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Gkotsoulias DG, Jäger C, Müller R, Gräßle T, Olofsson KM, Møller T, Unwin S, Crockford C, Wittig RM, Bilgic B, Möller HE. Chaos and COSMOS-Considerations on QSM methods with multiple and single orientations and effects from local anisotropy. Magn Reson Imaging 2024; 110:104-111. [PMID: 38631534 DOI: 10.1016/j.mri.2024.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/07/2024] [Accepted: 04/14/2024] [Indexed: 04/19/2024]
Abstract
PURPOSE Field-to-susceptibility inversion in quantitative susceptibility mapping (QSM) is ill-posed and needs numerical stabilization through either regularization or oversampling by acquiring data at three or more object orientations. Calculation Of Susceptibility through Multiple Orientations Sampling (COSMOS) is an established oversampling approach and regarded as QSM gold standard. It achieves a well-conditioned inverse problem, requiring rotations by 0°, 60° and 120° in the yz-plane. However, this is impractical in vivo, where head rotations are typically restricted to a range of ±25°. Non-ideal sampling degrades the conditioning with residual streaking artifacts whose mitigation needs further regularization. Moreover, susceptibility anisotropy in white matter is not considered in the COSMOS model, which may introduce additional bias. The current work presents a thorough investigation of these effects in primate brain. METHODS Gradient-recalled echo (GRE) data of an entire fixed chimpanzee brain were acquired at 7 T (350 μm resolution, 10 orientations) including ideal COSMOS sampling and realistic rotations in vivo. Comparisons of the results included ideal COSMOS, in-vivo feasible acquisitions with 3-8 orientations and single-orientation iLSQR QSM. RESULTS In-vivo feasible and optimal COSMOS yielded high-quality susceptibility maps with increased SNR resulting from averaging multiple acquisitions. COSMOS reconstructions from non-ideal rotations about a single axis required additional L2-regularization to mitigate residual streaking artifacts. CONCLUSION In view of unconsidered anisotropy effects, added complexity of the reconstruction, and the general challenge of multi-orientation acquisitions, advantages of sub-optimal COSMOS schemes over regularized single-orientation QSM appear limited in in-vivo settings.
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Affiliation(s)
- Dimitrios G Gkotsoulias
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roland Müller
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias Gräßle
- Epidemiology of Highly Pathogenic Microorganisms, Robert Koch-Institute, Berlin, Germany
| | | | | | - Steve Unwin
- Wildlife Health Australia, Canberra, Australia
| | - Catherine Crockford
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany; The Ape Social Mind Lab, Institut des Sciences Cognitives Marc Jeannerod, Bron, France; Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
| | - Roman M Wittig
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany; The Ape Social Mind Lab, Institut des Sciences Cognitives Marc Jeannerod, Bron, France; Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
| | - Harald E Möller
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Fushimi Y, Nakajima S, Sakata A, Okuchi S, Otani S, Nakamoto Y. Value of Quantitative Susceptibility Mapping in Clinical Neuroradiology. J Magn Reson Imaging 2024; 59:1914-1929. [PMID: 37681441 DOI: 10.1002/jmri.29010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a unique technique for providing quantitative information on tissue magnetic susceptibility using phase image data. QSM can provide valuable information regarding physiological and pathological processes such as iron deposition, hemorrhage, calcification, and myelin. QSM has been considered for use as an imaging biomarker to investigate physiological status and pathological changes. Although various studies have investigated the clinical applications of QSM, particularly regarding the use of QSM in clinical practice, have not been examined well. This review provides on an overview of the basics of QSM and its clinical applications in neuroradiology. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Cho J, Gagoski B, Kim TH, Wang F, Manhard MK, Dean D, Kecskemeti S, Caprihan A, Lo WC, Splitthoff DN, Liu W, Polak D, Cauley S, Setsompop K, Grant PE, Bilgic B. Time-efficient, high-resolution 3T whole-brain relaxometry using 3D-QALAS with wave-CAIPI readouts. Magn Reson Med 2024; 91:630-639. [PMID: 37705496 DOI: 10.1002/mrm.29865] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/16/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023]
Abstract
PURPOSE Volumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS), enabling full-brain quantitative T1 , T2 , and proton density (PD) maps at 1.15-mm3 isotropic voxels in 3 min. METHODS Wave-CAIPI readouts were embedded in the standard 3D-QALAS encoding scheme, enabling full-brain quantitative parameter maps (T1 , T2 , and PD) at acceleration factors of R = 3 × 2 with minimum SNR loss due to g-factor penalties. The quantitative parameter maps were estimated using a dictionary-based mapping algorithm incorporating inversion efficiency and B1 -field inhomogeneity effects. The parameter maps using the accelerated protocol were quantitatively compared with those obtained from the conventional 3D-QALAS sequence using GRAPPA acceleration of R = 2 in the ISMRM/NIST phantom, and in 10 healthy volunteers. RESULTS When tested in both the ISMRM/NIST phantom and 10 healthy volunteers, the quantitative maps using the accelerated protocol showed excellent agreement against those obtained from conventional 3D-QALAS at RGRAPPA = 2. CONCLUSION Three-dimensional QALAS enhanced with wave-CAIPI readouts enables time-efficient, full-brain quantitative T1 , T2 , and PD mapping at 1.15 mm3 in 3 min at R = 3 × 2 acceleration. The quantitative maps obtained from the accelerated wave-CAIPI 3D-QALAS protocol showed very similar values to those from the standard 3D-QALAS (R = 2) protocol, alluding to the robustness and reliability of the proposed method.
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Affiliation(s)
- Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Tae Hyung Kim
- Department of Computer Engineering, Hongik University, Seoul, South Korea
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mary Kate Manhard
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Douglas Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Steven Kecskemeti
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Wei-Ching Lo
- Siemens Medical Solutions USA, Inc., Charlestown, Massachusetts, USA
| | | | - Wei Liu
- Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Stephen Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Patricia Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard/MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
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Madden DJ, Merenstein JL. Quantitative susceptibility mapping of brain iron in healthy aging and cognition. Neuroimage 2023; 282:120401. [PMID: 37802405 PMCID: PMC10797559 DOI: 10.1016/j.neuroimage.2023.120401] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/14/2023] [Accepted: 09/30/2023] [Indexed: 10/10/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA
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Gkotsoulias DG, Müller R, Jäger C, Schlumm T, Mildner T, Eichner C, Pampel A, Jaffe J, Gräßle T, Alsleben N, Chen J, Crockford C, Wittig R, Liu C, Möller HE. High angular resolution susceptibility imaging and estimation of fiber orientation distribution functions in primate brain. Neuroimage 2023; 276:120202. [PMID: 37247762 DOI: 10.1016/j.neuroimage.2023.120202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 05/21/2023] [Accepted: 05/27/2023] [Indexed: 05/31/2023] Open
Abstract
Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution.
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Affiliation(s)
- Dimitrios G Gkotsoulias
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Roland Müller
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Torsten Schlumm
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Toralf Mildner
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Cornelius Eichner
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - André Pampel
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jennifer Jaffe
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany; Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Côte d'Ivoire
| | - Tobias Gräßle
- Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Côte d'Ivoire; Helmholtz Institute for One Health, Greifswald, Germany; Robert Koch Institute, Epidemiology of Highly Pathogenic Microorganisms, Berlin, Germany
| | - Niklas Alsleben
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jingjia Chen
- Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Catherine Crockford
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany; Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Côte d'Ivoire; Institute of Cognitive Sciences, CNRS UMR5229 University of Lyon, Bron, France
| | - Roman Wittig
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany; Taï Chimpanzee Project, Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Côte d'Ivoire; Institute of Cognitive Sciences, CNRS UMR5229 University of Lyon, Bron, France
| | - Chunlei Liu
- Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Harald E Möller
- Nuclear Magnetic Resonance Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Fang Z, Lai KW, van Zijl P, Li X, Sulam J. DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging. Med Image Anal 2023; 87:102829. [PMID: 37146440 PMCID: PMC10288385 DOI: 10.1016/j.media.2023.102829] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 03/11/2023] [Accepted: 04/18/2023] [Indexed: 05/07/2023]
Abstract
Susceptibility tensor imaging (STI) is an emerging magnetic resonance imaging technique that characterizes the anisotropic tissue magnetic susceptibility with a second-order tensor model. STI has the potential to provide information for both the reconstruction of white matter fiber pathways and detection of myelin changes in the brain at mm resolution or less, which would be of great value for understanding brain structure and function in healthy and diseased brain. However, the application of STI in vivo has been hindered by its cumbersome and time-consuming acquisition requirement of measuring susceptibility induced MR phase changes at multiple head orientations. Usually, sampling at more than six orientations is required to obtain sufficient information for the ill-posed STI dipole inversion. This complexity is enhanced by the limitation in head rotation angles due to physical constraints of the head coil. As a result, STI has not yet been widely applied in human studies in vivo. In this work, we tackle these issues by proposing an image reconstruction algorithm for STI that leverages data-driven priors. Our method, called DeepSTI, learns the data prior implicitly via a deep neural network that approximates the proximal operator of a regularizer function for STI. The dipole inversion problem is then solved iteratively using the learned proximal network. Experimental results using both simulation and in vivo human data demonstrate great improvement over state-of-the-art algorithms in terms of the reconstructed tensor image, principal eigenvector maps and tractography results, while allowing for tensor reconstruction with MR phase measured at much less than six different orientations. Notably, promising reconstruction results are achieved by our method from only one orientation in human in vivo, and we demonstrate a potential application of this technique for estimating lesion susceptibility anisotropy in patients with multiple sclerosis.
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Affiliation(s)
- Zhenghan Fang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA
| | - Kuo-Wei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Peter van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD 21205, USA.
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD 21218, USA.
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Lee EJ, Kim MG, Chung MS, Kim SO, Byun JS, Yim Y. Diagnosis of intracranial lesions using accelerated 3D T1 MPRAGE with wave-CAIPI technique: comparison with conventional 3D T1 MPRAGE. Sci Rep 2022; 12:21930. [PMID: 36536040 PMCID: PMC9763340 DOI: 10.1038/s41598-022-25725-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
We aimed to evaluate the agreement in the diagnosis of intracranial lesions between conventional pre-contrast 3D T1 magnetization-prepared rapid gradient echo (MPRAGE) and wave-CAIPI (wave-controlled aliasing in parallel imaging) MPRAGE. Institutional review board approval was obtained and informed consent was waived for this retrospective study. We included 149 consecutive patients who had undergone brain MR with both conventional MPRAGE (scan time: 5 min 42 s) and wave-CAIPI MPRAGE (scan time: 2 min 44 s) from February to June 2018. All images were independently reviewed by two radiologists for the diagnosis of intracranial lesion and scored image quality using visual analysis. One technician measured signal-to-noise ratio. The agreement for diagnosis of intracranial lesion was calculated, and the intra- and interobserver agreements were analyzed by using kappa value. For the diagnosis of intracranial lesion, the conventional and wave-CAIPI MPRAGE demonstrated 99.7% of agreement (297 of 298) in the pooled analysis with very good agreement (k = 0.994). Intra- and inter-observer agreement showed very good (k > 0.9 in all) and good (k > 0.75) agreement, respectively. In the quantitative analysis, the signal-to-noise ratio had no difference (P > 0.05 for all). The overall image quality was poorer in images of wave-CAIPI MPRAGE (P < 0.001), but motion artifact had no difference between two sequences (P = 0.06). Compared to conventional MPRAGE, pre-contrast 3D T1 wave-CAIPI MPRAGE achieved higher agreement for the diagnosis of intracranial lesions and reduced the scan time by approximately 50%.
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Affiliation(s)
- Eun Jung Lee
- Department of Radiology, Human Medical Imaging & Intervention Center, Seoul, Korea ,grid.254224.70000 0001 0789 9563Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea
| | - Min Gu Kim
- grid.254224.70000 0001 0789 9563Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea
| | - Mi Sun Chung
- Department of Radiology, Human Medical Imaging & Intervention Center, Seoul, Korea ,grid.254224.70000 0001 0789 9563Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea
| | - Seon-Ok Kim
- grid.267370.70000 0004 0533 4667Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, Republic of Korea
| | - Jun Soo Byun
- Department of Radiology, Human Medical Imaging & Intervention Center, Seoul, Korea ,grid.254224.70000 0001 0789 9563Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea
| | - Younghee Yim
- grid.254224.70000 0001 0789 9563Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea
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Yu FF, Yi Huang S, Kumar A, Witzel T, Liao C, Duval T, Cohen-Adad J, Bilgic B. Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps. Magn Reson Med 2022; 87:781-790. [PMID: 34480768 PMCID: PMC8627440 DOI: 10.1002/mrm.28995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 07/13/2021] [Accepted: 08/10/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast parametric maps. We sought to reduce the acquisition time for QSM and macromolecular tissue volume by acquiring both contrasts simultaneously by leveraging their redundancies. The joint virtual coil concept with GRAPPA (JVC-GRAPPA) was applied to reduce acquisition time further. METHODS Three adult volunteers were imaged on a 3 Tesla scanner using a multi-echo 3D GRE sequence acquired at 3 head orientations. Macromolecular tissue volume, QSM, R2∗ , T1 , and proton density maps were reconstructed. The same sequence (GRAPPA R = 4) was performed in subject 1 with a single head orientation for comparison. Fully sampled data was acquired in subject 2, from which retrospective undersampling was performed (R = 6 GRAPPA and R = 9 JVC-GRAPPA). Prospective undersampling was performed in subject 3 (R = 6 GRAPPA and R = 9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes. RESULTS Subject 1's multi-orientation and single-orientation macromolecular tissue volume maps were not significantly different based on RMSE. For subject 2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject 3. Using QSM, R2∗ , and macromolecular tissue volume, the contributions of myelin and iron content to susceptibility were estimated. CONCLUSION We have developed a novel strategy to simultaneously acquire data for the reconstruction of 5 intrinsically coregistered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 min using JVC-GRAPPA.
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Affiliation(s)
- Fang Frank Yu
- Radiology, University of Texas Southwestern Medical Center, Dallas, TX, United States,,Corresponding author. Fang Frank Yu, MD, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, Ph: 214-648-7813, Fax: 214-648-3904,
| | - Susie Yi Huang
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Ashwin Kumar
- Vanderbilt University, Nashville, TN, United States
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford Medicine, Stanford, CA, United States
| | - Tanguy Duval
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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Stanley OW, Menon RS, Klassen LM. Receiver phase alignment using fitted SVD derived sensitivities from routine prescans. PLoS One 2021; 16:e0256700. [PMID: 34460849 PMCID: PMC8404984 DOI: 10.1371/journal.pone.0256700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 08/12/2021] [Indexed: 11/19/2022] Open
Abstract
Magnetic resonance imaging radio frequency arrays are composed of multiple receive coils that have their signals combined to form an image. Combination requires an estimate of the radio frequency coil sensitivities to align signal phases and prevent destructive interference. At lower fields this can be accomplished using a uniform physical reference coil. However, at higher fields, uniform volume coils are lacking and, when available, suffer from regions of low receive sensitivity that result in poor sensitivity estimation and combination. Several approaches exist that do not require a physical reference coil but require manual intervention, specific prescans, or must be completed post-acquisition. This makes these methods impractical for large multi-volume datasets such as those collected for novel types of functional MRI or quantitative susceptibility mapping, where magnitude and phase are important. This pilot study proposes a fitted SVD method which utilizes existing combination methods to create a phase sensitive combination method targeted at large multi-volume datasets. This method uses any multi-image prescan to calculate the relative receive sensitivities using voxel-wise singular value decomposition. These relative sensitivities are fitted to the solid harmonics using an iterative least squares fitting algorithm. Fits of the relative sensitivities are used to align the phases of the receive coils and improve combination in subsequent acquisitions during the imaging session. This method is compared against existing approaches in the human brain at 7 Tesla by examining the combined data for the presence of singularities and changes in phase signal-to-noise ratio. Two additional applications of the method are also explored, using the fitted SVD method in an asymmetrical coil and in a case with subject motion. The fitted SVD method produces singularity-free images and recovers between 95-100% of the phase signal-to-noise ratio depending on the prescan data resolution. Using solid harmonic fitting to interpolate singular value decomposition derived receive sensitivities from existing prescans allows the fitted SVD method to be used on all acquisitions within a session without increasing exam duration. Our fitted SVD method is able to combine imaging datasets accurately without supervision during online reconstruction.
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Affiliation(s)
- Olivia W. Stanley
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
- * E-mail:
| | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - L. Martyn Klassen
- Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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10
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Feng R, Zhao J, Wang H, Yang B, Feng J, Shi Y, Zhang M, Liu C, Zhang Y, Zhuang J, Wei H. MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping. Neuroimage 2021; 240:118376. [PMID: 34246768 DOI: 10.1016/j.neuroimage.2021.118376] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 07/02/2021] [Accepted: 07/07/2021] [Indexed: 11/25/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ13, χ23 and χ33) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ33 and phase induced by χ13 and χ23 terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.
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Affiliation(s)
- Ruimin Feng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jiayi Zhao
- School of Psychology, Shanghai University of Sport, Shanghai, China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Baofeng Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jie Feng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ming Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jie Zhuang
- School of Psychology, Shanghai University of Sport, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
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11
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Cao S, Wei H, Chen J, Liu C. Asymmetric susceptibility tensor imaging. Magn Reson Med 2021; 86:2266-2275. [PMID: 34014008 DOI: 10.1002/mrm.28823] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 04/08/2021] [Accepted: 04/11/2021] [Indexed: 11/06/2022]
Abstract
PURPOSE To investigate the symmetry constraint in susceptibility tensor imaging. THEORY The linear relationship between the MRI frequency shift and the magnetic susceptibility tensor is derived without constraining the tensor to be symmetric. In the asymmetric case, the system matrix is shown to be maximally rank 6. Nonetheless, relaxing the symmetry constraint may still improve tensor estimation because noise and image artifacts do not necessarily follow the constraint. METHODS Gradient echo phase data are obtained from postmortem mouse brain and kidney samples. Both symmetric and asymmetric tensor reconstructions are applied to the data. The reconstructions are then used for susceptibility tensor imaging fiber tracking. Simulations with ground truth and at various noise levels are also performed. The reconstruction methods are compared qualitatively and quantitatively. RESULTS Compared to regularized and unregularized symmetric reconstructions, the asymmetric reconstruction shows reduced noise and streaking artifacts, better contrast, and more complete fiber tracking. In simulation, the asymmetric reconstruction achieves better mean squared error and better angular difference in the presence of noise. Decomposing the asymmetric tensor into its symmetric and antisymmetric components confirms that the underlying susceptibility tensor is symmetric and that the main sources of asymmetry are noise and streaking artifacts. CONCLUSION Whereas the susceptibility tensor is symmetric, asymmetric reconstruction is more effective in suppressing noise and artifacts, resulting in more accurate estimation of the susceptibility tensor.
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Affiliation(s)
- Steven Cao
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.,Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jingjia Chen
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
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12
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许 欢, 孟 庆, 樊 文, 王 雪, 刘 梦, 陈 志. [Reproducibility analysis of quantitative susceptibility mapping of cerebral subcortical nuclei in healthy adults]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2020; 40:1810-1815. [PMID: 33380400 PMCID: PMC7835684 DOI: 10.12122/j.issn.1673-4254.2020.12.17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Indexed: 06/12/2023]
Abstract
OBJECTIVE To investigate the intra- and inter-scanner reproducibility of quantitative susceptibility mapping (QSM) of cerebral subcortical nuclei in healthy adults. METHODS QSM was performed in 21 healthy adults on two different 3.0T MR scanners, and the region of interest (ROI) method was used to measure the magnetic susceptibility value of the left subcortical nuclei (the head of the caudate, putamen, globus pallidus, thalamus, substantia nigra and red nucleus). The intraclass correlation coefficient (ICC) and Bland-Altman method were used to evaluate the inter-scanner and intra-scanner reliability. RESULTS The ICCs of the susceptibility value ranged from 0.90 to 0.99 for all the subcortical gray nuclei except for the head of the caudate nucleus measured on the same MR scanner by the same observer. Bland-Altman analysis revealed that the points with susceptibility differences for all the subcortical gray nuclei except for substantia nigra located in the 95% CI of limits of agreement for the same MR scanner. The ICCs of the susceptibility value for the inter-scanner was 0.49 (0.08-0.75) for the head of the caudate nuleus, 0.80 (0.57-0.91) for the putamen, 0.77 (0.51-0.90) for the globus pallidus, 0.78 (0.54-0.91) for the thalamus, 0.80 (0.56-0.91) for the substantia nigra and 0.93 (0.83-0.97) for the red nucleus. The points with susceptibility difference (95.2%, 20/21) located in the 95% CI of limits of agreement for the putamen and the thalamus measured on two different MR scanners. CONCLUSIONS The intra-scanner reproducibility of QSM of the subcortical gray nuclei is superior to the inter-scanner reproducibility in healthy adults.
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Affiliation(s)
- 欢 许
- 海南省儋州市人民医院放射科,海南 儋州 571700Department of Radiology, Danzhou People's Hospital, Danzhou 571700, China
| | - 庆林 孟
- 解放军总医院海南医院放射科,海南 三亚 572013Department of Radiology, Hainan Hospital Affiliated to General Hospital of PLA, Sanya 572013, China
| | - 文萍 樊
- 解放军总医院海南医院放射科,海南 三亚 572013Department of Radiology, Hainan Hospital Affiliated to General Hospital of PLA, Sanya 572013, China
| | - 雪 王
- 解放军总医院海南医院放射科,海南 三亚 572013Department of Radiology, Hainan Hospital Affiliated to General Hospital of PLA, Sanya 572013, China
| | - 梦琦 刘
- 解放军总医院海南医院放射科,海南 三亚 572013Department of Radiology, Hainan Hospital Affiliated to General Hospital of PLA, Sanya 572013, China
- 解放军总医院第一医学中心放射科,北京 100853Department of Radiology, First Medical Center of General Hospital of PLA, Beijing 100853, China
| | - 志晔 陈
- 解放军总医院海南医院放射科,海南 三亚 572013Department of Radiology, Hainan Hospital Affiliated to General Hospital of PLA, Sanya 572013, China
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13
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Abstract
The habenula plays an important role in brain reward circuitry and psychiatric conditions. While much work has been done on the function and structure of the habenula in animal models, in vivo imaging studies of the human habenula have been relatively scarce due to its small size, deep brain location, and lack of clear biomarkers for its heterogeneous substructure. In this paper, we report high-resolution (0.5 × 0.5 × 0.8 mm3) MRI of the human habenula with quantitative susceptibility mapping (QSM) at 3 T. By analyzing 48 scan datasets collected from 21 healthy subjects, we found that magnetic susceptibility contrast is highly non-uniform within the habenula and across the subjects. In particular, we observed high prevalence of elevated susceptibility in the posterior subregion of the habenula. Correlation analysis between the susceptibility and the effective transverse relaxation rate (R2*) indicated that localized susceptibility enhancement in the habenula is more associated with increased paramagnetic (such as iron) rather than decreased diamagnetic (such as myelin) sources. Our results suggest that high-resolution QSM could make a potentially useful tool for substructure-resolved in vivo habenula imaging, and provide a groundwork for the future development of magnetic susceptibility as a quantitative biomarker for human habenula studies.
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14
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Kaden E, Gyori NG, Rudrapatna SU, Barskaya IY, Dragonu I, Does MD, Jones DK, Clark CA, Alexander DC. Microscopic susceptibility anisotropy imaging. Magn Reson Med 2020; 84:2739-2753. [PMID: 32378746 PMCID: PMC7402021 DOI: 10.1002/mrm.28303] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/07/2020] [Accepted: 04/08/2020] [Indexed: 11/25/2022]
Abstract
PURPOSE The gradient-echo MR signal in brain white matter depends on the orientation of the fibers with respect to the external magnetic field. To map microstructure-specific magnetic susceptibility in orientationally heterogeneous material, it is thus imperative to regress out unwanted orientation effects. METHODS This work introduces a novel framework, referred to as microscopic susceptibility anisotropy imaging, that disentangles the 2 principal effects conflated in gradient-echo measurements, (a) the susceptibility properties of tissue microenvironments, especially the myelin microstructure, and (b) the axon orientation distribution relative to the magnetic field. Specifically, we utilize information about the orientational tissue structure inferred from diffusion MRI data to factor out the B 0 -direction dependence of the frequency difference signal. RESULTS A human pilot study at 3 T demonstrates proxy maps of microscopic susceptibility anisotropy unconfounded by fiber crossings and orientation dispersion as well as magnetic field direction. The developed technique requires only a dual-echo gradient-echo scan acquired at 1 or 2 head orientations with respect to the magnetic field and a 2-shell diffusion protocol achievable on standard scanners within practical scan times. CONCLUSIONS The quantitative recovery of microscopic susceptibility features in the presence of orientational heterogeneity potentially improves the assessment of microstructural tissue integrity.
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Affiliation(s)
- Enrico Kaden
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | - Noemi G. Gyori
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | | | | | | | - Mark D. Does
- Institute of Imaging ScienceVanderbilt UniversityNashvilleTNUSA
| | - Derek K. Jones
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiffUK
- School of PsychologyAustralian Catholic UniversityMelbourneVICAustralia
| | - Chris A. Clark
- Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
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15
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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] [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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16
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Lee SH, Han MJ, Lee J, Lee SK. Experimental setup for bulk susceptibility effect-minimized, multi-orientation MRI of ex vivo tissue samples. Med Phys 2020; 47:3032-3043. [PMID: 32282079 DOI: 10.1002/mp.14174] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 03/06/2020] [Accepted: 03/20/2020] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Many conventional ex vivo magnetic resonance imaging (MRI) setups utilize cylindrical or other nonspherical tissue containers which can cause static field (B0 ) inhomogeneity affecting the accuracy of the measurements in an orientation-dependent manner. In this work we demonstrate an experimental method to obtain MRI of ex vivo tissue samples held in a spherical container in order to minimize bulk susceptibility-induced B0 inhomogeneity in arbitrary orientations. METHODS B0 inhomogeneity caused by tissue-air susceptibility mismatch can be theoretically eliminated if the surface of susceptibility discontinuity is spherical. This situation can be approximated by putting a tissue sample in a spherical shell filled with materials with tissue-like magnetic susceptibility. We achieved this on an intact monkey brain by (a) holding the brain with a three-dimensional (3D)-printed holder with tissue-like (within 0.5 ppm) susceptibility, and (b) enclosing the brain and the holder in an acrylic spherical shell filled with diamagnetic liquid. Furthermore, the sphere and the radio-frequency coil for MRI were mounted on a 3D-printed frame designed to reduce B0 inhomogeneity contributions. The sphere could be rotated freely without disturbing the RF coil to facilitate multi-orientation imaging. We verified our setup by mapping B0 in the monkey brain at 13 different orientations in a human 7T scanner, and measuring orientation-dependent R 2 ∗ relaxation rates in the white and gray matters of the brain. The results were then compared with a setup where the brain was held inside a cylindrical container. RESULTS In all orientations, the B0 standard deviation in the brain in the spherical setup (converted to Larmor frequency offset) was less than about 10 Hz. This corresponds to two-sigma deviation of B0 of <0.07 ppm. The B0 gradient was <9 Hz/mm in 95 % of the brain voxels in all orientations. In high-resolution imaging with e.g. voxel size <0.4 mm, this corresponds to voxel line broadening of <4 Hz (0.013 ppm). R 2 ∗ in the corpus callosum showed distinctly different orientation dependence compared to the gray matter. The B0 uniformity and R 2 ∗ reliability were much reduced in the cylindrical container setup. CONCLUSIONS We have demonstrated an experimental method to effectively minimize bulk susceptibility-induced B0 perturbation in multi-orientation ex vivo MRI. The method promises to benefit a range of tissue orientation-dependent MR property studies.
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Affiliation(s)
- So-Hee Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Min-Jun Han
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Joonyeol Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Seung-Kyun Lee
- Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.,Biomedical Institute for Convergence, Sungkyunkwan University, Suwon, South Korea.,Department of Physics, Sungkyunkwan University, Suwon, South Korea
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17
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Chung MS, Lee EJ, Kim S, Kim SO, Byun JS. Wave-CAIPI susceptibility-weighted imaging achieves diagnostic performance comparable to conventional susceptibility-weighted imaging in half the scan time. Eur Radiol 2020; 30:2182-2190. [PMID: 31953660 DOI: 10.1007/s00330-019-06574-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 10/31/2019] [Accepted: 11/06/2019] [Indexed: 11/30/2022]
Abstract
OBJECTIVES We aimed to evaluate the agreement in the detection of cerebral microbleeds (CMBs) between conventional susceptibility-weighted imaging (SWI) and fast SWI using wave-controlled aliasing in parallel imaging (CAIPI) acceleration. We also scrutinized the diagnostic agreement for intracranial lesions and compared the image quality between both sequences. METHODS Institutional review board approval was obtained and informed consent was waived for this retrospective study. We included 181 consecutive patients who had undergone brain MRI with both conventional SWI (scan time, 251 s) and wave-CAIPI SWI (scan time, 113 s) from September 2017 to November 2017. All images were independently reviewed by two radiologists for the detection and counting of CMBs using the Microbleed Anatomical Rating Scale (MARS). One neuroradiologist diagnosed intracranial lesions and scored image quality using visual analysis. The agreement for detection of CMBs and intracranial lesions was calculated, and interobserver agreements were analyzed by using kappa and intraclass correlation. RESULTS For detection of CMBs, both the conventional and wave-CAIPI SWI showed significantly high agreement of 100% for the presence of CMBs, and 94.5% using MARS. Wave-CAIPI SWI achieved more than 97% agreement of MARS when divided by anatomical locations, with excellent agreement. Interobserver agreements were also excellent. The diagnosis for intracranial lesions (33 lesions in 28 patients) demonstrated 100% agreement. The image quality of both sequences is not significantly different (p = 0.20). CONCLUSIONS Wave-CAIPI SWI achieved high agreement for CMB detection and diagnosis of intracranial lesions compared to conventional SWI within half of the scan time. KEY POINTS • Wave-CAIPI SWI achieves a diagnostic performance for the detection of cerebral microbleeds that is comparable to that of conventional SWI in half the scan time. • Interobserver agreement for the detection (presence vs. absence) and counting of cerebral microbleeds of wave-CAIPI SWI was excellent. • Wave-CAIPI SWI demonstrated a 100% agreement for the diagnosis of intracranial lesions and comparable image quality compared to conventional SWI.
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Affiliation(s)
- Mi Sun Chung
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea
| | - Eun Jung Lee
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea
| | - Sujin Kim
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea
| | - Seon-Ok Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, Republic of Korea
| | - Jun Soo Byun
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea.
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18
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Rivera-Rivera LA, Schubert T, Johnson KM. Measurements of cerebral blood volume using quantitative susceptibility mapping, R 2 * relaxometry, and ferumoxytol-enhanced MRI. NMR IN BIOMEDICINE 2019; 32:e4175. [PMID: 31482602 PMCID: PMC6868300 DOI: 10.1002/nbm.4175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 07/30/2019] [Accepted: 08/13/2019] [Indexed: 05/08/2023]
Abstract
Ferumoxytol-enhanced MRI holds potential for the non-invasive assessment of vascular architecture using estimates of cerebral blood volume (CBV). Ferumoxytol specifically enables steady-state imaging with extended acquisition times, for substantial improvements in resolution and contrast-to-noise ratio. With such data, quantitative susceptibility mapping (QSM) can be used to obtain images of local tissue magnetic susceptibility and hence estimate the increase in blood susceptibility after administration of a contrast agent, which in turn can be correlated to tissue CBV. Here, we explore the use of QSM for CBV estimation and compare it with R2 * (1/T2 *)-based results. Institutional review board approval was obtained, and all subjects provided written informed consent. For this prospective study, MR images were acquired on a 3.0 T scanner in 19 healthy subjects using a multiple-echo T2 *-weighted sequence. Scanning was performed before and after the administration of two doses of ferumoxytol (1 mg FE/kg and 4 mg FE/kg). Different QSM approaches were tested on numerical phantom simulations. Results showed that the accuracy of magnetic susceptibility measurements improved with increasing image resolution and decreasing vascular density. In vivo changes in magnetic susceptibility were measured after the administration of ferumoxytol utilizing QSM, and significantly higher QSM-based CBV was measured in gray matter compared with white matter. QSM- and R2 *-based CBV estimates correlated well, with similar average values, but a larger variance was found in QSM-based estimates.
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Affiliation(s)
- Leonardo A Rivera-Rivera
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705-2275, USA
| | - Tilman Schubert
- Department of Radiology and Nuclear Medicine, Basel University Hospital, Petersgraben 4, 4031 Basel, Switzerland
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705-2275, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI 53705-2275, USA
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19
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Conklin J, Longo MGF, Cauley SF, Setsompop K, González RG, Schaefer PW, Kirsch JE, Rapalino O, Huang SY. Validation of Highly Accelerated Wave-CAIPI SWI Compared with Conventional SWI and T2*-Weighted Gradient Recalled-Echo for Routine Clinical Brain MRI at 3T. AJNR Am J Neuroradiol 2019; 40:2073-2080. [PMID: 31727749 DOI: 10.3174/ajnr.a6295] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 09/09/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE SWI is valuable for characterization of intracranial hemorrhage and mineralization but has long acquisition times. We compared a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) SWI sequence with 2 commonly used alternatives, standard SWI and T2*-weighted gradient recalled-echo (T2*W GRE), for routine clinical brain imaging at 3T. MATERIALS AND METHODS A total of 246 consecutive adult patients were prospectively evaluated using a conventional SWI or T2*W GRE sequence and an optimized wave-CAIPI SWI sequence, which was 3-5 times faster than the standard sequence. Two blinded radiologists scored each sequence for the presence of hemorrhage, the number of microhemorrhages, and severity of motion artifacts. Wave-CAIPI SWI was then evaluated in head-to-head comparison with the conventional sequences for visualization of pathology, artifacts, and overall diagnostic quality. Forced-choice comparisons were used for all scores. Wave-CAIPI SWI was tested for superiority relative to T2*W GRE and for noninferiority relative to standard SWI using a 15% noninferiority margin. RESULTS Compared with T2*W GRE, wave-CAIPI SWI detected hemorrhages in more cases (P < .001) and detected more microhemorrhages (P < .001). Wave-CAIPI SWI was superior to T2*W GRE for visualization of pathology, artifacts, and overall diagnostic quality (all P < .001). Compared with standard SWI, wave-CAIPI SWI showed no difference in the presence or number of hemorrhages identified. Wave-CAIPI SWI was noninferior to standard SWI for the visualization of pathology (P < .001), artifacts (P < .01), and overall diagnostic quality (P < .01). Motion was less severe with wave-CAIPI SWI than with standard SWI (P < .01). CONCLUSIONS Wave-CAIPI SWI provided superior visualization of pathology and overall diagnostic quality compared with T2*W GRE and was noninferior to standard SWI with reduced scan times and reduced motion artifacts.
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Affiliation(s)
- J Conklin
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - M G F Longo
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - S F Cauley
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging (S.F.C., K.S., S.Y.H.), Boston, Massachusetts
| | - K Setsompop
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging (S.F.C., K.S., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - R G González
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - P W Schaefer
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - J E Kirsch
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - O Rapalino
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - S Y Huang
- From the Department of Radiology (J.C., M.G.F.L., S.F.C., K.S., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging (S.F.C., K.S., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
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20
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Extracting more for less: multi‐echo MP2RAGE for simultaneous T
1
‐weighted imaging, T
1
mapping, mapping, SWI, and QSM from a single acquisition. Magn Reson Med 2019; 83:1178-1191. [DOI: 10.1002/mrm.27975] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 08/05/2019] [Accepted: 08/06/2019] [Indexed: 12/22/2022]
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21
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ENLIVE: An Efficient Nonlinear Method for Calibrationless and Robust Parallel Imaging. Sci Rep 2019; 9:3034. [PMID: 30816312 PMCID: PMC6395635 DOI: 10.1038/s41598-019-39888-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 02/04/2019] [Indexed: 12/05/2022] Open
Abstract
Robustness against data inconsistencies, imaging artifacts and acquisition speed are crucial factors limiting the possible range of applications for magnetic resonance imaging (MRI). Therefore, we report a novel calibrationless parallel imaging technique which simultaneously estimates coil profiles and image content in a relaxed forward model. Our method is robust against a wide class of data inconsistencies, minimizes imaging artifacts and is comparably fast, combining important advantages of many conceptually different state-of-the-art parallel imaging approaches. Depending on the experimental setting, data can be undersampled well below the Nyquist limit. Here, even high acceleration factors yield excellent imaging results while being robust to noise and the occurrence of phase singularities in the image domain, as we show on different data. Moreover, our method successfully reconstructs acquisitions with insufficient field-of-view. We further compare our approach to ESPIRiT and SAKE using spin-echo and gradient echo MRI data from the human head and knee. In addition, we show its applicability to non-Cartesian imaging on radial FLASH cardiac MRI data. Using theoretical considerations, we show that ENLIVE can be related to a low-rank formulation of blind multi-channel deconvolution, explaining why it inherently promotes low-rank solutions.
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22
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Wang N, Cofer G, Anderson RJ, Qi Y, Liu C, Johnson GA. Accelerating quantitative susceptibility imaging acquisition using compressed sensing. ACTA ACUST UNITED AC 2018; 63:245002. [DOI: 10.1088/1361-6560/aaf15d] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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23
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Sun H, Ma Y, MacDonald ME, Pike GB. Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method. Neuroimage 2018; 179:166-175. [PMID: 29906634 DOI: 10.1016/j.neuroimage.2018.06.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 06/06/2018] [Accepted: 06/10/2018] [Indexed: 10/28/2022] Open
Abstract
A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods.
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Affiliation(s)
- Hongfu Sun
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada; Department of Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Yuhan Ma
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - M Ethan MacDonald
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada; Department of Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - G Bruce Pike
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada; Department of Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
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24
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Magnetic Resonance Imaging technology-bridging the gap between noninvasive human imaging and optical microscopy. Curr Opin Neurobiol 2018; 50:250-260. [PMID: 29753942 DOI: 10.1016/j.conb.2018.04.026] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 04/20/2018] [Accepted: 04/24/2018] [Indexed: 12/23/2022]
Abstract
Technological advances in Magnetic Resonance Imaging (MRI) have provided substantial gains in the sensitivity and specificity of functional neuroimaging. Mounting evidence demonstrates that the hemodynamic changes utilized in functional MRI can be far more spatially and thus neuronally specific than previously believed. This has motivated a push toward novel, high-resolution MR imaging strategies that can match this biological resolution limit while recording from the entire human brain. Although sensitivity increases are a necessary component, new MR encoding technologies are required to convert improved sensitivity into higher resolution. These new sampling strategies improve image acquisition efficiency and enable increased image encoding in the time-frame needed to follow hemodynamic changes associated with brain activation.
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25
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Guo L, Mei Y, Guan J, Tan X, Xu Y, Chen W, Feng Q, Feng Y. Morphology-adaptive total variation for the reconstruction of quantitative susceptibility map from the magnetic resonance imaging phase. PLoS One 2018; 13:e0196922. [PMID: 29738526 PMCID: PMC5940224 DOI: 10.1371/journal.pone.0196922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 04/23/2018] [Indexed: 11/18/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging technique that quantifies the magnetic susceptibility distribution within biological tissues. QSM calculates the underlying magnetic susceptibility by deconvolving the tissue magnetic field map with a unit dipole kernel. However, this deconvolution problem is ill-posed. The morphology enabled dipole inversion (MEDI) introduces total variation (TV) to regularize the susceptibility reconstruction. However, MEDI results still contain artifacts near tissue boundaries because MEDI only imposes TV constraint on voxels inside smooth regions. We introduce a Morphology-Adaptive TV (MATV) for improving TV-regularized QSM. The MATV method first classifies imaging target into smooth and nonsmooth regions by thresholding magnitude gradients. In the dipole inversion for QSM, the TV regularization weights are a monotonically decreasing function of magnitude gradients. Thus, voxels inside smooth regions are assigned with larger weights than those in nonsmooth regions. Using phantom and in vivo datasets, we compared the performance of MATV with that of MEDI. MATV results had better visual quality than MEDI results, especially near tissue boundaries. Preliminary brain imaging results illustrated that MATV has potential to improve the reconstruction of regions near tissue boundaries.
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Affiliation(s)
- Li Guo
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Yingjie Mei
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Philips Healthcare, Guangzhou, China
| | - Jijing Guan
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Xiangliang Tan
- Department of Medical Imaging Center, Southern Medical University Nanfang Hospital, Guangzhou, China
| | - Yikai Xu
- Department of Medical Imaging Center, Southern Medical University Nanfang Hospital, Guangzhou, China
| | - Wufan Chen
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- * E-mail: (WC); (YF)
| | - Qianjin Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- * E-mail: (WC); (YF)
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26
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Langkammer C, Schweser F, Shmueli K, Kames C, Li X, Guo L, Milovic C, Kim J, Wei H, Bredies K, Buch S, Guo Y, Liu Z, Meineke J, Rauscher A, Marques JP, Bilgic B. Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge. Magn Reson Med 2018; 79:1661-1673. [PMID: 28762243 PMCID: PMC5777305 DOI: 10.1002/mrm.26830] [Citation(s) in RCA: 117] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Revised: 06/03/2017] [Accepted: 06/17/2017] [Indexed: 01/10/2023]
Abstract
PURPOSE The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully. METHODS Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions. RESULTS Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance. CONCLUSION Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA; Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - Christian Kames
- UBC MRI Research Centre, Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Li Guo
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Jinsuh Kim
- Department of Radiology, University of Illinois at Chicago, IL, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Kristian Bredies
- Institute of Mathematics and Scientific Computing, University of Graz, Austria
| | - Sagar Buch
- The MRI Institute for Biomedical Research, Waterloo, Ontario, Canada
| | - Yihao Guo
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Zhe Liu
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | | | - Alexander Rauscher
- UBC MRI Research Centre, Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - José P. Marques
- Donders Centre for Cognitive Neuroimaging, Radboud University, The Netherlands
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, MGH, Boston, MA, USA
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27
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Poser BA, Setsompop K. Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field. Neuroimage 2018; 168:101-118. [PMID: 28392492 PMCID: PMC5630499 DOI: 10.1016/j.neuroimage.2017.04.006] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 04/01/2017] [Accepted: 04/03/2017] [Indexed: 12/18/2022] Open
Abstract
The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B1+ and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.
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Affiliation(s)
- Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Kawin Setsompop
- Department of Radiology, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
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28
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How to choose the right MR sequence for your research question at 7 T and above? Neuroimage 2018; 168:119-140. [DOI: 10.1016/j.neuroimage.2017.04.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
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29
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Vaas M, Deistung A, Reichenbach JR, Keller A, Kipar A, Klohs J. Vascular and Tissue Changes of Magnetic Susceptibility in the Mouse Brain After Transient Cerebral Ischemia. Transl Stroke Res 2017; 9:426-435. [PMID: 29177950 PMCID: PMC6061250 DOI: 10.1007/s12975-017-0591-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 11/17/2017] [Indexed: 12/04/2022]
Abstract
Quantitative susceptibility mapping (QSM) has been recently introduced as a novel MRI post-processing technique of gradient recalled echo (GRE) data. QSM is useful in depicting both brain anatomy and for detecting abnormalities. Its utility in the context of ischemic stroke has, however, not been extensively characterized so far. In this study, we explored the potential of QSM to characterize vascular and tissue changes in the transient middle cerebral artery occlusion (tMCAO) mouse model of cerebral ischemia. We acquired GRE data of mice brains at different time points after tMCAO, from which we computed QSM and MR frequency maps, and compared these maps with diffusion imaging and multi-slice multi-echo imaging data acquired in the same animals. Prominent vessels with increased magnetic susceptibility were visible surrounding the lesion on both frequency and magnetic susceptibility maps at all time points (mostly visible at > 12 h after reperfusion). Immunohistochemistry revealed the presence of compressed capillaries and dilated larger vessels, suggesting that the appearance of prominent vessels after reestablishment of reperfusion may serve compensatory purposes. In addition, on both contrast maps, tissue regions of decreased magnetic susceptibility were observed at 24 and 48 h after reperfusion that were distinctly different from the lesions seen on maps of the apparent diffusion coefficient and T2 relaxation time constant. Since QSM can be extracted as an add-on from GRE data and thus requires no additional acquisition time in the course of acute stroke MRI examination, it may provide unique and complementary information during the course of acute stroke MRI examinations.
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Affiliation(s)
- Markus Vaas
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Vladimir-Prelog-Weg 4, 8093, Zurich, Switzerland.,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, University Hospital Jena, 07743, Jena, Germany.,Section of Experimental Neurology, Department of Neurology, Essen University Hospital, 45147, Essen, Germany.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141, Essen, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, University Hospital Jena, 07743, Jena, Germany.,Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, 07743, Jena, Germany
| | - Annika Keller
- Division of Neurosurgery, University Hospital Zurich, 8091, Zurich, Switzerland
| | - Anja Kipar
- Institute of Veterinary Pathology, University of Zurich, 8057, Zurich, Switzerland
| | - Jan Klohs
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Vladimir-Prelog-Weg 4, 8093, Zurich, Switzerland. .,Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.
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30
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Wei H, Gibbs E, Zhao P, Wang N, Cofer GP, Zhang Y, Johnson GA, Liu C. Susceptibility tensor imaging and tractography of collagen fibrils in the articular cartilage. Magn Reson Med 2017; 78:1683-1690. [PMID: 28856712 PMCID: PMC5786159 DOI: 10.1002/mrm.26882] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Revised: 07/24/2017] [Accepted: 07/30/2017] [Indexed: 12/17/2022]
Abstract
PURPOSE To investigate the B0 orientation-dependent magnetic susceptibility of collagen fibrils within the articular cartilage and to determine whether susceptibility tensor imaging (STI) can detect the 3D collagen network within cartilage. METHODS Multiecho gradient echo datasets (100-μm isotropic resolution) were acquired from fixed porcine articular cartilage specimens at 9.4 T. The susceptibility tensor was calculated using phase images acquired at 12 or 15 different orientations relative to B0 . The susceptibility anisotropy of the collagen fibril was quantified and diffusion tensor imaging (DTI) was compared against STI. 3D tractography was performed to visualize and track the collagen fibrils with DTI and STI. RESULTS STI experiments showed the distinct and significant anisotropic magnetic susceptibility of collagen fibrils within the articular cartilage. STI can be used to measure and quantify susceptibility anisotropy maps. Furthermore, STI provides orientation information of the underlying collagen network via 3D tractography. CONCLUSION The findings of this study demonstrate that STI can characterize the orientation variation of collagen fibrils where diffusion anisotropy fails. We believe that STI could serve as a sensitive and noninvasive marker to study the collagen fibrils microstructure. Magn Reson Med 78:1683-1690, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Eric Gibbs
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Peida Zhao
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Nian Wang
- Center for In Vivo Microscopy, Duke University, Durham, NC, USA
| | - Gary P. Cofer
- Center for In Vivo Microscopy, Duke University, Durham, NC, USA
| | - Yuyao Zhang
- 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
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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Kee Y, Cho J, Deh K, Liu Z, Spincemaille P, Wang Y. Coherence enhancement in quantitative susceptibility mapping by means of anisotropic weighting in morphology enabled dipole inversion. Magn Reson Med 2017; 79:1172-1180. [PMID: 28556244 DOI: 10.1002/mrm.26748] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2016] [Revised: 03/23/2017] [Accepted: 04/15/2017] [Indexed: 02/06/2023]
Abstract
PURPOSE To investigate an anisotropic structural prior in morphology enabled dipole inversion (MEDI) for improving accuracy in quantitative susceptibility mapping (QSM). THEORY AND METHODS Anisotropic weighting (AW) was devised and implemented to incorporate orientation information into the edge agreement in the MEDI method. AW performance was compared with isotropic weighting by testing and validating on in vivo brain multiple orientation MRI data using COSMOS and the (33) component of the susceptibility tensor as reference. RESULTS Suppressing streaking artifacts, AW improved not only QSM image quality but also accuracy in terms of RMSE (root mean square error), HFEN (high frequency error norm), SSIM (structural similarity index), and GDA (gradient direction agreement). In addition, it outperformed isotropic weighting in region of interest-based analysis. From a computational perspective, AW was as fast as isotropic weighting, taking approximately the same central processing unit times. CONCLUSION Using AW in MEDI improves QSM accuracy compared with isotropic weighting. Magn Reson Med 79:1172-1180, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Youngwook Kee
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Junghun Cho
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Kofi Deh
- Department of Physiology, Systems Biology and Biophysics, Weill Cornell Medical College, New York, New York, USA
| | - Zhe Liu
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA.,Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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32
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Bilgic B, Ye H, Wald LL, Setsompop K. Simultaneous Time Interleaved MultiSlice (STIMS) for Rapid Susceptibility Weighted acquisition. Neuroimage 2017; 155:577-586. [PMID: 28435102 DOI: 10.1016/j.neuroimage.2017.04.036] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 04/14/2017] [Accepted: 04/15/2017] [Indexed: 01/30/2023] Open
Abstract
T2* weighted 3D Gradient Echo (GRE) acquisition is the main sequence used for Susceptibility Weighted Imaging (SWI) and Quantitative Susceptibility Mapping (QSM). These applications require a long echo time (TE) to build up phase contrast, requiring a long repetition time (TR), and leading to excessively lengthy scans. The long TE acquisition creates a significant amount of unused time within each TR, which can be utilized for either multi-echo sampling or additional image encoding with the echo-shift technique. The latter leads to significant saving in acquisition time while retaining the desired phase and T2* contrast. In this work, we introduce the Simultaneous Time Interleaved MultiSlice (STIMS) echo-shift technique, which mitigates slab boundary artifacts by interleaving comb-shaped slice groups with Simultaneous MultiSlice (SMS) excitation. This enjoys the same SNR benefit of 3D signal averaging as previously introduced multi-slab version, where each slab group is sub-resolved with kz phase encoding. Further, we combine SMS echo-shift with Compressed Sensing (CS) Wave acceleration, which enhances Wave-CAIPI acquisition/reconstruction with random undersampling and sparsity prior. STIMS and CS-Wave combination thus yields up to 45-fold acceleration over conventional full encoding, allowing a 15sec full-brain acquisition with 1.5 mm isotropic resolution at long TE of 39 ms at 3T. In addition to utilizing empty sequence time due to long TE, STIMS is a general concept that could exploit gaps due to e.g. inversion modules in magnetization-prepared rapid gradient-echo (MPRAGE) and fluid attenuated inversion recovery (FLAIR) sequences.
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Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Huihui Ye
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China; Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
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33
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Dibb R, Xie L, Wei H, Liu C. Magnetic susceptibility anisotropy outside the central nervous system. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3544. [PMID: 27199082 PMCID: PMC5112155 DOI: 10.1002/nbm.3544] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Revised: 03/29/2016] [Accepted: 03/30/2016] [Indexed: 06/01/2023]
Abstract
Magnetic-susceptibility-based MRI has made important contributions to the characterization of tissue microstructure, chemical composition, and organ function. This has motivated a number of studies to explore the link between microstructure and susceptibility in organs and tissues throughout the body, including the kidney, heart, and connective tissue. These organs and tissues have anisotropic magnetic susceptibility properties and cellular organizations that are distinct from the lipid organization of myelin in the brain. For instance, anisotropy is traced to the epithelial lipid orientation in the kidney, the myofilament proteins in the heart, and the collagen fibrils in the knee cartilage. The magnetic susceptibility properties of these and other tissues are quantified using specific MRI tools: susceptibility tensor imaging (STI), quantitative susceptibility mapping (QSM), and individual QSM measurements with respect to tubular and filament directions determined from diffusion tensor imaging. These techniques provide complementary and supplementary information to that produced by traditional MRI methods. In the kidney, STI can track tubules in all layers including the cortex, outer medulla, and inner medulla. In the heart, STI detected myofibers throughout the myocardium. QSM in the knee revealed three unique layers in articular cartilage by exploiting the anisotropic susceptibility features of collagen. While QSM and STI are promising tools to study tissue susceptibility, certain technical challenges must be overcome in order to realize routine clinical use. This paper reviews essential experimental findings of susceptibility anisotropy in the body, the underlying mechanisms, and the associated MRI methodologies. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Russell Dibb
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710
| | - Luke Xie
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah 84108
| | - Hongjiang Wei
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina, 27710
| | - Chunlei Liu
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27710
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina, 27710
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Li W, Liu C, Duong TQ, van Zijl PC, Li X. Susceptibility tensor imaging (STI) of the brain. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3540. [PMID: 27120169 PMCID: PMC5083244 DOI: 10.1002/nbm.3540] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 03/22/2016] [Accepted: 03/23/2016] [Indexed: 05/23/2023]
Abstract
Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility and magnetic susceptibility anisotropy can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping to remove such dependence. Similar to diffusion tensor imaging, STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of the susceptibility anisotropy in brain white matter is myelin. Another unique feature of the susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in the myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Wei Li
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229
- Department of Ophthalmology, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229
| | - Chunlei Liu
- Brain Imaging and Analysis Center, School of Medicine, Duke University, Durham, NC 27710
- Department of Radiology, School of Medicine, Duke University, Durham, NC 27710
| | - Timothy Q. Duong
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229
- Department of Ophthalmology, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229
| | - Peter C.M. van Zijl
- F.M. Kirby Research Center for functional brain imaging, Kennedy Krieger Institute, Baltimore, MD, 21205
- Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205
| | - Xu Li
- F.M. Kirby Research Center for functional brain imaging, Kennedy Krieger Institute, Baltimore, MD, 21205
- Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205
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Liu S, Buch S, Chen Y, Choi HS, Dai Y, Habib C, Hu J, Jung JY, Luo Y, Utriainen D, Wang M, Wu D, Xia S, Haacke EM. Susceptibility-weighted imaging: current status and future directions. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3552. [PMID: 27192086 PMCID: PMC5116013 DOI: 10.1002/nbm.3552] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 04/01/2016] [Accepted: 04/11/2016] [Indexed: 05/14/2023]
Abstract
Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Saifeng Liu
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
| | - Sagar Buch
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
| | - Yongsheng Chen
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Hyun-Seok Choi
- Department of Radiology, St. Mary’s Hospital, The Catholic University of Korea, Seoul, Korea
| | - Yongming Dai
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
| | - Charbel Habib
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Joon-Yong Jung
- Department of Radiology, St. Mary’s Hospital, The Catholic University of Korea, Seoul, Korea
| | - Yu Luo
- Department of Radiology, the Branch of Shanghai First Hospital, Shanghai, China
| | - David Utriainen
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People’s Hospital, Zhengzhou, Henan, China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Shuang Xia
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - E. Mark Haacke
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
- Department of Radiology, Wayne State University, Detroit, MI, US
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
- Address correspondence to: E. Mark Haacke, Ph.D., 3990 John R Street, MRI Concourse, Detroit, MI 48201. 313-745-1395,
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Deistung A, Schweser F, Reichenbach JR. Overview of quantitative susceptibility mapping. NMR IN BIOMEDICINE 2017; 30:e3569. [PMID: 27434134 DOI: 10.1002/nbm.3569] [Citation(s) in RCA: 167] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 05/03/2016] [Accepted: 05/09/2016] [Indexed: 06/06/2023]
Abstract
Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
- MRI Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
- Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, Jena, Germany
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Chatnuntawech I, McDaniel P, Cauley SF, Gagoski BA, Langkammer C, Martin A, Grant PE, Wald LL, Setsompop K, Adalsteinsson E, Bilgic B. Single-step quantitative susceptibility mapping with variational penalties. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3570. [PMID: 27332141 PMCID: PMC5179325 DOI: 10.1002/nbm.3570] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Revised: 04/21/2016] [Accepted: 05/09/2016] [Indexed: 05/21/2023]
Abstract
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from the gradient echo (GRE) phase signal through background phase removal and dipole inversion steps. Each of these steps typically requires the solution of an ill-posed inverse problem and thus necessitates additional regularization. Recently developed single-step QSM algorithms directly relate the unprocessed GRE phase to the unknown susceptibility distribution, thereby requiring the solution of a single inverse problem. In this work, we show that such a holistic approach provides susceptibility estimation with artifact mitigation and develop efficient algorithms that involve simple analytical solutions for all of the optimization steps. Our methods employ total variation (TV) and total generalized variation (TGV) to jointly perform the background removal and dipole inversion in a single step. Using multiple spherical mean value (SMV) kernels of varying radii permits high-fidelity background removal whilst retaining the phase information in the cortex. Using numerical simulations, we demonstrate that the proposed single-step methods reduce the reconstruction error by up to 66% relative to the multi-step methods that involve SMV background filtering with the same number of SMV kernels, followed by TV- or TGV-regularized dipole inversion. In vivo single-step experiments demonstrate a dramatic reduction in dipole streaking artifacts and improved homogeneity of image contrast. These acquisitions employ the rapid three-dimensional echo planar imaging (3D EPI) and Wave-CAIPI (controlled aliasing in parallel imaging) trajectories for signal-to-noise ratio-efficient whole-brain imaging. Herein, we also demonstrate the multi-echo capability of the Wave-CAIPI sequence for the first time, and introduce an automated, phase-sensitive coil sensitivity estimation scheme based on a 4-s calibration acquisition. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Itthi Chatnuntawech
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Correspondence to: Itthi Chatnuntawech, Massachusetts Institute of Technology, Room 36-776A, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, , Phone: 617-324-1738
| | - Patrick McDaniel
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Stephen F. Cauley
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan A. Gagoski
- Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Adrian Martin
- Applied Mathematics, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain
| | - P. Ellen Grant
- Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Lawrence L. Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kawin Setsompop
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Berkin Bilgic
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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Ropele S, Langkammer C. Iron quantification with susceptibility. NMR IN BIOMEDICINE 2017; 30:e3534. [PMID: 27119601 DOI: 10.1002/nbm.3534] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Revised: 02/19/2016] [Accepted: 03/11/2016] [Indexed: 05/26/2023]
Abstract
Iron is an essential trace element involved in a variety of biological mechanisms in the human body. Disturbances of iron homeostasis have been observed in several inflammatory and degenerative diseases, which have raised strong interest in non-invasive iron mapping techniques. Numerous MRI techniques have been proposed so far, mostly based on the field changes induced by the magnetic properties of iron. Each of these approaches has a specific sensitivity for iron and its microstructural environment. Quantitative susceptibility mapping is the latest development and provides a direct measure of bulk susceptibility. However, field changes induced by iron are not always directly related to the concentration of iron, but rather reflect the structure of iron compounds and its cellular distribution. This review provides an overview of the most relevant iron compounds in the human body, their magnetic properties and their cellular distribution. In addition, MRI methods based on direct or indirect susceptibility changes are presented and discussed with respect to technical aspects and clinical applicability. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
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Soman S, Bregni JA, Bilgic B, Nemec U, Fan A, Liu Z, Barry RL, Du J, Main K, Yesavage J, Adamson MM, Moseley M, Wang Y. Susceptibility-Based Neuroimaging: Standard Methods, Clinical Applications, and Future Directions. CURRENT RADIOLOGY REPORTS 2017; 5. [PMID: 28695062 DOI: 10.1007/s40134-017-0204-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The evaluation of neuropathologies using MRI methods that leverage tissue susceptibility have become standard practice, especially to detect blood products or mineralization. Additionally, emerging MRI techniques have the ability to provide new information based on tissue susceptibility properties in a robust and quantitative manner. This paper discusses these advanced susceptibility imaging techniques and their clinical applications.
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Affiliation(s)
- Salil Soman
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Rosenberg 90A, 1 Deaconess Road, Boston, MA 02215, Tel: 617-754-2009
| | | | - Berkin Bilgic
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, A.A. Martinos Center for Biomedical Imaging 149 13th Street, Room 2.102, Charlestown, MA 02129, Tel: 617-866-8740
| | - Ursula Nemec
- Department of Radiology, Medical University of Vienna, Austria
| | - Audrey Fan
- Department of Radiology, Stanford School of Medicine 300 Pasteur Dr, MC 5105, Stanford, CA94305
| | - Zhe Liu
- Cornell MRI Research Lab, Cornell University, 515 East 71st St, Suite 104, New York, NY 10021, ,
| | - Robert L Barry
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, A.A. Martinos Center for Biomedical Imaging 149 13th Street, Suite 2.301, Charlestown, MA 02129 USA, Tel: 615-801-0795
| | - Jiang Du
- Department of Radiology, UCSD, 200 West Arbor Drive, San Diego, CA 92103-8226, Tel: 619-471-0519
| | - Keith Main
- Principal Scientist (SME), Research Division, Defense and Veterans Brain Injury Center, General Dynamics Health Solutions, 1335 East-West Hwy, Suite 4-100, Silver Spring, MD 20910
| | - Jerome Yesavage
- Department of Psychiatry & Behavioral Sciences, Stanford School of Medicine, Mail Code 151-Y, 3801 Miranda Avenue, Palo Alto, California 94304, Phone (650) 852-3287
| | - Maheen M Adamson
- Department of Neurosurgery, Department of Psychiatry & Behavioral Sciences, Stanford School of Medicine, Defense and Veterans Brain Injury Center, VA Palo Alto Health Care System (PSC/117), 3801 Miranda Avenue (151Y), Palo Alto, CA 94304
| | - Michael Moseley
- Department of Radiology, Stanford School of Medicine, Mail Code 5488, Route 8, Rm PS059, Stanford, CA, 94305-5488, Tel: 650-725-6077
| | - Yi Wang
- Department of Radiology, Cornell Medical School, Department of Biomedical Engineering, Cornell University, 301 Weill Hall, 237 Tower Road, Ithaca, NY 14853, Tel: 646 962-2631
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40
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Xie L, Bennett KM, Liu C, Johnson GA, Zhang JL, Lee VS. MRI tools for assessment of microstructure and nephron function of the kidney. Am J Physiol Renal Physiol 2016; 311:F1109-F1124. [PMID: 27630064 DOI: 10.1152/ajprenal.00134.2016] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Accepted: 09/08/2016] [Indexed: 12/13/2022] Open
Abstract
MRI can provide excellent detail of renal structure and function. Recently, novel MR contrast mechanisms and imaging tools have been developed to evaluate microscopic kidney structures including the tubules and glomeruli. Quantitative MRI can assess local tubular function and is able to determine the concentrating mechanism of the kidney noninvasively in real time. Measuring single nephron function is now a near possibility. In parallel to advancing imaging techniques for kidney microstructure is a need to carefully understand the relationship between the local source of MRI contrast and the underlying physiological change. The development of these imaging markers can impact the accurate diagnosis and treatment of kidney disease. This study reviews the novel tools to examine kidney microstructure and local function and demonstrates the application of these methods in renal pathophysiology.
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Affiliation(s)
- Luke Xie
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah;
| | - Kevin M Bennett
- Department of Biology, University of Hawaii at Manoa, Honolulu, Hawaii
| | - Chunlei Liu
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina; and.,Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina
| | - G Allan Johnson
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, North Carolina; and
| | - Jeff Lei Zhang
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah
| | - Vivian S Lee
- Utah Center for Advanced Imaging Research, Department of Radiology, University of Utah, Salt Lake City, Utah
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41
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Setsompop K, Feinberg DA, Polimeni JR. Rapid brain MRI acquisition techniques at ultra-high fields. NMR IN BIOMEDICINE 2016; 29:1198-221. [PMID: 26835884 PMCID: PMC5245168 DOI: 10.1002/nbm.3478] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 11/28/2015] [Accepted: 12/02/2015] [Indexed: 05/04/2023]
Abstract
Ultra-high-field MRI provides large increases in signal-to-noise ratio (SNR) as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher-spatial-resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, there is a concurrent increased image-encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI - particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development - such as the move from conventional 2D slice-by-slice imaging to more efficient simultaneous multislice (SMS) or multiband imaging (which can be viewed as "pseudo-3D" encoding) as well as full 3D imaging - have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multichannel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - David A. Feinberg
- Helen Wills Institute for Neuroscience, University of California, Berkeley, CA, USA
- Advanced MRI Technologies, Sebastopol, CA, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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Schneider TM, Deistung A, Biedermann U, Matthies C, Ernestus RI, Volkmann J, Heiland S, Bendszus M, Reichenbach JR. Susceptibility Sensitive Magnetic Resonance Imaging Displays Pallidofugal and Striatonigral Fiber Tracts. Oper Neurosurg (Hagerstown) 2016; 12:330-338. [DOI: 10.1227/neu.0000000000001256] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Accepted: 02/29/2016] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND
The pallidofugal and striatonigral fiber tracts form a functional part of the basal ganglionic neuronal networks. For deep brain stimulation, a surgical procedure applied in the treatment of Parkinson disease and dystonia, precise localization of pallidofugal pathways may be of particular clinical relevance for correct electrode positioning.
OBJECTIVE
To investigate whether the pallidofugal and striatonigral pathways can be visualized with magnetic resonance imaging in vivo by exploiting their intrinsic magnetic susceptibility.
METHODS
Three-dimensional gradient-echo imaging of 5 volunteers was performed on a 7 T magnetic resonance imaging system. To demonstrate that the displayed tubular structures in the vicinity of the subthalamic nucleus and substantia nigra truly represent fiber tracts rather than veins, gradient-echo data of a formalin-fixated brain and a volunteer during inhalation of ambient air and carbogen were collected at 3 T. Susceptibility weighted images, quantitative susceptibility maps, and effective transverse relaxation maps were reconstructed and the depiction of fiber tracts was qualitatively assessed.
RESULTS
High-resolution susceptibility-based magnetic resonance imaging contrasts enabled visualization of pallidofugal and striatonigral fiber tracts noninvasively at 3 T and 7 T. We verified that the stripe-like pattern observed on susceptibility-sensitive images is not caused by veins crossing the internal capsule but by fiber tracts traversing the internal capsule.
CONCLUSION
Pallidofugal and striatonigral fiber tracts have been visualized in vivo for the first time by using susceptibility-sensitive image contrasts. Considering the course of pallidofugal pathways, in particular for deep brain stimulation procedures in the vicinity of the subthalamic nucleus, could provide landmarks for optimal targeting during stereotactic planning.
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Affiliation(s)
- Till M Schneider
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital—Friedrich Schiller University Jena, Jena, Germany
| | - Uta Biedermann
- Institute of Anatomy I, Jena University Hospital—Friedrich Schiller University Jena, Jena, Germany
| | - Cordula Matthies
- Department of Neurosurgery, Würzburg University Hospital, Würzburg, Germany
| | - Ralf-Ingo Ernestus
- Department of Neurosurgery, Würzburg University Hospital, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, Würzburg University Hospital, Würzburg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital—Friedrich Schiller University Jena, Jena, Germany
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Liu C, Wei H, Gong NJ, Cronin M, Dibb R, Decker K. Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications. ACTA ACUST UNITED AC 2015; 1:3-17. [PMID: 26844301 PMCID: PMC4734903 DOI: 10.18383/j.tom.2015.00136] [Citation(s) in RCA: 122] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Quantitative susceptibility mapping (QSM) is a recently developed magnetic resonance imaging (MRI) technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field results from a superposition of the dipole fields generated by all voxels and that each voxel has its own unique magnetic susceptibility. QSM provides an improved contrast-to-noise ratio for certain tissues and structures compared with its magnitude counterpart. More importantly, magnetic susceptibility directly reflects the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism that generates susceptibility contrast within tissues and some associated applications.
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Affiliation(s)
- Chunlei Liu
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC 27710; Department of Radiology, Duke University School of Medicine, Durham, NC 27710; Center for In Vivo Microscopy, Duke University School of Medicine, Durham, NC 27710
| | - Hongjiang Wei
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC 27710
| | - Nan-Jie Gong
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC 27710
| | - Matthew Cronin
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC 27710
| | - Russel Dibb
- Center for In Vivo Microscopy, Duke University School of Medicine, Durham, NC 27710
| | - Kyle Decker
- Center for In Vivo Microscopy, Duke University School of Medicine, Durham, NC 27710
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