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Wu D, Kang L, Li H, Ba R, Cao Z, Liu Q, Tan Y, Zhang Q, Li B, Yuan J. Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging. Neuroimage 2024; 290:120553. [PMID: 38403092 DOI: 10.1016/j.neuroimage.2024.120553] [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: 07/03/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024] Open
Abstract
Recent advances in neuroscience requires high-resolution MRI to decipher the structural and functional details of the brain. Developing a high-performance gradient system is an ongoing effort in the field to facilitate high spatial and temporal encoding. Here, we proposed a head-only gradient system NeuroFrontier, dedicated for neuroimaging with an ultra-high gradient strength of 650 mT/m and 600 T/m/s. The proposed system features in 1) ultra-high power of 7MW achieved by running two gradient power amplifiers using a novel paralleling method; 2) a force/torque balanced gradient coil design with a two-step mechanical structure that allows high-efficiency and flexible optimization of the peripheral nerve stimulation; 3) a high-density integrated RF system that is miniaturized and customized for the head-only system; 4) an AI-empowered compressed sensing technique that enables ultra-fast acquisition of high-resolution images and AI-based acceleration in q-t space for diffusion MRI (dMRI); and 5) a prospective head motion correction technique that effectively corrects motion artifacts in real-time with 3D optical tracking. We demonstrated the potential advantages of the proposed system in imaging resolution, speed, and signal-to-noise ratio for 3D structural MRI (sMRI), functional MRI (fMRI) and dMRI in neuroscience applications of submillimeter layer-specific fMRI and dMRI. We also illustrated the unique strength of this system for dMRI-based microstructural mapping, e.g., enhanced lesion contrast at short diffusion-times or high b-values, and improved estimation accuracy for cellular microstructures using diffusion-time-dependent dMRI or for neurite microstructures using q-space approaches.
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Affiliation(s)
- Dan Wu
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China.
| | - Liyi Kang
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; Innovation Center for Smart Medical Technologies & Devices, Binjiang Institute of Zhejiang University, Hangzhou, China
| | - Haotian Li
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Ruicheng Ba
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Zuozhen Cao
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Qian Liu
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Yingchao Tan
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Qinwei Zhang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Bo Li
- United Imaging Healthcare Co., Ltd, Shanghai, China
| | - Jianmin Yuan
- United Imaging Healthcare Co., Ltd, Shanghai, China
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Endt S, Engel M, Naldi E, Assereto R, Molendowska M, Mueller L, Mayrink Verdun C, Pirkl CM, Palombo M, Jones DK, Menzel MI. In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods. APPLIED MAGNETIC RESONANCE 2023; 54:1571-1588. [PMID: 38037641 PMCID: PMC10682074 DOI: 10.1007/s00723-023-01584-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/18/2023] [Accepted: 07/25/2023] [Indexed: 12/02/2023]
Abstract
Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.
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Affiliation(s)
- Sebastian Endt
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Emanuele Naldi
- Technische Universität Braunschweig, Braunschweig, Germany
| | | | - Malwina Molendowska
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, Leeds, United Kingdom
| | - Claudio Mayrink Verdun
- Technical University of Munich, Munich, Germany
- Munich Center for Machine Learning, Munich, Germany
| | | | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Marion I. Menzel
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- GE HealthCare, Munich, Germany
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3
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Fan Q, Eichner C, Afzali M, Mueller L, Tax CMW, Davids M, Mahmutovic M, Keil B, Bilgic B, Setsompop K, Lee HH, Tian Q, Maffei C, Ramos-Llordén G, Nummenmaa A, Witzel T, Yendiki A, Song YQ, Huang CC, Lin CP, Weiskopf N, Anwander A, Jones DK, Rosen BR, Wald LL, Huang SY. Mapping the Human Connectome using Diffusion MRI at 300 mT/m Gradient Strength: Methodological Advances and Scientific Impact. Neuroimage 2022; 254:118958. [PMID: 35217204 DOI: 10.1016/j.neuroimage.2022.118958] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 12/20/2022] Open
Abstract
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in Continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength dMRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for dMRI and where the field is headed in the coming years.
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Affiliation(s)
- Qiuyun Fan
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Cornelius Eichner
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Lars Mueller
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, LS2 9JT, UK
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Image Sciences Institute, University Medical Center (UMC) Utrecht, Utrecht, Netherlands
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | | | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (MOE & STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
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Oliviero S, Del Gratta C. Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study. MAGMA (NEW YORK, N.Y.) 2021; 34:523-543. [PMID: 33417079 DOI: 10.1007/s10334-020-00899-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/19/2020] [Accepted: 11/22/2020] [Indexed: 06/12/2023]
Abstract
OBJECTIVE To evaluate: (a) the specific effect that the demyelination and axonal loss have on the DW signal, and (b) the impact of the sequence parameters on the sensitivity to damage of two clinically feasible DWI techniques, i.e. DKI and NODDI. METHODS We performed a Monte Carlo simulation of water diffusion inside a novel synthetic model of white matter in the presence of axonal loss and demyelination, with three compartments with permeable boundaries between them. We compared DKI and NODDI in their ability to detect and assess the damage, using several acquisition protocols. We used the F test statistic as an index of the sensitivity for each DWI parameter to axonal loss and demyelination, respectively. RESULTS DKI parameters significantly changed with increasing axonal loss, but, in most cases, not with demyelination; all the NODDI parameters showed sensitivity to both the damage processes (at p < 0.01). However, the acquisition protocol strongly affected the sensitivity to damage of both the DKI and NODDI parameters and, especially for NODDI, the parameter absolute values also. DISCUSSION This work is expected to impact future choices for investigating white matter microstructure in focusing on specific stages of the disease, and for selecting the appropriate experimental framework to obtain optimal data quality given the purpose of the experiment.
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Affiliation(s)
- Stefania Oliviero
- Department Neurosciences, Imaging, and Clinical Sciences, Institute for Advanced Biomedical Technologies, ITAB, Gabriele D'Annunzio University, Chieti, Italy.
| | - Cosimo Del Gratta
- Department Neurosciences, Imaging, and Clinical Sciences, Institute for Advanced Biomedical Technologies, ITAB, Gabriele D'Annunzio University, Chieti, Italy
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5
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Shinar H, Eliav U, Navon G. Deuterium double quantum-filtered NMR studies of peripheral and optic nerves. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:889-902. [PMID: 34328573 DOI: 10.1007/s10334-021-00949-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/09/2021] [Accepted: 07/19/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Characterization of the nerve components by deuterium double quantum-filtered magnetization transfer (DQF-MT) NMR. METHODS Nerves were equilibrated in deuterated saline and 2H single-pulse and 2H DQF-MT NMR spectra were measured, enabling the separation of the different water compartments, according to their quadrupolar splittings. RESULTS Rat sciatic and brachial nerves and porcine optic nerve immersed in deuterated saline yielded 2H DQF spectra composed of three pairs of quadrupolar-split signals assigned to the water in the collagenous compartments and the myelin bilayer and one narrow signal assigned to the axonal water. Stretching of the nerves, application of osmotic stress and incubation in collagenase did not affect the quadrupolar splitting of the myelin water. The signals of myelin and axonal water were shown to decay during Wallerian degeneration and to rise during maturation. The chemical exchange between the myelin and the intra-axonal water was measured for optic nerve during maturation. The quadrupolar splitting of the signal of myelin water was not sensitive to its orientation relative to the magnetic field. This resembles liquid crystalline behavior, but leaves its mechanism open for interpretation. CONCLUSIONS 2H DQF-MT NMR characterizes the different components of nerves, the water exchange between them and their changes during processes such as nerve maturation and Wallerian degeneration.
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Affiliation(s)
| | - Uzi Eliav
- School of Chemistry, Tel Aviv University, Tel Aviv, Israel
| | - Gil Navon
- School of Chemistry, Tel Aviv University, Tel Aviv, Israel.
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6
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Wilm BJ, Hennel F, Roesler MB, Weiger M, Pruessmann KP. Minimizing the echo time in diffusion imaging using spiral readouts and a head gradient system. Magn Reson Med 2020; 84:3117-3127. [PMID: 32573807 DOI: 10.1002/mrm.28346] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 04/26/2020] [Accepted: 05/14/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE Diffusion weighted imaging (DWI) is commonly limited by low signal-to-noise ratio (SNR) as well as motion artifacts. To address this limitation, a method that allows to maximize the achievable signal yield and increase the resolution in motion robust single-shot DWI is presented. METHODS DWI was performed on a 3T scanner equipped with a recently developed gradient insert (gradient strength: 200 mT/m, slew rate: 600 T/m/s). To further shorten the echo time, Stejskal-Tanner diffusion encoding with a single-shot spiral readout was implemented. To allow non-Cartesian image reconstruction using such strong and fast gradients, the characterization of eddy current and concomitant field effects was performed based on field-camera measurements. RESULTS An echo time of only 19 ms was achieved for a b-factor of 1000 s/mm2 . An in-plane resolution of 0.68 mm was encoded by a single-shot spiral readout of 40.5 ms using 3-fold undersampling. The resulting images did not suffer from off-resonance artifacts and T 2 ∗ blurring that are common to single-shot images acquired with regular gradient systems. CONCLUSION Spiral diffusion imaging using a head gradient system, together with an accurate characterization of the encoding process allows for a substantial reduction of the echo time, and improves the achievable resolution in motion-insensitive single-shot DWI.
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Affiliation(s)
- Bertram Jakob Wilm
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Franciszek Hennel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Manuela Barbara Roesler
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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7
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Lee J, Hyun JW, Lee J, Choi EJ, Shin HG, Min K, Nam Y, Kim HJ, Oh SH. So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging. J Magn Reson Imaging 2020; 53:360-373. [PMID: 32009271 DOI: 10.1002/jmri.27059] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/01/2020] [Accepted: 01/02/2020] [Indexed: 12/22/2022] Open
Abstract
Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T2 -, T2 *-, T1 -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.
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Affiliation(s)
- Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Jae-Won Hyun
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Jieun Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Eun-Jung Choi
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Hyeong-Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Kyeongseon Min
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Yoonho Nam
- Department of Radiology, Seoul Saint Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Ho Jin Kim
- Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang-si, Korea
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, Korea.,Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
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8
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McKinnon ET, Jensen JH. Measuring intra-axonal T 2 in white matter with direction-averaged diffusion MRI. Magn Reson Med 2018; 81:2985-2994. [PMID: 30506959 DOI: 10.1002/mrm.27617] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Revised: 10/21/2018] [Accepted: 11/05/2018] [Indexed: 01/14/2023]
Abstract
PURPOSE To demonstrate how the T2 relaxation time of intra-axonal water (T2a ) in white matter can be measured with direction-averaged diffusion MRI. METHODS For b-values larger than about 4000 s/mm2 , the direction-averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T2a to be estimated by acquiring data for multiple TE values and fitting a mono-exponential decay curve. If given a value of the intra-axonal diffusivity, an extension of the method allows the extra-axonal relaxation time (T2e ) to be calculated also. This approach was applied to estimate T2a in white matter for 3 healthy subjects at 3 T, as well as T2e for a selected set of assumed intra-axonal diffusivities. RESULTS The estimated T2a values ranged from about 50 ms to 110 ms, with considerable variation among white matter regions. For white matter tracts with primarily collinear fibers, T2a was found to depend on the angle of the tract relative to the main magnetic field, which is consistent with T2a being affected by magnetic field inhomogeneities arising from spatial differences in magnetic susceptibility. The T2e values were significantly smaller than the T2a values across white matter regions for several plausible choices of the intra-axonal diffusivity. CONCLUSION The relaxation time for intra-axonal water in white matter can be determined in a straightforward manner by measuring the direction-averaged diffusion MRI signal with a large b-value for multiple TEs. In healthy brain, T2a is greater than T2e and varies considerably with anatomical region.
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Affiliation(s)
- Emilie T McKinnon
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina.,Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina.,Department of Neurology, Medical University of South Carolina, Charleston, South Carolina
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina.,Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina.,Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina
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9
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Kurz FT, Buschle LR, Hahn A, Jende JME, Bendszus M, Heiland S, Ziener CH. Diffusion effects in myelin sheath free induction decay. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 297:61-75. [PMID: 30366221 DOI: 10.1016/j.jmr.2018.10.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 09/27/2018] [Accepted: 10/01/2018] [Indexed: 06/08/2023]
Abstract
Myelin sheath microstructure and composition produce MR signal decay characteristics that can be used to evaluate status and outcome of demyelinating disease. We extend a recently proposed model of neuronal magnetic susceptibility, that accounts for both the structural and inherent anisotropy of the myelin sheath, by including the whole dynamic range of diffusion effects. The respective Bloch-Torrey equation for local spin dephasing is solved with a uniformly convergent perturbation expansion method, and the resulting magnetization decay is validated with a numerical solution based on a finite difference method. We show that a variation of diffusion strengths can lead to substantially different MR signal decay curves. Our results may be used to adjust or control simulations for water diffusion in neuronal structures.
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Affiliation(s)
- F T Kurz
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany.
| | - L R Buschle
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany; Heidelberg University, Faculty of Physics and Astronomy, INF 227, D-69120 Heidelberg, Germany
| | - A Hahn
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - J M E Jende
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - M Bendszus
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - S Heiland
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany
| | - C H Ziener
- Heidelberg University Hospital, INF 400, D-69120 Heidelberg, Germany; German Cancer Research Center, INF 280, D-69120 Heidelberg, Germany.
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10
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Jones DK, Alexander DC, Bowtell R, Cercignani M, Dell'Acqua F, McHugh DJ, Miller KL, Palombo M, Parker GJM, Rudrapatna US, Tax CMW. Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI. Neuroimage 2018; 182:8-38. [PMID: 29793061 DOI: 10.1016/j.neuroimage.2018.05.047] [Citation(s) in RCA: 105] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 05/17/2018] [Accepted: 05/18/2018] [Indexed: 12/13/2022] Open
Abstract
The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.
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Affiliation(s)
- D K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; School of Psychology, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, 3065, Australia.
| | - D C Alexander
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK; Clinical Imaging Research Centre, National University of Singapore, Singapore
| | - R Bowtell
- Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - M Cercignani
- Department of Psychiatry, Brighton and Sussex Medical School, Brighton, UK
| | - F Dell'Acqua
- Natbrainlab, Department of Neuroimaging, King's College London, London, UK
| | - D J McHugh
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, UK
| | - K L Miller
- Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - M Palombo
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK
| | - G J M Parker
- Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK; CRUK and EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, UK; Bioxydyn Ltd., Manchester, UK
| | - U S Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - C M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
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11
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Studying neurons and glia non-invasively via anomalous subdiffusion of intracellular metabolites. Brain Struct Funct 2018; 223:3841-3854. [DOI: 10.1007/s00429-018-1719-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Accepted: 07/12/2018] [Indexed: 12/31/2022]
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12
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MRI gradient-echo phase contrast of the brain at ultra-short TE with off-resonance saturation. Neuroimage 2018; 175:1-11. [PMID: 29604452 DOI: 10.1016/j.neuroimage.2018.03.066] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Revised: 03/07/2018] [Accepted: 03/28/2018] [Indexed: 02/06/2023] Open
Abstract
Larmor-frequency shift or image phase measured by gradient-echo sequences has provided a new source of MRI contrast. This contrast is being used to study both the structure and function of the brain. So far, phase images of the brain have been largely obtained at long echo times as maximum phase signal-to-noise ratio (SNR) is achieved at TE = T2* (∼40 ms at 3T). The structures of the brain, however, are compartmentalized and complex with a wide range of signal relaxation times. At such long TE, the short-T2 components are largely attenuated and contribute minimally to phase contrast. The purpose of this study was to determine whether proton gradient-echo images of the brain exhibit phase contrast at ultra-short TE (UTE). Our data showed that UTE images acquired at 7 T without off-resonance saturation do not contain significant phase contrast between gray and white matter. However, UTE images of the brain can attain strong phase contrast even at a nominal TE of 106 μs by using off-resonance RF saturation pulses, which provide direct saturation of ultra-short-T2 components and indirect saturation of longer-T2 components via magnetization transfer. In addition, phase contrast between gray and white matter acquired at UTE with off-resonance saturation is reversed compared to that of the long-T2 signals acquired at long TEs. This finding opens up a potential new way to manipulate image phase contrast of the brain. By accessing short and ultra-short-T2 species, MRI phase images may further improve the characterization of tissue microstructure in the brain.
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13
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Does MD. Inferring brain tissue composition and microstructure via MR relaxometry. Neuroimage 2018; 182:136-148. [PMID: 29305163 DOI: 10.1016/j.neuroimage.2017.12.087] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 12/25/2017] [Accepted: 12/27/2017] [Indexed: 11/28/2022] Open
Abstract
MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T1, T2, and T2*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.
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Affiliation(s)
- Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
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14
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Abstract
Susceptibility Weighted Imaging (SWI) is an established part of the clinical neuroimaging toolbox and, since its inception, has also successfully been used in various preclinical studies. Exploiting the effect of variations of magnetic susceptibility between different tissues on the externally applied, static, homogeneous magnetic field, the method visualizes venous vasculature, hemorrhages and blood degradation products, calcifications, and tissue iron deposits. The chapter describes in vivo and ex vivo protocols for preclinical SWI in rodents.
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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.
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA.
| | - Marilena Preda
- 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
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Robert Zivadinov
- 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
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, USA
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15
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Cercignani M, Bouyagoub S. Brain microstructure by multi-modal MRI: Is the whole greater than the sum of its parts? Neuroimage 2017; 182:117-127. [PMID: 29097317 DOI: 10.1016/j.neuroimage.2017.10.052] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 09/12/2017] [Accepted: 10/25/2017] [Indexed: 12/11/2022] Open
Abstract
The MRI signal is dependent upon a number of sub-voxel properties of tissue, which makes it potentially able to detect changes occurring at a scale much smaller than the image resolution. This "microstructural imaging" has become one of the main branches of quantitative MRI. Despite the exciting promise of unique insight beyond the resolution of the acquired images, its widespread application is limited by the relatively modest ability of each microstructural imaging technique to distinguish between differing microscopic substrates. This is mainly due to the fact that MRI provides a very indirect measure of the tissue properties in which we are interested. A strategy to overcome this limitation lies in the combination of more than one technique, to exploit the relative contributions of differing physiological and pathological substrates to selected MRI contrasts. This forms the basis of multi-modal MRI, a broad concept that refers to many different ways of effectively combining information from more than one MRI contrast. This paper will review a range of methods that have been proposed to maximise the output of this combination, primarily falling into one of two approaches. The first one relies on data-driven methods, exploiting multivariate analysis tools able to capture overlapping and complementary information. The second approach, which we call "model-driven", aims at combining parameters extracted by existing biophysical or signal models to obtain new parameters, which are believed to be more accurate or more specific than the original ones. This paper will attempt to provide an overview of the advantages and limitations of these two philosophies.
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Affiliation(s)
- Mara Cercignani
- Clinical Imaging Sciences Centre, Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RR, Brighton, East Sussex, UK; Neuroimaging Laboratory, Santa Lucia Foundation, Via Ardeatina 306, 00179, Rome, Italy.
| | - Samira Bouyagoub
- Clinical Imaging Sciences Centre, Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, BN1 9RR, Brighton, East Sussex, UK
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16
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Harkins KD, Does MD. Simulations on the influence of myelin water in diffusion-weighted imaging. Phys Med Biol 2016; 61:4729-45. [PMID: 27271991 DOI: 10.1088/0031-9155/61/13/4729] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (D app) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (D m), but exhibited important differences compared to D app values simulated that neglect D m (=0). Compared to D app, the apparent diffusion kurtosis (K app) was generally more sensitive to D m. Simulations also tested the sensitivity of D app and K app to the amount of myelin present. Unique variations in D app and K app caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in D app and K app with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter.
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Affiliation(s)
- K D Harkins
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA. Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
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17
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Dhital B, Labadie C, Stallmach F, Möller HE, Turner R. Temperature dependence of water diffusion pools in brain white matter. Neuroimage 2016; 127:135-143. [DOI: 10.1016/j.neuroimage.2015.11.064] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 11/15/2015] [Accepted: 11/25/2015] [Indexed: 10/22/2022] Open
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18
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Xu J, Li H, Harkins KD, Jiang X, Xie J, Kang H, Does MD, Gore JC. Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy. Neuroimage 2014; 103:10-19. [PMID: 25225002 PMCID: PMC4312203 DOI: 10.1016/j.neuroimage.2014.09.006] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Revised: 09/02/2014] [Accepted: 09/04/2014] [Indexed: 02/01/2023] Open
Abstract
Mapping mean axon diameter and intra-axonal volume fraction may have significant clinical potential because nerve conduction velocity is directly dependent on axon diameter, and several neurodegenerative diseases affect axons of specific sizes and alter axon counts. Diffusion-weighted MRI methods based on the pulsed gradient spin echo (PGSE) sequence have been reported to be able to assess axon diameter and volume fraction non-invasively. However, due to the relatively long diffusion times used, e.g. >20ms, the sensitivity to small axons (diameter<2μm) is low, and the derived mean axon diameter has been reported to be overestimated. In the current study, oscillating gradient spin echo (OGSE) diffusion sequences with variable frequency gradients were used to assess rat spinal white matter tracts with relatively short effective diffusion times (1-5ms). In contrast to previous PGSE-based methods, the extra-axonal diffusion cannot be modeled as hindered (Gaussian) diffusion when short diffusion times are used. Appropriate frequency-dependent rates are therefore incorporated into our analysis and validated by histology-based computer simulation of water diffusion. OGSE data were analyzed to derive mean axon diameters and intra-axonal volume fractions of rat spinal white matter tracts (mean axon diameter of ~1.27-5.54μm). The estimated values were in good agreement with histology, including the small axon diameters (<2.5μm). This study establishes a framework for the quantification of nerve morphology using the OGSE method with high sensitivity to small axons.
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Affiliation(s)
- Junzhong Xu
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA.
| | - Hua Li
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA
| | - Kevin D Harkins
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA
| | - Xiaoyu Jiang
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Jingping Xie
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37203, USA
| | - Mark D Does
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA
| | - John C Gore
- Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN 37232, USA; Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37232, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
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19
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Lundell H, Alexander DC, Dyrby TB. High angular resolution diffusion imaging with stimulated echoes: compensation and correction in experiment design and analysis. NMR IN BIOMEDICINE 2014; 27:918-25. [PMID: 24890716 PMCID: PMC4312915 DOI: 10.1002/nbm.3137] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2013] [Revised: 04/01/2014] [Accepted: 04/18/2014] [Indexed: 05/18/2023]
Abstract
Stimulated echo acquisition mode (STEAM) diffusion MRI can be advantageous over pulsed-gradient spin-echo (PGSE) for diffusion times that are long compared with T2 . It therefore has potential for biomedical diffusion imaging applications at 7T and above where T2 is short. However, gradient pulses other than the diffusion gradients in the STEAM sequence contribute much greater diffusion weighting than in PGSE and lead to a disrupted experimental design. Here, we introduce a simple compensation to the STEAM acquisition that avoids the orientational bias and disrupted experiment design that these gradient pulses can otherwise produce. The compensation is simple to implement by adjusting the gradient vectors in the diffusion pulses of the STEAM sequence, so that the net effective gradient vector including contributions from diffusion and other gradient pulses is as the experiment intends. High angular resolution diffusion imaging (HARDI) data were acquired with and without the proposed compensation. The data were processed to derive standard diffusion tensor imaging (DTI) maps, which highlight the need for the compensation. Ignoring the other gradient pulses, a bias in DTI parameters from STEAM acquisition is found, due both to confounds in the analysis and the experiment design. Retrospectively correcting the analysis with a calculation of the full B matrix can partly correct for these confounds, but an acquisition that is compensated as proposed is needed to remove the effect entirely.
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Affiliation(s)
- Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital HvidovreDenmark
- *Correspondence to: H. Lundell, DRCMR, Kettegaards Allé 30, DK-2650 Hvidovre, Denmark., E-mail:
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College LondonGower Street, London, WC1E 6BT, UK
| | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital HvidovreDenmark
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20
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Chen WC, Foxley S, Miller KL. Detecting microstructural properties of white matter based on compartmentalization of magnetic susceptibility. Neuroimage 2012; 70:1-9. [PMID: 23268785 PMCID: PMC3591254 DOI: 10.1016/j.neuroimage.2012.12.032] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2012] [Revised: 11/18/2012] [Accepted: 12/18/2012] [Indexed: 11/24/2022] Open
Abstract
The microscopic structure of neuronal tissue is crucial to brain function, with axon diameter, axonal density and myelination directly influencing signal conduction in the white matter. There is increasing evidence that these microstructural properties alter signal in magnetic resonance imaging (MRI) driven by magnetic susceptibility of different compartments (e.g., myelin sheaths and iron-laden cells). To explain these observations, we have developed a multi-compartmental geometric model of whitematter microstructure. Using a single set of literature parameters, this forward model predicts experimentally observed orientation dependence and temporal evolution of the MRI signal. Where previous models have aimed to explain only the orientation dependence of signal phase, the proposed approach encapsulates the full repertoire of signal behavior. The frequency distribution underlying signal behavior is predicted to be a rich source of microstructural information with relevance to neuronal pathology.
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Affiliation(s)
- Way Cherng Chen
- Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK.
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21
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Harkins KD, Dula AN, Does MD. Effect of intercompartmental water exchange on the apparent myelin water fraction in multiexponential T2 measurements of rat spinal cord. Magn Reson Med 2011; 67:793-800. [PMID: 21713984 DOI: 10.1002/mrm.23053] [Citation(s) in RCA: 74] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2010] [Revised: 05/20/2011] [Accepted: 05/20/2011] [Indexed: 02/05/2023]
Abstract
The myelin water fraction has been used as a quantitative measure of the amount of myelin present in tissue. However, recent work has suggested that intercompartmental exchange of water between myelin and nonmyelin compartments may cause the myelin water fraction to underestimate the true myelin content of tissue. In this work, multiexponential T(2) experiments were performed in vivo within the rat spinal cord, and a wide variation of the myelin water fraction (10-35%) was measured within four rat spinal cord tracts with similar myelin content. A numerical simulation based upon segmented histology images was used to quantitatively account for T(2) variations between tracts. The model predicts that a difference in exchange between the four spinal cord tracts, mediated by a difference in the average axon radius and myelin thickness, is sufficient to account for the variation in myelin water fraction measured in vivo.
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Affiliation(s)
- Kevin D Harkins
- Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA
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22
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Hwang D, Chung H, Nam Y, Du YP, Jang U. Robust mapping of the myelin water fraction in the presence of noise: Synergic combination of anisotropic diffusion filter and spatially regularized nonnegative least squares algorithm. J Magn Reson Imaging 2011; 34:189-95. [PMID: 21618330 DOI: 10.1002/jmri.22586] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2010] [Accepted: 03/04/2011] [Indexed: 11/07/2022] Open
Affiliation(s)
- Dosik Hwang
- School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
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23
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Velumian AA, Samoilova M, Fehlings MG. Visualization of cytoplasmic diffusion within living myelin sheaths of CNS white matter axons using microinjection of the fluorescent dye Lucifer Yellow. Neuroimage 2010; 56:27-34. [PMID: 21073961 DOI: 10.1016/j.neuroimage.2010.11.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2010] [Revised: 08/10/2010] [Accepted: 11/04/2010] [Indexed: 01/16/2023] Open
Abstract
The compactness of myelin allows for efficient insulation defining rapid propagation of action potentials, but also raises questions about how cytoplasmic access to its membranes is achieved, which is critical for physiological activity. Understanding the organization of cytoplasmic ('water') spaces of myelin is also important for diffusion MRI studies of CNS white matter. Using longitudinal slices of mature rat spinal cord, we monitored the diffusion of the water-soluble fluorescent dye Lucifer Yellow injected into individual oligodendrocytes or internodal myelin. We show that living myelin sheaths on CNS axons are fenestrated by a network of diffusionally interconnected cytoplasmic 'pockets' (1.9 ± 0.2 pockets per 10μm sheath length, n=58) that included Schmidt-Lanterman clefts (SLCs) and numerous smaller compartments. 3-D reconstructions of these cytoplasmic networks show that the outer cytoplasmic layer of CNS myelin is cylindrically 'encuffing', which differs from EM studies using fixed tissue. SLCs were found in different 'open states' and remained stable within a 1-2hour observation period. Unlike the peripheral nervous system, where similarly small (<500Da) molecules diffuse along the whole myelin segment within a few minutes, in mature CNS this takes more than one hour. The slower cytoplasmic diffusion in CNS myelin possibly contributes to its known vulnerability to injury and limited capacity for repair. Our findings point to an elaborate cytoplasmic access to compact CNS myelin. These results could be of relevance to MRI studies of CNS white matter and to CNS repair/regeneration strategies.
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Affiliation(s)
- Alexander A Velumian
- Division of Genetics and Development, Toronto Western Research Institute, Canada.
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24
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Dula AN, Gochberg DF, Valentine HL, Valentine WM, Does MD. Multiexponential T2, magnetization transfer, and quantitative histology in white matter tracts of rat spinal cord. Magn Reson Med 2010; 63:902-9. [PMID: 20373391 DOI: 10.1002/mrm.22267] [Citation(s) in RCA: 120] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Quantitative MRI measures of multiexponential T(2) relaxation and magnetization transfer were acquired from six samples of excised and fixed rat spinal cord and compared with quantitative histology. MRI and histology data were analyzed from six white matter tracts, each of which possessed unique microanatomic characteristics (axon diameter and myelin thickness, in particular) but a relatively constant volume fraction of myelin. The results indicated that multiexponential T(2) relaxation characteristics varied substantially with variation of microanatomy, while the magnetization transfer characteristics remained close to constant. The most-often-cited multiexponential T(2) relaxation metric, myelin water fraction, varied by almost a factor of 2 between two regions with myelin volume fractions that differed by only approximately 12%. Based on the quantitative histology, the proposed explanation for this variation was intercompartmental water exchange, which caused the underestimation of myelin water fraction and T(2) values and is, presumably, a greater factor in white matter regions where axons are small and myelin is thin. In contrast to the multiexponential T(2) relaxation observations, magnetization transfer metrics were relatively constant across white matter tracts and concluded to be relatively insensitive to intercompartmental water exchange.
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Affiliation(s)
- Adrienne N Dula
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
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25
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Avram AV, Guidon A, Song AW. Myelin water weighted diffusion tensor imaging. Neuroimage 2010; 53:132-8. [PMID: 20587369 DOI: 10.1016/j.neuroimage.2010.06.019] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2010] [Revised: 06/04/2010] [Accepted: 06/06/2010] [Indexed: 11/18/2022] Open
Abstract
In this study we describe our development and implementation of a magnetization transfer (MT) prepared stimulated-echo diffusion tensor imaging (DTI) technique that can be made sensitive to the microanatomy of myelin tissue. The short echo time (TE) enabled by the stimulated-echo acquisition preserves significant signal from the short T(2) component (myelin water), and the MT preparation further provides differentiating sensitization to this signal. It was found that this combined strategy could provide sufficient sensitivity in our first attempt to image myelin microstructure. Compared to the diffusion tensor derived from the conventional DTI technique, the myelin water weighted (MWW) tensor has the same principal diffusion direction but exhibits a significant increase in fractional anisotropy (FA), which is mainly due to a decrease in radial diffusivity. These findings are consistent with the microstructural organization of the myelin sheaths that wrap around the axons in the white matter and therefore hinder radial diffusion. Given that many white matter diseases (e.g. multiple sclerosis) begin with a degradation of myelin microanatomy but not a loss of myelin content (e.g. loosening of the myelin sheaths), our newly implemented MWW DTI has the potential to lead to improved assessment of myelin pathology and early detection of demyelination.
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Affiliation(s)
- Alexandru V Avram
- Biomedical Engineering Department, Pratt School of Engineering, Duke University, 136 Hudson Hall, Durham, NC 27708, USA
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26
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Diffusion tensor imaging segments the human amygdala in vivo. Neuroimage 2009; 49:2958-65. [PMID: 19931398 DOI: 10.1016/j.neuroimage.2009.11.027] [Citation(s) in RCA: 85] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2009] [Revised: 10/14/2009] [Accepted: 11/11/2009] [Indexed: 11/21/2022] Open
Abstract
The amygdala plays an important role in emotion, learning, and memory. It would be highly advantageous to understand more precisely its internal structure and connectivity for individual human subjects in vivo. Earlier cytoarchitectural research in post-mortem human and animal brains has revealed multiple subdivisions and connectivity patterns, probably related to different functions. With standard magnetic resonance imaging (MRI) techniques, however, the amygdala appears as an undifferentiated area of grey matter. Using high-quality diffusion tensor imaging (DTI) at 3 Tesla, we show diffusion anisotropy in this grey matter area. Such data allowed us to subdivide the amygdala for the first time in vivo. In 15 living subjects, we applied a spectral clustering algorithm to the principal diffusion direction in each amygdala voxel and found a consistent subdivision of the amygdala into a medial and a lateral region. The topography of these regions is in good agreement with the fibre architecture visible in myelin-stained sections through the amygdala of a human post-mortem brain. From these in vivo results we derived a probabilistic map of amygdalar fibre orientations. This segmentation technique has important implications for functional studies in the processing of emotions, cognitive function, and psychiatric disorders and in studying morphometry and volumetry of amygdala subdivisions.
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Hwang D, Du YP. Improved myelin water quantification using spatially regularized non-negative least squares algorithm. J Magn Reson Imaging 2009; 30:203-8. [DOI: 10.1002/jmri.21783] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
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Morphological analysis in patients with sciatica: a magnetic resonance imaging study using three-dimensional high-resolution diffusion-weighted magnetic resonance neurography techniques. Spine (Phila Pa 1976) 2009; 34:E245-50. [PMID: 19333087 DOI: 10.1097/brs.0b013e318197162e] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
STUDY DESIGN A prospective observational study of patients with sciatica. OBJECTIVE We investigated the effectiveness of 3-dimensional high-spatial resolution diffusion-weighted MR neurography based on steady state free precession (3-dimensional diffusion-weighted steady-state free precession [DW-SSFP]) in the diagnosis of sciatica. SUMMARY OF BACKGROUND DATA Patients with sciatica challenge a physician who desires a precise diagnosis for the etiology of the pain. Direct imaging of the sciatic nerve with high resolution and high contrast may contribute to accurate localization and help to find the causes of sciatica and provide reliable information to clinicians in treatment choice. Thus, we supposed that 3-dimensional DW-SSFP method have the ability to confirm the etiologies of sciatica. METHODS The 3-dimensional DW-SSFP sequence was performed on 137 patients with sciatica and 32 patients in control group. The postprocessing techniques were used to generate images of lumbosacral plexus and sciatic nerve, and the images acquired were assessed based on the presence or absence of nerve abnormality. The certainty of identifying the lumbosacral plexus and main branches from all cases was determined in each of the reconstruction planes for each case individually and assessed by using a 3-score scale. RESULTS All subjects were successfully performed. The sciatic nerve and its main branches were differentiated and a clear picture was obtained in all subjects. Compared with the control group, the presence of nerve root compression or increased T2 signal intensity changes can be observed in all patients. The mean score of certainty of identifying the sciatic nerve and main branches was 1.76 +/- 0.4, which indicate that the sciatic nerve and main branches can be identified with certainty. CONCLUSION The 3-dimensional DW-SSFP MRI with high spatial and sufficient contrast is an excellent technique to define the nature of sciatica and assists in prognostication and possibly in management.
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Ou X, Sun SW, Liang HF, Song SK, Gochberg DF. Quantitative magnetization transfer measured pool-size ratio reflects optic nerve myelin content in ex vivo mice. Magn Reson Med 2009; 61:364-71. [PMID: 19165898 DOI: 10.1002/mrm.21850] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Optic nerves from mice that have undergone retinal ischemia were examined using a newly implemented quantitative magnetization transfer (qMT) technique. Previously published results indicate that the optic nerve from retinal ischemia mice suffered significant axon degeneration without detectable myelin injury at 3 days after reperfusion. At this time point, we acquired ex vivo qMT parameters from both shiverer mice (which have nearly no myelin) and control mice that have undergone retinal ischemia, and these qMT measures were compared with diffusion tensor imaging (DTI) results. Our findings suggests that the qMT estimated ratio of the pool sizes of the macromolecular and free water protons reflected the different myelin contents in the optic nerves between the shiverer and control mice. This pool size ratio was specific to myelin content only and was not significantly affected by the presence of axon injury in mouse optic nerve 3 days after retinal ischemia.
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Affiliation(s)
- Xiawei Ou
- Department of Radiology, Vanderbilt University Institute of Imaging Science, Nashville, Tennessee 37232-2310, USA.
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Quarles CC, Lepage M, Gorden DL, Fingleton B, Yankeelov TE, Price RR, Matrisian LM, Gore JC, McIntyre JO. Functional colonography of Min mice using dark lumen dynamic contrast-enhanced MRI. Magn Reson Med 2009; 60:718-26. [PMID: 18727087 DOI: 10.1002/mrm.21724] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Dark lumen MRI colonography detects colonic polyps by minimization of the intestinal lumen signal intensity. Here we validate the use of perfluorinated oil as an intestinal-filling agent for dark lumen MRI studies in mice, enabling the physiological characterization of colonic polyps by dynamic contrast-enhanced MRI. In control and Min (multiple intestinal neoplasia) mice with and without pretreatment with oral dextran sodium sulfate (DSS), polyps as small as 0.94 mm diameter were consistently identified using standard 2D gradient echo imaging (voxel size, 0.23 x 0.16 x 0.5 mm). In serial studies, polyp growth rates were heterogeneous with an average approximately 5% increase in polyp volume per day. In DSS-treated control mice the colon wall contrast agent extravasation rate constant, K(trans), and extravascular extracellular space volume fraction, v(e), values were measured for the first time and found to be 0.10 +/- 0.03 min(-1) and 0.23 +/- 0.09, respectively. In DSS-treated Min mice, polyp K(trans) values (0.09 +/- 0.04 min(-1)) were similar to those in the colon wall but the v(e) values were substantially lower (0.16 +/- 0.03), suggesting increased cellular density. The functional dark-lumen colonography approach described herein provides new opportunities for the noninvasive assessment of gastrointestinal disease pathology and treatment response in mouse models.
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Affiliation(s)
- C Chad Quarles
- Department of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37232-2310, USA.
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On the problem of diffusivity in heterogeneous biological materials with random structure. J Biol Phys 2008; 34:551-67. [PMID: 19669513 DOI: 10.1007/s10867-008-9119-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2008] [Accepted: 09/23/2008] [Indexed: 10/21/2022] Open
Abstract
Biological tissues are multicompartmental heterogeneous media composed of cellular and subcellular domains. Randomly walking water molecules may have different diffusion coefficients and densities (concentrations) in different domains, namely within cells and within the outer medium. Results of the proposed effective media scale-averaging iterative scheme are used to explore the effects of a large range of microstructural and compositional parameters on the apparent (effective) diffusion coefficient. A self-consistent modelling framework for predicting the steady-state effective diffusion coefficient is presented; the framework reveals the strong dependence of the apparent diffusion coefficient on the ratio of the microscopic diffusion coefficients of the comprising phases, permeability of the cells, and their volume fractions.
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Ronen I, Kim DS. Compartment-specific q-space analysis of diffusion-weighted data from isolated rhesus optic and sciatic nerves. Magn Reson Imaging 2008; 27:531-40. [PMID: 18929454 DOI: 10.1016/j.mri.2008.08.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2008] [Revised: 08/14/2008] [Accepted: 08/29/2008] [Indexed: 12/01/2022]
Abstract
We investigated compartment-specific water diffusion properties in two widely structurally different isolated bovine nerves. Sciatic and optic nerves were immersed in saline containing Gd-DTPA(2+). Consequently, T(1) became non-monoexponential and fit well to a biexponential function. q-Space diffusion data were collected for each component. In the sciatic nerve, the slow-decaying component (T(1s)) was considerably more restricted and directional than the fast-decaying component (T(1f)). In the optic nerve, fractional anisotropy of both components was comparable and similar to that of the total H(2)O signal. The root mean square of the displacement distribution functions of T(1s) correlated well with the widely different axonal diameters of both nerves. Possibly, the source of T(1s) is the intra-axonal compartment and that of T(1f) is associated with the inter-axonal space. The compartment specificity of the method shown makes it useful for the investigation of the contribution of each nerve compartment to diffusion tensor imaging measurements and other diffusion-based methods.
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Affiliation(s)
- Itamar Ronen
- Center for Biomedical Imaging, Boston University School of Medicine, 715 Albany Street, Boston, MA 02118, USA.
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Mädler B, Drabycz SA, Kolind SH, Whittall KP, MacKay AL. Is diffusion anisotropy an accurate monitor of myelination? Magn Reson Imaging 2008; 26:874-88. [PMID: 18524521 DOI: 10.1016/j.mri.2008.01.047] [Citation(s) in RCA: 190] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2007] [Accepted: 01/14/2008] [Indexed: 11/16/2022]
Affiliation(s)
- Burkhard Mädler
- Department of Physics and Astronomy, University of British Columbia Hospital, Vancouver BC, Canada.
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Myelin water imaging of multiple sclerosis at 7 T: Correlations with histopathology. Neuroimage 2008; 40:1575-80. [PMID: 18321730 DOI: 10.1016/j.neuroimage.2007.12.008] [Citation(s) in RCA: 270] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2007] [Revised: 11/23/2007] [Accepted: 12/03/2007] [Indexed: 11/23/2022] Open
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