofrontal cortex, mainly due to the signal dropout and distortion artifacts caused by large susceptibility effects from the sinonasal cavity and temporal bone. To date, few studies have demonstrated successful fMRI in the OB in humans. T2-prepared (T2prep) BOLD fMRI is an alternative approach developed especially for performing fMRI in regions affected by large susceptibility artifacts. The purpose of this technical study is to evaluate T2prep BOLD fMRI for olfactory functional experiments in humans. Olfactory fMRI scans were performed on 7T in 14 healthy participants. T2prep BOLD showed greater sensitivity than GRE EPI BOLD in the OB, orbitofrontal cortex and the temporal pole. Functional activation was detected using T2prep BOLD in the OB and associated olfactory regions. Habituation effects and a bi-phasic pattern of fMRI signal changes during olfactory stimulation were observed in all regions. Both positively and negatively activated regions were observed during olfactory stimulation. These signal characteristics are generally consistent with literature and showed a good intra-subject reproducibility comparable to previous human BOLD fMRI studies. In conclusion, the methodology demonstrated in this study holds promise for future olfactory fMRI studies in the OB and other brain regions that suffer from large susceptibility artifacts.
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Affiliation(s)
- Xinyuan Miao
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Adrian G Paez
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Suraj Rajan
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Di Cao
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Dapeng Liu
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Alex Y Pantelyat
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Liana I Rosenthal
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Peter C M van Zijl
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Susan S Bassett
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - David M Yousem
- Department of Radiology, Johns Hopkins Hospital, Baltimore, MD, United States
| | - Vidyulata Kamath
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Jun Hua
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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20
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van Zijl PCM, Brindle K, Lu H, Barker PB, Edden R, Yadav N, Knutsson L. Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo. Curr Opin Chem Biol 2021; 63:209-218. [PMID: 34298353 PMCID: PMC8384704 DOI: 10.1016/j.cbpa.2021.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/12/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022]
Abstract
Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.
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Affiliation(s)
- Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA.
| | - Kevin Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Nirbhay Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Medical Radiation Physics, Lund University, Lund, Sweden
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21
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Li W, Liu D, van Zijl PCM, Qin Q. Three-dimensional whole-brain mapping of cerebral blood volume and venous cerebral blood volume using Fourier transform-based velocity-selective pulse trains. Magn Reson Med 2021; 86:1420-1433. [PMID: 33955583 DOI: 10.1002/mrm.28815] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 03/28/2021] [Accepted: 04/01/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To develop 3D MRI methods for cerebral blood volume (CBV) and venous cerebral blood volume (vCBV) estimation with whole-brain coverage using Fourier transform-based velocity-selective (FT-VS) pulse trains. METHODS For CBV measurement, FT-VS saturation pulse trains were used to suppress static tissue, whereas CSF contamination was corrected voxel-by-voxel using a multi-readout acquisition and a fast CSF T2 scan. The vCBV mapping was achieved by inserting an arterial-nulling module that included a FT-VS inversion pulse train. Using these methods, CBV and vCBV maps were obtained on 6 healthy volunteers at 3 T. RESULTS The mean CBV and vCBV values in gray matter and white matter in different areas of the brain showed high correlation (r = 0.95 and P < .0001). The averaged CBV and vCBV values of the whole brain were 5.4 ± 0.6 mL/100 g and 2.5 ± 0.3 mL/100 g in gray matter, and 2.6 ± 0.5 mL/100 g and 1.5 ± 0.2 mL/100 g in white matter, respectively, comparable to the literature. CONCLUSION The feasibility of FT-VS-based CBV and vCBV estimation was demonstrated for 3D acquisition with large spatial coverage.
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Affiliation(s)
- Wenbo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Dapeng Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, 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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22
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Sui R, Chen L, Li Y, Huang J, Chan KWY, Xu X, van Zijl PCM, Xu J. Whole-brain amide CEST imaging at 3T with a steady-state radial MRI acquisition. Magn Reson Med 2021; 86:893-906. [PMID: 33772859 DOI: 10.1002/mrm.28770] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/15/2021] [Accepted: 02/18/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a steady-state saturation with radial readout chemical exchange saturation transfer (starCEST) for acquiring CEST images at 3 Tesla (T). The polynomial Lorentzian line-shape fitting approach was further developed for extracting amideCEST intensities at this field. METHOD StarCEST MRI using periodically rotated overlapping parallel lines with enhanced reconstruction-based spatial sampling was implemented to acquire Z-spectra that are robust to brain motion. Multi-linear singular value decomposition postprocessing was applied to enhance the CEST SNR. The egg white phantom studies were performed at 3T to reveal the contributions to the 3.5 ppm CEST signal. Based on the phantom validation, the amideCEST peak was quantified using the polynomial Lorentzian line-shape fitting, which exploits the inverse relationship between Z-spectral intensity and the longitudinal relaxation rate in the rotating frame. The 3D turbo spin echo CEST was also performed to compare with the starCEST method. RESULTS The amideCEST peak showed a negligible peak B1 dependence between 1.2 µT and 2.4 µT. The amideCEST images acquired with starCEST showed much improved image quality, SNR, and motion robustness compared to the conventional 3D turbo spin echo CEST method with the same scan time. The amideCEST contrast extracted by the polynomial Lorentzian line-shape fitting method trended toward a stronger gray matter signal (1.32% ± 0.30%) than white matter (0.92% ± 0.08%; P = .02, n = 5). When calculating the magnetization transfer contrast and T1 -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter. CONCLUSION Rapid multi-slice amideCEST mapping can be achieved by the starCEST method (< 5 min) at 3T by combing with the polynomial Lorentzian line-shape fitting method.
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Affiliation(s)
- Ran Sui
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, People's Republic of China
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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23
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Affiliation(s)
- Peter C M van Zijl
- From the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 720 Rutland Ave, 217 Traylor Bldg, Baltimore, MD 21205; and F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Md
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Han Z, Liu S, Pei Y, Ding Z, Li Y, Wang X, Zhan D, Xia S, Driedonks T, Witwer KW, Weiss RG, van Zijl PCM, Bulte JWM, Cheng L, Liu G. Highly efficient magnetic labelling allows MRI tracking of the homing of stem cell-derived extracellular vesicles following systemic delivery. J Extracell Vesicles 2021; 10:e12054. [PMID: 33489014 PMCID: PMC7809601 DOI: 10.1002/jev2.12054] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 12/05/2020] [Accepted: 12/16/2020] [Indexed: 12/14/2022] Open
Abstract
Human stem‐cell‐derived extracellular vesicles (EVs) are currently being investigated for cell‐free therapy in regenerative medicine applications, but the lack of noninvasive imaging methods to track EV homing and uptake in injured tissues has limited the refinement and optimization of the approach. Here, we developed a new labelling strategy to prepare magnetic EVs (magneto‐EVs) allowing sensitive yet specific MRI tracking of systemically injected therapeutic EVs. This new labelling strategy relies on the use of ‘sticky’ magnetic particles, namely superparamagnetic iron oxide (SPIO) nanoparticles coated with polyhistidine tags, to efficiently separate magneto‐EVs from unencapsulated SPIO particles. Using this method, we prepared pluripotent stem cell (iPSC)‐derived magneto‐EVs and subsequently used MRI to track their homing in different animal models of kidney injury and myocardial ischemia. Our results showed that iPSC‐derived EVs preferentially accumulated in the injury sites and conferred substantial protection. Our study paves a new pathway for preparing highly purified magnetic EVs and tracking them using MRI towards optimized, systemically administered EV‐based cell‐free therapies.
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Affiliation(s)
- Zheng Han
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,F.M. Kirby Research Center Kennedy Krieger Institute Baltimore Maryland USA
| | - Senquan Liu
- Cellular Imaging Section and Vascular Biology Program Institute for Cell Engineering Johns Hopkins University School of Medicine Baltimore Maryland USA.,Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA.,Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui China
| | - Yigang Pei
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,Department of Radiology Xiangya Hospital Central South University Changsha Hunan China
| | - Zheng Ding
- Cellular Imaging Section and Vascular Biology Program Institute for Cell Engineering Johns Hopkins University School of Medicine Baltimore Maryland USA
| | - Yuguo Li
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,F.M. Kirby Research Center Kennedy Krieger Institute Baltimore Maryland USA
| | - Xinge Wang
- Department of Bioengineering University of Illinois at Chicago Chicago Illinois USA
| | - Daqian Zhan
- Department of Neurology Hugo W. Moser Research Institute at Kennedy Krieger Baltimore Maryland USA
| | - Shuli Xia
- Department of Neurology Hugo W. Moser Research Institute at Kennedy Krieger Baltimore Maryland USA
| | - Tom Driedonks
- Department of Molecular and Comparative Pathobiology Johns Hopkins University School of Medicine Baltimore Maryland USA
| | - Kenneth W Witwer
- Department of Molecular and Comparative Pathobiology Johns Hopkins University School of Medicine Baltimore Maryland USA
| | - Robert G Weiss
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,Division of Cardiology Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,F.M. Kirby Research Center Kennedy Krieger Institute Baltimore Maryland USA
| | - Jeff W M Bulte
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,F.M. Kirby Research Center Kennedy Krieger Institute Baltimore Maryland USA.,Cellular Imaging Section and Vascular Biology Program Institute for Cell Engineering Johns Hopkins University School of Medicine Baltimore Maryland USA
| | - Linzhao Cheng
- Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA.,Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui China
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology Johns Hopkins University School of Medicine Baltimore Maryland USA.,F.M. Kirby Research Center Kennedy Krieger Institute Baltimore Maryland USA
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Chen L, Cao S, Koehler RC, van Zijl PCM, Xu J. High-sensitivity CEST mapping using a spatiotemporal correlation-enhanced method. Magn Reson Med 2020; 84:3342-3350. [PMID: 32597519 PMCID: PMC7722217 DOI: 10.1002/mrm.28380] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 05/01/2020] [Accepted: 05/23/2020] [Indexed: 01/29/2023]
Abstract
PURPOSE To obtain high-sensitivity CEST maps by exploiting the spatiotemporal correlation between CEST images. METHODS A postprocessing method accomplished by multilinear singular value decomposition (MLSVD) was used to enhance the CEST SNR by exploiting the correlation between the Z-spectrum for each voxel and the low-rank property of the overall CEST data. The performance of this method was evaluated using CrCEST in ischemic mouse brain at 11.7 tesla. Then, MLSVD CEST was applied to obtain Cr, amide, and amine CEST maps of the ischemic mouse brain to demonstrate its general applications. RESULTS Complex-valued Gaussian noise was added to CEST k-space data to mimic a low SNR situation. MLSVD CEST analysis was able to suppress the noise, recover the degraded CEST peak, and provide better CrCEST quality compared to the smoothing and singular value decomposition (SVD)-based denoising methods. High-resolution Cr, amide, and amine CEST maps of an ischemic stroke using MLSVD CEST suggest that CrCEST is also a sensitive pH mapping method, and a wide range of pH changes can be detected by combing CrCEST with amine CEST at high magnetic fields. CONCLUSION MLSVD CEST provides a simple and efficient way to improve the SNR of CEST images.
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Affiliation(s)
- Lin Chen
- 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,Corresponding Author: Lin Chen, Ph.D., Kennedy Krieger Institute, Johns Hopkins University School of Medicine, 707 N. Broadway, Baltimore, MD, 21205,
| | - Suyi Cao
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raymond C. Koehler
- Department of Anesthesiology and Critical Care Medicine, 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
| | - 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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26
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Chen L, Soldan A, Oishi K, Faria A, Zhu Y, Albert M, van Zijl PCM, Li X. Quantitative Susceptibility Mapping of Brain Iron and β-Amyloid in MRI and PET Relating to Cognitive Performance in Cognitively Normal Older Adults. Radiology 2020; 298:353-362. [PMID: 33231528 DOI: 10.1148/radiol.2020201603] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Background For individuals with mild cognitive impairment (MCI) or dementia, elevated brain iron together with β-amyloid is associated with lower cognitive functioning. But this needs further investigation among cognitively normal older adults. Purpose To investigate via quantitative susceptibility mapping (QSM) in MRI and PET how cerebral iron together with β-amyloid affects cognition among cognitively normal older adults. Materials and Methods In this secondary analysis of a prospective study, cognitively normal older adults underwent QSM MRI to measure brain iron. A majority underwent PET to measure cerebral β-amyloid within 30 days of MRI. Multiple linear regression analyses were performed for 12 cortical and subcortical gray matter regions to assess the effect of brain iron on cognitive functions. Voxel-based analyses investigated the associations between tissue iron and β-amyloid load and their relationship to cognitive performance. Results Evaluated were 150 cognitively normal older adults (mean age, 69 years ± 8 [standard deviation]; 93 women). Of 150, 97 underwent PET; 22 of the 97 (mean age, 71 years ± 6; 13 women) were positive for β-amyloid. In all participants, brain iron content in the hippocampus negatively correlated with global cognitive composite score (standardized β = -0.24; 95% CI: -0.40, -0.07; P = .005). In the PET subgroup, brain iron in the hippocampus negatively correlated with episodic memory (β = -0.24; 95% CI: -0.40, -0.08; P = .004) and visuospatial score (β = -0.34; 95% CI: -0.56, -0.12; P = .003) independent of β-amyloid burden. Both negative and positive correlations between brain iron and β-amyloid were observed in the PET subgroup, revealing clusters where brain iron content negatively correlated with β-amyloid and global cognitive scores (eg, in the frontal cortex: β = -0.13; 95% CI: -0.23, -0.02; P = .02). No clusters showed associations between β-amyloid and global cognition. Conclusion Among cognitively normal older adults, quantitative susceptibility mapping in MRI and PET indicated that elevated cerebral iron load was related to lower cognitive performance independent of β-amyloid. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Chiang in this issue.
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Affiliation(s)
- Lin Chen
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Anja Soldan
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Kenichi Oishi
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Andreia Faria
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Yuxin Zhu
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Marilyn Albert
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Peter C M van Zijl
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
| | - Xu Li
- From the F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N Broadway, Room G-25, Baltimore, MD 21205 (L.C., P.C.M.v.Z., X.L.); Department of Radiology and Radiological Sciences (L.C., K.O., A.F., P.C.M.v.Z., X.L.) and Department of Neurology (A.S., M.A.), Johns Hopkins University School of Medicine, Baltimore, Md; and Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, Md (Y.Z.)
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27
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Bao L, Xiong C, Wei W, Chen Z, van Zijl PCM, Li X. Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain. Med Image Anal 2020; 67:101827. [PMID: 33166777 DOI: 10.1016/j.media.2020.101827] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Revised: 08/19/2020] [Accepted: 08/31/2020] [Indexed: 10/23/2022]
Abstract
Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
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Affiliation(s)
- Lijun Bao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China.
| | - Congcong Xiong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Wenping Wei
- Medical Imaging Diagnostic Center, First Affiliated Hospital of Xiamen University, Xiamen 361000, China
| | - Zhong Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Xu Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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28
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Zhou Y, van Zijl PCM, Xu J, Yadav NN. Mechanism and quantitative assessment of saturation transfer for water-based detection of the aliphatic protons in carbohydrate polymers. Magn Reson Med 2020; 85:1643-1654. [PMID: 32970889 DOI: 10.1002/mrm.28503] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 07/20/2020] [Accepted: 08/10/2020] [Indexed: 12/23/2022]
Abstract
PURPOSE CEST MRI experiments of mobile macromolecules, for example, proteins, carbohydrates, and phospholipids, often show signals due to saturation transfer from aliphatic protons to water. Currently, the mechanism of this nuclear Overhauser effect (NOE)-based transfer pathway is not completely understood and could be due either to NOEs directly to bound water or NOEs relayed intramolecularly via exchangeable protons. We used glycogen as a model system to investigate this saturation transfer pathway in sugar polymer solution. METHODS To determine whether proton exchange affected saturation transfer, saturation spectra (Z-spectra) were measured for glycogen solutions of different pH, D2 O/H2 O ratio, and glycogen particle size. A theoretical model was derived to analytically describe the NOE-based signals in these spectra. Numerical simulations were performed to verify this theory, which was further tested by fitting experimental data for different exchange regimes. RESULTS Signal intensities of aliphatic NOEs in Z-spectra of glycogen in D2 O solution were influenced by hydroxyl proton exchange rates, whereas those in H2 O were not. This indicates that the primary transfer pathway is an exchange-relayed NOE from these aliphatic protons to neighboring hydroxyl protons, followed by the exchange to water protons. Experimental data for glycogen solutions in D2 O and H2 O could be analyzed successfully using an analytical theory derived for such relayed NOE transfer, which was further validated using numerical simulations with the Bloch equations. CONCLUSION The predominant mechanism underlying aliphatic signals in Z-spectra of mobile carbohydrate polymers is intramolecular relayed NOE transfer followed by proton exchange.
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Affiliation(s)
- Yang Zhou
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Nirbhay N Yadav
- The Russell H. Morgan Department of Radiology, The 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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29
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Xu X, Sehgal AA, Yadav NN, Laterra J, Blair L, Blakeley J, Seidemo A, Coughlin JM, Pomper MG, Knutsson L, van Zijl PCM. d-glucose weighted chemical exchange saturation transfer (glucoCEST)-based dynamic glucose enhanced (DGE) MRI at 3T: early experience in healthy volunteers and brain tumor patients. Magn Reson Med 2020; 84:247-262. [PMID: 31872916 PMCID: PMC7083699 DOI: 10.1002/mrm.28124] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 10/30/2019] [Accepted: 11/19/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Dynamic glucose enhanced (DGE) MRI has shown potential for imaging glucose delivery and blood-brain barrier permeability at fields of 7T and higher. Here, we evaluated issues involved with translating d-glucose weighted chemical exchange saturation transfer (glucoCEST) experiments to the clinical field strength of 3T. METHODS Exchange rates of the different hydroxyl proton pools and the field-dependent T2 relaxivity of water in d-glucose solution were used to simulate the water saturation spectra (Z-spectra) and DGE signal differences as a function of static field strength B0 , radiofrequency field strength B1 , and saturation time tsat . Multislice DGE experiments were performed at 3T on 5 healthy volunteers and 3 glioma patients. RESULTS Simulations showed that DGE signal decreases with B0 , because of decreased contributions of glucoCEST and transverse relaxivity, as well as coalescence of the hydroxyl and water proton signals in the Z-spectrum. At 3T, because of this coalescence and increased interference of direct water saturation and magnetization transfer contrast, the DGE effect can be assessed over a broad range of saturation frequencies. Multislice DGE experiments were performed in vivo using a B1 of 1.6 µT and a tsat of 1 second, leading to a small glucoCEST DGE effect at an offset frequency of 2 ppm from the water resonance. Motion correction was essential to detect DGE effects reliably. CONCLUSION Multislice glucoCEST-based DGE experiments can be performed at 3T with sufficient temporal resolution. However, the effects are small and prone to motion influence. Therefore, motion correction should be used when performing DGE experiments at clinical field strengths.
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Affiliation(s)
- Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Akansha Ashvani Sehgal
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Nirbhay N. Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - John Laterra
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lindsay Blair
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jaishri Blakeley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anina Seidemo
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Jennifer M. Coughlin
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Martin G. Pomper
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
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30
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Wei Z, Chen L, Hou X, van Zijl PCM, Xu J, Lu H. Age-Related Alterations in Brain Perfusion, Venous Oxygenation, and Oxygen Metabolic Rate of Mice: A 17-Month Longitudinal MRI Study. Front Neurol 2020; 11:559. [PMID: 32595596 PMCID: PMC7304368 DOI: 10.3389/fneur.2020.00559] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 05/15/2020] [Indexed: 12/31/2022] Open
Abstract
Background: Characterization of physiological parameters of the aging brain, such as perfusion and brain metabolism, is important for understanding brain function and diseases. Aging studies on human brain have mostly been based on the cross-sectional design, while the few longitudinal studies used relatively short follow-up time compared to the lifespan. Objectives: To determine the longitudinal time courses of cerebral physiological parameters across the adult lifespan in mice. Methods: The present work examined longitudinal changes in cerebral blood flow (CBF), cerebral venous oxygenation (Yv), and cerebral metabolic rate of oxygen (CMRO2) using MRI in healthy C57BL/6 mice from 3 to 20 months of age. Each mouse received 16 imaging sessions at an ~1-month interval. Results: Significant increases with age were observed in CBF (p = 0.017) and CMRO2 (p < 0.001). Meanwhile, Yv revealed a significant decrease (p = 0.002) with a non-linear pattern (p = 0.013). The rate of change was 0.87, 2.26, and -0.24% per month for CBF, CMRO2, and Yv, respectively. On the other hand, systemic parameters such as heart rate did not show a significant age dependence (p = 0.47). No white-matter-hyperintensities (WMH) were observed on the T2-weighted image at any age of the mice. Conclusion: With age, the mouse brain revealed an increase in oxygen consumption. This observation is consistent with previous findings in humans using a cross-sectional design and suggests a degradation of the brain's energy production or utilization machinery. Cerebral perfusion remains relatively intact in aged mice, at least until 20 months of age, consistent with the absence of WMH in mice.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
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31
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Huang J, van Zijl PCM, Han X, Dong CM, Cheng GWY, Tse KH, Knutsson L, Chen L, Lai JHC, Wu EX, Xu J, Chan KWY. Altered d-glucose in brain parenchyma and cerebrospinal fluid of early Alzheimer's disease detected by dynamic glucose-enhanced MRI. Sci Adv 2020; 6:eaba3884. [PMID: 32426510 PMCID: PMC7220384 DOI: 10.1126/sciadv.aba3884] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 02/27/2020] [Indexed: 05/09/2023]
Abstract
Altered cerebral glucose uptake is one of the hallmarks of Alzheimer's disease (AD). A dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) approach was developed to simultaneously monitor d-glucose uptake and clearance in both brain parenchyma and cerebrospinal fluid (CSF). We observed substantially higher uptake in parenchyma of young (6 months) transgenic AD mice compared to age-matched wild-type (WT) mice. Notably lower uptakes were observed in parenchyma and CSF of old (16 months) AD mice. Both young and old AD mice had an obviously slower CSF clearance than age-matched WT mice. This resembles recent reports of the hampered CSF clearance that leads to protein accumulation in the brain. These findings suggest that DGE MRI can identify altered glucose uptake and clearance in young AD mice upon the emergence of amyloid plaques. DGE MRI of brain parenchyma and CSF has potential for early AD stratification, especially at 3T clinical field strength MRI.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Xiongqi Han
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Celia M. Dong
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
| | - Gerald W. Y. Cheng
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Kai-Hei Tse
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Joseph H. C. Lai
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Ed X. Wu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Corresponding author. (K.W.Y.C.); (J.X.)
| | - Kannie W. Y. Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Corresponding author. (K.W.Y.C.); (J.X.)
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Affiliation(s)
- Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Kevin M Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
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Chen L, Schär M, Chan KWY, Huang J, Wei Z, Lu H, Qin Q, Weiss RG, van Zijl PCM, Xu J. In vivo imaging of phosphocreatine with artificial neural networks. Nat Commun 2020; 11:1072. [PMID: 32102999 PMCID: PMC7044432 DOI: 10.1038/s41467-020-14874-0] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 02/10/2020] [Indexed: 12/01/2022] Open
Abstract
Phosphocreatine (PCr) plays a vital role in neuron and myocyte energy homeostasis. Currently, there are no routine diagnostic tests to noninvasively map PCr distribution with clinically relevant spatial resolution and scan time. Here, we demonstrate that artificial neural network-based chemical exchange saturation transfer (ANNCEST) can be used to rapidly quantify PCr concentration with robust immunity to commonly seen MRI interferences. High-quality PCr mapping of human skeletal muscle, as well as the information of exchange rate, magnetic field and radio-frequency transmission inhomogeneities, can be obtained within 1.5 min on a 3 T standard MRI scanner using ANNCEST. For further validation, we apply ANNCEST to measure the PCr concentrations in exercised skeletal muscle. The ANNCEST outcomes strongly correlate with those from 31P magnetic resonance spectroscopy (R = 0.813, p < 0.001, t test). These results suggest that ANNCEST has potential as a cost-effective and widely available method for measuring PCr and diagnosing related diseases.
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Affiliation(s)
- Lin Chen
- 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
| | - Michael Schär
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Zhiliang Wei
- 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
| | - Hanzhang Lu
- 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
| | - 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, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert G Weiss
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Cardiology, Department of Medicine, 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, The 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, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Kagerer SM, van Bergen JMG, Li X, Quevenco FC, Gietl AF, Studer S, Treyer V, Meyer R, Kaufmann PA, Nitsch RM, van Zijl PCM, Hock C, Unschuld PG. APOE4 moderates effects of cortical iron on synchronized default mode network activity in cognitively healthy old-aged adults. Alzheimers Dement (Amst) 2020; 12:e12002. [PMID: 32211498 PMCID: PMC7085281 DOI: 10.1002/dad2.12002] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 10/21/2019] [Accepted: 11/01/2019] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Apolipoprotein E ε4 (APOE4)-related genetic risk for sporadic Alzheimer's disease is associated with an early impairment of cognitive brain networks. The current study determines relationships between APOE4 carrier status, cortical iron, and cortical network-functionality. METHODS Sixty-nine cognitively healthy old-aged individuals (mean age [SD] 66.1 [± 7.2] years; Mini-Mental State Exam [MMSE] 29.3 ± 1.1) were genotyped for APOE4 carrier-status and received 3 Tesla magnetic resonance imaging (MRI) for blood oxygen level-dependent functional magnetic resonance imaging (MRI) at rest, three-dimensional (3D)-gradient echo (six echoes) for cortical gray-matter, non-heme iron by quantitative susceptibility mapping, and 18F-flutemetamol positron emission tomography for amyloid-β. RESULTS A spatial pattern consistent with the default mode network (DMN) could be identified by independent component analysis. DMN activity was enhanced in APOE4 carriers and related to cortical iron burden. APOE4 and cortical iron synergistically interacted with DMN activity. Secondary analysis revealed a positive, APOE4 associated, relationship between cortical iron and DMN connectivity. DISCUSSION Our findings suggest that APOE4 moderates effects of iron on brain functionality prior to manifestation of cognitive impairment.
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Affiliation(s)
- Sonja M. Kagerer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | | | - Xu Li
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | | | - Anton F. Gietl
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Sandro Studer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
| | - Valerie Treyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Rafael Meyer
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
| | - Philipp A. Kaufmann
- Department of Nuclear MedicineUniversity Hospital Zurich and University of ZurichZurichSwitzerland
| | - Roger M. Nitsch
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Peter C. M. van Zijl
- The Russell H. Morgan Department of Radiology and Radiological ScienceDivision of MR ResearchThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
- F.M. Kirby Research Center for Functional Brain ImagingKennedy Krieger InstituteBaltimoreMarylandUSA
| | - Christoph Hock
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
- NeurimmuneSchlierenSwitzerland
| | - Paul G. Unschuld
- Institute for Regenerative MedicineUniversity of ZurichZurichSwitzerland
- Department of Psychogeriatric MedicinePsychiatric University Hospital Zurich (PUK)ZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and ETH ZurichZurichSwitzerland
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35
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Miao X, Wu Y, Liu D, Jiang H, Woods D, Stern MT, Blair NIS, Airan RD, Bettegowda C, Rosch KS, Qin Q, van Zijl PCM, Pillai JJ, Hua J. Whole-Brain Functional and Diffusion Tensor MRI in Human Participants with Metallic Orthodontic Braces. Radiology 2020; 294:149-157. [PMID: 31714192 PMCID: PMC6939835 DOI: 10.1148/radiol.2019190070] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 09/12/2019] [Accepted: 09/26/2019] [Indexed: 11/11/2022]
Abstract
Background MRI performed with echo-planar imaging (EPI) sequences is sensitive to susceptibility artifacts in the presence of metallic objects, which presents a substantial barrier for performing functional MRI and diffusion tensor imaging (DTI) in patients with metallic orthodontic material and other head implants. Purpose To evaluate the ability to reduce susceptibility artifacts in healthy human participants wearing metallic orthodontic braces for two alternative approaches: T2-prepared functional MRI and diffusion-prepared DTI with three-dimensional fast gradient-echo readout. Materials and Methods In this prospective study conducted from February to September 2018, T2-prepared functional MRI and diffusion-prepared DTI were performed in healthy human participants. Removable dental braces with bonding trays were used so that MRI could be performed with braces and without braces in the same participants. Results were evaluated in regions with strong (EPI dropout regions for functional MRI and the inferior fronto-occipital fasciculus for DTI) and minimal (motor cortex for functional MRI and the posterior limb of internal capsule for DTI) susceptibility artifacts. Signal-to-noise ratio (SNR), contrast-to-noise ratio for functional MRI, apparent diffusion coefficient and fractional anisotropy for DTI, and degree of distortion (quantified with the Jaccard index, which measures the similarity of geometric shapes) were compared in regions with strong or minimal susceptibility effects between the current standard EPI sequences and the proposed alternatives by using paired t test. Results Six participants were evaluated (mean age ± standard deviation, 40 years ± 6; three women). In brain regions with strong susceptibility effects from the metallic braces, T2-prepared functional MRI showed significantly higher SNR (37.8 ± 2.4 vs 15.5 ± 5.3; P < .001) and contrast-to-noise ratio (0.83 ± 0.16 vs 0.29 ± 0.10; P < .001), whereas diffusion-prepared DTI showed higher SNR (5.8 ± 1.5 vs 3.8 ± 0.7; P = .03) than did conventional EPI methods. Apparent diffusion coefficient and fractional anisotropy were consistent with the literature. Geometric distortion was substantially reduced throughout the brain with the proposed methods (significantly higher Jaccard index, 0.95 ± 0.12 vs 0.81 ± 0.61; P < .001). Conclusion T2-prepared functional MRI and diffusion-prepared diffusion tensor imaging can acquire functional and diffusion MRI, respectively, in healthy human participants wearing metallic dental braces with less susceptibility artifacts and geometric distortion than with conventional echo-planar imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Dietrich in this issue.
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Affiliation(s)
| | | | - Dapeng Liu
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Hangyi Jiang
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - David Woods
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Moshe T. Stern
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Nicholas I. S. Blair
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Raag D. Airan
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Chetan Bettegowda
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Keri S. Rosch
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Qin Qin
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Peter C. M. van Zijl
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Jay J. Pillai
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
| | - Jun Hua
- From the Neurosection, Division of MRI Research, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, 707 N Broadway, Baltimore, Md 21205 (X.M., Y.W., D.L., H.J.,
Q.Q., P.C.M.v.Z., J.H.); F.M. Kirby Research Center for Functional Brain
Imaging, Kennedy Krieger Institute, Baltimore, Md (X.M., Y.W., D.L., Q.Q.,
P.C.M.v.Z., J.H.); Department of Medical Imaging, Nanfang Hospital, Southern
Medical University, Guangzhou, P.R. China (Y.W.); Department of Orthodontics and
Pediatric Dentistry, University of Maryland School of Dentistry, Baltimore, Md
(D.W., M.T.S.); Department of Biomedical Engineering, Johns Hopkins University,
Baltimore, Md (N.I.S.B.); Division of Neuroradiology, Russell H. Morgan
Department of Radiology and Radiological Science, Johns Hopkins University
School of Medicine, Baltimore, Md (R.D.A., J.J.P.); Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, Md (C.B., J.J.P.);
Center for Neurodevelopmental and Imaging Research and Department of
Neuropsychology, Kennedy Krieger Institute, Baltimore, Md (K.S.R.); and
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University
School of Medicine, Baltimore, Md (K.S.R.)
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Dewey BE, Zhao C, Reinhold JC, Carass A, Fitzgerald KC, Sotirchos ES, Saidha S, Oh J, Pham DL, Calabresi PA, van Zijl PCM, Prince JL. DeepHarmony: A deep learning approach to contrast harmonization across scanner changes. Magn Reson Imaging 2019; 64:160-170. [PMID: 31301354 PMCID: PMC6874910 DOI: 10.1016/j.mri.2019.05.041] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 05/30/2019] [Accepted: 05/30/2019] [Indexed: 11/16/2022]
Abstract
Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibility between protocols and scanners. It has been shown that even when care is taken to standardize acquisitions, any changes in hardware, software, or protocol design can lead to differences in quantitative results. This greatly impacts the quantitative utility of MRI in multi-site or long-term studies, where consistency is often valued over image quality. We propose a method of contrast harmonization, called DeepHarmony, which uses a U-Net-based deep learning architecture to produce images with consistent contrast. To provide training data, a small overlap cohort (n = 8) was scanned using two different protocols. Images harmonized with DeepHarmony showed significant improvement in consistency of volume quantification between scanning protocols. A longitudinal MRI dataset of patients with multiple sclerosis was also used to evaluate the effect of a protocol change on atrophy calculations in a clinical research setting. The results show that atrophy calculations were substantially and significantly affected by protocol change, whereas such changes have a less significant effect and substantially reduced overall difference when using DeepHarmony. This establishes that DeepHarmony can be used with an overlap cohort to reduce inconsistencies in segmentation caused by changes in scanner protocol, allowing for modernization of hardware and protocol design in long-term studies without invalidating previously acquired data.
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Affiliation(s)
- Blake E Dewey
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA; Kirby Center for Functional Brain Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Can Zhao
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Jacob C Reinhold
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA
| | - Aaron Carass
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, MD, USA
| | - Kathryn C Fitzgerald
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elias S Sotirchos
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shiv Saidha
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiwon Oh
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dzung L Pham
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA; Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Peter A Calabresi
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- Kirby Center for Functional Brain Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, MD, USA; Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Chen Z, Li Y, Airan R, Han Z, Xu J, Chan KWY, Xu Y, Bulte JWM, van Zijl PCM, McMahon MT, Zhou S, Liu G. CT and CEST MRI bimodal imaging of the intratumoral distribution of iodinated liposomes. Quant Imaging Med Surg 2019; 9:1579-1591. [PMID: 31667143 DOI: 10.21037/qims.2019.06.10] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background To develop liposomes loaded with iodinated agents as nanosized CT/MRI bimodal contrast agents for monitoring liposome-mediated drug delivery. Methods Rhodamine-labeled iodixanol (VisipaqueTM)-loaded liposomes (IX-lipo) were prepared and tested for their properties as a diamagnetic CEST contrast agent in vitro. Mice bearing subcutaneous CT26 colon tumors were injected i.v. with 1 g/kg (535 mg iodine/kg) IX-lipo, and in vivo CT and CEST MR images were acquired on day 3. CT and CEST MR images were also acquired for tumor-bearing mice co-injected with IX-lipo and tumor necrosis factor (TNF-α). Results In addition to CT contrast, IX-lipo exhibited a strong CEST contrast similar to its non-liposomal form, with a detectability of ~2 nM per liposome. Both CT imaging and CEST MRI showed that i.v. injection of IX-lipo resulted in a rim enhancement of CT26 tumors with a heterogeneous central distribution. In contrast, co-injection of TNF-α caused a significantly augmented CT/MRI contrast in the tumor center. The intratumoral biodistribution of IX-lipo correlated well to the rhodamine patterns observed with fluorescence microscopy. Conclusions We have developed a CT/MRI bimodal imaging approach for monitoring the delivery and biodistribution of liposomes by loading them with the clinically approved X-ray/CT contrast agent iodixanol. Our approach may be easily adapted for other-FDA approved iodinated agents and thus has great translational potential.
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Affiliation(s)
- Zelong Chen
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yuguo Li
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Raag Airan
- Department of Radiology, Stanford University Medical Center, Stanford, CA, USA
| | - Zheng Han
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.,Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Yikai Xu
- Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jeff W M Bulte
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.,Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Michael T McMahon
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Shibin Zhou
- Ludwig Center, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Chen L, Wei Z, Cai S, Li Y, Liu G, Lu H, Weiss RG, van Zijl PCM, Xu J. High-resolution creatine mapping of mouse brain at 11.7 T using non-steady-state chemical exchange saturation transfer. NMR Biomed 2019; 32:e4168. [PMID: 31461196 DOI: 10.1002/nbm.4168] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 07/27/2019] [Accepted: 07/31/2019] [Indexed: 06/10/2023]
Abstract
The current study aims to optimize the acquisition scheme for the creatine chemical exchange saturation transfer weighted (CrCESTw) signal on mouse brain at 11.7 T, in which a strong magnetization transfer contrast (MTC) is present, and to further develop the polynomial and Lorentzian line-shape fitting (PLOF) method for quantifying CrCESTw signal with a non-steady-state (NSS) acquisition scheme. Studies on a Cr phantom with cross-linked bovine serum albumin (BSA) as well as on mouse brain demonstrated that the maximum CrCESTw signal was reached with a short saturation time determined by the rotating frame relaxation time of the MTC pool instead of the steady-state saturation. The saturation power for the maximal signal was around 1-1.5 μT for Cr with 20% cross-linked BSA and in vivo applications, but 2 μT was found to be most practical for signal stability. For the CrCEST acquisition with strong MTC interference, the optimal saturation power and length are completely different from those on Cr solution alone. This observation could be explained well using R1ρ theory by incorporating the strong MTC pool. Finally, a high-resolution Cr map was obtained on mouse brain using the PLOF method with the NSS CEST acquisition and a cryogenic coil. The Cr map obtained by CEST showed homogenous intensity across the mouse brain except for regions with cerebrospinal fluid.
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Affiliation(s)
- Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Yuguo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Robert G Weiss
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
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Thomas AM, Xu J, Calabresi PA, van Zijl PCM, Bulte JWM. Monitoring diffuse injury during disease progression in experimental autoimmune encephalomyelitis with on resonance variable delay multiple pulse (onVDMP) CEST MRI. Neuroimage 2019; 204:116245. [PMID: 31605825 DOI: 10.1016/j.neuroimage.2019.116245] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 09/16/2019] [Accepted: 10/03/2019] [Indexed: 12/24/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune disorder that targets myelin proteins and results in extensive damage in the central nervous system in the form of focal lesions as well as diffuse molecular changes. Lesions are currently detected using T1-weighted, T2-weighted, and gadolinium-enhanced magnetic resonance imaging (MRI); however, monitoring such lesions has been shown to be a poor predictor of disease progression. Chemical exchange saturation transfer (CEST) MRI is sensitive to many of the biomolecules in the central nervous system altered in MS that cannot be detected using conventional MRI. We monitored disease progression in an experimental autoimmune encephalomyelitis (EAE) model of MS using on resonance variable delay multiple pulse (onVDMP) CEST MRI. Alterations in onVDMP signal were observed in regions responsible for hindlimb function throughout the central nervous system. Histological analysis revealed glial activation in areas highlighted in onVDMP CEST MRI. onVDMP signal changes in the 3rd ventricle preceded paralysis onset that could not be observed with conventional MRI techniques. Hence, the onVDMP CEST MRI signal has potential as a novel imaging biomarker and predictor of disease progression in MS.
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Affiliation(s)
- Aline M Thomas
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter A Calabresi
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jeff W M Bulte
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Chemical & Biomolecular Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Li W, Xu X, Liu P, Strouse JJ, Casella JF, Lu H, van Zijl PCM, Qin Q. Quantification of whole-brain oxygenation extraction fraction and cerebral metabolic rate of oxygen consumption in adults with sickle cell anemia using individual T 2 -based oxygenation calibrations. Magn Reson Med 2019; 83:1066-1080. [PMID: 31483528 DOI: 10.1002/mrm.27972] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/18/2019] [Accepted: 08/05/2019] [Indexed: 12/23/2022]
Abstract
PURPOSE To evaluate different T2 -oxygenation calibrations for estimating venous oxygenation in people with sickle cell anemia (SCA). METHODS Blood T2 values were measured at 3 T in the internal jugular veins of 12 healthy volunteers and 11 SCA participants with no history of stroke, recent transfusion, or renal impairment. T2 -oxygenation relationships of both sickled and normal blood samples were calibrated individually and compared with values generated from published models. After converting venous T2 values to venous oxygenation, whole-brain oxygen extraction fraction and cerebral metabolic rate of oxygen were calculated. RESULTS Sickle blood samples' oxygenation values calculated from our individual calibrations agreed well with measurements using a blood analyzer, whereas previous T2 calibrations based on normal blood samples showed 13%-19% underestimation. Meanwhile, oxygenation values calculated from previous grouped T2 calibration for sickle blood agreed well with experimental measurement on averaged values, but showed up to 20% variation for several individual samples. Using individual T2 calibrations, the whole-brain oxygen extraction fraction and cerebral metabolic rate of oxygen of SCA participants were 0.38 ± 0.08 and 172 ± 42 µmol/min/100 g, respectively, which were comparable to those values measured on healthy volunteers. CONCLUSION Our results confirm that sickle blood T2 values not only depend on the hematocrit and oxygenation values, but also on other hematological factors. The individual T2 calibrations minimized the effect of heterogeneity of sickle blood between different SCA populations and improved the accuracy of T2 -based oximetry. The measured oxygen extraction fraction and cerebral metabolic rate of oxygen of this group of SCA participants were found to not differ significantly from those of healthy individuals.
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Affiliation(s)
- Wenbo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Peiying Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - John J Strouse
- Department of Pediatrics, Division of Pediatric Hematology, Johns Hopkins University School of Medicine, Baltimore, Maryland.,Division of Hematology, Duke University, Durham, North Carolina
| | - James F Casella
- Department of Pediatrics, Division of Pediatric Hematology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Qin Qin
- Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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Kronenbuerger M, Hua J, Bang JYA, Ultz KE, Miao X, Zhang X, Pekar JJ, van Zijl PCM, Duan W, Margolis RL, Ross CA. Differential Changes in Functional Connectivity of Striatum-Prefrontal and Striatum-Motor Circuits in Premanifest Huntington's Disease. NEURODEGENER DIS 2019; 19:78-87. [PMID: 31412344 DOI: 10.1159/000501616] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 06/19/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Huntington's disease (HD) is a progressive neurodegenerative disorder. The striatum is one of the first brain regions that show detectable atrophy in HD. Previous studies using functional magnetic resonance imaging (fMRI) at 3 tesla (3 T) revealed reduced functional connectivity between striatum and motor cortex in the prodromal period of HD. Neuroanatomical and neurophysiological studies have suggested segregated corticostriatal pathways with distinct loops involving different cortical regions, which may be investigated using fMRI at an ultra-high field (7 T) with enhanced sensitivity compared to lower fields. OBJECTIVES We performed fMRI at 7 T to assess functional connectivity between the striatum and several chosen cortical areas including the motor and prefrontal cortex, in order to better understand brain changes in the striatum-cortical pathways. METHOD 13 manifest subjects (age 51 ± 13 years, cytosine-adenine-guanine [CAG] repeat 45 ± 5, Unified Huntington's Disease Rating Scale [UHDRS] motor score 32 ± 17), 8 subjects in the close-to-onset premanifest period (age 38 ± 10 years, CAG repeat 44 ± 2, UHDRS motor score 8 ± 2), 11 subjects in the far-from-onset premanifest period (age 38 ± 11 years, CAG repeat 42 ± 2, UHDRS motor score 1 ± 2), and 16 healthy controls (age 44 ± 15 years) were studied. The functional connectivity between the striatum and several cortical areas was measured by resting state fMRI at 7 T and analyzed in all participants. RESULTS Compared to controls, functional connectivity between striatum and premotor area, supplementary motor area, inferior frontal as well as middle frontal regions was altered in HD (all p values <0.001). Specifically, decreased striatum-motor connectivity but increased striatum-prefrontal connectivity were found in premanifest HD subjects. Altered functional connectivity correlated consistently with genetic burden, but not with clinical scores. CONCLUSIONS Differential changes in functional connectivity of striatum-prefrontal and striatum-motor circuits can be found in early and premanifest HD. This may imply a compensatory mechanism, where additional cortical regions are recruited to subserve functions that have been impaired due to HD pathology. Our results suggest the potential value of functional connectivity as a marker for future clinical trials in HD.
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Affiliation(s)
- Martin Kronenbuerger
- Division of Movement Disorders, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA, .,Department of Neurology, University Medicine Greifswald, Greifswald, Germany,
| | - Jun Hua
- 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
| | - Jee Y A Bang
- Division of Movement Disorders, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kia E Ultz
- Division of Movement Disorders, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xinyuan Miao
- 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
| | - Xiaoyu Zhang
- 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
| | - James J Pekar
- 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
| | - Peter C M van Zijl
- 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
| | - Wenzhen Duan
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Neuroscience and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Russell L Margolis
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Neuroscience and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Christopher A Ross
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Neuroscience and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Bao L, Ye F, Cai C, Wu J, Zeng K, van Zijl PCM, Chen Z. Undersampled MR image reconstruction using an enhanced recursive residual network. J Magn Reson 2019; 305:232-246. [PMID: 31323504 DOI: 10.1016/j.jmr.2019.07.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 06/24/2019] [Accepted: 07/08/2019] [Indexed: 06/10/2023]
Abstract
When using aggressive undersampling, it is difficult to recover the high quality image with reliably fine features. In this paper, we propose an enhanced recursive residual network (ERRN) that improves the basic recursive residual network with a high-frequency feature guidance, an error-correction unit and dense connections. The feature guidance is designed to predict the underlying anatomy based on image a priori learned from the label data, playing a complementary role to the residual learning. The ERRN is adapted for two important applications: compressed sensing (CS) MRI and super resolution (SR) MRI, while an application-specific error-correction unit is added into the framework, i.e. data consistency for CS-MRI and back projection for SR-MRI due to their different sampling schemes. Our proposed network was evaluated using a real-valued brain dataset, a complex-valued knee dataset, pathological brain data and in vivo rat brain data with different undersampling masks and rates. Experimental results demonstrated that ERRN presented superior reconstructions at all cases with distinctly restored structural features and highest image quality metrics compared to both the state-of-the-art convolutional neural networks and the conventional optimization-based methods, particularly for the undersampling rate over 5-fold. Thus, an excellent framework design can endow the network with a flexible architecture, fewer parameters, outstanding performances for various undersampling schemes, and reduced overfitting in generalization, which will facilitate real-time reconstruction on MRI scanners.
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Affiliation(s)
- Lijun Bao
- Department of Electronic Science, Xiamen University, Xiamen 361000, China.
| | - Fuze Ye
- Department of Electronic Science, Xiamen University, Xiamen 361000, China
| | - Congbo Cai
- Department of Electronic Science, Xiamen University, Xiamen 361000, China
| | - Jian Wu
- Department of Electronic Science, Xiamen University, Xiamen 361000, China
| | - Kun Zeng
- Department of Electronic Science, Xiamen University, Xiamen 361000, China
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Zhong Chen
- Department of Electronic Science, Xiamen University, Xiamen 361000, China
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Zhang J, Yuan Y, Gao M, Han Z, Chu C, Li Y, van Zijl PCM, Ying M, Bulte JWM, Liu G. Carbon Dots as a New Class of Diamagnetic Chemical Exchange Saturation Transfer (diaCEST) MRI Contrast Agents. Angew Chem Int Ed Engl 2019; 58:9871-9875. [PMID: 31162873 PMCID: PMC6897491 DOI: 10.1002/anie.201904722] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Indexed: 12/22/2022]
Abstract
While carbon dots (C-dots) have been extensively investigated pertaining to their fluorescent, phosphorescent, electrochemiluminescent, optoelectronic, and catalytic features, their inherent chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) properties are unknown. By virtue of their hydrophilicity and abundant exchangeable protons of hydroxyl, amine, and amide anchored on the surface, we report here that C-dots can be adapted as effective diamagnetic CEST (diaCEST) MRI contrast agents. As a proof-of-concept demonstration, human glioma cells were labeled with liposomes with or without encapsulated C-dots and implanted in mouse brain. In vivo CEST MRI was able to clearly differentiate labeled cells from non-labeled cells. The present findings may encourage new applications of C-dots for in vivo imaging in deep tissues, which is currently not possible using conventional fluorescent (near-infrared) C-dots.
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Affiliation(s)
- Jia Zhang
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Yue Yuan
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Minling Gao
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Zheng Han
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Chengyan Chu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Yuguo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Peter C. M. van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- F.M Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD (USA)
| | - Mingyao Ying
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Jeff W. M. Bulte
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- F.M Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD (USA)
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
| | - Guanshu Liu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD (USA)
- F.M Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD (USA)
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44
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Heo HY, Xu X, Jiang S, Zhao Y, Keupp J, Redmond KJ, Laterra J, van Zijl PCM, Zhou J. Prospective acceleration of parallel RF transmission-based 3D chemical exchange saturation transfer imaging with compressed sensing. Magn Reson Med 2019; 82:1812-1821. [PMID: 31209938 DOI: 10.1002/mrm.27875] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 05/07/2019] [Accepted: 05/30/2019] [Indexed: 12/26/2022]
Abstract
PURPOSE To develop prospectively accelerated 3D CEST imaging using compressed sensing (CS), combined with a saturation scheme based on time-interleaved parallel transmission. METHODS A variable density pseudo-random sampling pattern with a centric elliptical k-space ordering was used for CS acceleration in 3D. Retrospective CS studies were performed with CEST phantoms to test the reconstruction scheme. Prospectively CS-accelerated 3D-CEST images were acquired in 10 healthy volunteers and 6 brain tumor patients with an acceleration factor (RCS ) of 4 and compared with conventional SENSE reconstructed images. Amide proton transfer weighted (APTw) signals under varied RF saturation powers were compared with varied acceleration factors. RESULTS The APTw signals obtained from the CS with acceleration factor of 4 were well-preserved as compared with the reference image (SENSE R = 2) both in retrospective phantom and prospective healthy volunteer studies. In the patient study, the APTw signals were significantly higher in the tumor region (gadolinium [Gd]-enhancing tumor core) than in the normal tissue (p < .001). There was no significant APTw difference between the CS-accelerated images and the reference image. The scan time of CS-accelerated 3D APTw imaging was dramatically reduced to 2:10 minutes (in-plane spatial resolution of 1.8 × 1.8 mm2 ; 15 slices with 4-mm slice thickness) as compared with SENSE (4:07 minutes). CONCLUSION Compressed sensing acceleration was successfully extended to 3D-CEST imaging without compromising CEST image quality and quantification. The CS-based CEST imaging can easily be integrated into clinical protocols and would be beneficial for a wide range of applications.
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Affiliation(s)
- Hye-Young Heo
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Xiang Xu
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Shanshan Jiang
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | | | | | - Kristin J Redmond
- Department of Radiation Oncology and Molecular Radiation Science, Johns Hopkins University, Baltimore, Maryland
| | - John Laterra
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland.,Department of Neurology, Johns Hopkins University, Baltimore, Maryland
| | - Peter C M van Zijl
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Jinyuan Zhou
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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45
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Chen H, Liu D, Li Y, Xu X, Xu J, Yadav NN, Zhou S, van Zijl PCM, Liu G. CEST MRI monitoring of tumor response to vascular disrupting therapy using high molecular weight dextrans. Magn Reson Med 2019; 82:1471-1479. [PMID: 31106918 DOI: 10.1002/mrm.27818] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 04/25/2019] [Accepted: 04/29/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE Vascular disrupting therapy of cancer has become a promising approach not only to regress tumor growth directly but also to boost the delivery of chemotherapeutics in the tumor. An imaging approach to monitor the changes in tumor vascular permeability, therefore, has important applications for monitoring of vascular disrupting therapies. METHODS Mice bearing CT26 subcutaneous colon tumors were injected intravenously with 150 kD dextran (Dex150, diameter, d~ 20 nm, 375 mg/kg), tumor necrosis factor-alpha (TNF-α; 1 µg per mouse), or both (n = 3 in each group). The Z-spectra were acquired before and 2 h after the injection, and the chemical exchange saturation transfer (CEST) signals in the tumors as quantified by asymmetric magnetization transfer ratio (MTRasym ) at 1 ppm were compared. RESULTS The results showed a significantly stronger CEST contrast enhancement at 1 ppm (∆MTRasym = 0.042 ± 0.002) in the TNF-α-treated tumors than those by Dex150 alone (∆MTRasym = 0.000 ± 0.005, P = 0.0229) or TNF-α alone (∆MTRasym = 0.002 ± 0.004, P = 0.0264), indicating that the TNF-α treatment strongly augmented the tumor uptake of 150 kD dextran. The MRI findings were verified by fluorescence imaging and immunofluorescence microscopy. CONCLUSIONS High molecular weight dextrans can be used as safe and sensitive CEST MRI contrast agents for monitoring tumor response to vascular disrupting therapy and, potentially, for developing dextran-based theranostic drug delivery systems.
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Affiliation(s)
- Hanwei Chen
- Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Dexiang Liu
- Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Yuguo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Nirbhay N Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Shibin Zhou
- Ludwig Center, Howard Hughes Medical Institute and Sidney Kimmel Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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46
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Han Z, Zhang S, Fujiwara K, Zhang J, Li Y, Liu J, van Zijl PCM, Lu ZR, Zheng L, Liu G. Extradomain-B Fibronectin-Targeted Dextran-Based Chemical Exchange Saturation Transfer Magnetic Resonance Imaging Probe for Detecting Pancreatic Cancer. Bioconjug Chem 2019; 30:1425-1433. [PMID: 30938983 PMCID: PMC6896991 DOI: 10.1021/acs.bioconjchem.9b00161] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
A dextran-peptide conjugate was developed for magnetic resonance (MR) molecular imaging of pancreatic ductal adenocarcinoma (PDAC) through its overexpressed microenvironment biomarker, extradomain-B fibronectin (EDB-FN). This new agent consists of diamagnetic and biocompatible dextran and a targeting peptide. Dextrans can be directly detected by chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) without the need for radionuclide or metallic labeling. In addition, large molecular weight dextran, dextran 10 (MW ∼ 10 kDa), provides an approximately 50 times higher sensitivity per molecule than a single glucose unit. The potential of this highly biocompatible diamagnetic probe is demonstrated in a murine syngeneic allograft PDAC tumor model. The biocompatibility and sensitivity of this new agent clearly show potential for a path to clinical translation.
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Affiliation(s)
- Zheng Han
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
| | - Shuixing Zhang
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guandong 510630, China
| | - Kenji Fujiwara
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Jia Zhang
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
| | - Yuguo Li
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
| | - Jing Liu
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- Radiology Department, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou 550004, China
| | - Peter C. M. van Zijl
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
| | - Zheng-Rong Lu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Lei Zheng
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland 21231, United States
| | - Guanshu Liu
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland 21205, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205, United States
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47
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Hua J, Blair NIS, Paez A, Choe A, Barber AD, Brandt A, Lim IAL, Xu F, Kamath V, Pekar JJ, van Zijl PCM, Ross CA, Margolis RL. Altered functional connectivity between sub-regions in the thalamus and cortex in schizophrenia patients measured by resting state BOLD fMRI at 7T. Schizophr Res 2019; 206:370-377. [PMID: 30409697 PMCID: PMC6500777 DOI: 10.1016/j.schres.2018.10.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 10/11/2018] [Accepted: 10/20/2018] [Indexed: 12/21/2022]
Abstract
The thalamus is a small brain structure that relays neuronal signals between subcortical and cortical regions. Abnormal thalamocortical connectivity in schizophrenia has been reported in previous studies using blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI) performed at 3T. However, anatomically the thalamus is not a single entity, but is subdivided into multiple distinct nuclei with different connections to various cortical regions. We sought to determine the potential benefit of using the enhanced sensitivity of BOLD fMRI at ultra-high magnetic field (7T) in exploring thalamo-cortical connectivity in schizophrenia based on subregions in the thalamus. Seeds placed in thalamic subregions of 14 patients and 14 matched controls were used to calculate whole-brain functional connectivity. Our results demonstrate impaired thalamic connectivity to the prefrontal cortex and the cerebellum, but enhanced thalamic connectivity to the motor/sensory cortex in schizophrenia. This altered functional connectivity significantly correlated with disease duration in the patients. Remarkably, comparable effect sizes observed in previous 3T studies were detected in the current 7T study with a heterogeneous and much smaller cohort, providing evidence that ultra-high field fMRI may be a powerful tool for measuring functional connectivity abnormalities in schizophrenia. Further investigation with a larger cohort is merited to validate the current findings.
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Affiliation(s)
- Jun Hua
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Nicholas I S Blair
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Adrian Paez
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Ann Choe
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Anita D Barber
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York, USA; Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA
| | - Allison Brandt
- Department of Psychiatry and Behavioral Sciences and Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Issel Anne L Lim
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Feng Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Vidyulata Kamath
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James J Pekar
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter C M van Zijl
- The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Christopher A Ross
- Department of Psychiatry and Behavioral Sciences and Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neuroscience and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Russell L Margolis
- Department of Psychiatry and Behavioral Sciences and Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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48
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Chen L, Wei Z, Chan K, Cai S, Liu G, Lu H, Wong PC, van Zijl PCM, Li T, Xu J. Protein aggregation linked to Alzheimer's disease revealed by saturation transfer MRI. Neuroimage 2019; 188:380-390. [PMID: 30553917 PMCID: PMC6401270 DOI: 10.1016/j.neuroimage.2018.12.018] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 12/08/2018] [Accepted: 12/10/2018] [Indexed: 12/12/2022] Open
Abstract
The goal of this study was to develop a molecular biomarker for the detection of protein aggregation involved in Alzheimer's disease (AD) by exploiting the features of the water saturation transfer spectrum (Z-spectrum), the CEST signal of which is sensitive to the molecular configuration of proteins. A radial-sampling steady-state sequence based ultrashort echo time (UTE) readout was implemented to image the Z-spectrum in the mouse brain, especially the contributions from mobile proteins at the frequency offsets for the composite protein amide proton (+3.6 ppm) and aliphatic proton (-3.6 ppm) signals. Using a relatively weak radiofrequency (RF) saturation amplitude, contributions due to strong magnetization transfer contrast (MTC) from solid-like macromolecules and direct water saturation (DS) were minimized. For practical measure of the changes in the mobile protein configuration, we defined a saturation transfer difference (ΔST) by subtracting the Z-spectral signals at ±3.6 ppm from a control signal at 8 ppm. Phantom studies of glutamate solution, protein (egg white) and hair conditioner show the capability of the proposed scheme to minimize the contributions from amine protons, DS, and MTC, respectively. The ST signal at ±3.6 ppm of the cross-linked bovine serum albumin (BSA) solutions demonstrated that the ΔST signal can be used to monitor the aggregation process of the mobile proteins. High-resolution ΔST images of AD mouse brains at ±3.6 ppm of mouse brains showed significantly reduced ΔST (-3.6) signal compared to the age-matched wild-type (WT) mice. Thus, this signal has potential to serve as a molecular biomarker for monitoring protein aggregation in AD.
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Affiliation(s)
- Lin Chen
- 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
| | - Zhiliang Wei
- 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
| | - Kannie Chan
- 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
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Guanshu Liu
- 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
| | - Hanzhang Lu
- 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
| | - Philip C. Wong
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, The 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, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tong Li
- Department of Pathology, The 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, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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49
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Xu X, Xu J, Knutsson L, Liu J, Liu H, Li Y, Lal B, Laterra J, Artemov D, Liu G, van Zijl PCM, Chan KWY. The effect of the mTOR inhibitor rapamycin on glucoCEST signal in a preclinical model of glioblastoma. Magn Reson Med 2019; 81:3798-3807. [PMID: 30793789 DOI: 10.1002/mrm.27683] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 01/02/2019] [Accepted: 01/14/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE The mammalian target of rapamycin is an enzyme that regulates cell metabolism and proliferation. It is up-regulated in aggressive tumors, such as glioblastoma, leading to increased glucose uptake and consumption. It has been suggested that glucose CEST signals reflect the delivery and tumor uptake of glucose. The inhibitor rapamycin (sirolimus) has been applied as a glucose deprivation treatment; thus, glucose CEST MRI could potentially be useful for monitoring the tumor responses to inhibitor treatment. METHODS A human U87-EGFRvIII xenograft model in mice was studied. The mice were treated with a mammalian target of Rapamycin inhibitor, rapamycin. The effect of the treatment was evaluated in vivo with dynamic glucose CEST MRI. RESULTS Rapamycin treatment led to significant increases (P < 0.001) in dynamic glucose-enhanced signal in both the tumor and contralateral brain as compared to the no-treatment group, namely a maximum enhancement of 3.7% ± 2.3% (tumor, treatment) versus 1.9% ± 0.4% (tumor, no-treatment), 1.7% ± 1.1% (contralateral, treatment), and 1.0% ± 0.4% (contralateral, no treatment). Dynamic glucose-enhanced contrast remained consistently higher in treatment versus no-treatment groups for the duration of the experiment (17 min). This was confirmed with area-under-curve analysis. CONCLUSION Increased glucose CEST signal was found after mammalian target of Rapamycin inhibition treatment, indicating potential for dynamic glucose-enhanced MRI to study tumor response to glucose deprivation treatment.
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Affiliation(s)
- Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,FM Kirby Research Center, Kennedy Krieger Institute, Johns Hopkins Medicine, Baltimore, Maryland
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,FM Kirby Research Center, Kennedy Krieger Institute, Johns Hopkins Medicine, Baltimore, Maryland
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,Department of Medical Radiation Physics, Lund University, Lund, Sweden
| | - Jing Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, People's Republic of China
| | - Huanling Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,Department of Ultrasound, Guangzhou Panyu Central Hospital, Panyu, People's Republic of China
| | - Yuguo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,FM Kirby Research Center, Kennedy Krieger Institute, Johns Hopkins Medicine, Baltimore, Maryland
| | - Bachchu Lal
- Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland
| | - John Laterra
- Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland.,Department of Oncology and Neuroscience, Johns Hopkins Medicine, Baltimore, Maryland
| | - Dmitri Artemov
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,JHU In Vivo Cellular Molecular Imaging Center, Johns Hopkins University Medicine, Baltimore, Maryland
| | - Guanshu Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,FM Kirby Research Center, Kennedy Krieger Institute, Johns Hopkins Medicine, Baltimore, Maryland
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,FM Kirby Research Center, Kennedy Krieger Institute, Johns Hopkins Medicine, Baltimore, Maryland
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, Maryland.,Department of Biomedical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong
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50
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Li X, Chen L, Kutten K, Ceritoglu C, Li Y, Kang N, Hsu JT, Qiao Y, Wei H, Liu C, Miller MI, Mori S, Yousem DM, van Zijl PCM, Faria AV. Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility. Neuroimage 2019; 191:337-349. [PMID: 30738207 DOI: 10.1016/j.neuroimage.2019.02.016] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 02/03/2019] [Accepted: 02/06/2019] [Indexed: 01/09/2023] Open
Abstract
Quantification of tissue magnetic susceptibility using MRI offers a non-invasive measure of important tissue components in the brain, such as iron and myelin, potentially providing valuable information about normal and pathological conditions during aging. Despite many advances made in recent years on imaging techniques of quantitative susceptibility mapping (QSM), accurate and robust automated segmentation tools for QSM images that can help generate universal and sharable susceptibility measures in a biologically meaningful set of structures are still not widely available. In the present study, we developed an automated process to segment brain nuclei and quantify tissue susceptibility in these regions based on a susceptibility multi-atlas library, consisting of 10 atlases with T1-weighted images, gradient echo (GRE) magnitude images and QSM images of brains with different anatomic patterns. For each atlas in this library, 10 regions of interest in iron-rich deep gray matter structures that are better defined by QSM contrast were manually labeled, including caudate, putamen, globus pallidus internal/external, thalamus, pulvinar, subthalamic nucleus, substantia nigra, red nucleus and dentate nucleus in both left and right hemispheres. We then tested different pipelines using different combinations of contrast channels to bring the set of labels from the multi-atlases to each target brain and compared them with the gold standard manual delineation. The results showed that the segmentation accuracy using dual contrasts QSM/T1 pipeline outperformed other dual-contrast or single-contrast pipelines. The dice values of 0.77 ± 0.09 using the QSM/T1 multi-atlas pipeline rivaled with the segmentation reliability obtained from multiple evaluators with dice values of 0.79 ± 0.07 and gave comparable or superior performance in segmenting subcortical nuclei in comparison with standard FSL FIRST or recent multi-atlas package of volBrain. The segmentation performance of the QSM/T1 multi-atlas was further tested on QSM images acquired using different acquisition protocols and platforms and showed good reliability and reproducibility with average dice of 0.79 ± 0.08 to manual labels and 0.89 ± 0.04 in an inter-protocol manner. The extracted quantitative magnetic susceptibility values in the deep gray matter nuclei also correlated well between different protocols with inter-protocol correlation constants all larger than 0.97. Such reliability and performance was ultimately validated in an external dataset acquired at another study site with consistent susceptibility measures obtained using the QSM/T1 multi-atlas approach in comparison to those using manual delineation. In summary, we designed a susceptibility multi-atlas tool for automated and reliable segmentation of QSM images and for quantification of magnetic susceptibilities. It is publicly available through our cloud-based platform (www.mricloud.org). Further improvement on the performance of this multi-atlas tool is expected by increasing the number of atlases in the future.
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Affiliation(s)
- Xu Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Lin Chen
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Kwame Kutten
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA
| | - Can Ceritoglu
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yue Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ningdong Kang
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - John T Hsu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ye Qiao
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Michael I Miller
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David M Yousem
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Andreia V Faria
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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